doi,title,abstract,journal_eissn,journal_category
10.3389/fonc.2019.01452,Association Between the Microsatellite Instability Status and the Efficacy of Postoperative Adjuvant Chemoradiotherapy in Patients With Gastric Cancer,"Purpose: The effect of microsatellite instability (MSI) on the response to radiotherapy remains unknown. The aim of this study was to investigate the association between the MSI status and the outcomes of gastric cancer (GC) treated by surgical resection with or without postoperative adjuvant chemoradiotherapy. Methods: The records of patients who underwent surgical resection of stage IB–III GC with or without postoperative adjuvant chemoradiotherapy were retrospectively retrieved from the Affiliated Hospital of Jiangsu University (n = 89), The Cancer Genome Atlas (n = 202), and the Asian Cancer Research Group (n = 138). The primary endpoint was overall survival (OS). Results: The MSI status had no significant influence on OS in all cohorts. Compared with surgery alone, adjuvant chemoradiotherapy improved or tended to improve OS of patients with stage III disease, irrespective of the MSI status, in all cohorts. Among patients with stage Ib/II disease, only those with microsatellite stability (MSS) benefited from chemoradiotherapy in terms of OS, whereas those with MSI showed no improvement in OS. A comparison of gene expression profiles between MSI stage Ib/II GC and MSS stage Ib/II GC revealed that MSI correlated with the overexpression of thymidylate synthetase, a marker of fluoropyrimidine resistance. Furthermore, tumor hypoxia scoring for stage Ib/II lesions showed significantly greater hypoxia in MSI tumors than in MSS tumors. Conclusions: The findings of this study suggest that postoperative adjuvant chemoradiotherapy is effective for stage III GC, regardless of the MSI status. However, MSI may predict a poor response to postoperative adjuvant chemoradiotherapy in patients with stage Ib/II GC.",2234943X,ONCOLOGY
10.3389/feduc.2019.00153,Developing a Short Form of the Self-Assessment Practices Scale: Psychometric Evidence,"This research aimed to develop a short form of the Self-assessment Practices Scale (SaPS). Guided by a process model of self-assessment, the SaPS scale was designed to assess the actions students engage in during the self-assessment process. The data used for developing the original 20-item SaPS (SaPS-20), i.e., 1,416 Hong Kong students ranging from Primary 4 to Secondary 3, were reanalyzed, and a 12-item short form (SaPS-SF) was developed. Factor analysis and Rasch analysis were applied in complementary ways to examine the psychometric properties of the SaPS-SF. The results showed that factor structure of the original scale held in the SaPS-SF, and all items fitted the Rasch model requirements sufficiently and measured the constructs as theorized. The findings presented in this study facilitate the measurement of self-assessment practice in a parsimonious and effective way.",2504284X,EDUCATION
10.3389/fonc.2019.01510,Non-invasive Molecular Detection of Minimal Residual Disease in Papillary Thyroid Cancer Patients,"Background: Papillary thyroid cancer (PTC) is the most common type of thyroid malignancy. Serum thyroglobulin (Tg) levels are used to monitor PTC treatment response and recurrences however, in about 25% of the cases the sensitivity of this method is compromised due to either the presence of neutralizing anti-Tg antibodies (TgAb) or the absence of Tg in less differentiated tumors. Up to 80% of PTC tumors harbor the c.1799T>A hotspot mutation in the BRAF gene (BRAFV600E). Here, we assessed the potential use of plasma cell-free BRAFV600E mutant tumor DNA (ctDNA) levels in determining the minimal residual tumor status of PTC patients. Methods: Patients were classified as either having persistent disease (PD) or no evidence of disease (NED) based on clinicopathological assessments. Tumor BRAFV600E status was determined by both direct sequencing and digital PCR. Plasma total cell-free BRAFV600 wild type DNA (cfDNA) and ctDNA fractions circulating in the plasma of PTC patients were determined by an emulsion based-digital PCR and total ctDNA was quantified by 3D digital PCR. The total ctDNA levels (copies/ml) were then compared to patients' clinicopathological features. Results: About 74% (28/38) of tumors harbored the BRAFV600E mutation. Percent plasma ctDNA fractions for PD patients with BRAFV600E tumors ranged from 0 to 2.07%, whereas absolute plasma ctDNA copies ranged from 0 to 62 copies. The ctDNA levels accurately detected tumor burden of PTC patients whose tumors harbored BRAFV600E; median plasma ctDNA copy numbers were significantly higher (Wilcoxon test, p = 0.03) in patients with metastasis (MET) (20 copies/ml) compared to patients with non-metastatic (non-MET) tumors (1 copy/ml). The plasma ctDNA levels (copies/ml) accurately determined the disease status of PTC patients with sensitivity of 86% and specificity of 90% as compared to 78% sensitivity and 65% specificity determined by serum Tg levels (ng/ml) with areas under the curves (AUC) of 0.88 and 0.71, respectively. Intriguingly, plasma total cfDNA levels were significantly higher in patients with no evidence of residual disease (NED) compared to persistent disease (PD) patients. Conclusions: Our study supports the clinical applicability of plasma ctDNA as biomarker to determine the residual tumor status and tumor burden of PTC patients.",2234943X,ONCOLOGY
10.3390/ejihpe10010029,Measuring Heart Rate Variability Using Commercially Available Devices in Healthy Children: A Validity and Reliability Study,"Heart rate variability (HRV) is an accepted method for determining autonomic nervous system activity and cardiovascular risk in various populations. This study assessed the validity and reliability of a commercially available finger photoplethysmography (PPG) system for measuring pediatric HRV in a real-world setting. Sixteen healthy children (4.06 ± 0.58 years) were recruited. The PPG system was compared to the Polar H10 heart rate (HR) sensor validated against ECG (gold standard) for HRV measurement. Seated short-term resting R-R intervals were recorded simultaneously using both systems. Recordings were performed on 3 days at the participants’ school. Paired t-tests, effect sizes and Bland–Altman analyses determined the validity of the PPG system. The relative and absolute reliability of both systems were calculated. No HRV parameters were valid for the PPG system. Polar H10 yielded moderate (0.50–0.75) to good (0.75–0.90) relative reliability with R-R intervals and the standard deviation of instantaneous and continuous R-R variability ratio showing the best results (ICCs = 0.84). Polar H10 displayed better absolute reliability with the root mean square of successive differences, R-R intervals and HR showing the lowest values (TEM% < 12%). The use of the Polar H10 and not the PPG system is encouraged for HRV measurement of young children in an educational real-world setting.",22549625,PSYCHOLOGY
10.3390/cancers12010182,Predictors of Response and Survival in Immune Checkpoint Inhibitor-Treated Unresectable Hepatocellular Carcinoma,"Immune checkpoint inhibitors (ICIs) with nivolumab and pembrolizumab are promising agents for advanced hepatocellular carcinoma (HCC) but lack of effective biomarkers. We aimed to investigate the potential predictors of response and factors associated with overall survival (OS) for ICI treatment in unresectable HCC patients. Ninety-five patients who received nivolumab or pembrolizumab for unresectable HCC were enrolled for analyses. Radiologic evaluation was based on RECIST v1.1. Factors associated with outcomes were analyzed. Of 90 patients with evaluable images, the objective response rate (ORR) was 24.4%. Patients at Child–Pugh A or received combination treatment had higher ORR. Early alpha-fetoprotein (AFP) >10% reduction (within 4 weeks) was the only independent predictor of best objective response (odds ratio: 7.259, p = 0.001). For patients with baseline AFP ≥10 ng/mL, significantly higher ORR (63.6% vs. 10.2%, p < 0.001) and disease control rate (81.8% vs. 14.3%, p < 0.001) were observed in those with early AFP reduction than those without. In addition, early AFP reduction and albumin-bilirubin (ALBI) grade or Child–Pugh class were independent factors associated with OS in different models. In conclusion, a 10-10 rule of early AFP response can predict objective response and survival to ICI treatment in unresectable HCC. ALBI grade and Child–Pugh class determines survival by ICI treatment.",20726694,ONCOLOGY
10.3390/cancers12010223,"MAGI1, a New Potential Tumor Suppressor Gene in Estrogen Receptor Positive Breast Cancer","Membrane-associated guanylate kinase (MAGUK) with inverted domain structure-1 (MAGI1) is an intracellular adaptor protein that stabilizes epithelial junctions consistent with a tumor suppressive function in several cancers of epithelial origin. Here we report, based on experimental results and human breast cancer (BC) patients’ gene expression data, that MAGI1 is highly expressed and acts as tumor suppressor in estrogen receptor (ER)+/HER2− but not in HER2+ or triple negative breast cancer (TNBC). Within the ER+/HER2− subset, high MAGI1 expression associates with ESR1 and luminal genes GATA3 and FOXA1 expression and better prognosis, while low MAGI1 levels correlates with higher histological grade, more aggressive phenotype and worse prognosis. Experimentally, MAGI1 downregulation in the ER+ human BC cells MCF7 impairs ER expression and signaling, promotes cell proliferation, and reduces apoptosis and epithelial differentiation. MAGI1 downregulation in the ER+ murine BC cell line 67NR accelerates primary tumor growth and enhances experimental lung metastasis formation. MAGI1 expression is upregulated by estrogen/ER, downregulated by prostaglandin E2/COX-2axis, and negatively correlates with inflammation in ER+/HER2− BC patients. Taken together, we show that MAGI1 is a new potential tumor suppressor in ER+/HER2− breast cancer with possible prognostic value for the identification of patients at high-risk of relapse within this subset.",20726694,ONCOLOGY
10.3389/fpsyg.2019.03033,Life History and Multi-Partner Mating: A Novel Explanation for Moral Stigma Against Consensual Non-monogamy,"Life history theory (LHT) predicts that individuals vary in their sexual, reproductive, parental, familial, and social behavior according to the physical and social challenges imposed upon them throughout development. LHT provides a framework for understanding why non-monogamy may be the target of significant moral condemnation: individuals who habitually form multiple romantic or sexual partnerships may pursue riskier, more competitive interpersonal strategies that strain social cooperation. We compared several indices of life history (i.e., the Mini-K, the High-K Strategy Scale, pubertal timing, sociosexuality, disease avoidance, and risk-taking) between individuals practicing monogamous and consensually non-monogamous (CNM) romantic relationships. Across several measures, CNM individuals reported a faster life history strategy than monogamous individuals, and women in CNM relationships reported earlier pubertal development. CNM individuals also reported more social and ethical risk-taking, less aversion to germs, and greater interest in short-term mating (and less interest in long-term mating) than monogamous individuals. From these data, we discuss a model to explain how moral stigma toward non-monogamy evolved and how these attitudes may be mismatched to the modern environment. Specifically, we argue that the culture of sexual ethics that pervades contemporary CNM communities (e.g., polyamory, swinging) may attenuate risky interpersonal behaviors (e.g., violent intrasexual competition, retributive jealousy, partner/child abandonment, disease transmission) that are relatively more common among those who pursue multi-partner mating.",16641078,PSYCHOLOGY
10.3389/frai.2019.00032,"Mysteries, Epistemological Modesty, and Artificial Intelligence in Surgery","Mysteries, Epistemological Modesty, and Artificial Intelligence in Surgery",26248212,AI
10.3389/fpsyg.2019.03023,The Emotional Stroop Effect Is Modulated by the Biological Salience and Motivational Intensity Inherent in Stimuli,"Prior research has found significant emotional Stroop effects for negative stimuli, but the results have been inconsistent for positive stimuli. Combining an evolutionary perspective of emotion with the motivational dimensional model of affect, we speculated that the emotional Stroop effect of a stimulus may be influenced by the biological salience and inherent motivational intensity of the stimulus. In the present study, we examined this issue with two experiments. The results indicated that both low- and high-withdrawal-motivation negative stimuli produced a robust emotional Stroop effect; however, the high-withdrawal-motivation negative stimuli produced a stronger emotional Stroop effect than the low-withdrawal-motivation negative stimuli. Regarding positive stimuli, only the high-approach-motivated positive stimuli produced the emotional Stroop effect, unlike the low-approach-motivation positive stimuli. These findings suggest that the emotional Stroop effect is modulated by the biological salience of stimuli and by the motivational intensity inherent in the stimuli. Biological salience and motivational intensity play an additive effect in the emotional Stroop effect.",16641078,PSYCHOLOGY
10.3389/fonc.2019.01575,"A Novel LncRNA, AC091729.7 Promotes Sinonasal Squamous Cell Carcinomas Proliferation and Invasion Through Binding SRSF2","Long non-coding RNAs (lncRNAs) play important roles in various biological progresses of carcinogenesis. However, the function of lncRNAs in human sinonasal squamous cell carcinoma (SNSCC) remains greatly unclear. In the current study, lncRNA AC091729.7 expression was examined in SNSCC samples by using microarray, RNA in situ hybridization (ISH) and real-time fluorescence quantitative PCR (qRT-PCR). Cell viability, colony-formation, wound-healing, and transwell assays were applied to SNSCC cells. Xenograft mouse models were employed to evaluate the role of AC091729.7 in growth of SNSCC in vivo. Human protein microarray (HuprotTM Protoarray) and RNA immunoprecipitation (RIP) were used for identifying AC091729.7 binding proteins in SNSCC. Results showed AC091729.7 was upregulated and closely connected with the survival of the SNSCC patients. Knockdown of AC091729.7 suppressed SNSCC cell migration, proliferation, invasion in vitro. Furthermore, downregulation of AC091729.7 could inhibit the growth of SNSCC in vivo. Moreover, Human protein microarray and RIP suggested that AC091729.7 directly combine with the serine/arginine rich splicing factor 2 (SRSF2). Our results suggest that in the cell progression of SNSCC, lncRNA AC091729.7 plays a carcinogenic role and serves as a novel biomarker and latent curative target in SNSCC patients.",2234943X,ONCOLOGY
10.3389/feduc.2020.00002,Definitions of Formative Assessment Need to Make a Distinction Between a Psychometric Understanding of Assessment and “Evaluative Judgment”,Definitions of Formative Assessment Need to Make a Distinction Between a Psychometric Understanding of Assessment and “Evaluative Judgment”,2504284X,EDUCATION
10.3390/cancers12020325,Mutation Analysis of Colorectal and Gastric Carcinomas Originating from Adenomas: Insights into Genomic Evolution Associated with Malignant Progression,"Small malignant tumor foci arising from benign lesions are rare but offer a unique opportunity to investigate the genomic evolution that occurs during malignant transformation. In this study, we analyzed 11 colorectal and 10 gastric adenoma–carcinoma pairs, each of which represented malignant tumors (carcinomas) embedded in benign lesions (adenomas) found in the same patient. Whole-exome sequencing revealed that mutation abundance was variable across different cases, but comparable between adenoma–carcinoma pairs. When mutations were classified as adenoma-specific, carcinoma-specific, or common, adenoma-specific mutations were more enriched with subclonal mutations than were carcinoma-specific mutations, indicative of a perturbation in mutational subclonal architecture (such as selective sweep) during malignant transformation. Among the recurrent mutations in colorectal cancers, APC and KRAS mutations were common between adenomas and carcinomas, indicative of their early occurrence during genomic evolution. TP53 mutations were often observed as adenoma-specific and therefore likely not associated with the emergence of malignant clones. Clonality-based enrichment analysis revealed that subclonal mutations of extracellular matrix genes in adenomas are more likely to be clonal in carcinomas, indicating potential roles for these genes in malignant transformation. Compared with colorectal cancers, gastric cancers showed more lesion-specific mutations than common mutations and higher levels of discordance in copy number profiles between matched adenomas and carcinomas, which may explain the elevated evolutionary dynamics and heterogeneity of gastric cancers compared to colorectal cancers. Taken together, this study demonstrates that co-existing benign and malignant lesions enable the evolution-based categorization of genomic alterations that may reveal clinically important biomarkers in colorectal and gastric cancers.",20726694,ONCOLOGY
10.1186/s40594-019-0201-4,Defining interdisciplinary collaboration based on high school teachers’ beliefs and practices of STEM integration using a complex designed system,"Background: Teachers’ beliefs play an important role in how teachers think about how students learn, and how content should be organized and taught. Integrated STEM is pushing the boundaries of some of the traditional assumptions in education—disciplined-based courses, courses taught independently by teachers, standards and content-driven, and no collaborative planning time for teachers. Six teachers, located in two high schools, participated in a year-long program to develop interdisciplinary collaboration to implement integrated STEM learning in their courses. A qualitative instrumental case study of the two teams of teachers was conducted to gain insights and understandings of the teachers’ beliefs and instructional practices of STEM integration through interdisciplinary approaches in a complex system (i.e., hydroponics). Results: Themes regarding features, beliefs and practices, and challenges emerged from cross-case analysis of the teachers’ stories, which resulted in two interdisciplinary collaboration models, multi-classroom and extracurricular activity, from each of the teams at each of the two high schools. Multi-classroom and extracurricular activity models had some resemblances, but also had differences. Both cases had the same goals to use real-world problems to help students see STEM connections, learn STEM knowledge and skills, and apply STEM knowledge and skills to solve real-world problems. Conclusions: Based on teachers’ beliefs and their interdisciplinary STEM collaboration practices, three components were identified. Team size, teaching goal, and collaboration structure highly affect a successful interdisciplinary STEM collaboration model in high school settings. The study also contributes to expend the concept of a continuum of STEM approaches to curriculum integration, disciplinary, multidisciplinary, interdisciplinary, and transdisciplinary (Vasquez, Sneider, & Comer, STEM lesson essentials: Integrating science, technology, engineering, and mathematics, 2013), and provides frameworks for structuring a successful interdisciplinary collaboration model in high school settings.",21967822,EDUCATION
10.1186/s40359-020-0378-9,The clinical effects of school sandplay group therapy on general children with a focus on Korea Child & Youth Personality Test,"Background: This study intended to examine the comprehensive clinical effects of school sandplay group counseling on the emotions and behaviors of children for the first time in Korea. Methods: To this objective, 10 sessions of in-school sandplay group counseling were administered to 113 fourth- to sixth-graders in an elementary school located in Cheonan city for 12 weeks from March to July 2015. Each small group consisted of 10 to 16 children and the entire 12 sessions were composed of a baseline test, 10 therapy sessions, and a post-test and evaluation session. The study subjects consisted of 56 boys (49.6%) and 57 girls (50.4%). As the evaluation instruments, an epidemiologic questionnaire and the Korea Child & Youth Personality Test were used during the baseline phase and after the termination of the counseling. Results: The comparison of the scores according to the KCYP clinical scales and detailed evaluation scales before and after the 12-week counseling showed an increase in the self-esteem and a significant decline in depression in the elementary students after the counseling. Conclusion: It is deemed that school sandplay group counseling can help elementary school students to solve emotional problems and improve their self-esteem.",20507283,PSYCHOLOGY
10.3389/fpsyg.2020.00013,Influences of a Luck Game on Offers in Ultimatum and Dictator Games: Is There a Mediation of Emotions?,"The ultimatum (UG) and dictator (DG) games are two tasks where a sum of money has to be divided between two players: a proposer and a receiver. Following the rational choice theory, proposers should offer the minimum in the UG and nothing in the DG, due to the presence/absence of the receivers’ bargaining power. The fact that people generally make non-negligible offers in both games has suggested divergent explicative hypotheses and has generated extensive research to examine exogenous and endogenous factors underlying such decisions. Among the contextual factors affecting the proposers’ offers, the sense of entitlement or of ownership has been shown to reduce offers significantly. A frequent way to induce the sense of entitlement/ownership has been to assign the role of proposer to the player who apparently has better scored in skill tasks executed before the UG or DG or has more contributed, through a previous luck game, to the amount to be shared. Such manipulations, however, could produce a possible overlapping between “ownership” and “merit,” that in this study we aimed to disentangle. We manipulated the participants’ initial endowment through a luck game, by increasing, decreasing or leaving it unchanged, to investigate whether winnings or losses by chance influenced offers in UG and DG in similar or different ways depending on their respective features. All participants played as proposers but this role was apparently random and disconnected from the outcomes of the luck game. Furthermore, we investigated whether the putative effect of experimental manipulation was mediated by the changes in emotions elicited by the luck game and/or by the emotions and beliefs related to decision-making. We used a non-economic version of the games, in which tokens were divided instead of money. In the study, 300 unpaid undergraduates (M = 152) from different degree programs, aged between 18 and 42 years, participated. The results revealed that the effect of outcome manipulation on offers was moderated by the specific structure of the UG and DG. Instead, emotional reactions barely mediated the effect of the experimental manipulation, suggesting that their role in those decisions is less relevant than is assumed in the literature.",16641078,PSYCHOLOGY
10.3390/ejihpe10010031,The Organization of Self-Knowledge in Adolescence: Some Contributions Using the Repertory Grid Technique,"(1) Background: This study aims to explore the usefulness of personal construct psychology as a comprehensive framework and assessment tool to embrace a diversity of self-knowledge organization constructs, and to account for developmental differences across adolescence. (2) Methods: The repertory grid technique was used to measure self-knowledge differentiation, polarization, discrepancies between Actual Self, Ideal Self, and Others, and implicative dilemmas, a particular kind of intrapersonal conflict. Data were collected from two samples of early and late adolescents, respectively. (3) Results: Globally, they showed that the organization of self-knowledge was different in both samples. In particular, older adolescents revealed a less polarized self-knowledge. In addition, they tended to construe higher Actual–Ideal self-discrepancies and to present more internal conflicts. No differences were found between early and late adolescents concerning global differentiation and the discrepancies between the self (Actual and Ideal) and the Others. (4) Conclusions: Despite the limitations of the study (e.g., small sample size, cross-sectional design), these novel results support the suitability of the repertory grid technique to capture developmental changes in self-knowledge organization during adolescence, as well as the explanatory potential of personal construct psychology to advance their understanding.",22549625,PSYCHOLOGY
10.3390/cancers12020379,Uncovering Tumour Heterogeneity through PKR and nc886 Analysis in Metastatic Colon Cancer Patients Treated with 5-FU-Based Chemotherapy,"Colorectal cancer treatment has advanced over the past decade. The drug 5-fluorouracil is still used with a wide percentage of patients who do not respond. Therefore, a challenge is the identification of predictive biomarkers. The protein kinase R (PKR also called EIF2AK2) and its regulator, the non-coding pre-mir-nc886, have multiple effects on cells in response to numerous types of stress, including chemotherapy. In this work, we performed an ambispective study with 197 metastatic colon cancer patients with unresectable metastases to determine the relative expression levels of both nc886 and PKR by qPCR, as well as the location of PKR by immunohistochemistry in tumour samples and healthy tissues (plasma and colon epithelium). As primary end point, the expression levels were related to the objective response to first-line chemotherapy following the response evaluation criteria in solid tumours (RECIST) and, as the second end point, with survival at 18 and 36 months. Hierarchical agglomerative clustering was performed to accommodate the heterogeneity and complexity of oncological patients’ data. High expression levels of nc886 were related to the response to treatment and allowed to identify clusters of patients. Although the PKR mRNA expression was not associated with chemotherapy response, the absence of PKR location in the nucleolus was correlated with first-line chemotherapy response. Moreover, a relationship between survival and the expression of both PKR and nc886 in healthy tissues was found. Therefore, this work evaluated the best way to analyse the potential biomarkers PKR and nc886 in order to establish clusters of patients depending on the cancer outcomes using algorithms for complex and heterogeneous data.",20726694,ONCOLOGY
10.3390/ai1010005,Detection of Anomalies in Large-Scale Cyberattacks Using Fuzzy Neural Networks,"The fuzzy neural networks are hybrid structures that can act in several contexts of the pattern classification, including the detection of failures and anomalous behaviors. This paper discusses the use of an artificial intelligence model based on the association between fuzzy logic and training of artificial neural networks to recognize anomalies in transactions involved in the context of computer networks and cyberattacks. In addition to verifying the accuracy of the model, fuzzy rules were obtained through knowledge from the massive datasets to form expert systems. The acquired rules allow the creation of intelligent systems in high-level languages with a robust level of identification of anomalies in Internet transactions, and the accuracy of the results of the test confirms that the fuzzy neural networks can act in anomaly detection in high-security attacks in computer networks.",26732688,AI
10.3389/fpsyg.2020.00123,Virtual Reality for the Assessment of Everyday Cognitive Functions in Older Adults: An Evaluation of the Virtual Reality Action Test and Two Interaction Devices in a 91-Year-Old Woman,"Performance-based functional tests for the evaluation of daily living activities demonstrate strong psychometric properties and solve many of the limitations associated with self- and informant-report questionnaires. Virtual reality (VR) technology, which has gained interest as an effective medium for administering interventions in the context of healthcare, has the potential to minimize the time-demands associated with the administration and scoring of performance-based assessments. To date, efforts to develop VR systems for assessment of everyday function in older adults generally have relied on non-immersive systems. The aim of the present study was to evaluate the feasibility of an immersive VR environment for the assessment of everyday function in older adults. We present a detailed case report of an elderly woman who performed an everyday activity in an immersive VR context (Virtual Reality Action Test) with two different types of interaction devices (controller vs. sensor). VR performance was compared to performance of the same task with real objects outside of the VR system (Real Action Test). Comparisons were made on several dimensions, including (1) quality of task performance (e.g., order of task steps, errors, use and speed of hand movements); (2) subjective impression (e.g., attitudes), and (3) physiological markers of stress. Subjective impressions of performance with the different controllers also were compared for presence, cybersickness, and usability. Results showed that the participant was capable of using controllers and sensors to manipulate objects in a purposeful and goal-directed manner in the immersive VR paradigm. She performed the everyday task similarly across all conditions. She reported no cybersickness and even indicated that interactions in the VR environment were pleasant and relaxing. Thus, immersive VR is a feasible approach for function assessment even with older adults who might have very limited computer experience, no prior VR exposure, average educational experiences, and mild cognitive difficulties. Because of inherent limitations of single case reports (e.g., unknown generalizability, potential practice effects, etc.), group studies are needed to establish the full psychometric properties of the Virtual Reality Action Test.",16641078,PSYCHOLOGY
10.3389/fpsyg.2020.00133,Trajectories of Development and Socialization of Trans Brazilian Youth Through Self-Portraits,"The aim of this research was to explore the meanings of childhood memory established by young people who identify themselves as trans. In a chauvinistic country such as Brazil, sexual socialization of non-cisgender youth is beset by unique challenges, such as discrimination and violence. This study was based on the proposal of a self-portrait method as a content trigger in interviews with three trans young women who reported their life stories. We analyzed data using the oral story technique, through which the described themes came up. The results presented developmental narratives related to gender issue from childhood, which reflected on the experience on youth. Reports of discrimination based on the image of others (family, school, and community) about the gender development of the participants and their relationship with their bodies stand out. We see the importance of reflecting on life history memories in trans identity in order to give meaning to this experience. The influence of heteronormative and sexist Brazilian culture is noticed in the participants’ reports.",16641078,PSYCHOLOGY
10.1186/s40359-020-0383-z,The relationship between personality traits and marital satisfaction: a systematic review and meta-analysis,"Background: Personality traits can be used to predict an individual’s behaviors in different life situations, including marital life situations. Marital satisfaction that is influenced by different factors is a criterion used to assess couples’ relationship quality. The goal of the present study was to review Iranian studies on the correlation between personality traits and marital satisfaction.Methods: In this systematic review, all the related Iranian studies in international databases, including Google Scholar, PubMed, Web of Science (ISI) and Scopus, and national databases, including Scientific Information Database (SID) and MagIran were reviewed. The following keywords and also combinations of them were used to search the databases: “Marital satisfaction,” “Personality traits,” “Personality factors,” “Big five model of personality,” and “Iran.”Results: A total of 18 correlational studies, without any time limitation, with a total sample of 4049, were reviewed. The following correlation coefficients were found between marital satisfaction and personality traits: r = − 0.439 with neuroticism (95% Confidence Interval [CI]: 0.27–0.60), r = 0.833 with extraversion (95% CI: 0.77–0.88), r = 0.777 with openness (95% CI: 0.70–0.84), r = 0.855 with agreeableness (95% CI: 0.80–0.90), and r = 0.90 with conscientiousness (95% CI: 0.84–0.95).Conclusions: Couples high in Neuroticism experience lower levels of marital satisfaction, and couples high in Conscientiousness are more satisfied with their marital life.",20507283,PSYCHOLOGY
10.1186/s40594-019-0199-7,"The use and effectiveness of colorful, contextualized, student-made material for elementary mathematics instruction","Background: There is anecdotal evidence that many elementary teachers integrate mathematics lessons and art activities by having students first make colorful, rich material that is subsequently used in an instructional activity. However, it is unclear whether such activities effectively promote learning and transfer of mathematical concepts. The goal of the present research was to examine the use and effectiveness of such “math-and-art” activities on children’s ability to acquire basic fraction knowledge. We report the results of a survey of practicing elementary school teachers in the United States, their use of activities involving physical material, and the resources they use for ideas to supplement the standard curriculum. Two experiments examined first-grade students’ learning, transfer, and recognition of fraction knowledge from rich, contextualized material versus simple, generic material. Results: The survey results confirm that many U.S. teachers use math-and-art activities and are often inspired by informal sources, such as Pinterest and YouTube. Experiment 1 examined the effectiveness of colorful, contextualized student-constructed material (paper pizzas) versus simple, pre-made material (monochromatic paper circles) in an instructional activity on fractions. Students who used the pre-made circles scored higher than those who used the student-made pizzas on pre-instruction tests of basic fraction knowledge, immediate tests of learning, and delayed tests of transfer. Experiment 2 tested students’ ability to spontaneously write fractions to describe proportions of pizzas and circles. Students who answered generic circle questions first were markedly more accurate than those who answered pizza questions first. Conclusions: These findings suggest that rich, contextualized representations, including those made by the student, can hinder students’ learning and transfer of mathematical concepts. We are not suggesting that teachers never integrate mathematics and colorful, contextualized material, and activities. We do suggest that elementary students’ mathematics learning can benefit when initial instruction involves simple, generic, pre-made material and opportunities for students to make and use colorful, contextualized representations come later.",21967822,EDUCATION
10.3389/feduc.2020.00009,"Difficulty of Summarization Items for Japanese Learners: Effects of Passages, Distractors, and Response Formats","This study aims to examine factors affecting the difficulty of summarization items for Japanese learners. In the process of item development, creating a connection between cognitive features related to target construct and the difficulty of test items is necessary to define the abilities to be measured. Previous studies have mainly focused on local reading comprehension, while this study addressed summarization skills at the paragraph level. The study originally developed items for an experiment that elicited three macrorules of the paragraph and text: deletion, generalization, and integration. This study evaluated the influence of passages, distractor characteristics central to summarization processes, and response formats on item difficulty, using item difficulty modeling. When editing distractors, characteristics of L2 learners' summarization were carefully reviewed and reflected. The participants included 150 freshmen from Japan, who were asked to answer experimental summarization items. The results of the linear logistic test model (LLTM) indicated that the main source of difficulty in summarization items was distractor characteristics. In particular, summaries with unnecessary information or lacking necessary information increased the level of difficulty. In addition, summaries with detailed information, such as episodes and examples, and with a viewpoint different from the author's, also increased difficulty. The effect of passage differences was found to be minimal. A difference in response formats moderately affected item difficulty, and the extended-matching format was slightly more difficult than the conventional multiple-choice format. This study suggested that test developers and item writers should pay attention to distractor development, to limit students' errors when measuring summarization skills of L2 learners.",2504284X,EDUCATION
10.3389/feduc.2019.00165,Contrast and Assimilation Effects on Self-Evaluation of Performance and Task Interest in a Sample of Elementary School Children,"Social comparison processes and the social position within a school class already play a major role in performance evaluation as early as in elementary school. The influence of contrast and assimilation effects on self-evaluation of performance as well as task interest has been widely researched in observational studies under the labels big-fish-little-pond and basking-in-reflected-glory effect. This study examined the influence of similar contrast and assimilation effects in an experimental paradigm. Fifth and sixth grade students (n = 230) completed a computer-based learning task during which they received social comparative feedback based on 2 × 2 experimentally manipulated feedback conditions: social position (high vs. low) and peer performance (high vs. low). Results show a more positive development of task interest and self-evaluation of performance in both the high social position and the high peer performance condition. When applied to the school setting, results of this study suggest that students who already perform well in comparison to their peer group are also the ones who profit most from social comparative feedback, given that they are the ones who usually receive the corresponding positive performance feedback.",2504284X,EDUCATION
10.3389/fpsyg.2020.00143,Metacognitive Therapy for Adjustment Disorder in a Patient With Newly Diagnosed Pulmonary Arterial Hypertension: A Case Report,"Adjustment disorders (ADs) belong to the worldwide most diagnosed mental disorders and are particularly frequent in patients with an underlying physical illness. Pulmonary arterial hypertension (PAH) is a severe and disabling disease, which significantly impacts on quality of life and has high mortality rates. The authors here present the case of a young female who developed a severe adjustment disorder with both anxious and depressive symptoms after a diagnosis of PAH requiring intensive care treatment due to right heart failure. Psychosocial functioning was severely impaired, and physical health reduced. Following hemodynamic stabilization and the establishment of PAH treatment, the patient was admitted to the Department of Psychiatry, Social Psychiatry and Psychotherapy and received metacognitive therapy (MCT). AD with mixed anxiety and depressed mood was diagnosed according to DSM-V criteria. At the start of treatment, she reported significant mental distress, indicated by a total sum score of the Hospital Anxiety and Depression Scale (HADS) of 20 points. The 6-min walking distance was only 358 m before the patient was exhausted. She then was treated with MCT without further psychopharmacological drugs. After only four MCT sessions, she fully remitted from AD which was accompanied by an 11-point reduction in the HADS (to 9 points). MCT specific scores also improved (MCQ-30 sum score decreased from 77 to 35). Notably, physical capacity improved as well, documented by an improved walking distance (439 m; +22%). This is the first case of a patient with AD in the context of PAH treated with MCT. The case report suggests that MCT is a possible psychotherapeutic treatment option for AD in the context of a potentially life-threatening disease. The study design does not permit an attribution of outcome to MCT but it suggests MCT is a potentially viable and acceptable treatment option.",16641078,PSYCHOLOGY
10.3389/fpsyg.2020.00225,Southerners Are Wiser Than Northerners Regarding Interpersonal Conflicts in China,"Initial evidence suggests that cultural differences have consequences for wise reasoning (perspective taking, consideration of change and alternatives, intellectual humility, search for compromise, and adopting an outsider’s vantage point), with more reports of wise reasoning about interpersonal conflicts among Japanese (as compared to American) young and middle-aged adults. Similarly, we found that people from the rice-farming area of southern China also exhibited greater wise reasoning when they encountered conflicts with a friend or in the workplace than those from the wheat-farming area of northern China (N = 487, 25 provinces). The relationship between rice farming and wise reasoning was mediated by loyalty/nepotism. This research advances study of the relationship between wisdom and culture. It also provides evidence for the influence of social-ecological factors on wisdom and culture.",16641078,PSYCHOLOGY
10.3389/fpsyg.2020.00038,How Does Work Motivation Impact Employees’ Investment at Work and Their Job Engagement? A Moderated-Moderation Perspective Through an International Lens,"This paper aims at shedding light on the effects that intrinsic and extrinsic motivation, as predictors, have on heavy work investment of time and effort and on job engagement. Using a questionnaire survey, this study conducted a moderated-moderation analysis, considering two conditional effects—worker’s status (working students vs. non-student employees) and country (Israel vs. Japan)—as potential moderators, since there are clear cultural differences between these countries. Data were gathered from 242 Israeli and 171 Japanese participants. The analyses revealed that worker’s status moderates the effects of intrinsic and extrinsic motivation on heavy work investment of time and effort and on job engagement and that the moderating effects were conditioned by country differences. Theoretical and practical implications and future research suggestions are discussed.",16641078,PSYCHOLOGY
10.3390/cancers12020503,A Novel pH-Tunable Secondary Conformation Containing Mixed Micellar System in Anticancer Treatment,"In this study, for the first time, we precisely assembled the poly-γ-benzyl-l-glutamate and an amphiphilic copolymer d-α-tocopherol polyethylene glycol succinate into a mixed micellar system for the embedment of the anticancer drug doxorubicin. Importantly, the intracellular drug-releasing behaviors could be controlled by changing the secondary structures of poly-γ-benzyl-l-glutamate via the precise regulation of the buffer’s pH value. Under neutral conditions, the micellar architectures were stabilized by both α-helix secondary structures and the microcrystalline structures. Under acidic conditions (pH 4.0), the interior structures transformed into a coil state with a disordered alignment, inducing the release of the loaded drug. A remarkable cytotoxicity of the Dox-loaded mixed micelles was exhibited toward human lung cancer cells in vitro. The internalizing capability into the cancer cells, as well as the intracellular drug-releasing behaviors, were also identified and observed. The secondary structures containing Dox-loaded mixed micelles had an outstanding antitumor efficacy in human lung cancer A549 cells-bearing nude mice, while little toxicities occurred or interfered with the hepatic or renal functions after the treatments. Thus, these pH-tunable α-helix-containing mixed micelles are innovative and promising for controlled intracellular anticancer drug delivery.",20726694,ONCOLOGY
10.3389/feduc.2020.00018,Three Flute Players’ Lived Experiences of Dalcroze Eurhythmics in Preparing Contemporary Music for Performance,"This qualitative study presents an interpretative phenomenological analysis of the lived experiences of three flute players who practice Dalcroze Eurhythmics, an approach to teaching, learning, and understanding music through exploring various music-movement relationships in social, creative, and rigorous ways. Our research seeks to understand how these individuals make sense of their lived experiences of Dalcroze Eurhythmics in learning, rehearsing, and performing contemporary music. Data collected through semi-structured interviews were analyzed and interpreted to create codes and categories in each data set. A cross-case analysis brought to light eight main themes: Body and breath; The body as a ‘way in’; Learning through the body overcomes specific technical difficulties; An embodied relationship with the score; Deeper knowledge and connection to music; Clarifying own interpretations; Communication with the audience; A bigger picture beyond the instrument. This study provides new insights into how learning through Dalcroze Eurhythmics can help individuals prepare repertoire for performance. As such, it may be of use to Dalcroze students and teachers, to flute performers and teachers, and to teachers and performers of other instruments who wish to explore the potential of Dalcroze Eurhythmics in learning, rehearsing, and performing contemporary music. The analysis also reveals insights that may be relevant to other repertoires.",2504284X,EDUCATION
10.3389/fonc.2020.00192,Clinico-Immunological Profile of a 67-Year-Old Woman Affected by HER2-Positive Breast Cancer and Autoimmune Dermatomyositis,"A patient with HER2-positive early breast cancer (BC) developed dermatomyositis (DM), which disappeared after the first administration of adjuvant trastuzumab. No HER2 overexpression/amplification was observed in DM skin biopsies. Both BC and skin immune infiltrates were composed mostly of CD3+ T-lymphocytes. Interestingly, tumor-infiltrating lymphocytes expressed PD-1, which was negligible in skin-infiltrating lymphocytes, while both BC cells and keratinocytes were PD-L1-positive. High serum levels of endogenous anti-HER2 antibodies were detected, confirming the induction of a HER2-specific adaptive immune response. It may be argued that HER2-specific T-lymphocytes cross-reacted with one or more unknown skin antigens, causing DM. Trastuzumab may have silenced skin cross-reaction by eliminating any residual HER2-positive micrometastatic disease and, thus, inducing DM remission.",2234943X,ONCOLOGY
10.3389/fonc.2020.00212,Mouse Tumor-Bearing Models as Preclinical Study Platforms for Oral Squamous Cell Carcinoma,"Preclinical animal models of oral squamous cell carcinoma (OSCC) have been extensively studied in recent years. Investigating the pathogenesis and potential therapeutic strategies of OSCC is required to further progress in this field, and a suitable research animal model that reflects the intricacies of cancer biology is crucial. Of the animal models established for the study of cancers, mouse tumor-bearing models are among the most popular and widely deployed for their high fertility, low cost, and molecular and physiological similarity to humans, as well as the ease of rearing experimental mice. Currently, the different methods of establishing OSCC mouse models can be divided into three categories: chemical carcinogen-induced, transplanted and genetically engineered mouse models. Each of these methods has unique advantages and limitations, and the appropriate application of these techniques in OSCC research deserves our attention. Therefore, this review comprehensively investigates and summarizes the tumorigenesis mechanisms, characteristics, establishment methods, and current applications of OSCC mouse models in published papers. The objective of this review is to provide foundations and considerations for choosing suitable model establishment methods to study the relevant pathogenesis, early diagnosis, and clinical treatment of OSCC.",2234943X,ONCOLOGY
10.3390/educsci10030046,An Experiential Online Training Approach for Underrepresented Engineering and Technology Students,"Workforce pipelines are essential to sustain a productive workforce in an increasingly competitive, high-tech environment. Advanced automation, sensors, materials and data analytics will increase the need for highly skilled workers in the manufacturing (and manufactured construction) sector. Attracting and developing the next-generation workforce is not without its challenges; however, students are often deficient in technical skills and generally have negative perceptions about manufacturing and construction. As a result, new education and training models have been developed to provide instruction at all levels of the educational system, with a focus on both traditional students and non-traditional students, including ethnic minorities, women, veterans, disabled persons and older adult learners. This study focused specifically on certain underrepresented students in STEM programs offered at community colleges in the Great Plains region of the U.S. An available online training program by the Society of Manufacturing Engineers was used as a contextualized online training tool. The Learning Management System embedded in this online training tool was used to gather student data. Conducting multiple regression analyses on the test outcomes, completion rates, and improvement between post-test and pre-test scores showed that female participants achieved greater improvement between pre- and post-test scores than males, and achieved higher rates of credentialing compared to all other demographic groups. African American participants achieved greatest improvement between pre- and post-test scores than all other ethnic groups while Hispanics achieved higher rates of module completion. Additionally, this study also examines the background related to contextualized teaching and learning, as well as the effectiveness of this delivery method for these underrepresented populations.",22277102,EDUCATION
10.1186/s40594-020-00206-7,Exploring STEM postsecondary instructors’ accounts of instructional planning and revisions,"Background: Local and national initiatives to improve the learning experiences of students enrolled in Science, Technology, Engineering, and Mathematics (STEM) courses have been on-going for a couple of decades with a heightened momentum within the last 10 years. However, recent large-scale studies have demonstrated that transmission of information is still the primary mode of instruction in STEM courses across the undergraduate curriculum. The limited impact of instructional change reform efforts can be partly explained by the one-sided focus of educational research on the development of evidence-based instructional practices and production of evidence demonstrating their impact on student learning. This has been done at the expense of understanding faculty members’ instructional practices and mindsets about teaching and learning that underlie their practices. This study addresses this gap in the literature by characterizing STEM instructors’ instructional intentions and reflections on their teaching performance for a week of instruction. Data was collected through semi-structured interviews with 42 STEM faculty members from one doctorate-granting institution in the USA. Results: STEM instructors in this study had teacher-centric mindsets with respect to their instructional planning (e.g., content-focused learning goals, lecture is seen as an engagement strategy). We found that these instructors mostly saw formative assessment tools as engagement strategy rather than tools to monitor student learning. Reflections on their level of satisfaction with their week of teaching focused heavily on content coverage and personal feelings and minimally considered student learning. Finally, we found that pedagogical discontent was not a driver of planned course revisions. Conclusions: This study identifies mismatches between STEM instructors’ teaching mindsets and current approaches to instructional change. STEM instructors in this study paid minimal attention to student learning when considering course-level revisions and many of their reflections were anchored in their personal feelings. However, instructional reform strategies often attempt to convince faculty of a new approach by demonstrating its impact on student learning. The misalignment identified in this study further highlights the need to better characterize STEM instructors’ cognition around teaching so that reform efforts can better meet them where they are.",21967822,EDUCATION
10.3390/ai1010006,R-KG: A Novel Method for Implementing a Robot Intelligent Service,"Aiming to solve the problem of environmental information being difficult to characterize when an intelligent service is used, knowledge graphs are used to express environmental information when performing intelligent services. Here, we specially design a kind of knowledge graph for environment expression referred to as a robot knowledge graph (R-KG). The main work of a R-KG is to integrate the diverse semantic information in the environment and pay attention to the relationship at the instance level. Also, through the efficient knowledge organization of a R-KG, robots can fully understand the environment. The R-KG firstly integrates knowledge from different sources to form a unified and standardized representation of a knowledge graph. Then, the deep logical relationship hidden in the knowledge graph is explored. To this end, a knowledge reasoning model based on a Markov logic network is proposed to realize the self-developmental ability of the knowledge graph and to further enrich it. Finally, as the strength of environment expression directly affects the efficiency of robots performing services, in order to verify the efficiency of the R-KG, it is used here as the semantic map that can be directly used by a robot for performing intelligent services. The final results prove that the R-KG can effectively express environmental information.",26732688,AI
10.1186/s40594-020-00205-8,Conceptual framework of STEM based on Japanese subject principles,"Background: School education should improve science, technology, engineering, and mathematics (STEM) ability not only in science and mathematics but also in technology and engineering. However, practice and research are being conducted without clear definitions and methods for STEM education. Moreover, the positioning and characteristics of the technology included in each STEM field are unclear. Therefore, it is necessary to propose an appropriate framework for practice of STEM from the viewpoint of technology education. In response to this need, this commentary proposes a conceptual framework for the appropriate practice of STEM education. Results: First, we referred to the perspectives and thinking styles of the fields of science, technology, and mathematics in the Japanese curriculum to specify the approach of the education system to each subject included in STEM. Next, to determine the concept of engineering in STEM education, we referred to the definition of engineering presented in Japan, the USA, and the UK. We positioned engineering, which means creating structures, processes, systems, etc., as a practical STEM activity and attempted to relate it to the unique perspectives and thinking styles of mathematics, science, and technology. Conclusion: We proposed a conceptual framework for the appropriate practice of STEM education based on the principles of subjects in the Japanese curriculum. The conceptual framework suggests that a means to improve the practice of STEM education is to retain the principles of science, technology, and mathematics in the activity of engineering. It can be inferred that the key point for practicing STEM education is to examine and design the appropriate order and combination of the learning process and activities based on the proposed conceptual framework. Although this framework is theoretical, it can be useful in determining an adequate practice of STEM education and clarifying the relationship between STEM education and technology education.",21967822,EDUCATION
10.3390/ejihpe10010037,The Role of Field Training in STEM Education: Theoretical and Practical Limitations of Scalability,"In this article, we consider the features of the perception of student information in science, technology, engineering, and mathematics (STEM) education, in order to draw the attention of researchers to the topic of learning in practice through field training. The article shows the results of these studies in Russia and the Commonwealth of Independent States (CIS countries: Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, and Uzbekistan, as an example) to reflect the global trends. For this purpose, we examined the expectations of students in Russia and the CIS countries from training related to lectures and field training. We created a questionnaire and distributed it in three Moscow-based universities (Moscow State University of Geodesy and Cartography—MIIGAiK, Moscow Aviation Institute—MAI, and Moscow City University—MCU). Our key assumption is that field practices in Russian universities are qualitatively different from the phenomenon described in European literature, where digital or remote field practices have already emerged. The results obtained through the survey show the tendency of students’ perceptions to fulfill practical duties (in a laboratory with instruments of field training) in STEM education.",22549625,PSYCHOLOGY
10.3390/cancers12030640,"Proton Pump Inhibitors Reduce Pancreatic Adenocarcinoma Progression by Selectively Targeting H+, K+-ATPases in Pancreatic Cancer and Stellate Cells","Pancreatic duct cells are equipped with acid/base transporters important for exocrine secretion. Pancreatic ductal adenocarcinoma (PDAC) cells may utilize such transporters to acidify extracellular tumor microenvironment, creating a niche favoring cell proliferation, fibrosis and resistance to chemotherapy—all contributing to the notoriously bad prognosis of this disease. Here, we report that gastric and non-gastric H+, K+-ATPases (coded by ATP4A and ATP12A) are overexpressed in human and murine pancreatic cancer and that we can target them specifically with proton pump inhibitors (PPIs) and potassium-competitive acid blockers (P-CABs) in in vitro models of PDAC. Focusing on pantoprazole, we show that it significantly reduced human cancer cell proliferation by inhibiting cellular H+ extrusion, increasing K+ conductance and promoting cyclin D1-dependent cell cycle arrest and preventing STAT3 activation. Pantoprazole also decreased collagen secretion from pancreatic stellate cells. Importantly, in vivo studies show that pantoprazole treatment of tumor-bearing mice reduced tumor size, fibrosis and expression of angiogenic markers. This work provides the first evidence that H+, K+-ATPases contribute to PDAC progression and that these can be targeted by inhibitors of these pumps, thus proving a promising therapeutic strategy.",20726694,ONCOLOGY
10.3389/fonc.2020.00324,Macrophage and Tumor Cell Cross-Talk Is Fundamental for Lung Tumor Progression: We Need to Talk,"Regardless of the promising results of certain immune checkpoint blockers, current immunotherapeutics have met a bottleneck concerning response rate, toxicity, and resistance in lung cancer patients. Accumulating evidence forecasts that the crosstalk between tumor and immune cells takes center stage in cancer development by modulating tumor malignancy, immune cell infiltration, and immune evasion in the tumor microenvironment (TME). Cytokines and chemokines secreted by this crosstalk play a major role in cancer development, progression, and therapeutic management. An increased infiltration of Tumor-associated macrophages (TAMs) was observed in most of the human cancers, including lung cancer. In this review, we emphasize the role of cytokines and chemokines in TAM-tumor cell crosstalk in the lung TME. Given the role of cytokines and chemokines in immunomodulation, we propose that TAM-derived cytokines and chemokines govern the cancer-promoting immune responses in the TME and offer a new immunotherapeutic option for lung cancer treatment.",2234943X,ONCOLOGY
10.1186/s40594-020-00209-4,Effects of school climate and teacher self-efficacy on job satisfaction of mostly STEM teachers: a structural multigroup invariance approach,"Background: Identification and retention of effective teachers in STEM education play cardinal roles in teacher recruitment exercises worldwide. Studies on factors that characterize effective teachers have therefore gained popularity in recent times. Teacher self-efficacy, job satisfaction and school climate are among other factors that have attracted global attention. Thus, proper understanding of the relations between these factors is equally important. The purpose of this study is to validate and cross-validate a model of direct/indirect effects of school climate and teacher self-efficacy on job satisfaction. Results: The data used for the current study are extracted from a publicly available data of Teaching and Learning International Survey (TALIS) 2018 survey. Structural equation modeling approach was used in the analyses coupled with robust maximum likelihood to ensure accurate estimations in the models. The results of the validated models show a strong direct impact of school climate on job satisfaction, a direct impact of teacher self-efficacy on job satisfaction and a mediating effect of teacher self-efficacy between school climate and job satisfaction. This model exhibits structural invariance in factor loadings, intercepts and regression weights across two independent samples from a population of 3951 lower secondary school teachers in Norway. Conclusion: The findings of this study do provide empirical evidence for the relations between teacher self-efficacy, job satisfaction and school climate among Norwegian lower secondary school teachers. The cross-validation of these relations was also established using an independent sample to enhance generalization of the findings. Two methodological observations concerning recoding of some items as well as an addition of item cross-loading in the measurement model of the job satisfaction scales are raised and addressed. It is therefore recommended that researchers who will be using TALIS 2018 data should take note of these observations.",21967822,EDUCATION
10.1186/s40594-020-00207-6,Research and trends in STEM education: a systematic review of journal publications,"With the rapid increase in the number of scholarly publications on STEM education in recent years, reviews of the status and trends in STEM education research internationally support the development of the field. For this review, we conducted a systematic analysis of 798 articles in STEM education published between 2000 and the end of 2018 in 36 journals to get an overview about developments in STEM education scholarship. We examined those selected journal publications both quantitatively and qualitatively, including the number of articles published, journals in which the articles were published, authorship nationality, and research topic and methods over the years. The results show that research in STEM education is increasing in importance internationally and that the identity of STEM education journals is becoming clearer over time.",21967822,EDUCATION
10.3389/fpsyg.2020.00356,A Multiple-Baseline Evaluation of Acceptance and Commitment Therapy Focused on Repetitive Negative Thinking for Comorbid Generalized Anxiety Disorder and Depression,"Repetitive negative thinking (RNT) is a core feature of generalized anxiety disorder (GAD) and depression. Recently, some studies have shown promising results with brief protocols of acceptance and commitment therapy (ACT) focused on RNT in the treatment of emotional disorders in adults. The current study analyzes the effect of an individual, 3-session, RNT-focused ACT protocol in the treatment of severe and comorbid GAD and depression. Six adults meeting criteria for both disorders and showing severe symptoms of at least one of them participated in the study. A delayed multiple-baseline design was implemented. All participants completed a 5-week baseline without showing improvement trends in emotional symptoms (Depression Anxiety and Stress Scale – 21; DASS-21) and pathological worry (Penn State Worry Questionnaire; PSWQ). The ACT protocol was then implemented, and a 3-month follow-up was conducted. Five of the six participants showed clinically significant changes in the DASS-21 and the PSWQ. The standardized mean difference effect sizes for single-case experimental design were very large for emotional symptoms (d = 3.34), pathological worry (d = 4.52), experiential avoidance (d = 3.46), cognitive fusion (d = 3.90), repetitive thinking (d = 4.52), and valued living (d = 0.92 and d = 1.98). No adverse events were observed. Brief, RNT-focused ACT protocols for treating comorbid GAD and depression deserve further empirical tests.",16641078,PSYCHOLOGY
10.1186/s40594-020-00210-x,Integrating science and engineering practices: outcomes from a collaborative professional development,"Background: The Next Generation Science Standards accentuate engineering design along with scientific inquiry, emphasizing the relationship between scientific investigations and engineering design in solving problems and devising new ideas and technologies. The goal is for students to realize the importance of science and engineering in innovation and in solving many of today’s challenges. The Next Generation Science Standards contends that a working knowledge and practicality of engineering design prepares students for embracing the challenges of the future. To support students in developing these capabilities, teachers are tasked with the responsibility of facilitating science instruction that integrates science and engineering practices. This is a challenge since a majority of them have little to no understanding of engineering applications.Results: An interdisciplinary team, consisting of science education and mechanical engineering faculty and doctoral students from each discipline, and science, mathematics, and career and technical curriculum supervisors, collaborated with middle school science, mathematics, and career and technical education teachers to develop a framework for integrating engineering practices into their curricula. The exploratory nature of the project, and instructional outcomes with their students, supported teachers in developing an understanding and value for science and engineering practices. As a result, they were motivated to critique and revise their practices, aiming to develop and implement instruction that they perceived as beneficial to their students.Conclusion: With the surge in emphasis on preparing K-12 students for the STEM workforce, initiatives devoted to exposing teachers and students to STEM applications have also increased. The findings from this study could be useful for informing these initiatives, since they reveal the learning experiences of the teachers while processing instructional strategies for integrating science and engineering practices into their curriculum. The findings highlight factors that motivated these teachers to reform their instructional practices, as well as their deliberations while endeavoring to assimilate the strategies into their curricular activities.",21967822,EDUCATION
10.1186/s40594-020-00208-5,Rubrics to assess critical thinking and information processing in undergraduate STEM courses,"Background: Process skills such as critical thinking and information processing are commonly stated outcomes for STEM undergraduate degree programs, but instructors often do not explicitly assess these skills in their courses. Students are more likely to develop these crucial skills if there is constructive alignment between an instructor’s intended learning outcomes, the tasks that the instructor and students perform, and the assessment tools that the instructor uses. Rubrics for each process skill can enhance this alignment by creating a shared understanding of process skills between instructors and students. Rubrics can also enable instructors to reflect on their teaching practices with regard to developing their students’ process skills and facilitating feedback to students to identify areas for improvement. Results: Here, we provide rubrics that can be used to assess critical thinking and information processing in STEM undergraduate classrooms and to provide students with formative feedback. As part of the Enhancing Learning by Improving Process Skills in STEM (ELIPSS) Project, rubrics were developed to assess these two skills in STEM undergraduate students’ written work. The rubrics were implemented in multiple STEM disciplines, class sizes, course levels, and institution types to ensure they were practical for everyday classroom use. Instructors reported via surveys that the rubrics supported assessment of students’ written work in multiple STEM learning environments. Graduate teaching assistants also indicated that they could effectively use the rubrics to assess student work and that the rubrics clarified the instructor’s expectations for how they should assess students. Students reported that they understood the content of the rubrics and could use the feedback provided by the rubric to change their future performance. Conclusion: The ELIPSS rubrics allowed instructors to explicitly assess the critical thinking and information processing skills that they wanted their students to develop in their courses. The instructors were able to clarify their expectations for both their teaching assistants and students and provide consistent feedback to students about their performance. Supporting the adoption of active-learning pedagogies should also include changes to assessment strategies to measure the skills that are developed as students engage in more meaningful learning experiences. Tools such as the ELIPSS rubrics provide a resource for instructors to better align assessments with intended learning outcomes.",21967822,EDUCATION
10.1186/s40359-020-0391-z,The use of a psychological testing instrument as an indicator of dissatisfaction with aesthetic dental treatment – a preliminary study,"Background: The use of psychological testing to indicate the potential for dissatisfaction with dental treatment has many potential patient and clinician benefits but has been rarely investigated. The study aimed to explore the use of the Symptom Checklist-90-Revised (SCL-90-R) psychological testing instrument in describing the relationship between pre-treatment psychological traits and aesthetic restorative treatment satisfaction. Methods: Thirty patients requiring aesthetic restorative dental treatment completed three questionnaires, namely 1) a pre-treatment expectation assessment, 2) an SCL-90-R analysis pre-treatment and 3) an outcome assessment post-treatment to assess patient’s expectations and satisfaction of the proposed dental treatment relating to function, aesthetics, comfort and tissue preservation. Logistic regression models were used to assess the impact of psychological variables on patient satisfaction after adjusting for baseline expectations (P < 0.05). Results: The satisfaction for the aesthetic component of treatment was significantly associated with psychoticism and positive symptom distress index. The satisfaction for the comfort component of treatment was significantly associated with obsessive compulsive symptoms, depression and anxiety. Following adjustment for baseline expectation, tissue preservation satisfaction was associated with somatization, obsessive compulsive, interpersonal sensitivity, depression and global severity index. No baseline psychological measures were significantly associated with chewing satisfaction. Conclusions: The SCL-90-R shows initial promise in assisting clinicians to identify and understanding patients who have a high risk of dissatisfaction with aesthetic dental treatment. The ability to indicate aesthetic restorative treatment dissatisfaction is of great benefit to clinicians in maximising success and mitigating risk.",20507283,PSYCHOLOGY
10.3389/frai.2020.00009,Toward a Taxonomy for Adaptive Data Visualization in Analytics Applications,"Data analytics as a field is currently at a crucial point in its development, as a commoditization takes place in the context of increasing amounts of data, more user diversity, and automated analysis solutions, the latter potentially eliminating the need for expert analysts. A central hypothesis of the present paper is that data visualizations should be adapted to both the user and the context. This idea was initially addressed in Study 1, which demonstrated substantial interindividual variability among a group of experts when freely choosing an option to visualize data sets. To lay the theoretical groundwork for a systematic, taxonomic approach, a user model combining user traits, states, strategies, and actions was proposed and further evaluated empirically in Studies 2 and 3. The results implied that for adapting to user traits, statistical expertise is a relevant dimension that should be considered. Additionally, for adapting to user states different user intentions such as monitoring and analysis should be accounted for. These results were used to develop a taxonomy which adapts visualization recommendations to these (and other) factors. A preliminary attempt to validate the taxonomy in Study 4 tested its visualization recommendations with a group of experts. While the corresponding results were somewhat ambiguous overall, some aspects nevertheless supported the claim that a user-adaptive data visualization approach based on the principles outlined in the taxonomy can indeed be useful. While the present approach to user adaptivity is still in its infancy and should be extended (e.g., by testing more participants), the general approach appears to be very promising.",26248212,AI
10.3390/educsci10030081,Teacher Training in Intercultural Education: Teacher Perceptions,"Background: The aim of the present study was to evaluate teacher perceptions on the training received in intercultural education. Methods: The article presents a quantitative, non- experimental and ex-post-facto type of research; directed to inquire about the perceptions of the teachers of primary education in Andalusia (Spain) in relation to the intercultural training received. Based on the descriptive survey method, two questionnaires were administered to a sample composed of 320 students and 80 teachers. Results: The results show certain strengths of the training teacher programs in the field of interculturality (encouragement of reflection, participation and collaboration …), as well as weaknesses (decontextualization, inflexibility, primacy of theoretical learning, non-transversal character, etc.). Conclusions: Despite strengths, intercultural teacher training continues to be a challenge in Andalusia.",22277102,EDUCATION
10.3390/cancers12030745,A Disintegrin and Metalloproteinase 9 (ADAM9) in Advanced Hepatocellular Carcinoma and Their Role as a Biomarker During Hepatocellular Carcinoma Immunotherapy,"The chemotherapeutics sorafenib and regorafenib inhibit shedding of MHC class I-related chain A (MICA) from hepatocellular carcinoma (HCC) cells by suppressing a disintegrin and metalloprotease 9 (ADAM9). MICA is a ligand for natural killer (NK) group 2 member D (NKG2D) and is expressed on tumor cells to elicit attack by NK cells. This study measured ADAM9 mRNA levels in blood samples of advanced HCC patients (n = 10). In newly diagnosed patients (n = 5), the plasma ADAM9 mRNA level was significantly higher than that in healthy controls (3.001 versus 1.00, p < 0.05). Among four patients treated with nivolumab therapy, two patients with clinical response to nivolumab showed significant decreases in fold changes of serum ADAM9 mRNA level from 573.98 to 262.58 and from 323.88 to 85.52 (p < 0.05); however, two patients with no response to nivolumab did not. Using the Cancer Genome Atlas database, we found that higher expression of ADAM9 in tumor tissues was associated with poorer survival of HCC patients (log-rank p = 0.00039), while ADAM10 and ADAM17 exhibited no such association. In addition, ADAM9 expression showed a positive correlation with the expression of inhibitory checkpoint molecules. This study, though small in sample size, clearly suggested that ADAM9 mRNA might serve as biomarker predicting clinical response and that the ADAM9-MICA-NKG2D system can be a good therapeutic target for HCC immunotherapy. Future studies are warranted to validate these findings.",20726694,ONCOLOGY
10.3390/cancers12030755,Landscape of Mitochondria Genome and Clinical Outcomes in Stage 1 Lung Adenocarcinoma,"Risk factors including genetic effects are still being investigated in lung adenocarcinoma (LUAD). Mitochondria play an important role in controlling imperative cellular parameters, and anomalies in mitochondrial function might be crucial for cancer development. The mitochondrial genomic aberrations found in lung adenocarcinoma and their associations with cancer development and progression are not yet clearly characterized. Here, we identified a spectrum of mitochondrial genome mutations in early-stage lung adenocarcinoma and explored their association with prognosis and clinical outcomes. Next-generation sequencing was used to reveal the mitochondrial genomes of tumor and conditionally normal adjacent tissues from 61 Stage 1 LUADs. Mitochondrial somatic mutations and clinical outcomes including relapse-free survival (RFS) were analyzed. Patients with somatic mutations in the D-loop region had longer RFS (adjusted hazard ratio, adjHR = 0.18, p = 0.027), whereas somatic mutations in mitochondrial Complex IV and Complex V genes were associated with shorter RFS (adjHR = 3.69, p = 0.012, and adjHR = 6.63, p = 0.002, respectively). The risk scores derived from mitochondrial somatic mutations were predictive of RFS (adjHR = 9.10, 95%CI: 2.93–28.32, p < 0.001). Our findings demonstrated the vulnerability of the mitochondrial genome to mutations and the potential prediction ability of somatic mutations. This research may contribute to improving molecular guidance for patient treatment in precision medicine.",20726694,ONCOLOGY
10.3389/fonc.2020.00377,Editorial: Precision/Personalized Pediatric Oncology and Immune Therapies: Rather Customize Than Randomize,"Editorial on the Research Topic Precision/Personalized Pediatric Oncology and Immune Therapies: Rather Customize Than Randomize Personalization of treatment based on biological markers is being utilized in clinical medicine with increasing frequency. This trend, despite an effort to identify possible common patterns, reflects the reality that no two patients are alike, and no single clinical course is identical; not even within a group of seemingly similar patients (1). There are numerous clinical variations related to host or environment-dependent factors. Numerous examples of these interpersonal differences have been recognized with drugs such as pain-control medications, heart medications, or antimicrobials. The differences have been attributed to increased pharmacometabolic capacity, to different individual microbiomes and to genetic differences between individuals (2). The latter has led to development of an entirely new specialty—pharmacogenomics. While this clinical heterogeneity is well-appreciated in most major medical specialties, clinical oncology seems to represent, surprisingly enough, one of the exceptions (3, 4). Individualized treatments aim to optimize patient outcomes based on specific knowledge about diseases and their biological heterogeneity (5). This individualization of therapy is being adopted even in adult oncology where, at least traditionally, new therapeutic directions depended on success in large randomized clinical trials. Even in cancers where the numbers of adult patients are sufficient for large randomized double-blind clinical trials, the recent trends are to select the most suitable, genetically homogeneous, target population. This trend has been more inherent to pediatrics, where malignancies are implicitly considered rare diseases. However, the smaller populations and a personalized approach, has led to a very small number of drugs being approved for pediatric indications. The small number of patients and more personalized combinations of drugs tended to complicate statistical analysis and created problems for providing evidence of treatment efficacy in children with rare malignancies (Kyr et al.). When a large homogeneous population can be used—a randomized, double blind, placebo controlled trial should remain the gold standard. However, this is rarely possible considering cancer heterogeneity and interpersonal differences in drug response. In pediatrics, the numbers of patients are relatively small and the diseases heterogeneous. The process of randomization and blinding were originally developed to protect the subjects and the investigators from pre-existing subjective preferences for a procedure or a compound under evaluation (6, 7). Randomization was intended to minimalize the effect of confounders, to achieve comparable groups and to permit calculation of an unbiased estimate of the treatment effect. While the use of “blinding” in order to eliminate bias is obvious, there is another important tool that makes randomized trials powerful with regard to rendering reliable and unbiased results. It is the balancing effect between investigated groups, especially with respect unknown covariates that cannot be easily eliminated through model adjustments nor stratification. As stressed above, randomization requires sufficient number of patients and adequate sample size to work. A test sample >200 is said to be less likely to be imbalanced for an important covariate (8). But in rare diseases, where the sample sizes are small (rarely more than a hundred), the usefulness of randomization for balancing of the groups is lost. Similarly, randomized, double blind, placebo-controlled trials may not be suitable for populations that are selected on a common, but infrequent genetic alteration(s). Those groups are also quite small. While the gold standard of clinical trials, a randomized, double blind, placebo controlled trial, may have made logical sense in the era before genomics, it may need to be modified for the era informed by testing for individualized traits and smaller groups. The concept of time-dependent variations is equally important (9). As documented in numerous recent publications, variations within an individual and implicitly, within the individual's macroscopic tumor, occur at velocity rates that cannot be measured by any contemporary techniques (10). It is this variability that constitutes a fundamental concern with the use of treatment group randomization. For a set of individuals being randomized using current rules, a critical prior assumption is made that all randomized individuals are, and will remain, biologically homogenous, and any further events can only be related to the time point of randomization. A further assumption is then made that no change within the set of investigated subjects occurs during the study period except the changes due to treatment. This is not true for cancers, which are known to evolve through continuously accumulating additional genomic alterations through mutations. Consequently, even if randomization was performed at baseline, the randomization effect is lost in any repeated evaluation during subsequent phases of such trials (11). Single patient trial designs or “N = 1” trials (12) are an alternative to population-based clinical trials, but a broad clinical application of this approach is hindered by the absence of a standardized work-up. Current practices are based on physician-specific or institution-enabled assessments of the biological characteristics of the patient and of the cancer tissue. This usually occurs in the form of a multidisciplinary institutional expert consensus referred to as “tumor boards” (13). This personalized treatment approach allows for consideration of disease heterogeneity as well as of time-dependent variations. This clinical plasticity, allows for treatment to be modified at various phases of the patient's journey based on disease course or on the patient's pharmacometabolic capacity to tolerate the selected treatment. The much-needed standardization of the pre-treatment workup of a patient selected to undergo personalized therapy would enable collection of outcomes from these “N = 1” trials in pediatric cancer across many institutions, enable statistical analysis, and provide evidence for changing therapeutic paradigms. Another issue arising in rare diseases, and therefore personalized pediatric oncology, is the identification of future target population likely to benefit from a trial result—the so called “patient horizon” (14). Patient horizon is either the number of patients in the trial, or the number who have the condition under treatment. This well-known concept is rarely utilized. To improve understanding of this concept let us take an extreme situation where all patients from the target population were randomized in 1:1 ratio for effective and ineffective treatment. In this case half of the patients are forced to receive an ineffective treatment as a price for knowing the absolute truth about the relative treatment efficacy between the two treatments. Yet, the same result could be obtained by giving either of the treatment randomly without any knowledge. An optimal size of a trial balances both extremes and maximizes the number of patients who benefit. The exact number of patients may not be known, but the order of magnitude of the optimal number can be calculated using the square root of the patient horizon size for a simple trial design. For example, for a finite population of 1,000 subjects, the optimal size of a trial is a few tenths. Considering disease rarity, especially in the era of molecular medicine, the issue of the target population size (the patient horizon) becomes relevant not in pediatric oncology, but in medicine in general (14). There are two principal issues to be addressed in current cancer medicine pertaining to: (i) Regulatory mechanisms of drug approval and market authorization. (ii) Evaluation of real-life clinical efficacy. A newly proposed drug approval marketing authorization pathway shall require an initial “Candidate Medicinal Product Safety Evaluation” (CMPSE, currently Phase I) and subsequent “Dose Defining Study” (DDS, currently Phase II). As we explained above a current medicinal product approval pathway is mechanistically “drug-centric” as the present practice relies on the ability of a Phase III clinical trial to provide evidence that the addition of a single compound to a standard treatment regimen is of clinical benefit leading to marketing authorization. This approach has become so biased that most resulting Phase III registration trial data do not provide clinically meaningful benefit (3); on top of that, testing for “me-too” drugs toward endpoints as “substantial equivalence or non-inferiority” is vastly contributing. Furthermore, it disregards the clinical need for different pathways for approval of medicines intended for use (A) in the entire world population (e.g., vaccines, antipyretics, pain killers, etc.) and for those intended for (B) specific subpopulations (e.g., LDL-C marker based treatments). In the latter setting, clinical laboratory diagnostics (CDx) are used as a guide or companion to a medicinal product to determine its applicability to a subject. A regulatory approval of medications targeting (C) somatic mutations, and/or (D) diseases that follow Mendelian inheritance or germline mutation (e.g., tyrosinemia type I. and the drug nitisinone) requires a special approval pathway and expedited translation to clinical practice. Summing up from a regulatory point of view, the testing phases CMPSE Phase I + DDS Phase II would allow for conditional medicinal product (pre)approval. Real-life clinical practice-based evaluation should then focus on designing “patient-centric” treatment strategies. Considering there are about 300 active drugs in oncology, and the number of 2 drugs combinations is about 45,000, or 4.4 million combinations for 3 drug combinations, Phase I testing for all these drug combinations is neither feasible nor realistic. New models such as: (i) identification of smaller pediatric cancer patient cohorts likely to benefit from a specific treatment because they have the relevant gene alteration(s), or (ii) the increasing use of multilayer profiling (markers) to diagnose, classify and monitor response in pediatric cancers (Fedorova et al.; Polaskova et al.) are therefore gaining in popularity. There is a need to validate combination treatment strategies, not just individual drugs or individual biomarkers. Attention should be directed at studying drug dosing in respective preclinical models and at identifying optimal biological dose rather than persist with the present maximum-tolerated dose. With most targeted agents, a target occupancy dose, i.e., dose required to stop/minimize pathway phosphorylation and RP2D /dose used in clinical setting (15) is the more appropriate identifier of a clinically relevant dose. As noted in many pre-clinical studies, combinations of targeted agents are often synergistic, and potentiate the effects of chemotherapy. A very good example of how combination therapy dosing can negatively influence the overall success of an innovative drug is the Mylotarg (gemtuzumab ozogamicin, alias GO) story. Gemtuzumab ozogamicin is a recombinant humanized IgG4 kappa antibody that is used to treat CD33 positive AML. It is conjugated with calicheamicin derivative, a cytotoxic antitumor antibiotic. The drug was initially tested in a randomized controlled trial leading to FDA approval via accelerated review in May 2000. However, the drug had intolerable toxicity and mortality at the 9 mg/m2 dose, and was voluntarily withdrawn from the market on 15th October 2010. It was subsequently tested at a much lower drug dose (3 mg/m2 instead of 9 mg/m2) and was shown to be just as effective with greatly improved safety profile. GO was therefore re-approved by the FDA on 1st September 2017 at lower dose (16). Taken together, if a new compound allowed to enter the real-life clinical practice-based evaluation (i.e., CMPSE + DDS passed) brings clinically meaningful benefit, this will lead to the full marketing authorization and consequently, reimbursement of such a novel compound. The use of chemotherapy in combination with a targeted biological agent is a commonly employed approach for enhancing the ability of chemotherapy to fight cancer. Commonly, the assumption that the inhibitory effect of the biological agent would be additive to the effect achieved by traditional chemotherapy or radiation is made. However, because of the synergistic action, the addition of a targeted biologic agent to a maximum tolerated dose (MTD) of chemotherapy, may make an already maximally toxic regimen almost lethal. In most cases, any benefit of tumor response ends up being concealed by unacceptable toxicities, and no overall survival benefit is seen. Yet, because the present design of clinical trials permits modification of only one variable between the two study arms, the dose of chemotherapy in the experimental treatment arm is rarely modified. The use of metronomic chemotherapy, with its goal of long-term “tumor control,” lower toxicity, and prevention of tumor progression (rather than immediate reduction in tumor size), may represent a more realistic strategy for testing targeted and immune therapies as add on to chemotherapy (13). However, because this low toxicity regimen can have a delayed onset of radiologically visible effect, it is often abandoned too early for a patient to benefit. An example of how biomarker assessment can help document the effects of targeted therapy earlier than it could be documented radiologically is provided in this issue (Polaskova et al.) discussing three patients with multiply relapsed Burkitt lymphoma treated with personalized therapy and their response being monitored using target phosphorylation. In summary, data for real-life evidence-based medicine addressing patient-focused clinical efficacy can be derived from time-dependent single-case designs. The new comprehensive efficacy evaluation model we present here, should be focused on treatment strategies using drug combinations rather than testing a single-compound within a randomized setting. We should modify the Phase III wherever feasible. The drug approval pathway should consist of “Candidate Medicinal Product Safety Evaluation” (previously Phase I) and “Dose Defining Study” (previously Phase II). This will bypass the often futile end-of-life enrollments in single drug clinical trials and bring about substantial cost reductions in development and implementation of new medicinal anticancer compounds to the market. All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. LM2018125, AZV MZCR 16-33209A, 16-34083A, LQ1605, LO1604, LO1413, and LQ1601 projects from the National Program of Sustainability II (MEYS). 1. Liu K, Meng XL. There is individualized treatment. Why not individualized inference? Annu Rev Stat Its Appl. (2016) 3:79–111. doi: 10.1146/annurev-statistics-010814-020310 CrossRef Full Text | Google Scholar 2. Roden DM, McLeod HL, Relling MV, Williams MS, Mensah GA, Peterson JF, et al. Pharmacogenomics. Lancet. 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Efficiency of new dose escalation designs in dose-finding phase I trials of molecularly targeted agents. PLoS ONE. (2012) 7:e51039. doi: 10.1371/journal.pone.0051039 PubMed Abstract | CrossRef Full Text | Google Scholar 16. Umukoro C. A Start, Stop, GO Story in AML – Gemtuzumab Ozogamicin (Mylotarg®). (2017) Available online at: (accessed January 9, 2020). Keywords: personalized medicine, precision oncology, pediatric oncology, trial models, drug models, personalized precision pediatric oncology, clinical trial designs Citation: Kýr M, Klement GL, Zdrazilova-Dubska L, Demlova R, Valik D, Slaby O, Slavc I and Sterba J (2020) Editorial: Precision/Personalized Pediatric Oncology and Immune Therapies:...",2234943X,ONCOLOGY
10.3389/fpsyg.2020.00524,Onlife Extremism: Dynamic Integration of Digital and Physical Spaces in Radicalization,"This article argues that one should consider online and offline radicalization in an integrated way. Occasionally, the design of some counter-measure initiatives treats the internet and the “real” world as two separate and independent realms. New information communication technologies (ICTs) allow extremists to fuse digital and physical settings. As a result, our research contends that radicalization takes place in onlife spaces: hybrid environments that incorporate elements from individuals’ online and offline experiences. This study substantiates this claim, and it examines how algorithms structure information on social media by tracking users’ online and offline activities. Then, it analyzes how the Islamic State promoted onlife radicalization. We focus on how the Islamic State used Telegram, specific media techniques, and videos to connect the Web to the territories it controlled in Syria. Ultimately, the article contributes to the recalibration of the current debate on the relationship between online and offline radicalization on a theoretical level and suggests, on a practical level, potential counter measures.",16641078,PSYCHOLOGY
10.3389/fpsyg.2020.00443,Discrepancy in Ratings of Shared Decision Making Between Patients and Health Professionals: A Cross Sectional Study in Mental Health Care,"Background: A defined goal in mental health care is to increase the opportunities for patients to more actively participate in their treatment. This goal includes integrating aspects of user empowerment and shared decision-making (SDM) into treatment courses. To achieve this goal, more knowledge is needed about how patients and therapists perceive this integration. Objective: To explore patient experiences of SDM, to describe differences between patient and therapist experiences, and to identify patient factors that might reduce SDM experiences for patients compared to the experiences of their therapists. Methods: This cross-sectional study included 992 patients that had appointments with 267 therapists at Sørlandet Hospital, Division of Mental Health during a 1-week period. Both patients and therapists completed the CollaboRATE questionnaire, which was used to rate SDM experiences. Patients reported demographic and treatment-related information. Therapists provided clinical information. Results: The analysis included 953 patient-therapist responder pairs that completed the CollaboRATE questionnaire. The mean SDM score was 80.7 (SD 20.8) among patients, and 86.6 (SD 12.1) among therapists. Females and patients that did not use medication for mental health disorders reported higher SDM scores than males and patients that used psychiatric medications (83.3 vs. 77.7; p < 0.001 and 82.6 vs. 79.8; p = 0.03, respectively). Patients with diagnoses involving psychotic symptoms reported lower SDM scores than all the other patients (66.8 vs. 82.3; p < 0.001). The probability that a patient would report lower SDM scores than their therapist was highest among patients that received involuntary treatment (OR 3.2, p = 0.02), patients with treatment durations longer than 2.2 years (OR 1.9, p = 0.001), and patients that required day care or in-patient care (OR 3.2, p = 0.01 and OR 3.2, p < 0.001, respectively). Conclusion: We showed that both therapists and patients reported good SDM experiences in decisional situations, which indicated that SDM was implemented well. However, the SDM scores reported by in-patients and patients with prolonged or involuntary treatments were significantly lower than scores reported by their therapists. Our findings suggested that it remains a struggle in mental health care to establish a common understanding between patients and therapists in decisional processes regarding treatments for some patient groups.",16641078,PSYCHOLOGY
10.1007/s00432-020-03190-1,Attitude of cancer patients from online self-help groups towards physical activity,"Purpose Physical activity (PA) is important for cancer patients during and after therapy with respect to reducing side effects and improving quality of life. The aim of the study was to examine how physically active German cancer patients are and to identify predictors for PA. In addition, patients were asked about their attitude towards PA. Methods A questionnaire was passed on to members of self-help groups. Multiple regression analyses were run to examine possible predictors such as self-efficacy, patient activation, gender, previous PA, therapy status, and age for PA. Results 62% of the participants followed the official recommendations by the American Cancer Society for weekly aerobic activity. Multiple regression analyses could confirm age as a predictor for total PA. Higher self-efficacy and patient activation were associated with lower disease burden and a more positive attitude towards PA. Conclusion This study contributes to the minor knowledge about PA among cancer patients. The examined group showed that there is potential for improvement regarding PA, although the majority had a positive attitude towards PA. Because of the small sample size existing of online self-help group members, results should be taken with caution.",14321335,ONCOLOGY
10.3389/fonc.2020.00416,Inhibition of microRNA-155 Reduces Neuropathic Pain During Chemotherapeutic Bortezomib via Engagement of Neuroinflammation,"As a chemotherapeutic agent, bortezomib (BTZ) is used for the treatment of multiple myeloma with adverse effect of painful peripheral neuropathy. Our current study was to determine the inhibitory effects of blocking microRNA-155 (miR-155) signal on BTZ-induced neuropathic pain and the underlying mechanisms. We employed real time RT-PCR and western blot analysis to examine the miR-155 and expression of pro-inflammatory tumor necrosis factor-alpha receptor (TNFR1) in the dorsal horn of the spinal cord. Its downstream signals p38-MAPK and JNK and transient receptor potential ankyrin 1 (TRPA1) were also determined. Mechanical pain and cold sensitivity were assessed by behavioral test. In result, inhibition of miR-155 significantly attenuated mechanical allodynia and thermal hyperalgesia in BTZ rats, which was accompanied with decreasing expression of TNFR1, p38-MAPK, JNK, and TRPA1. In contrast, miRNA-155 mimics amplified TNFR1-TRPA1 pathway and augmented mechanical pain and cold sensitivity. In addition, mechanical and thermal hypersensitivity induced by miRNA-155 mimics were attenuated after blocking TNFR1, p38-MAPK, JNK, and TRPA1. Overall, we show the key role of miR-155 in modifying BTZ-induced neuropathic pain through TNFR1-TRPA1 pathway, suggesting that miR-155 is a potential target in preventing neuropathic pain development during intervention of BTZ.",2234943X,ONCOLOGY
10.3389/fpsyg.2020.00562,The Gold Standard and the Pyrite Principle: Toward a Supplemental Frame of Reference,"In medicine and social sciences, the phrase “gold standard” is often used to characterize an object or procedure described as unequivocally the best in its genre, against which all others should be compared. Examples of this usage are readily available in rigorously peer-reviewed publications, touted by test publishers, and appear in descriptions of methodologies by social science researchers. The phrase does not accurately describe commonly accepted measures, tests, and instruments. Instead, the descriptor can be ambiguous and misleading. This paper presents an overview of the history of the gold standard and its current applications to medicine and the social sciences. We question the use of the phrase “the gold standard” and suggest the additional operational use of a “pyrite principle” as a less presumptuous frame of reference. In thinking about validity and standards, the pyrite principle permits an understanding of standards as authoritative rather than fixed constructs in behavioral and health sciences.",16641078,PSYCHOLOGY
10.3390/educsci10040105,Analysis of Courses and Teacher Training Programs on Playful Methodology in Andalusia (Spain),"In this study we analyzed the primary teaching and training experiences that observe play as a didactic resource to facilitate learning, highlighting fundamental elements and characteristics. A descriptive analysis of the different programs and contents with respect to playful methodology proposed by the Ministry of Education of Andalusian Government (Spain) is presented. The purpose of this type of descriptive idiographic research is to define, classify, catalogue, or characterize the experiences of innovation and projects on ludic methodology. The results show a total of 217 experiences and programs that deal with the use of playful methodology in the classroom. The results conclude that there are training resources interested and involved in the training of teachers in relation to play as a didactic resource. This type of training is carried out outside the university environment and has the characteristics of permanent training.",22277102,EDUCATION
10.3390/ai1020008,Artificial Intelligence (AI) or Intelligence Augmentation (IA): What Is the Future?,"Artificial intelligence (AI) is a rapidly growing technological phenomenon that all industries wish to exploit to benefit from efficiency gains and cost reductions. At the macrolevel, AI appears to be capable of replacing humans by undertaking intelligent tasks that were once limited to the human mind. However, another school of thought suggests that instead of being a replacement for the human mind, AI can be used for intelligence augmentation (IA). Accordingly, our research seeks to address these different views, their implications, and potential risks in an age of increased artificial awareness. We show that the ultimate goal of humankind is to achieve IA through the exploitation of AI. Moreover, we articulate the urgent need for ethical frameworks that define how AI should be used to trigger the next level of IA.",26732688,AI
10.3389/fpsyg.2020.00669,Math Anxiety and Working Memory Updating: Difficulties in Retrieving Numerical Information From Working Memory,"This study aimed to determine whether math anxiety was related to working memory (WM) updating performance and, specifically, to the retrieval and substitution components of updating. A set of WM updating (WMU) tasks that involve different retrieval and substitution requirements were administered to 114 university students. In addition, participants completed a math anxiety assessment on two occasions: 1–2 weeks before and immediately prior to task administration to increase the likelihood of observing the relationship between math anxiety and updating performance. The results showed a relationship between math anxiety scores and updating performance. Math anxious individuals took longer and made more errors, especially on tasks that required retrieving information from WM. These results suggest that math anxious individuals are less efficient when it comes to accessing numerical information in WM. Consequently, they may struggle with math-related tasks that involve retrieving numerical information from WM.",16641078,PSYCHOLOGY
10.3389/fonc.2020.00528,Response: Commentary: The Impact of the Time Interval Between Radiation and Hyperthermia on Clinical Outcome in Patients With Locally Advanced Cervical Cancer,Response: Commentary: The Impact of the Time Interval Between Radiation and Hyperthermia on Clinical Outcome in Patients With Locally Advanced Cervical Cancer,2234943X,ONCOLOGY
10.1186/s40594-020-00211-w,Increasing high school teachers self-efficacy for integrated STEM instruction through a collaborative community of practice,"Background: Teachers can have a significant impact on student interest and learning in science, technology, engineering, and math (STEM) subjects and careers. Teacher self-efficacy can also significantly affect student learning. Researchers investigated the effects of teacher professional development and integrated STEM curriculum development on teacher self-efficacy. Participants in the study included high school science and engineering technology teachers enrolled in a National Science Foundation–ITEST project called Teachers and Researchers Advancing Integrated Lessons in STEM (TRAILS). The TRAILS program sought to prepare teachers to integrate STEM content using engineering design, biomimicry, science inquiry, and 3D printing as pedagogical approaches. Teachers learned within a community of practice working alongside industry partners and college faculty. The purpose of the study was to investigate the impact of the 70 h of professional development to train three cohorts of teachers over 3 years on teacher self-efficacy. The research design utilized a quasi-experimental nonequivalent control group approach, including an experimental group and an untreated control group.Results: Measurements on beliefs about teacher self-efficacy were collected on pretest, posttest, and delayed posttest survey assessments. Researchers analyzed the T-STEM survey results for teaching self-efficacy using the Wilcoxson signed-rank test for detecting significant differences. Science teachers showed a significant increase in teacher self-efficacy comparing the pretest and delayed posttest scores after TRAILS professional development and STEM lesson implementation (p=.001, effect size = .95). Additionally, significant differences between groups (science experimental vs science control group teachers) using the Wilcoxon rank-sum test were detected from pretest to posttest (p= .033, effect size = .46), posttest to delayed posttest (p= .029, effect size = .47), and pretest to delayed posttest (p= .005, effect size = .64). There were no significant differences detected in the control group. Engineering technology teachers showed no significant differences between the pretest, posttest, and delayed posttest self-efficacy scores.Conclusions: The results indicate the science teachers’ self-efficacy increased after professional development and after lesson implementation. Potential implications from this research suggest that the science teacher participants benefited greatly from learning within a community of practice, engaging in science practices, and using science knowledge to solve a real-world problem (engineering design).",21967822,EDUCATION
10.3389/fonc.2020.00558,Association of Body Composition With Survival and Treatment Efficacy in Castration-Resistant Prostate Cancer,"Objectives: The association of body composition with survival and the efficacy of first-line treatment was investigated in patients with castration-resistant prostate cancer (CRPC). Methods: The records of CRPC patients treated with docetaxel or androgen receptor signaling inhibitors (ARSi) between 2005 and 2018 were reviewed. Skeletal muscle index (SMI), visceral fat index, and subcutaneous fat index were evaluated using pretreatment computed tomography images. Results: Of 230 eligible patients, 144 received docetaxel, and 86 received ARSi as the first-line treatment for CRPC. The SMIhi (based on median values) group had higher prostate-specific antigen (PSA) progression-free survival (median 13.5 vs. 8.3 months, p = 0.030), radiologic progression-free survival (14.9 vs. 9.1 months, p < 0.001), and overall survival (24.1 vs. 16.9 months, p = 0.015) than the SMIlo group. In docetaxel-treated patients, the SMIhi group had higher PSA progression-free survival (13.5 vs. 5.9 months, p = 0.016) and radiologic progression-free survival (14.6 vs. 6.7 months, p < 0.001) than the SMIlo group. However, PSA progression-free survival and radiologic progression-free survival were comparable between the two groups in ARSi-treated patients. SMI was independently associated with the risk of radiologic progression in patients treated with docetaxel but not in those treated with ARSi. Conclusions: High skeletal muscle mass may be associated with reduced risk of disease progression and mortality in patients with CRPC. However, the significance of these relationships is limited in patients treated with docetaxel. These results suggest that assessing skeletal muscle mass may be worthwhile when selecting treatments for CRPC; however, further prospective validation and large-scale studies are needed.",2234943X,ONCOLOGY
10.3389/fonc.2020.00475,Delivery and Biosafety of Oncolytic Virotherapy,"In recent years, oncolytic virotherapy has emerged as a promising anticancer therapy. Oncolytic viruses destroy cancer cells, without damaging normal tissues, through virus self-replication and antitumor immunity responses, showing great potential for cancer treatment. However, the clinical guidelines for administering oncolytic virotherapy remain unclear. Delivery routes for oncolytic virotherapy to patients vary in existing studies, depending on the tumor sites and the objective of studies. Moreover, the biosafety of oncolytic virotherapy, including mainly uncontrolled adverse events and long-term complications, remains a serious concern that needs to be accurately measured. This review provides a comprehensive and detailed overview of the delivery and biosafety of oncolytic virotherapy.",2234943X,ONCOLOGY
10.3390/cancers12041003,Healthcare Costs of Metastatic Cutaneous Melanoma in the Era of Immunotherapeutic and Targeted Drugs,"Immunotherapeutic and targeted drugs improved survival of patients with metastatic melanoma. There is, however, a lack of evidence regarding their healthcare costs in clinical practice. The aim of our study was to provide insight into real-world healthcare costs of patients with metastatic cutaneous melanoma. Data were obtained from the Dutch Melanoma Treatment Registry for patients who were registered between July 2012 and December 2018. Mean total/monthly costs per patient were reported for all patients, patients who did not receive systemic therapy, and patients who received systemic therapy. Furthermore, mean episode/monthly costs per line of therapy and drug were reported for patients who received systemic therapy. Mean total/monthly costs were € 89,240/€ 6809: € 7988/€ 2483 for patients who did not receive systemic therapy (n = 784) and € 105,078/€ 7652 for patients who received systemic therapy (n = 4022). Mean episode/monthly costs were the highest for nivolumab plus ipilimumab (€ 79,675/€ 16,976), ipilimumab monotherapy (€ 79,110/€ 17,252), and dabrafenib plus trametinib (€ 77,053/€ 12,015). Dacarbazine yielded the lowest mean episode/monthly costs (€ 6564/€ 2027). Our study showed that immunotherapeutic and targeted drugs had a large impact on real-world healthcare costs. As new drugs continue entering the treatment landscape for (metastatic) melanoma, it remains crucial to monitor whether the benefits of these drugs outweigh their costs.",20726694,ONCOLOGY
10.3389/frai.2020.00023,PECLIDES Neuro: A Personalisable Clinical Decision Support System for Neurological Diseases,"Neurodegenerative diseases such as Alzheimer's and Parkinson's impact millions of people worldwide. Early diagnosis has proven to greatly increase the chances of slowing down the diseases' progression. Correct diagnosis often relies on the analysis of large amounts of patient data, and thus lends itself well to support from machine learning algorithms, which are able to learn from past diagnosis and see clearly through the complex interactions of a patient's symptoms and data. Unfortunately, many contemporary machine learning techniques fail to reveal details about how they reach their conclusions, a property considered fundamental when providing a diagnosis. Here we introduce our Personalisable Clinical Decision Support System (PECLIDES), an algorithmic process formulated to address this specific fault in diagnosis detection. PECLIDES provides a clear insight into the decision-making process leading to a diagnosis, making it a gray box model. Our algorithm enriches the fundamental work of Masheyekhi and Gras in data integration, personal medicine, usability, visualization, and interactivity. Our decision support system is an operation of translational medicine. It is based on random forests, is personalisable and allows a clear insight into the decision-making process. A well-structured rule set is created and every rule of the decision-making process can be observed by the user (physician). Furthermore, the user has an impact on the creation of the final rule set and the algorithm allows the comparison of different diseases as well as regional differences in the same disease. The algorithm is applicable to various decision problems. In this paper we will evaluate it on diagnosing neurological diseases and therefore refer to the algorithm as PECLIDES Neuro1.",26248212,AI
10.3389/feduc.2020.00038,"The MARquette Visualization Lab (MARVL): An Immersive Virtual Environment for Research, Teaching and Collaboration","The MARquette Visualization Lab (MARVL) is a large-scale immersive virtual environment for research, teaching, collaboration and outreach at our mid-sized liberal arts university. MARVL consists of multiple display surfaces including an extra wide front wall and floor, and two side walls. This resource includes stereoscopic viewing, motion tracking and space for a large audience. MARVL’s versatile configuration facilitates viewing of content by 30 people, while also projecting on the entire width of the floor. This feature uniquely facilitates comparative or separate content visible simultaneously via “split mode” operation (two 3-sided environments), as well as detailed motion for applications such as gait analysis and performing arts. Since establishing the lab, its members have received numerous queries and requests pertaining to how system attributes and applications were determined, suggesting these and related decisions remain a challenge nearly three decades since the first CAVE was constructed. This paper provides an overview of MARVL including the processes used in identifying a diverse group of cross campus users, understanding their collective vision for potential use, and synthesizing this information to create the resource described above. The subsequent design, qualitative and quantitative approaches to vendor selection, and software decisions are then discussed. Steps implemented for dealing with simulator sickness and latency are presented along with current approaches being implemented for project development with end users. Finally, we present results from the use of MARVL by several end users identified in the early planning stage, and recent upgrades to the system.",2504284X,EDUCATION
10.1186/s40594-020-00219-2,Factors influencing participation of underrepresented students in STEM fields: matched mentors and mindsets,"Background: Women and ethnic minorities remain underrepresented in science, technology, engineering, and math (STEM) fields. The goal of this pilot study is to better understand the beliefs and experiences of underrepresented US students pursuing STEM. Our focus was to gain insights into their mentorship experiences and preferences regarding having mentors who are gender and ethnicity matched. Environmental and psychological factors associated with participants’ decision to pursue STEM, such as family influences, academic mindsets, and attitudes towards STEM, were also studied. Methods: We developed a survey tool based on published literature and established instruments, including measures of STEM belonging, science identity, and growth mindset, as well as measures assessing students’ views on their STEM participation. We surveyed members of a STEM-focused non-profit who were in college, graduate school, or were recent graduates. Results: Forty-eight adults currently pursuing STEM responded to the survey. The majority (71%) were female and nearly all (96%) identified as an ethnic minority. Most reported knowing someone of their same gender (68%) or ethnicity (66%) with a STEM career who served as a role model. The majority (54%) stated that meeting a STEM professional of their own gender and ethnicity would be effective encouragement to pursue STEM. A similar percentage (56%) believed that media exposure to gender- and ethnicity-matched STEM professionals would be effective encouragement. Most (73%) demonstrated a growth mindset and had strong family support to pursue STEM (68%). Only two-thirds (66%) felt they belonged in STEM careers, and 30% agreed that people in their STEM classes are a lot like them. Conclusion: This study contributes additional information on the views and experiences of diverse students actively pursuing STEM. Most participants indicated the importance of meeting and being mentored in STEM by those of their same gender and ethnicity, either in person or through media. Future educational efforts to increase STEM diversity should consider students’ mentorship preferences and facilitate interactions with matched-background mentors accordingly, with consideration given to the use of media. Educators should focus on inclusive learning by highlighting the accomplishments of diverse STEM professionals, to help strengthen feelings of STEM belonging.",21967822,EDUCATION
10.3389/fpsyg.2020.00632,“I Invest by Following Lead Investors!” The Role of Lead Investors in Fundraising Performance of Equity Crowdfunding,"Psychological factors play a critical role in affecting investor decisions. This study explores how lead investors influence following investors psychologically, thus affecting fundraising performance of equity crowdfunding. We draw upon the signaling theory and observational learning theory to argue that following investors could be induced to invest in a project if they observe the proportion of funding by lead investors in the funding target to be high, that the lead investors have rich investment experience, and that the lead investors can offer help to the projects. To test our hypotheses, we analyze a sample of 215 projects from a Chinese equity crowdfunding platform. The results reveal that the proportion of lead investor investment in the funding target and their investment experience are positively related to fundraising performance. However, the help offered by lead investors toward the projects has no impact on funding performance. Theoretical and practical implications are discussed.",16641078,PSYCHOLOGY
10.1186/s40594-020-00214-7,Correlations between modes of student cognitive engagement and instructional practices in undergraduate STEM courses,"Background: Within STEM education, research on instructional practices has focused on ways to increase student engagement and thereby reap the associated benefits of increased learning, persistence, and academic success. These meaningful-learning goals have been tied most specifically to cognitive engagement, a construct that is often difficult for instructors to assess on their own. While it has been shown that certain instructional practices are tied to higher cognitive engagement in students, tools to measure instructional practices and student engagement have remained largely isolated in their development and use. Results: This research uses previously developed instruments to simultaneously assess modes of cognitive engagement in students (Student Course Cognitive Engagement Instrument [SCCEI]) and instructional practices (Postsecondary Instructional Practices Survey [PIPS]) within a course. A sample of 19 STEM courses was recruited to participate in this study, with instructors and students each self-reporting data. Results from the instructor and students in each course were scored, and ANOVA and partial correlation analysis were conducted on the sample. ANOVA indicated the significance of and classroom structure on student engagement. From the correlation analysis, a significant relationship was found between four student-reported modes of cognitive engagement and instructor-reported teaching practices. Conclusions: With an understanding of student engagement response to classroom structure, instructors may consider their teaching environment when implementing instructional practices. Moreover, Interactivity with Peers, the deepest mode of cognitive engagement suggested by previous research, was correlated with instructional practices in our study, suggesting that instructors may be able to shape their students’ learning by encouraging collaboration in the classroom. We also found that assessment played a role in students’ cognitive engagement; this indicates that instructors may wish to thoughtfully consider their methods of assessment to facilitate modes of cognitive engagement associated with deeper learning of course material. By understanding factor correlations, the PIPS and SCCEI can be used in tandem to understand impacts of instructional practices on student cognitive engagement within a course. We conclude that there is a need for ongoing research to study the interplay of instructional practices and student cognitive engagement as instruments are developed to measure such phenomena.",21967822,EDUCATION
10.3390/ai1020010,Deep Learning Based Wildfire Event Object Detection from 4K Aerial Images Acquired by UAS,"Unmanned Aerial Systems, hereafter referred to as UAS, are of great use in hazard events such as wildfire due to their ability to provide high-resolution video imagery over areas deemed too dangerous for manned aircraft and ground crews. This aerial perspective allows for identification of ground-based hazards such as spot fires and fire lines, and to communicate this information with fire fighting crews. Current technology relies on visual interpretation of UAS imagery, with little to no computer-assisted automatic detection. With the help of big labeled data and the significant increase of computing power, deep learning has seen great successes on object detection with fixed patterns, such as people and vehicles. However, little has been done for objects, such as spot fires, with amorphous and irregular shapes. Additional challenges arise when data are collected via UAS as high-resolution aerial images or videos; an ample solution must provide reasonable accuracy with low delays. In this paper, we examined 4K ( 3840 × 2160 ) videos collected by UAS from a controlled burn and created a set of labeled video sets to be shared for public use. We introduce a coarse-to-fine framework to auto-detect wildfires that are sparse, small, and irregularly-shaped. The coarse detector adaptively selects the sub-regions that are likely to contain the objects of interest while the fine detector passes only the details of the sub-regions, rather than the entire 4K region, for further scrutiny. The proposed two-phase learning therefore greatly reduced time overhead and is capable of maintaining high accuracy. Compared against the real-time one-stage object backbone of YoloV3, the proposed methods improved the mean average precision(mAP) from 0 . 29 to 0 . 67 , with an average inference speed of 7.44 frames per second. Limitations and future work are discussed with regard to the design and the experiment results.",26732688,AI
10.3389/frai.2020.00024,Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data,"Deep neural networks have been successfully applied in learning the board games Go, chess, and shogi without prior knowledge by making use of reinforcement learning. Although starting from zero knowledge has been shown to yield impressive results, it is associated with high computationally costs especially for complex games. With this paper, we present CrazyAra which is a neural network based engine solely trained in supervised manner for the chess variant crazyhouse. Crazyhouse is a game with a higher branching factor than chess and there is only limited data of lower quality available compared to AlphaGo. Therefore, we focus on improving efficiency in multiple aspects while relying on low computational resources. These improvements include modifications in the neural network design and training configuration, the introduction of a data normalization step and a more sample efficient Monte-Carlo tree search which has a lower chance to blunder. After training on 569537 human games for 1.5 days we achieve a move prediction accuracy of 60.4%. During development, versions of CrazyAra played professional human players. Most notably, CrazyAra achieved a four to one win over 2017 crazyhouse world champion Justin Tan (aka LM Jann Lee) who is more than 400 Elo higher rated compared to the average player in our training set. Furthermore, we test the playing strength of CrazyAra on CPU against all participants of the second Crazyhouse Computer Championships 2017, winning against twelve of the thirteen participants. Finally, for CrazyAraFish we continue training our model on generated engine games. In 10 long-time control matches playing Stockfish 10, CrazyAraFish wins three games and draws one out of 10 matches.",26248212,AI
10.3390/cancers12051099,The Role of miRNA for the Treatment of MGMT Unmethylated Glioblastoma Multiforme,"Glioblastoma multiforme (GBM) is the most common high-grade intracranial tumor in adults. It is characterized by uncontrolled proliferation, diffuse infiltration due to high invasive and migratory capacities, as well as intense resistance to chemo- and radiotherapy. With a five-year survival of less than 3% and an average survival rate of 12 months after diagnosis, GBM has become a focus of current research to urgently develop new therapeutic approaches in order to prolong survival of GBM patients. The methylation status of the promoter region of the O6-methylguanine–DNA methyltransferase (MGMT) is nowadays routinely analyzed since a methylated promoter region is beneficial for an effective response to temozolomide-based chemotherapy. Furthermore, several miRNAs were identified regulating MGMT expression, apart from promoter methylation, by degrading MGMT mRNA before protein translation. These miRNAs could be a promising innovative treatment approach to enhance Temozolomide (TMZ) sensitivity in MGMT unmethylated patients and to increase progression-free survival as well as long-term survival. In this review, the relevant miRNAs are systematically reviewed.",20726694,ONCOLOGY
10.3389/fonc.2020.00658,More Than a Metabolic Enzyme: MTHFD2 as a Novel Target for Anticancer Therapy?,"The bifunctional methylenetetrahydrofolate dehydrogenase/cyclohydrolase (MTHFD2) is a mitochondrial one-carbon folate metabolic enzyme whose role in cancer was not known until recently. MTHFD2 is highly expressed in embryos and a wide range of tumors but has low or absent expression in most adult differentiated tissues. Elevated MTHFD2 expression is associated with poor prognosis in both hematological and solid malignancy. Its depletion leads to suppression of multiple malignant phenotypes including proliferation, invasion, migration, and induction of cancer cell death. The non-metabolic functions of this enzyme, especially in cancers, have thus generated considerable research interests. This review summarizes current knowledge on both the metabolic functions and non-enzymatic roles of MTHFD2. Its expression, potential functions, and regulatory mechanism in cancers are highlighted. The development of MTHFD2 inhibitors and their implications in pre-clinical models are also discussed.",2234943X,ONCOLOGY
10.3389/fonc.2020.00641,Shaping Up the Tumor Microenvironment With Cellular Fibronectin,"Normal tissue homeostasis and architecture restrain tumor growth. Thus for a tumor to develop and spread, malignant cells must overcome growth-repressive inputs from surrounding tissue and escape immune surveillance mechanisms that curb cancer progression. This is achieved by promoting the conversion of a physiological microenvironment to a pro-tumoral state and it requires a constant dialog between malignant cells and ostensibly normal cells of adjacent tissue. Pro-tumoral reprogramming of the stroma is accompanied by an upregulation of certain extracellular matrix (ECM) proteins and their cognate receptors. Fibronectin (FN) is one such component of the tumor matrisome. This large multidomain glycoprotein dimer expressed over a wide range of human cancers is assembled by cell-driven forces into a fibrillar array that provides an obligate scaffold for the deposition of other matrix proteins and binding sites for functionalization by soluble factors in the tumor microenvironment. Encoded by a single gene, FN regulates the proliferation, motile behavior and fate of multiple cell types, largely through mechanisms that involve integrin-mediated signaling. These processes are coordinated by distinct isoforms of FN, collectively known as cellular FN (as opposed to circulating plasma FN) that arise through alternative splicing of the FN1 gene. Cellular FN isoforms differ in their solubility, receptor binding ability and spatiotemporal expression, and that exert functions that have yet to be fully defined. FN induction at tumor sites constitutes an important step in the acquisition of biological capabilities required for several cancer hallmarks by sustaining proliferative signaling, promoting angiogenesis, facilitating invasion and metastasis, modulating growth suppressor activity and regulating anti-tumoral immunity. In this review, we will first provide an overview of ECM reprogramming through tumor-stroma crosstalk then focus on the role of cellular FN in tumor progression with respect to these hallmarks. Last, we will discuss the impact of dysregulated ECM on clinical efficacy of classical (radio-/chemo-) therapies and emerging treatments that target immune checkpoints and explore how our growing knowledge of the tumor ECM and the central role of FN can be leveraged for therapeutic benefit.",2234943X,ONCOLOGY
10.3390/cancers12051141,Molecular Signatures of JMJD10/MINA53 in Gastric Cancer,"The JMJD10 gene and its encoded protein MYC-induced nuclear antigen (MINA53) are associated with multiple cancers. Besides having both an oncogenic and tumor suppressor function, the intricate role of JMJD10 in cancer is complex as it depends on the cancer type. In particular, the functional role of JMJD10/MINA53 in gastric cancer has been poorly understood. In this study, we have unraveled the molecular signatures and functional roles of JMJD10/MINA53 in gastric cancer by multiple approaches, i.e., multi-omics bioinformatics study, analysis of human gastric cancer tissues, and studies in vitro using knockdown or overexpression strategies in gastric cancer cell lines. The results indicated that the JMJD10 gene and MINA53 protein are commonly overexpressed in cancer patients. JMJD10/MINA53 is involved in the regulation of proliferation and survival of gastric cancer by controlling cell cycle gene expression. These processes are highly associated with MINA53 enzymatic activity in the regulation of H3K9me3 methylation status and controlling activation of AP-1 signaling pathways. This highlights the oncogenic role of JMJD10/MINA53 in gastric cancer and opens the opportunity to develop therapeutic targeting of JMJD10/MINA53 in gastric cancer.",20726694,ONCOLOGY
10.1007/s00432-020-03218-6,Active HPV infection and its influence on survival in head and neck squamous-cell cancer,"Purpose: HPV is involved in the development of some head and neck squamous-cell carcinomas (HNSCC). It was suggested that only transcriptionally active virus can induce carcinogenesis, therefore, the aim of our study was to analyze the frequency of active HPV infection, virus type, and its prognostic role in HNSCC patients.Methods: Status of active HPV infection was assessed for 155 HNSCC patients based on p16 expression and HPV DNA presence. Univariate and multivariate analyses with Cox proportional regression model were performed to select independent prognostic factors.Results: Active HPV infection was detected in 20.65% of patients. We identified 16.0, 40.9 and 1.7% of HPV positive oral cavity, oropharyngeal, and laryngeal cancer cases, respectively. HPV16 was dominant (81.25%) followed by HPV35 (9.38%) and double infections with HPV16 and 35 (6.25%) or HPV35 and 18 (3.12%). Patients with active HPV infection demonstrated significantly higher survival than HPV negative ones (OS 80.89% vs. 37.08%,p = 0.000; DFS 93.0% vs. 53.35%,p = 0.000, respectively). Longer OS and DFS were maintained for infected patients when oropharyngeal and non-oropharyngeal cases were analyzed separately. Interestingly, all patients infected with other than HPV16 types survived 5 years without cancer progression. In the analyzed group of 155 patients the strongest independent favourable prognostic factor for both OS and DFS was HPV presence.Conclusions: High prevalence of HPV-driven HNSCC (mostly within oropharynx) was detected, with HPV16 type the most frequent, followed by HPV35 and HPV18. The presence of active HPV infection improved survival of both oropharyngeal and non-oropharyngeal cancer patients and should be taken into account in treatment planning.",14321335,ONCOLOGY
10.3389/frai.2020.00028,Predicting Biomass and Yield in a Tomato Phenotyping Experiment Using UAV Imagery and Random Forest,"Biomass and yield are key variables for assessing the production and performance of agricultural systems. Modeling and predicting the biomass and yield of individual plants at the farm scale represents a major challenge in precision agriculture, particularly when salinity and other abiotic stresses may play a role. Here, we evaluate a diversity panel of the wild tomato species (Solanum pimpinellifolium) through both field and unmanned aerial vehicle (UAV)-based phenotyping of 600 control and 600 salt-treated plants. The study objective was to predict fresh shoot mass, tomato fruit numbers, and yield mass at harvest based on a range of variables derived from the UAV imagery. UAV-based red–green–blue (RGB) imageries collected 1, 2, 4, 6, 7, and 8 weeks before harvest were also used to determine if prediction accuracies varied between control and salt-treated plants. Multispectral UAV-based imagery was also collected 1 and 2 weeks prior to harvest to further explore predictive insights. In order to estimate the end of season biomass and yield, a random forest machine learning approach was implemented using UAV-imagery-derived predictors as input variables. Shape features derived from the UAV, such as plant area, border length, width, and length, were found to have the highest importance in the predictions, followed by vegetation indices and the entropy texture measure. The multispectral UAV imagery collected 2 weeks prior to harvest produced the highest explained variances for fresh shoot mass (87.95%), fruit numbers (63.88%), and yield mass per plant (66.51%). The RGB UAV imagery produced very similar results to those of the multispectral UAV dataset, with the explained variance reducing as a function of increasing time to harvest. The results showed that predicting the yield of salt-stressed plants produced higher accuracies when the models excluded control plants, whereas predicting the yield of control plants was not affected by the inclusion of salt-stressed plants within the models. This research demonstrates that it is possible to predict the average biomass and yield up to 8 weeks prior to harvest within 4.23% of field-based measurements and up to 4 weeks prior to harvest at the individual plant level. Results from this work may be useful in providing guidance for yield forecasting of healthy and salt-stressed tomato plants, which in turn may inform growing practices, logistical planning, and sales operations.",26248212,AI
10.3389/frai.2020.00034,On Consequentialism and Fairness,"Recent work on fairness in machine learning has primarily emphasized how to define, quantify, and encourage “fair” outcomes. Less attention has been paid, however, to the ethical foundations which underlie such efforts. Among the ethical perspectives that should be taken into consideration is consequentialism, the position that, roughly speaking, outcomes are all that matter. Although consequentialism is not free from difficulties, and although it does not necessarily provide a tractable way of choosing actions (because of the combined problems of uncertainty, subjectivity, and aggregation), it nevertheless provides a powerful foundation from which to critique the existing literature on machine learning fairness. Moreover, it brings to the fore some of the tradeoffs involved, including the problem of who counts, the pros and cons of using a policy, and the relative value of the distant future. In this paper we provide a consequentialist critique of common definitions of fairness within machine learning, as well as a machine learning perspective on consequentialism. We conclude with a broader discussion of the issues of learning and randomization, which have important implications for the ethics of automated decision making systems.",26248212,AI
10.3390/educsci10050134,The Impact of Learning Strategies and Future Orientation on Academic Success: The Moderating Role of Academic Self-Efficacy among Italian Undergraduate Students,"Promoting academic success among undergraduate students is crucial for tackling the need to foster employability competencies. Low levels of academic attainment in higher education, along with the increasing number of persons participating in tertiary education, represent crucial trends, which need to be studied in order to develop efficient retention practices. The current study aimed to investigate the relationship between relevant factors that can foster academic success: learning strategies, future orientation, and academic self-efficacy. To this purpose, a longitudinal study was performed on a sample of N = 87 undergraduate students from one of the largest Italian universities (63.4% males, 74.2% enrolled in the first year). Participants filled in an online questionnaire at two different time points, with a time lag of 12 months. Results of a moderated mediation model indicated that the relationship between learning strategies at Time 1 (T1) and Grade Point Average (GPA) at Time 2 (T2) was mediated by students’ future orientation. Moreover, this association was moderated by T1 academic self-efficacy. These results suggest that learning strategies positively influence GPA through an enhanced future orientation, in particular when students report high or medium levels of self-efficacy. The current findings invite a thorough review of training interventions for improving academic achievement.",22277102,EDUCATION
10.1007/s00432-020-03225-7,Prognostic significance of VEGF and components of the plasminogen activator system in endometrial cancer,"Objective The plasminogen activator system (PAS) and vascular endothelial growth factor (VEGF) are important in the carcinogenesis and play a key role in cancer invasion and mediating metastasis of carcinomas. The aim of the study was to evaluate the correlation of serum levels of VEGF and components of the PAS with clinicopathological risk factors and outcome in patients with endometrial cancer (EC). Methods Preoperative blood was collected from 173 patients treated for EC between 1999 and 2009. Serum concentrations of VEGF, urokinase plasminogen activator (uPA) tissue plasminogen activator (tPA), plasminogen activator inhibitor type-1 (PAI-1) and -2 (PAI-2) were assessed by enzyme-linked immunosorbent assays (ELISA). Results Serum levels of VEGF and components of the PAS were significantly associated with stage of the disease, tumor histology, tumor grade, myometrial invasion (MI), presence of lymphovascular space invasion (LVSI) and lymph node metastases (LNM). Preoperative serum levels of PAI-1 and -2 and tPA were higher in patients who experienced a recurrence than in patients who remained disease free (p < 0.01). PAI-1 and -2 and tPA were significantly independent prognostic factors for DFS with a HR of 3.85 (95% CI 1.84–8.07), 3.90 (95% CI 1.75–8.66) and 2.53 (95% CI 1.16–5.55), respectively. PAI-1 and tPA turned out to be independent prognostic factors for OS, with a HR of 2.09 (95% CI 1.08–4.05) and 2.16 (95% CI 1.06–4.44), respectively. Conclusion Serum levels of VEGF and components of the PAS at primary diagnosis were associated with well-known clinicopathological risk factors such as; FIGO stage, tumor histology, tumor grade, MI, LVSI and LNM. High concentrations of PAI-1 and-2 and tPA are independent factors for poor prognosis in patients with endometrial cancer.",14321335,ONCOLOGY
10.3390/educsci10050137,Tales from within: Gifted Students’ Lived Experiences with Teaching Practices in Regular Classrooms,"Gifted students in regular classrooms have fewer opportunities to develop activities that are based on their characteristics as learners and address their needs; however, many of them spend most of their school time in these classrooms. The results presented here were part of a 2-year qualitative project that analyzed 12 Chilean gifted students’ lived experiences in regular classrooms by exploring the factors that foster and hinder their learning through the use of photos, focus groups, and interviews. The results showed students’ discontent with the national curriculum and teaching practices related to rigidity, lack of meaning, and unchallenging assessments. Nevertheless, positive experiences were reported related to teaching strategies, especially when they add novelty and move away from traditional approaches. Waiting experiences were common, but were often seen by students as opportunities for creative production. Methods for engaging gifted students in their learning are highlighted.",22277102,EDUCATION
10.3390/ai1020012,Cities of the Future? The Potential Impact of Artificial Intelligence,"Artificial intelligence (AI), like many revolutionary technologies in human history, will have a profound impact on societies. From this viewpoint, we analyze the combined effects of AI to raise important questions about the future form and function of cities. Combining knowledge from computer science, urban planning, and economics while reflecting on academic and business perspectives, we propose that the future of cities is far from being a determined one and cities may evolve into ghost towns if the deployment of AI is not carefully controlled. This viewpoint presents a fundamentally different argument, because it expresses a real concern over the future of cities in contrast to the many publications who exclusively assume city populations will increase predicated on the neoliberal urban growth paradigm that has for centuries attracted humans to cities in search of work.",26732688,AI
10.1186/s40594-020-00222-7,Reducing withdrawal and failure rates in introductory programming with subgoal labeled worked examples,"Background: Programming a computer is an increasingly valuable skill, but dropout and failure rates in introductory programming courses are regularly as high as 50%. Like many fields, programming requires students to learn complex problem-solving procedures from instructors who tend to have tacit knowledge about low-level procedures that they have automatized. The subgoal learning framework has been used in programming and other fields to breakdown procedural problem solving into smaller pieces that novices can grasp more easily, but it has only been used in short-term interventions. In this study, the subgoal learning framework was implemented throughout a semester-long introductory programming course to explore its longitudinal effects. Of 265 students in multiple sections of the course, half received subgoal-oriented instruction while the other half received typical instruction. Results: Learning subgoals consistently improved performance on quizzes, which were formative and given within a week of learning a new procedure, but not on exams, which were summative. While exam performance was not statistically better, the subgoal group had lower variance in exam scores and fewer students dropped or failed the course than in the control group. To better understand the learning process, we examined students’ responses to open-ended questions that asked them to explain the problem-solving process. Furthermore, we explored characteristics of learners to determine how subgoal learning affected students at risk of dropout or failure. Conclusions: Students in an introductory programming course performed better on initial assessments when they received instructions that used our intervention, subgoal labels. Though the students did not perform better than the control group on exams on average, they were less likely to get failing grades or to drop the course. Overall, subgoal labels seemed especially effective for students who might otherwise struggle to pass or complete the course.",21967822,EDUCATION
10.3389/fonc.2020.00757,Integration of Digital Pathologic and Transcriptomic Analyses Connects Tumor-Infiltrating Lymphocyte Spatial Density With Clinical Response to BRAF Inhibitors,"Metastatic melanoma is one of the most immunogenic malignancies due to its high rate of mutations and neoantigen formation. Response to BRAF inhibitors (BRAFi) may be determined by intratumoral immune activation within melanoma metastases. To evaluate whether CD8+ T cell infiltration and distribution within melanoma metastases can predict clinical response to BRAFi, we developed a methodology to integrate immunohistochemistry with automated image analysis of CD8+ T cell position. CD8+ distribution patterns were correlated with gene expression data to identify and quantify “hot” areas within a tumor. Furthermore, the relative activation of CD8+cells, based on transcriptomic analysis, and their relationship to other CD8+ T cells and non-CD8+ cells within the tumor suggested a less crowded distribution of cells around activated CD8+ T cells. Furthermore, the relative activation of these CD8+ T cells was associated with improved clinical outcomes and decreased tumor cell proliferation. This study demonstrates the potential of digital pathomics to incorporate immune cell spatial distribution within metastases and RNAseq analysis to predict clinical response to BRAF inhibition in metastatic melanoma.",2234943X,ONCOLOGY
10.3389/frai.2020.00031,Bringing Big Data to Bear in Environmental Public Health: Challenges and Recommendations,"Understanding the role that the environment plays in influencing public health often involves collecting and studying large, complex data sets. There have been a number of private and public efforts to gather sufficient information and confront significant unknowns in the field of environmental public health, yet there is a persistent and largely unmet need for findable, accessible, interoperable, and reusable (FAIR) data. Even when data are readily available, the ability to create, analyze, and draw conclusions from these data using emerging computational tools, such as augmented and artificial intelligence (AI) and machine learning, requires technical skills not currently implemented on a programmatic level across research hubs and academic institutions. We argue that collaborative efforts in data curation and storage, scientific computing, and training are of paramount importance to empower researchers within environmental sciences and the broader public health community to apply AI approaches and fully realize their potential. Leaders in the field were asked to prioritize challenges in incorporating big data in environmental public health research: inconsistent implementation of FAIR principles in data collection and sharing, a lack of skilled data scientists and appropriate cyber-infrastructures, and limited understanding of possibilities and communication of benefits were among those identified. These issues are discussed, and actionable recommendations are provided.",26248212,AI
10.3390/cancers12051273,"Preclinical Efficacy and Involvement of AKT, mTOR, and ERK Kinases in the Mechanism of Sulforaphane against Endometrial Cancer","Sulforaphane exerts anti-cancer activity against multiple cancer types. Our objective was to evaluate utility of sulforaphane for endometrial cancer therapy. Sulforaphane reduced viability of endometrial cancer cell lines in association with the G2/M cell cycle arrest and cell division cycle protein 2 (Cdc2) phosphorylation, and intrinsic apoptosis. Inhibition of anchorage-independent growth, invasion, and migration of the cell lines was associated with sulforaphane-induced alterations in epithelial-to-mesenchymal transition (EMT) markers of increased E-cadherin and decreased N-cadherin and vimentin expression. Proteomic analysis identified alterations in AKT, mTOR, and ERK kinases in the networks of sulforaphane effects in the Ishikawa endometrial cancer cell line. Western blots confirmed sulforaphane inhibition of AKT, mTOR, and induction of ERK with alterations in downstream signaling. AKT and mTOR inhibitors reduced endometrial cancer cell line viability and prevented further reduction by sulforaphane. Accumulation of nuclear phosphorylated ERK was associated with reduced sensitivity to the ERK inhibitor and its interference with sulforaphane activity. Sulforaphane induced apoptosis-associated growth inhibition of Ishikawa xenograft tumors to a greater extent than paclitaxel, with no evidence of toxicity. These results verify sulforaphane’s potential as a non-toxic treatment candidate for endometrial cancer and identify AKT, mTOR, and ERK kinases in the mechanism of action with interference in the mechanism by nuclear phosphorylated ERK.",20726694,ONCOLOGY
10.1186/s40594-020-00217-4,Measuring university students’ interest in biology: evaluation of an instrument targeting Hidi and Renninger’s individual interest,"Background: Boosting students’ disciplinary interest has long been considered an important mechanism to increase student success and retention in STEM education. Yet, interest is a complex construct and can mean different things to different people, and many of the existing interest questionnaires do not identify a specific theoretical framework underlying their items. To demonstrate that curricular interventions targeting students’ interest are effective, educators need a theoretically based instrument to measure interest. The aim of this study was to develop an instrument measuring undergraduate students’ interest in the discipline of biology and collect initial validity evidence supporting the proposed use. The instrument structure is based on Hidi and Renninger’s (Educational Psychologist 41:111–127, 2006) conceptualization of individual interest, and the intended use is to evaluate changes in the biology interests of the US undergraduate students pursuing STEM degrees. To provide evidence of validity, the instrument was completed by 446 biology majors and 489 non-biology majors at two R1 universities. Exploratory and confirmatory factor analyses were applied to evaluate the internal structure of the instrument.Results: The final three-factor instrument supported by these analyses includes 6 items representing positive feelings towards biology, 5 items representing personal value of biology, and 8 items representing reengagement in biology-related activities. Measurement invariance across biology and non-biology majors was established and subsequent comparisons of these populations demonstrated that biology majors report significantly higher positive feelings, personal value, and reengagement in biology-related activities compared to non-biology majors.Conclusions: The study findings support the use of the instrument to gain a broad understanding of students’ individual interest in biology. With minor adaptions, the instrument could also be evaluated for use in other STEM disciplines and for use by other populations.",21967822,EDUCATION
10.3389/fonc.2020.00633,Long Non-coding RNA AK025387 Promotes Cell Migration and Invasion of Gastric Cancer,"Gastric cancer is one of the most common cancers in the world, and long non-coding RNAs (lncRNAs) play a crucial role in proliferation, metastasis, and invasion of gastric cancer. However, there are very few researches focusing on the effects of lncRNAs on metastatic gastric cancer. In this research, we identify one kind of lncRNA, called AK025387, which is highly expressed in metastatic gastric cancer samples compared with non-metastatic gastric cancer samples. The expression of AK025387 is significantly positively correlated with lymph node metastasis. The in situ hybridization demonstrates that AK025387 is located in both nucleus and cytoplasm, but mostly in cytoplasm. AK025387 promotes gastric cancer cells migratory and invasive ability, but it inhibits apoptosis in vitro. Furthermore, AK025387 regulates Raf-1, mitogen-activated protein kinase/extracellular signal-regulated kinase (MEK), and extracellular signal-regulated kinase (ERK) and is involved in mitogen-activated protein kinase (MAPK) signaling pathway to perform its biological functions. We conclude that AK025387 is highly expressed in metastatic gastric cancer, and its biological functions suggest the potential of AK025387 to be a biomarker of metastatic gastric cancer.",2234943X,ONCOLOGY
10.3389/fonc.2020.00786,Development and Validation of a Comprehensive Multivariate Dosimetric Model for Predicting Late Genitourinary Toxicity Following Prostate Cancer Stereotactic Body Radiotherapy,"Purpose: Dosimetric predictors of toxicity after Stereotactic Body Radiation Therapy (SBRT) are not well-established. We sought to develop a multivariate model that predicts Common Terminology Criteria for Adverse Events (CTCAE) late grade 2 or greater genitourinary (GU) toxicity by interrogating the entire dose-volume histogram (DVH) from a large cohort of prostate cancer patients treated with SBRT on prospective trials. Methods: Three hundred and thirty-nine patients with late CTCAE toxicity data treated with prostate SBRT were identified and analyzed. All patients received 40 Gy in five fractions, every other day, using volumetric modulated arc therapy. For each patient, we examined 910 candidate dosimetric features including maximum dose, volumes of each organ [CTV, organs at risk (OARs)], V100%, and other granular volumetric/dosimetric indices at varying volumetric/dosimetric values from the entire DVH as well as ADT use to model and predict toxicity from SBRT. Training and validation subsets were generated with 90 and 10% of the patients in our cohort, respectively. Predictive accuracy was assessed by calculating the area under the receiver operating curve (AROC). Univariate analysis with student t-test was first performed on each candidate DVH feature. We subsequently performed advanced machine-learning multivariate analyses including classification and regression tree (CART), random forest, boosted tree, and multilayer neural network. Results: Median follow-up time was 32.3 months (range 3–98.9 months). Late grade ≥2 GU toxicity occurred in 20.1% of patients in our series. No single dosimetric parameter had an AROC for predicting late grade ≥2 GU toxicity on univariate analysis that exceeded 0.599. Optimized CART modestly improved prediction accuracy, with an AROC of 0.601, whereas other machine learning approaches did not improve upon univariate analyses. Conclusions: CART-based machine learning multivariate analyses drawing from 910 dosimetric features and ADT use modestly improves upon clinical prediction of late GU toxicity alone, yielding an AROC of 0.601. Biologic predictors may enhance predictive models for identifying patients at risk for late toxicity after SBRT.",2234943X,ONCOLOGY
10.3389/fonc.2020.00788,The Landscape of Iron Metabolism-Related and Methylated Genes in the Prognosis Prediction of Clear Cell Renal Cell Carcinoma,"Background: Clear cell renal cell carcinoma (ccRCC) is characteristics of resistance to chemotherapy and radiotherapy. The prognosis of ccRCC was dismay with immense diversity. Iron metabolism disturbance is a common phenomenon in ccRCC. The purpose of our study is to identify and validate the candidate prognostic gene signature of iron metabolism and methylation closely related to the poor prognosis of ccRCC through comprehensive bioinformatics analysis in The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Methods: The prognostic iron metabolism-related genes were screened according to the overlapping differentially expressed genes (DEGs) from the TCGA database. We built a prognostic model using risk score method to predict OS, each ccRCC patient's risk score was calculated, and the resulting score can divide these patients into two categories according to the cut-point risk score. The prognostic significance of the hub genes was further evaluated with the Kaplan-Meier (KM) survival and Receiver Operating Characteristic (ROC) curve analysis. Univariate and multivariate Cox regression analysis was implemented to evaluate the impact of each variable on OS. Furthermore, the prediction power of the 25 gene signatures has been validated using an independent ccRCC cohort from the GEO database. The Gene Set Enrichment Analysis (GSEA) identified the characteristics of hub related oncogenes. Finally, we utilize Weighted Gene Co-expression Network Analysis (WGCNA) to investigate the co-expression network based on these DEGs. Results: In this study, we identified and validated 25 iron metabolism-related and methylated genes as the prognostic signatures, which differentiated ccRCC patients into high and low risk subgroups. The KM analysis showed that the survival rate of the high-risk patients was significantly lower than that of the low-risk patients. The risk score calculated with 25 gene signatures could largely predict OS and DFS for 1, 3, and 5 years in patients with ccRCC. Conclusions: Taken together, we identified the key iron metabolism-related and methylated genes for ccRCC through a comprehensive bioinformatics analysis. This study provides a reliable and robust gene signature for the prognostic predictor of ccRCC patients and maybe provides a promising treatment strategy for this lethal disease.",2234943X,ONCOLOGY
10.3389/frai.2020.00035,Implicit Standardization in a Minority Language Community: Real-Time Syntactic Change among Hasidic Yiddish Writers,"The recent turn to “big data” from social media corpora has enabled sociolinguists to investigate patterns of language variation and change at unprecedented scales. However, research in this paradigm has been slow to address variable phenomena in minority languages, where data scarcity and the absence of computational tools (e.g., taggers, parsers) often present significant barriers to entry. This article analyzes socio-syntactic variation in one minority language variety, Hasidic Yiddish, focusing on a variable for which tokens can be identified in raw text using purely morphological criteria. In non-finite particle verbs, the overt tense marker tsu (cf. English to, German zu) is variably realized either between the preverbal particle and verb (e.g., oyf-tsu-es-n up-to-eat-INF ‘to eat up’; the conservative variant) or before both elements (tsu oyf-es-n to up-eat-INF; the innovative variant). Nearly 38,000 tokens of non-finite particle verbs were extracted from the popular Hasidic Yiddish discussion forum Kave Shtiebel (the ‘coffee room’; kaveshtiebel.com). A mixed-effects regression analysis reveals that despite a forum-wide favoring effect for the innovative variant, users favor the conservative variant the longer their accounts remain open and active. This process of rapid implicit standardization is supported by ethnographic evidence highlighting the spread of language norms among Hasidic writers on the internet, most of whom did not have the opportunity to express themselves in written Yiddish prior to the advent of social media.",26248212,AI
10.3390/cancers12061425,A Phase 1 Study of mTORC1/2 Inhibitor BI 860585 as a Single Agent or with Exemestane or Paclitaxel in Patients with Advanced Solid Tumors,"This phase 1 trial (NCT01938846) determined the maximum tolerated dose (MTD) of the mTOR serine/threonine kinase inhibitor, BI 860585, as monotherapy and with exemestane or paclitaxel in patients with advanced solid tumors. This 3+3 dose-escalation study assessed BI 860585 monotherapy (5–300 mg/day; Arm A), BI 860585 (40–220 mg/day; Arm B) with 25 mg/day exemestane, and BI 860585 (80–220 mg/day; Arm C) with 60–80 mg/m2/week paclitaxel, in 28-day cycles. Primary endpoints were the number of patients with dose-limiting toxicities (DLTs) in cycle 1 and the MTD. Forty-one, 25, and 24 patients were treated (Arms A, B, and C). DLTs were observed in four (rash (n = 2), elevated alanine aminotransferase/aspartate aminotransferase, diarrhea), four (rash (n = 3), stomatitis, and increased gamma-glutamyl transferase), and two (diarrhea, increased blood creatine phosphokinase) patients in cycle 1. The BI 860585 MTD was 220 mg/day (Arm A) and 160 mg/day (Arms B and C). Nine patients achieved an objective response (Arm B: Four partial responses (PRs); Arm C: Four PRs; one complete response). The disease control rate was 20%, 28%, and 58% (Arms A, B, and C). The most frequent treatment-related adverse events (AEs) were hyperglycemia (54%) and diarrhea (39%) (Arm A); diarrhea (40%) and stomatitis (40%) (Arm B); fatigue (58%) and diarrhea (58%) (Arm C). The MTD was determined in all arms. Antitumor activity was observed with BI 860585 monotherapy and in combination with exemestane or paclitaxel.",20726694,ONCOLOGY
10.1007/s00432-020-03275-x,Appropriate arrangement of cancer treatment after COVID-19 epidemic peaks in China,"Purpose COVID-19 is causing a lot of problems in health services around the world, especially in medical institutions receiving cancer patients. On March 12, China’s National Health Commission announced that the peak of the COVID-19 epidemic has passed in China. Thus, a proper arrangement of medication, surgery and radiotherapy for patients with cancer is of vital importance after the epidemic peak. Methods A range of measures have been implemented in our center. Specific patients take priority for chemotherapy treatment. The amount of semi-elective and elective surgeries could be gradually increased beyond urgent and emergency surgery. The hypofractionated radiotherapy is recommended in the right circumstances. Results On March 13, our center announced that more than 5000 visits of chemotherapy and radiotherapy are arranged in our outpatient clinics and none of our patients and staffs have been diagnosed with COVID-19 as of March 28, 2020. Conclusion The rational arrangement we make now may be helpful to the future restoration of cancer treatments in other countries.",14321335,ONCOLOGY
10.3389/feduc.2020.00053,Form-Focused Instruction in the Heritage Language Classroom: Toward Research-Informed Heritage Language Pedagogy,"In the context of adult second language teaching, heritage language speakers have been recognized as a special group of language learners, whose experience with their home language, as well as their motivations for (re)learning it, differ drastically from those of an average learner of a second language. Current heritage language pedagogical approaches focus primarily on the development of communicative (or functional) abilities of the heritage learners and on critical exploration of bilingual practices and identities. However, structural accuracy remains a persistent issue for heritage speakers, who do not always reach higher levels of proficiency in their heritage language (as measured by standard language proficiency tests). In this paper, we use the example of heritage Russian instruction in American college classrooms to argue for the critical role of form-focused instruction in teaching a heritage language, and in particular in bringing heritage learners to greater proficiency. The argument for the importance of form-focused instruction is based on the results of extensive linguistic research combined with insights from the currently available pedagogically oriented research. We formulate and discuss instructional methods that help educators (1) develop heritage learners’ attention to grammatical form, (2) foster heritage learners’ understanding of grammatical concepts, and (3) increase the learners’ metalinguistic awareness. Given consistent parallels across different heritage languages, the methodologies developed for Russian learners can apply to other heritage language classrooms as well, with adjustments based on the sociolinguistic context of particular heritage languages.",2504284X,EDUCATION
10.3390/ai1020017,Improving Daily Peak Flow Forecasts Using Hybrid Fourier-Series Autoregressive Integrated Moving Average and Recurrent Artificial Neural Network Models,"In multi-purpose reservoirs, to achieve optimal operation, sophisticated models are required to forecast reservoir inflow in both short- and long-horizon times with an acceptable accuracy, particularly for peak flows. In this study, an auto-regressive hybrid model is proposed for long-horizon forecasting of daily reservoir inflow. The model is examined for a one-year horizon forecasting of high-oscillated daily flow time series. First, a Fourier-Series Filtered Autoregressive Integrated Moving Average (FSF-ARIMA) model is applied to forecast linear behavior of daily flow time series. Second, a Recurrent Artificial Neural Network (RANN) model is utilized to forecast FSF-ARIMA model’s residuals. The hybrid model follows the detail of observed flow time variation and forecasted peak flow more accurately than previous models. The proposed model enhances the ability to forecast reservoir inflow, especially in peak flows, compared to previous linear and nonlinear auto-regressive models. The hybrid model has a potential to decrease maximum and average forecasting error by 81% and 80%, respectively. The results of this investigation are useful for stakeholders and water resources managers to schedule optimum operation of multi-purpose reservoirs in controlling floods and generating hydropower.",26732688,AI
10.3390/cancers12061572,Quantitative Analysis of Differential Expression of HOX Genes in Multiple Cancers,"Transcription factors encoded by Homeobox (HOX) genes play numerous key functions during early embryonic development and differentiation. Multiple reports have shown that mis-regulation of HOX gene expression plays key roles in the development of cancers. Their expression levels in cancers tend to differ based on tissue and tumor type. Here, we performed a comprehensive analysis comparing HOX gene expression in different cancer types, obtained from The Cancer Genome Atlas (TCGA), with matched healthy tissues, obtained from Genotype-Tissue Expression (GTEx). We identified and quantified differential expression patterns that confirmed previously identified expression changes and highlighted new differential expression signatures. We discovered differential expression patterns that are in line with patient survival data. This comprehensive and quantitative analysis provides a global picture of HOX genes’ differential expression patterns in different cancer types.",20726694,ONCOLOGY
10.3390/educsci10070177,"Progression of Cognitive-Affective States During Learning in Kindergarteners: Bringing Together Physiological, Observational and Performance Data","It has been shown that combining data from multiple sources, such as observations, self-reports, and performance with physiological markers offers better insights into cognitive-affective states during the learning process. Through a study with 12 kindergarteners, we explore the role of utilizing insights from multiple data sources, as a potential arsenal to supplement and complement existing assessments methods in understanding cognitive-affective states across two main pedagogical approaches—constructionist and instructionist—as children explored learning a chosen Science, Technology, Engineering and Mathematics (STEM) concept. We present the trends that emerged across pedagogies from different data sources and illustrate the potential value of additional data channels through case illustrations. We also offer several recommendations for such studies, particularly when collecting physiological data, and summarize key challenges that provide potential avenues for future work.",22277102,EDUCATION
10.3390/cancers12071782,"A Novel Combination Treatment with Honokiol and Rapamycin Effectively Restricts c-Met-Induced Growth of Renal Cancer Cells, and also Inhibits the Expression of Tumor Cell PD-L1 Involved in Immune Escape","The mTOR inhibitor Rapamycin has tumor inhibitory properties; and it is also used as an immunosuppressive agent after organ transplantation. However, prolonged Rapamycin treatment re-activates Akt and can promote cancer growth. Honokiol is a natural compound with both anti-tumorigenic and anti-inflammatory properties. Here, we assessed the anti-tumor effects of Rapamycin and Honokiol combination in renal cell carcinoma (RCC). Receptor tyrosine kinase c-Met-mediated signaling plays a major role in RCC growth. We observed that compared with Rapamycin alone, Rapamycin + Honokiol combination can effectively down-regulate c-Met-induced Akt phosphorylation in renal cancer cells; and it markedly inhibited Ras activation and cell proliferation and promoted G1 phase cell cycle arrest. The combination treatment significantly induced ROS generation and cancer cell apoptosis even when c-Met is activated. Importantly, Honokiol, but not Rapamycin, decreased c-Met-induced expression of the co-inhibitory molecule PD-L1, implied in the immune escape of renal cancer cells. In mouse renal cancer cells and Balb/c splenocytes co-culture assay, Rapamycin + Honokiol markedly potentiated immune-cell-mediated killing of cancer cells, possibly through the down-regulation of PD-L1. Together, Honokiol can effectively overcome the limitation of Rapamycin treatment alone; and the combination treatment can markedly restrict the growth of RCC, with particular importance to post-transplantation renal cancer.",20726694,ONCOLOGY
10.1007/s00432-020-03298-4,Aberrant DNA methylation results in altered gene expression in non-alcoholic steatohepatitis-related hepatocellular carcinomas,"Purpose: The aim of this study was to investigate DNA methylation alterations in non-alcoholic steatohepatitis (NASH)-related hepatocellular carcinomas (HCCs). Methods: Genome-wide DNA methylation analysis was performed using the Infinium Human Methylation 450 K BeadChip, and levels of mRNA expression were analyzed by quantitative reverse transcription-PCR. Results: Compared to 36 samples of normal control liver tissue (C), DNA methylation alterations were observed on 19,281 probes in 22 samples of cancerous tissue (T) obtained from patients showing histological features compatible with NASH in their non-cancerous liver tissue (N). Among those probes, 1396 were located within CpG islands or their shores and shelves, designed around the transcription start sites of 726 genes. In representative genes, such as DCAF4L2, CKLF, TRIM4, PRC1, UBE2C and TUBA1B, both DNA hypomethylation and mRNA overexpression were observed in T samples relative to C samples, and the levels of DNA methylation and mRNA expression were inversely correlated with each other. DNA hypomethylation occurred even in N samples at the precancerous NASH stage, and this was inherited by or further strengthened in T samples. DNA hypomethylation of DCAF4L2, CKLF and UBE2C was observed in both NASH-related and viral hepatitis-related HCCs, whereas that of TRIM4, PRC1 and TUBA1B occurred in a NASH-related HCC-specific manner. DNA hypomethylation and/or mRNA overexpression of these genes was frequently associated with the necroinflammatory grade of NASH and was correlated with poorer tumor differentiation. Conclusion: DNA methylation alterations may occur under the necroinflammatory conditions characteristic of NASH and participate in NASH-related hepatocarcinogenesis through aberrant expression of tumor-related genes.",14321335,ONCOLOGY
10.3389/fonc.2020.01408,Risk Factor Analysis of Acute Kidney Injury After Microwave Ablation of Hepatocellular Carcinoma: A Retrospective Study,"Objectives:Acute kidney injury (AKI) is a recently observed side effect in patients after microwave ablation (MWA) of hepatocellular carcinoma (HCC) and is associated with negative outcomes. The aim of this study is to explore the risk factors of affecting the occurrence of AKI (stages 1b, 2, and 3), because they have a higher mortality rate than patients with AKI (stage 1a) and without AKI. Materials and methods:In this retrospective study, a total of 1,214 patients with HCC who were treated with MWA under ultrasound (US) guidance in our department between January 2005 and November 2017 were enrolled. We evaluated the influence of 20 risk factors. Univariate and multivariate analysis were used for statistical analysis. The possible risk factors of AKI after MWA for HCC were summarized. Results:AKI, AKI (stage 1a), and AKI (stages 1b, 2, and 3) after MWA were found in 34, 15, and 19 patients (2.80, 1.24, and 1.57%), respectively. Among 34 patients with AKI, 10 cases with AKI (stage 1a) and 6 cases with AKI (stages 1b, 2, and 3) recovered before their discharge without any treatment for AKI and 9 cases with AKI (stages 1b, 2, and 3) with further treatment. Four cases who had chronic renal failure before MWA of liver accepted renal dialysis. By univariate analysis, the number of antenna insertions (P= 0.027, OR = 3.3), MWA time >= 20 min (P= 0.029, OR = 4.3), creatinine (Cr)-pre above the upper limit of the reference value (P< 0.001, OR = 35.5), albumin (Alb)-pre (P= 0.030, OR = 0.9), and red blood cell (RBC)-pre (P< 0.001, OR = 0.3) were significant risk factors. By multivariate analysis, Cr-pre >= 110 mu mol/L (P< 0.001, OR = 31.4) and MWA time >= 20 min (P= 0.043 OR = 9.9) were the independent risk factors. Conclusion:AKI (stages 1b, 2, and 3) is a relatively serious complication after MWA for HCC, which is related to MWA time and Cr-pre. It requires attention by clinicians. So it is of great necessity to assess the Cr-pre level and reduce the MWA time to <20 min to minimize the risk of AKI after MWA for HCC.",2234943X,ONCOLOGY
10.3389/frai.2020.00070,Clustering and Recognition of Spatiotemporal Features Through Interpretable Embedding of Sequence to Sequence Recurrent Neural Networks,"Encoder-decoder recurrent neural network models (RNN Seq2Seq) have achieved success in ubiquitous areas of computation and applications. They were shown to be effective in modeling data with both temporal and spatial dependencies for translation or prediction tasks. In this study, we propose an embedding approach to visualize and interpret the representation of data by these models. Furthermore, we show that the embedding is an effective method for unsupervised learning and can be utilized to estimate the optimality of model training. In particular, we demonstrate that embedding space projections of the decoder states of RNN Seq2Seq model trained on sequences prediction are organized in clusters capturing similarities and differences in the dynamics of these sequences. Such performance corresponds to an unsupervised clustering of any spatio-temporal features and can be employed for time-dependent problems such as temporal segmentation, clustering of dynamic activity, self-supervised classification, action recognition, failure prediction, etc. We test and demonstrate the application of the embedding methodology to time-sequences of 3D human body poses. We show that the methodology provides a high-quality unsupervised categorization of movements. The source code with examples is available in a Github repository1.",26248212,AI
10.3389/fonc.2020.523577,Baoyuan Jiedu Decoction Alleviates Cancer-Induced Myotube Atrophy by Regulating Mitochondrial Dynamics Through p38 MAPK/PGC-1α Signaling Pathway,"Cancer cachexia is a multifactorial syndrome characterized by continuous body wasting and loss of skeletal muscle. Impaired mitochondria function is closely associated with muscle atrophy in cancer cachexia. Our previous study confirmed the effectiveness of Baoyuan Jiedu decoction (BJD) in inhibiting cancer-induced muscle atrophy in an in vivo model. However, little is known about its mechanisms in regulating mitochondria dysfunction. In this study, we evaluated the therapeutic effect and action mechanisms of BJD against atrophy both in the Lewis-conditioned medium induced C2C12 myotube atrophy model and in a BALB/c mice xenograft model using mouse colon cancer C26 cells. The mitochondrial content was tested by 10-Non-ylacridine orange staining. Expressions of related proteins and mRNAs were detected by western blotting (WB) and qPCR, respectively. As a result, 18 major components were identified in BJD by ultra-high performance liquid chromatography-quadrupole (UHPLC-Q) Exactive analysis. As shown in the in vitro results, BJD treatment prevented prominent myotube atrophy and increased the myotube diameter of C2C12 cells. Besides, BJD treatment increased mitochondrial content and ATPase activity. Furthermore, the protein and mRNA expressions that were related to mitochondrial functions and generation such as cytochrome-c oxidase IV, Cytochrome C, nuclear respiratory factor 1, and mitochondrial transcription factor A were significantly increased in BJD treatment compared to the control group. The in vivo results showed that BJD treatment prevented body weight loss and improved the gastrocnemius index in cachexia mice. Moreover, the expressions of Atrogin-1 and muscle RING-finger protein-1 were decreased by BJD treatment. Mechanically, BJD increased the expression of peroxisome proliferator-activated receptor-gamma coactivator 1, and consistently, inhibited the expression of p38 MAPK and its phosphorylation both in vivo and in vitro. Taken together, this study identified that BJD effectively relieved cancer-induced myotube atrophy and provided a potential mechanism for BJD in regulating mitochondrial dynamics through p38 MAPK/PGC-1α signaling pathway.",2234943X,ONCOLOGY
10.3389/fonc.2020.579445,"Pembrolizumab-Induced Psoriasis in Metastatic Melanoma: Activity and Safety of Apremilast, a Case Report","Background: Immune checkpoint inhibitors targeting cytotoxic T lymphocyte-associated antigen 4 (CTLA-4), programmed death-1 receptor (PD-1), and programmed death-1 receptor and its ligand (PD-L1) increased the survival of patients affected by metastatic malignant melanoma. Due to their mechanism of action, these drugs are associated with a unique toxicity profile. Indeed, immune-related adverse events (irAEs) present a wide clinical spectrum representing the Achilles’ heel of immunotherapy. Overall, cutaneous toxicities are among the most common irAEs. Immunomodulatory drugs are used for the management of irAEs and can theoretically lead to tumor escape. Case Presentation: We report the case of a 75-year-old man with metastatic melanoma receiving the anti-PD1 Pembrolizumab therapy. After 10 treatment cycles, the patient came to our clinic with itchy psoriatic manifestations widespread >30% of the body surface [12.3 Psoriasis Area and Severity Index (PASI) score] that negatively impacted on the patient’s quality of life and compliance with immunotherapy. Additionally, he had no positive personal history of psoriasis. Given the severity of the cutaneous manifestations, in a multidisciplinary approach, Apremilast (an oral small molecule PDE4 inhibitor) was started. Furthermore, Pembrolizumab was interrupted for 4 weeks until the improvement of skin lesions and the disappearance of itching. Immunosuppressive methylprednisolone therapy was initiated with a dose of 16 mg/die; then, this initial dose was progressively reduced until discontinuation. After 10 months, the patient had a good general clinical condition with psoriasis complete remission. Moreover, positron emission tomography (PET) and computed tomography (CT) scans showed complete response by immune Response Evaluation Criteria in Solid Tumors (iRECIST). Conclusion: To the best of our knowledge, this is the first report on the safety and efficacy of Apremilast for the treatment of immunotherapy-induced psoriasis in metastatic melanoma.",2234943X,ONCOLOGY
10.1007/s00432-020-03400-w,Health-related quality of life after Gamma Knife radiosurgery in patients with 1–10 brain metastases,"Purpose: Increasingly more patients with multiple (> 4) brain metastases (BM) are being treated with stereotactic radiosurgery (SRS). Preserving patients’ health-related quality of life (HRQoL) is an important treatment goal. The aim of this study was to assess (individual) changes in HRQoL in patients with 1–10 BM over time.Methods: A total of 92 patients were assessed before (n = 92) and at 3 (n = 66), 6 (n = 53), and 9 (n = 41) months after Gamma Knife radiosurgery (GKRS), using the Functional Assessment of Cancer Therapy-Brain (FACT-Br). The course of HRQoL was analyzed using linear mixed models. Clinical minimally important differences were used to evaluate individual changes.Results: At group level, patients’ physical well-being worsened, whereas emotional well-being improved over 9 months. Scores on other HRQoL subscales did not change significantly. Number (1–3 versus 4–10) and volume (small, medium, and large) of BM did not influence HRQoL over time, except for the subscale additional concerns; medium intracranial tumor volume was associated with less additional concerns. On the individual level as well, physical well-being declined while emotional well-being improved in most patients over 9 months after GKRS. At patient level, however, most patients had both declines as well as improvements in the different HRQoL aspects.Conclusion: Our results indicate that even in patients with up to 10 BM, both at group and individual subscale level, aspects of HRQoL remained stable over nine months after GKRS, except for an improvement in emotional well-being and a decline in physical well-being. Nevertheless, HRQoL scores varied considerably at the individual patient level.Trail registration number: ClinicalTrials.gov Identifier: NCT02953756, November 3, 2016.",14321335,ONCOLOGY
10.3389/fpsyg.2020.552831,Development of Chinese Junior High School Students’ Creative Potential: Within-Person and Between-Person Effects of Student–Student Support and Need for Cognition,"A longitudinal study was conducted to examine the developmental trend of creative potential in Chinese junior high school students and the within-person and between-person effects of student–student support and need for cognition. Two hundred and fourteen Chinese junior high school students participated in the present study (mean age = 13.29 years, SD = 0.49 years, 116 boys). Student–student support, need for cognition, and creative potential were measured once per year for 3 years. Longitudinal multilevel models indicated that (1) Chinese junior high school students’ creative potential showed a downward trend from grades 7 to 9; (2) at the within-person level, time-varying student–student support positively predicted time-varying creative potential; (3) at the within-person level, time-varying need for cognition moderated the positive link between time-varying student–student support and time-varying creative potential; and (4) at the between-person level, no support was found for the links between student–student support, need for cognition, and creative potential. Specifically, average levels of student–student support neither significantly predicted initial levels and developmental rates of creative potential nor moderated the links between average levels of student–student and initial levels and developmental rates of creative potential. The findings highlight that at the within-person and between-person levels, student–student support and need for cognition have differential influences on Chinese junior school students’ creative potential.",16641078,PSYCHOLOGY
10.3389/fpsyg.2020.590108,Measuring Gratitude in Germany: Validation Study of the German Version of the Gratitude Questionnaire-Six Item Form (GQ-6-G) and the Multi-Component Gratitude Measure (MCGM-G),"The Gratitude Questionnaire-Six Item Form (GQ-6; McCullough et al., 2002) is a well-established instrument for measuring gratitude. Recently, the Multi-Component Gratitude Measure (MCGM) was developed as a more holistic approach (Morgan et al., 2017). While the GQ-6 mainly focuses on the emotional component of gratitude, the MCGM encompasses conceptual, attitudinal, and behavioral aspects. As of today, there is no validated German measure for gratitude. In order to close that research gap, the present study focused on validating the German versions of the GQ-6 (GQ-6-G) and of the MCGM (MCGM-G). In addition, multi-group comparisons were conducted to test for cultural measurement invariance. Construct validity was tested similar to original validation studies of the two scales focusing on affect, well-being, empathy, anxiety and depression. The online survey was completed in random order by 508 participants. The one-factor model of the GQ-6-G and the hierarchical structure of the MCGM-G could be replicated. However, the model fit of the Gratitude Questionnaire was significantly better after eliminating one item (GQ-5-G). Multi-group comparisons revealed cultural measurement invariance was established for the GQ-5-G and partial measurement invariance for five of six factors of the MCGM-G, respectively. Reliability analyses revealed good internal consistency for both instruments, and measures for criterion-related and discriminant validity have shown hypothesized relationships. Thus, the GQ-5-G and the MCGM-G are two instruments with good reliability and validity for measuring gratitude in Germany.",16641078,PSYCHOLOGY
10.1186/s40594-020-00250-3,Undergraduates’ awareness of White and male privilege in STEM,"Background: It is well-documented that experiences in STEM courses for women and students of color are different from the experiences of White men. As part of a larger interview study, 183 college seniors from diverse gender and race backgrounds were asked their thoughts on whether the experience of being a STEM major was different for people of different races and genders. We use a framework of “science as White property”, derived from critical race theory, to frame this study and results.Results: White men were largely unaware of any impact of race or gender. In contrast, women of color overwhelmingly report, consistent with results from a large body of prior research, that both race and gender impact their experiences as STEM majors. Students who acknowledged race and gender impacts did not always attribute these impacts to cultural or systemic factors (i.e., some reported women are underrepresented because they are less interested in STEM rather than a structural reason). Impacts identified that were attributable to systemic factors included impacts related to being a demographic minority (i.e., intimidation, feeling out of place, feeling pressure to work harder) and/or discrimination (i.e., job discrimination, bias against women or people of color and cultural assumptions implying the superiority of White people and men). A small number of students (mostly White women) stated that women or people of color benefit from their underrepresented status, often attributing this benefit to a perception of extra encouragement and opportunities. A common theme across categorizations was that women and students of color work harder than men and White people either because they are perceived to be harder workers or as a response to the sexism and racism they encounter.Conclusions: We found that White men are largely unaware of the impacts of race or gender on the pursuit of a STEM degree. Additionally, with the exception of women of color, students are less likely to perceive race as having an impact on the experiences of students than gender. We conclude with a discussion of implications for future work related to gender and race representation in STEM.",21967822,EDUCATION
10.3389/fpsyg.2020.571792,Convergent and Discriminant Validities of SCBE-30 Questionnaire Using Correlated Trait–Correlated Method Minus One,"Correlated trait–correlated method minus one was used to evaluate convergent and discriminant validity of Social Competence Behavior Evaluation questionnaire (Social Competence, Anger-Aggression, Anxiety-Withdrawal) between multiple raters. A total of 369 children (173 boys and 196 girls; Mage = 55.85, SDage = 11.54) were rated by their mothers, fathers, and teachers. Results showed more convergence between parents than parent-teacher ratings. Mother-teacher share a common view of child behavior that is not shared with father. Parents had more difficulty distinguishing internalizing and externalizing behaviors (especially fathers). Measurement invariance across child sex was explored, results imply that differences between boys and girls were not due to measure. Girls (compare to boys) were described as more social competent by their fathers and teachers, while boys as more aggressive by mothers and teachers.",16641078,PSYCHOLOGY
10.1007/s00432-020-03428-y,Conditional knockdown of integrin beta-3 reveals its involvement in osteolytic and soft tissue lesions of breast cancer skeletal metastasis,"Integrin β3 (ITGB3) is probably related to skeletal metastasis, which is the most frequent complication in breast cancer progression. We aimed to define its role and suitability as target for anti-metastatic therapy. We generated two MDA-MB-231 cell clones with conditional miRNA-mediated ITGB3 knockdown for analyzing the resulting effects in vitro regarding mRNA expression, proliferation and migration, as well the impact on skeletal metastasis in a nude rat model. Furthermore, ITGB3 levels were analyzed in exosomes from plasma of rats with skeletal metastases, and from MDA-MB-231 cells incubated with these vesicles, as well as from exosomes secreted by cells with conditional ITGB3 knockdown. This inhibition of ITGB3 expression decreased cellular proliferation and more distinctly inhibited cellular migration. Reduction and even complete remissions of respective soft tissue and osteolytic lesions were detected after ITGB3 knockdown in vivo. Furthermore, ITGB3 levels were increased in exosomes isolated from plasma of rats harboring MDA-MB-231 lesions as well as in respective cells incubated with these vesicles in vitro. ITGB3 was distinctly decreased in exosomes from cells with ITGB3 knockdown. The observed in vitro and in vivo anti-ITGB3 effects can be explained by downregulation of specific genes, which have roles in angiogenesis (NPTN, RRM2), tumor growth (NPTN), energy metabolism (ISCA1), cytokinesis (SEPT11), migration (RRM2, STX6), cell proliferation, invasiveness, senescence, tumorigenesis (RRM2) and vesicle trafficking (SEPT11, STX6). ITGB3 has a role in breast cancer skeletal metastasis via gene expression modulation, as mirrored for ITGB3 in exosomes, thus it could serve as target for anti-metastatic therapy.",14321335,ONCOLOGY
10.3389/fonc.2020.583625,Evaluation of Polygenic Risk Scores for Prediction of Prostate Cancer in Korean Men,"Aims The purpose of this study is to evaluate an aggregate influence of prostate cancer (PCa) susceptibility variants on the development of PCa in Korean men by using the polygenic risk score (PRS) approach. Methods An analysis of 1,001 cases of PCa and 2,641 controls was performed to: (i) identify potential PCa-related risk loci in Koreans and (ii) validate the cumulative association between these loci and PCa using the PRS. Subgroup analyses based on risk stratification were conducted to better characterize the potential correlation to key PCa-related clinical outcomes (e.g., Gleason score, prostate-specific antigen levels). The results were replicated using 514 cases of PCa and 548 controls from an independent cohort. Results Genome-wide association analysis from our discovery cohort revealed 11 candidate single-nucleotide polymorphisms (SNPs) associated with PCa showing statistical significance of p < 5.0 x 10(-5). Seven variants were located at 8q24.21 (rs1016343, rs16901979, and rs13252298 in PRNCR1; rs4242384, rs7837688, and rs1447295 in CASC8; and rs1512268 in NKX3). Two variants located within HNF1B (rs7501939 and rs4430796) had a significant negative association with PCa risk [odds ratio (OR) = 0.717 and 0.747, p = 6.42 x 10(-7) and 3.67 x 10(-6), respectively]. Of the six independent SNPs that remained after linkage disequilibrium (LD) pruning, the top four SNPs best predicted PCa risk with an area under the receiver operating characteristic curve (AUC) of 0.637 (95% CI: 0.582-0.692). Those with top 25% polygenic risk had a 4.2-fold increased risk of developing PCa compared with those with low risk. Conclusion Eleven PCa risk variants in Korean men were identified; PRSs of a subset of these variants could help predict PCa susceptibility.",2234943X,ONCOLOGY
10.1007/s00432-020-03417-1,Penile cancer: a Brazilian consensus statement for low- and middle-income countries,"Purpose: Penile cancer is highly prevalent in low- and middle-income countries, with significant morbidity and mortality rates. The first Brazilian consensus provides support to improve penile cancer patients’ outcomes, based on expert’s opinion and evidence from medical literature. Methods: Fifty-one Brazilian experts (clinical oncologists, radiation oncologists, urologists, and pathologists) assembled and voted 104 multiple-choice questions, confronted the results with the literature, and ranked the levels of evidence. Results: Healthcare professionals need to deliver more effective communication about the risk factors for penile cancer. Staging and follow-up of patients include physical examination, computed tomography, and magnetic resonance imaging. Close monitoring is crucial, because most recurrences occur in the first 2–5 years. Lymph-node involvement is the most important predictive factor for survival, and management depends on the location (inguinal or pelvic) and the number of lymph nodes involved. Conservative treatment may be helpful in selected patients without compromising oncological outcomes; however, surgery yields the lowest rate of local recurrence. Conclusion: This consensus provides an essential decision-making orientation regarding this challenging disease.",14321335,ONCOLOGY
10.1186/s40594-020-00251-2,Transforming education with community-developed teaching materials: evidence from direct observations of STEM college classrooms,"The Classroom Observation Project employs direct observations of geoscience teaching across the USA using the Reformed Teaching Observation Protocol (RTOP) to quantify the use of reformed teaching practices. We report on 345 RTOP observations used to evaluate the extent of teaching reform when curricular materials developed as part of the InTeGrate Project (ITG) were used. The InTeGrate Project has published 40 modules of curricular materials that teach geoscience in the context of societal issues and support instructors through guided use of student-centered instructional practices. All ITG materials were developed by teams of instructors, follow a consistent structure, and were evaluated against a project rubric. RTOP scores for classes observed when ITG materials were used (ITG; n = 50, M = 54.0) are significantly higher than RTOP scores for classes observed when ITG materials were not used (non-ITG; n = 295; M = 39.8; p < .0001). ITG observations all have RTOP scores in the student-centered (≥ 50) or transitional (31–49) instructional categories, and none in the teacher-centered instructional category (≤ 30), demonstrating that ITG materials support more student-centered teaching in class sessions where they are used. In 33 paired observations of the same instructor teaching with and without ITG materials, mean RTOP scores when teaching with ITG are greater than mean RTOP scores when teaching without ITG (M = 54 and M = 47.1, respectively). RTOP observations reveal that more student-centered instructional practices occur in class sessions in which ITG materials are used. There is a small range of RTOP scores when individual ITG activities are used by multiple instructors, suggesting that using ITG materials results in a consistent quality of instruction. The complete absence of teacher-centered instruction when using ITG materials means the materials are a useful resource for practicing reformed teaching methods. The model of the ITG Project in the creation and broad dissemination of ready-made curricula for use in large numbers of classrooms can be replicated to transform teaching and learning in other disciplinary communities.",21967822,EDUCATION
10.3389/feduc.2020.545608,"Secondary School Leaving Examinations: The Impact of Expectancies, Values, and Dimensional Comparisons on Male and Female Students’ Science-Oriented Choices","In Germany, secondary school students have to choose at least one STEM subject (mathematics, biology, chemistry, and physics) for their Secondary School Leaving Examinations. In a representative sample of students in grade 13 in one federal state in Germany, we explore male and female students’ subject choices in an expectancy-value as well as dimensional comparison framework by considering prior performance, ability self-concept, and values in the chosen subject. We extend previous research by including dimensional comparisons that students make between the varying subjects they have to choose from. We discriminate between two opposing groups. One group shows a science-avoidance choice pattern by selecting only one science subject: biology (n = 439). The other group shows a science-oriented choice pattern by selecting either physics or chemistry or two STEM subjects of which one is physics or chemistry (n = 248). We measured achievement test scores, relative and absolute midterm grades, ability self-concepts, as well as attainment and utility values in chosen and non-chosen subjects and calculated logistic regressions as well as multigroup models. Our results showed that science-oriented final exam choices depended on two mechanisms. Within the expectancy-value framework, a science-oriented choice pattern was predicted by ability self-concept in mathematics for male and female students. However, attainment and utility values appeared to be irrelevant for this specific choice. Within the dimensional comparison framework, the relative mathematics-English midterm grade was relevant, but only for male students. Our findings raise the question whether male and female students should be encouraged differently in order to stay in the STEM pipeline and how structural conditions may shape pathways into or out of this pipeline.",2504284X,EDUCATION
10.3389/fpsyg.2020.01850,EEG Correlates of Learning From Speech Presented in Environmental Noise,"How the human brain retains relevant vocal information while suppressing irrelevant sounds is one of the ongoing challenges in cognitive neuroscience. Knowledge of the underlying mechanisms of this ability can be used to identify whether a person is distracted during listening to a target speech, especially in a learning context. This paper investigates the neural correlates of learning from the speech presented in a noisy environment using an ecologically valid learning context and electroencephalography (EEG). To this end, the following listening tasks were performed while 64-channel EEG signals were recorded: (1) attentive listening to the lectures in background sound, (2) attentive listening to the background sound presented alone, and (3) inattentive listening to the background sound. For the first task, 13 lectures of 5 min in length embedded in different types of realistic background noise were presented to participants who were asked to focus on the lectures. As background noise, multi-talker babble, continuous highway, and fluctuating traffic sounds were used. After the second task, a written exam was taken to quantify the amount of information that participants have acquired and retained from the lectures. In addition to various power spectrum-based EEG features in different frequency bands, the peak frequency and long-range temporal correlations (LRTC) of alpha-band activity were estimated. To reduce these dimensions, a principal component analysis (PCA) was applied to the different listening conditions resulting in the feature combinations that discriminate most between listening conditions and persons. Linear mixed-effect modeling was used to explain the origin of extracted principal components, showing their dependence on listening condition and type of background sound. Following this unsupervised step, a supervised analysis was performed to explain the link between the exam results and the EEG principal component scores using both linear fixed and mixed-effect modeling. Results suggest that the ability to learn from the speech presented in environmental noise can be predicted by the several components over the specific brain regions better than by knowing the background noise type. These components were linked to deterioration in attention, speech envelope following, decreased focusing during listening, cognitive prediction error, and specific inhibition mechanisms.",16641078,PSYCHOLOGY
10.1186/s40594-020-00254-z,How to foster the formation of STEM identity: studying diversity in an authentic learning environment,"Background: STEM identity has been shown to have a powerful role in an individual’s success in educational environments, as well as on their career goals and trajectories. Historically, however, STEM identity formation for underrepresented students has been hampered by the lack of representation of in STEM fields, which predominantly consist of white males. One educational challenge is diversifying STEM classrooms, both in terms of the students themselves and also in terms of the science and scientists they learn about.Methods: We piloted a 4-credit History, Philosophy, and Sociology of Science course at Michigan State University. Students were tasked with creating exhibits focused on themes of diversity and inclusion in science for a real client. Using a STEM identity survey, we assessed students’ attitudes towards the sciences, issues of diversity in science, and their sense of belonging to their educational communities. We also had the students respond to various short-answer questions throughout the semester to better understand their experiences working on a collaborative authentic learning task.Results: Our results suggest that authentic learning experiences based around ideas of diversity and inclusion can help students develop sense of belonging and positive STEM identities. Students demonstrated shifts in their self-identities as scientists, focusing more on the intersection between their gender, ethnicity, and self-perception as a scientist. Through qualitative analysis of short-answer questions, we were able to ascertain that working in groups in an authentic learning environment helped the students improve their communication and collaboration skills.Conclusions: Students’ increased focus on gender and ethnicity suggests that they are thinking critically about how their personal identities intersect with their scientific identities. Additional research would help us better understand if the coupling of authentic learning and inclusive teaching practices have significant impacts on the formation of students’ STEM identities.",21967822,EDUCATION
10.3389/fpsyg.2020.585745,Dissimilar Phonemes Create a Contextual Interference Effect During a Nonword Repetition Task,"Purpose: The contextual interference effect is a motor learning phenomenon where conditions that decrease overall learning during practice enhance overall learning with new tasks. In the limb literature, this effect is observed when different practice conditions are used (e.g., blocked vs. random practice schedules). In speech motor learning, contextual interference effects are mixed. The differences observed during speech motor learning may be due to the stimuli used. We hypothesized that dissimilar phonemes might create interference during speech motor learning, such that training accuracy would decrease. However, generalization accuracy would increase compared to practice with nonwords containing similar phonemes. Method: Thirty young adults with typical speech and hearing participated in a motor learning study using a cross-over design. Participants engaged in nonword repetition training followed by an immediate retention and transfer task with two sets of nonwords: nonwords with similar phonemes and nonwords with dissimilar phonemes. Percent consonants correct were calculated to examine the effects of the two different types of nonwords based on the stage of skill acquisition. Results: A contextual interference effect was observed in this study using nonwords that varied in phonemic similarity. Nonwords with similar phonemes were produced with greater accuracy during the training stage of skill acquisition, and nonwords with dissimilar phonemes were produced with greater accuracy during the transfer stage. Conclusion: The proposed hypothesis for this study was met – practicing nonwords with dissimilar phonemes resulted in greater accuracy in the transfer phase of this experiment. Results indicate that phonemic dissimilarity produced contextual interference and influenced speech motor learning. These results indicate that the linguistic properties of stimuli must be factored into speech motor learning. Future research should explore if other linguistic variables interact with variables of motor learning to enhance speech practice and generalization outcomes.",16641078,PSYCHOLOGY
10.3389/fonc.2020.01702,"Epidemiology of Thyroid Cancer: Incidence and Mortality in China, 2015","Objective: Using data from cancer registries to estimate thyroid cancer incidence and mortality in China, 2015. Methods: Data submitted from local cancer registries were checked and evaluated according to the criteria of data quality control, a total of 368 cancer registries' data were qualified for the final analysis. Data were stratified by area (urban/rural, eastern/central/western), sex and age, combined with national population data to estimate thyroid cancer incidence and mortality in China, 2015. Results: Approximately 200,700 new cases were diagnosed in 2015, accounting for 5.11% of all cancer cases. The crude incidence rate was 14.60/100,000. Age-standardized incidence rates by Chinese standard population (ASIRC) and world standard population (ASIRW) were 12.05/100,000 and 10.44/100,000, with the cumulative incidence rate (0–74 years old) of 1.00%. About 7,900 deaths of thyroid cancer were reported in 2015, accounting for 0.34% of all cancer deaths. The crude mortality rate was 0.58/100,000, age-standardized mortality rates by Chinese standard population (ASMRC) and world standard population (ASMRW) were 0.37/100,000 and 0.36/100,000. The age-standardized incidence and mortality in females were significantly higher than those in males (P < 0.001). The rates in urban areas were higher than those in rural areas (P < 0.001). The ASIRC in eastern areas was higher than that in central and western areas (P < 0.001), while the ASMRC in central areas was higher than that in eastern and western areas (P < 0.001). Conclusions: The burden of thyroid cancer was heavy in China, cancer control faces the problem of the disparity between geographic areas, and the incidence and mortality rates were varied by sex and age. Targeted cancer preventive measures should be put into practice.",2234943X,ONCOLOGY
10.3389/feduc.2020.601017,Foreign Language Development During Temporary School Closures in the 2020 Covid-19 Pandemic,"This report assesses effects of temporary school closures during the 2020 Covid-19 pandemic in Germany on early foreign language development among primary-school learners of English. We analyze English vocabulary and grammar skills before and after 15 weeks of school closures and the subsequent suspension of foreign-language (FL) instruction. In addition, we compare data from 141 students who experienced interruptions in schooling in 2020 to a matched group of 128 students who had received continuous instruction in the previous school year. The study did not find any negative effects of the temporary instructional suspension on FL vocabulary or grammar. Moreover, variance between students did not increase, and the effect structure of cognitive predictors of FL skills remained the same. Overall, temporary suspensions of FL instruction of the nature and length experienced during the 2020 Covid-19 pandemic did not appear to have detrimental effects on general foreign language learning among young students.",2504284X,EDUCATION
10.3389/fpsyg.2020.582572,"The Role of Phonological, Auditory Sensory and Cognitive Skills on Word Reading Acquisition: A Cross-Linguistic Study","Despite considerable evidence regarding the influence of orthography on reading processing, the impact of orthographic depth on reading predictors remains unclear. In addition, it also remains unknown the role of the orthography in the influence of auditory temporal processing and attention skills on word reading skills. The current study investigates the word reading predictors in a group of British and Brazilian children with typical development considering phonological, auditory sensory, short-term memory, and sustained attention skills. Rhyme and Alliteration skills predicted word reading in both groups; however, the correlation in the British group was more robust. Short-term memory was also correlated with reading in both groups; however, it was a significant word reading predictor only in the British group. The auditory sensory was not directly correlated with word reading in either group; however, it was involved with Rhyme and Alliteration performance only in the British group. Those results were discussed considering the complexity of the phonological structure and opaque orthography in English when compared to Portuguese, which indicates that the less transparent the orthography, the higher the importance of factors such as phonological awareness, short-term memory, and to some extent, auditory sensory processing skills on word reading acquisition. Those results emphasize the need to consider orthography and phonological features of a particular language when developing a reading assessment and treatments.",16641078,PSYCHOLOGY
10.3389/frai.2020.534696,Deep Learning for Understanding Satellite Imagery: An Experimental Survey,"Translating satellite imagery into maps requires intensive effort and time, especially leading to inaccurate maps of the affected regions during disaster and conflict. The combination of availability of recent datasets and advances in computer vision made through deep learning paved the way toward automated satellite image translation. To facilitate research in this direction, we introduce the Satellite Imagery Competition using a modified SpaceNet dataset. Participants had to come up with different segmentation models to detect positions of buildings on satellite images. In this work, we present five approaches based on improvements of U-Net and Mask R-Convolutional Neuronal Networks models, coupled with unique training adaptations using boosting algorithms, morphological filter, Conditional Random Fields and custom losses. The good results—as high as AP=0.937 and AR=0.959—from these models demonstrate the feasibility of Deep Learning in automated satellite image annotation.",26248212,AI
10.3389/fonc.2020.545460,Circular RNA Circ-03955 Promotes Epithelial-Mesenchymal Transition in Osteosarcoma by Regulating miR-3662/Metadherin Pathway,"Osteosarcoma is the most common primary malignant tumor, especially in children and adolescents. Circular RNAs (circRNAs) are found to play roles in the progression of osteosarcoma. However, the exact functions of circRNAs in osteosarcoma development still need to be clarified. We obtained differentially expressed circRNAs and miRNAs from a GSE99671 data set (GEO database). The gene co-expression network of ceRNAs and osteosarcoma-related genes was analyzed using the STRING database. qRT-PCR was used to detect the expression of circ-03955 and miR-3662. Transwell assays and flow cytometry were performed to detect phenotypic changes in cell function. A xenograft tumor model was established using BALB/c nude mice. Dual luciferase activity and RNA immunoprecipitation assays were performed to assess the relationship between circ-03955, miR-3662, and metadherin (MTDH). Immunohistochemistry, immunofluorescence, and Western blotting were used to assess protein expression levels. Circ-03955 was significantly upregulated, and miR-3662 was downregulated in osteosarcoma. Circ-03955 silencing inhibited the growth and metastasis of osteosarcoma. Mechanism analysis revealed that circ-03955 could bind to miR-3662, and the latter could target MTDH, leading to its suppressed expression and facilitating epithelial-mesenchymal transition (EMT). All these findings demonstrate that the presence of circ-03955 promotes EMT in osteosarcoma by acting as miR-3662 sponge-mediated MTDH expression.",2234943X,ONCOLOGY
10.3389/fonc.2020.596691,Dose–Response Between Serum Prealbumin and All-Cause Mortality After Hepatectomy in Patients With Hepatocellular Carcinoma,"Background: The relationship between serum prealbumin and the risk of all-cause mortality after hepatectomy in patients with hepatocellular carcinoma (HCC) needs to be evaluated. Methods: We conducted a retrospective study. A Cox proportional hazards regression model was used to adjust for potential confounders. Prealbumin level was transformed by Z-scores and categorized into quartiles (Q1: 239 mg/L). We assessed the dose-response relationship between serum prealbumin and the risk of all-cause mortality using a restricted cubic spline model. Results: Data were included from 2,022 HCC patients who underwent hepatectomy at Guangxi Medical University Cancer Hospital in China between January 2006 and January 2016. The adjusted hazard ratios (HRs) for increasing quartiles of serum prealbumin were 0.78 [95% confidence interval (CI): 0.64–0.95] for Q2, 0.66 (0.53–0.81) for Q3, and 0.51 (0.41–0.64) for Q4 in the Cox model (all P < 0.001). Serum prealbumin showed an L-shaped, non-linear dose-response relationship with the risk of all-cause mortality (P < 0.001). Among patients whose serum prealbumin was below 250 mg/L, risk of all-cause mortality decreased by 27% (95% CI: 18–36%) per increase of one standard deviation (69.8 mg/L) in serum prealbumin. Conclusions: Levels of serum prealbumin under 250 mg/L may be considered dangerous with respect to all-cause mortality after hepatectomy in HCC patients. Serum prealbumin may be useful as a prognostic marker in HCC patients undergoing hepatectomy.",2234943X,ONCOLOGY
10.3389/fpsyg.2020.587164,"Association Between Serum Lipid Levels, Resilience, and Self-Esteem in Japanese Adolescents: Results From A-CHILD Study","Previous studies have found that serum lipid levels independently associate with mental health problems in adulthood. However, little is known about the association between serum lipid levels and positive aspects of mental health such as resilience and self-esteem, which develop in adolescence. The aim of this study is to examine the association between serum lipid levels and resilience and self-esteem in Japanese adolescents. Data were pooled data from the Adachi Child Health Impact of Living Difficulty (A-CHILD) study in 2016 and 2018, a school-based, cross-sectional study in Adachi City, Tokyo, Japan (N = 1,056, aged 13–14 years). Resilience of the child was assessed by caregivers, and self-esteem was self-identified via questionnaires. Serum lipid levels [total cholesterol, low-density lipoproteins (LDL), and high-density lipoproteins (HDL)] were assessed in school health checkup, in addition to height and weight measurements. Multiple linear regression was applied to investigate the association between standardized serum lipid levels and resilience and self-esteem. LDL showed inverse association with resilience [β = −1.26, 95% confidence interval (CI) = −2.39 to −0.14] after adjusting for child’s BMI, month of birth, sex, absence of parent, household income, caregiver’s mental health, and lifestyle (e.g., habits of eating, physical activity, and sleep). We also found an inverse association of total cholesterol and higher LDL cholesterol with self-esteem (β = −0.58, 95% CI = −0.99 to −0.18; β = −0.42, 95% CI = −0.83 to −0.01, respectively). HDL cholesterol was not associated with resilience and self-esteem. Among Japanese adolescent, total and LDL cholesterol may be biomarkers of resilience and self-esteem.",16641078,PSYCHOLOGY
10.3389/fpsyg.2020.579986,Benefits and Challenges of Interdisciplinarity in CSCL Research: A View From the Literature,"Computer-supported collaborative learning (CSCL) has a history of being interdisciplinary from its conception. Its beginnings have included computer scientists, psychologists, cognitive scientists, and educational researchers. These collaborations have been fruitful but have also posed challenges (Suthers et al., 2013). This article builds on the authors’ extensive review of the CSCL literature to examine the nature of interdisciplinary collaboration in CSCL research as well as an interdisciplinary CSCL workshop. Using a corpus of more than 700 CSCL articles, we reported an updated analysis for the theories and methods used in CSCL research. In addition, bibliometric analyses examined journals that publish CSCL research and are cited by CSCL research. CSCL research is published in journals that are aligned with interdisciplinary research with large contributions from educational research followed by technology related fields and social sciences. The contributions from domain knowledge journals are relatively weak. These analyses revealed disciplinary influences and uptakes of CSCL research and how they might differ across CSCL research clusters. Lastly, we provide a case example of a CSCL workshop to further demonstrate the interdisciplinary nature of the field. Through these analyses we aim to characterize the benefits and challenges of interdisciplinary collaboration in CSCL research. Interdisciplinarity has helped CSCL research to adopt multiple theories and methods to understand CSCL. While cultivating diversity, we also need to be mindful that research outcomes are exchanged and appropriated actively across participating disciplines so that our understanding of CSCL rises above individual disciplines.",16641078,PSYCHOLOGY
10.3389/fpsyg.2020.611395,Longitudinal Performance in Basic Numerical Skills Mediates the Relationship Between Socio-Economic Status and Mathematics Anxiety: Evidence From Chile,"Socio-economic status (SES) and mathematical performance seem to be risk factors of mathematics anxiety (MA) in both children and adults. However, there is little evidence about how exactly these three constructs are related, especially during early stages of mathematical learning. In the present study, we assessed longitudinal performance in symbolic and non-symbolic basic numerical skills in pre-school and second grade students, as well as MA in second grade students. Participants were 451 children (average pre-school age = 5 years, 6 months) from 12 schools in Chile, which differed in school vulnerability index (SVI), an indicator of SES. We tested an explanatory model of MA that included SES and longitudinal performance in basic numerical skills as predictors. The results showed a direct effect of SES on MA and a mediating effect of performance in symbolic and non-symbolic comparison tasks in pre-school. However, in second grade, only performance in symbolic comparison significantly mediated the SES-MA relationship. These findings suggest that performance in non-symbolic comparison plays an important role in explaining MA at initial stages, but that its influence is no longer significant by the time children reach formal instruction in second grade. By contrast, as children’s formal educational experience in mathematics increases, MA becomes linked primarily to symbolic numerical tasks. In sum, SES affects MA and this is due in part to the effect of SES on the development of numerical learning in pre-school, which in turn has an impact on subsequent, more complex learning, ultimately leading to differences in MA. We discuss the implications of these findings for preventing and acting upon the emergence of MA.",16641078,PSYCHOLOGY
10.3389/frai.2021.556848,Artificial Intelligence and Telehealth may Provide Early Warning of Epidemics,"The COVID-19 pandemic produced a very sudden and serious impact on public health around the world, greatly adding to the burden of overloaded professionals and national medical systems. Recent medical research has demonstrated the value of using online systems to predict emerging spatial distributions of transmittable diseases. Concerned internet users often resort to online sources in an effort to explain their medical symptoms. This raises the prospect that incidence of COVID-19 may be tracked online by search queries and social media posts analyzed by advanced methods in data science, such as Artificial Intelligence. Online queries can provide early warning of an impending epidemic, which is valuable information needed to support planning timely interventions. Identification of the location of clusters geographically helps to support containment measures by providing information for decision-making and modeling.",26248212,AI
10.3389/fonc.2021.582277,DNAJC12 as a Mediator Between ESR1 and ERBB4 in Breast Carcinoma Cells,"Mutation of the DNAJC12 gene is typically associated with non-progressive Parkinsonism, but is also detectable in breast carcinoma where its contribution and mechanisms are unexplored. In breast carcinoma, ESR1 was positively correlated with DNAJC12 and ERBB4, and DNAJC12 was positively correlated with ERBB4. We used the GEO2R tool to compare differential gene expression of MCF-7 cells, following ESR1 knockdown (GEO database, E-GEOD-27473 array), and found decreased expression of DNAJC12 and ERBB4 in ESR1-silenced MCF-7 cells. The number of identical genes having correlativity with ESR1, DNAJC12, or ERBB4 was 12,165 (66.41%). These results suggest that ESR1 can promote the expression of DNAJC12 and ERBB4, and DNAJC12 can enhance the expression of ERBB4 in MCF-7 cells, implying that there may be a regulatory network among these three genes.",2234943X,ONCOLOGY
10.3389/fonc.2021.631007,Non-Genomic Actions of Estrogens on the DNA Repair Pathways Are Associated With Chemotherapy Resistance in Breast Cancer,"Estrogens have been implicated in the etiology of breast cancer for a long time. It has been stated that long-term exposure to estrogens is associated with a higher incidence of breast cancer, since estradiol (E2) stimulates breast cell growth; however, its effect on DNA damage/repair is only starting to be investigated. Recent studies have documented that estrogens are able to modify the DNA damage response (DDR) and DNA repair mechanisms. On the other hand, it has been proposed that DDR machinery can be altered by estrogen signaling pathways, that can be related to cancer progression and chemoresistance. We have demonstrated that E2 promotes c-Src activation and breast cancer cell motility, through a non-genomic pathway. This review discusses scientific evidence supporting this non-genomic mechanism where estrogen modifies the DNA repair pathways, and its relationship to potential causes of chemoresistance.",2234943X,ONCOLOGY
10.3389/feduc.2021.658973,Teacher and Student Practices Associated with Performance in the PISA Reading Literacy Evaluation,"This article aims at finding teacher’s and student’s practices that relate to performance in PISA reading literacy evaluations and that are feasible to intervene in order to assist the improvement of reading competency. To achieve this purpose, the study was developed with data collected from the population of Costa Rica that took the PISA evaluation in 2018 (n = 4691, 2340 men, and 2351 women). A linear regression of the reading score was performed utilizing plausible values and sampling weights. The predictors of the regression were contextual factors, teacher practices, and student habits. Time spent and interest in reading showed a positive and relevant association with student’s performance in reading, controlling important background aspects like economic resources and parents' education. Moreover, 28.19% to the obtained variance explanation of the reading literacy (27%) was only due to the teacher’s and student’s practices. These results provide favorable information to design interventions for the improvement of reading competency.",2504284X,EDUCATION
10.3389/fonc.2021.624240,A Combined Long Noncoding RNA Signature as a Candidate Prognostic Biomarker for Ovarian Cancer,"Aims: Dysregulated long noncoding RNAs (lncRNAs) contributing to ovarian cancer (OC) development may serve as prognostic biomarker. We aimed to explore a lncRNA signature to serve as prognostic biomarker of OC. Methods: Univariate Cox regression was conducted on the lncRNA expression dataset from the TCGA cohort, and 246 genes significantly associated with survival were retained for building a model. A random forest survival model was carried out, and a model was developed using 6 genes with the highest frequency. The selected genes were applied in a Cox multivariate regression model for prognostic prediction by calculating the risk score. We also used CCK-8, EdU, and colony formation assays to validate the function of these lncRNAs in OC cells. Results: This study confirmed that the 6-lncRNA combined signature was related to OC prognosis. Systematic analysis demonstrated that lncRNA-associated genes were enriched in oncogenic signalling pathways. Five out of the 6 lncRNAs participated in OC proliferation. Conclusion: We established a 6-lncRNA combined signature for OC prognosis, which may serve as powerful prognostic biomarker for OC after further validation.",2234943X,ONCOLOGY
10.3389/frai.2021.647999,"Machine Learning-Based Modeling of Spatio-Temporally Varying Responses of Rainfed Corn Yield to Climate, Soil, and Management in the U.S. Corn Belt","Better understanding the variabilities in crop yield and production is critical to assessing the vulnerability and resilience of food production systems. Both environmental (climatic and edaphic) conditions and management factors affect the variabilities of crop yield. In this study, we conducted a comprehensive data-driven analysis in the U.S. Corn Belt to understand and model how rainfed corn yield is affected by climate variability and extremes, soil properties (soil available water capacity, soil organic matter), and management practices (planting date and fertilizer applications). Exploratory data analyses revealed that corn yield responds non-linearly to temperature, while the negative vapor pressure deficit (VPD) effect on corn yield is monotonic and more prominent. Higher mean yield and inter-annual yield variability are found associated with high soil available water capacity, while lower inter-annual yield variability is associated with high soil organic matter (SOM). We also identified region-dependent relationships between planting date and yield and a strong correlation between planting date and the April weather condition (temperature and rainfall). Next, we built machine learning models using the random forest and LASSO algorithms, respectively, to predict corn yield with all climatic, soil properties, and management factors. The random forest model achieved a high prediction accuracy for annual yield at county level as early as in July (R2 = 0.781) and outperformed LASSO. The gained insights from this study lead to improved understanding of how corn yield responds to climate variability and projected change in the U.S. Corn Belt and globally.",26248212,AI
10.3389/fonc.2021.670047,An Immune-Related Signature Predicted Survival in Patients With Kidney Papillary Cell Carcinoma,"Immune-related genes are important factors in tumor progression. The main aim of this study was to identify the immune-related genes in kidney papillary cell carcinoma (pRCC) patients. We downloaded RNAseq data and clinical information of pRCC patients from the TCGA database and retrieved the immune-related genes list from Immport. From the data, we mined out 2,468 differential expression genes (DEGs) and 183 immune-related DEGs. Four hub DEGs (NTS, BIRC5, ELN, and CHGA) were identified after conducting Cox analysis and LASSO analysis. Moreover, the prognostic value of the signature based on four hub DEGs was verified using Kaplan–Meier analysis (P = 0.0041 in the training set and p = 0.021 in the test set) and ROC analysis (AUC: 0.957 in 1 year, 0.965 in 2 years, and 0.901 in 3 years in the training set, and 0.963 in 1 year, 0.898 in 2 years, and 0.742 in 3 years in the test set). Furthermore, we found that the high-risk score group had a higher percentage of B cells in the immune component, a higher expression of immune-related genes (CTLA4, LAG3, PDCD1LG2, and TIGIT), and a better immunotherapy response.",2234943X,ONCOLOGY
10.3389/fonc.2021.665217,"Different Patient Subgroup Different Maintenance, Proteasome Inhibitors or Immunomodulators Maintenance for Newly Diagnosed Multiple Myeloma: A 7-Year Single-Center Data in China","Introduction: We analyzed different patient subgroups to determine optimal maintenance therapy in newly diagnosed multiple myeloma (NDMM) patients.Methods: A total of 226 NDMM patients in our center were included in the study. The characteristics, survival, and adverse reactions were compared among patients who received maintenance therapy or not, and patients who received proteasome inhibitors (PIs) or immunomodulators (IMiDs) maintenance. The survival of different maintenance durations of bortezomib-based regimens was also analyzed.Results: The maintenance therapy not only upgraded more patient responses (34.3 vs 13.3%, P = 0.006), but also significantly prolonged their progression-free survival (PFS) (median PFS: 41.1 vs 10.5 months, P < 0.001) and overall survival (OS) (median OS: not reached vs 38.6 months, P < 0.001). Compared with IMiDs, the PFS (median PFS: 43.7 vs 38.5 months, P = 0.034) and OS (median OS: not reached vs 78.5 months, P = 0.041) were both enhanced by PIs maintenance. Patients younger than 65 years who received PIs had a significantly prolonged OS (P = 0.032). Patients achieving only a partial response (PR) after induction and consolidation therapy had significantly longer PFS and OS after PIs maintenance compared to IMiDs (P = 0.007, 0.002). High-risk patients (ISS 2–3, DS 2–3, and RISS 2–3) given PIs maintenance benefit from a prolonged PFS (P = 0.002, 0.02, 0.06) and OS (P = 0.059, 0.047, 0.044, respectively) compared with IMiDs therapy. OS was significantly prolonged in patients who received ≥ 12 months of bortezomib-based maintenance therapy compared to those who were treated for < 12 months (P < 0.001), but no difference was observed in OS between patients who received 12 to 24 or ≥ 24 months of bortezomib-based maintenance therapy (P = 0.292).Conclusion: PIs maintenance was superior to IMiDs in overall PFS and OS. The beneficial effect was most evident in patients achieving PR after induction and consolidation therapy, and in high-risk patients. Moreover, younger patients also benefited from PIs maintenance with an increased OS. A bortezomib-based maintenance therapy duration of 12 to 24 months after induction and consolidation therapy produced satisfactory OS.",2234943X,ONCOLOGY
10.3389/fpsyg.2021.691755,Evaluating Factors Influencing Knowledge-Sharing Behavior of Students in Online Problem-Based Learning,"Adopting online problem-based learning (OPBL) to internship educational programs is an effective teaching method to stimulate self-directed and collaborative learning and knowledge-sharing behavior (KSB) of students. However, the OPBL collaboration experience is different from the traditional lecture-based learning experience for students. Integrating social identity theory and commitment-trust theory develops a formative research model that explains the KSB of students when using social media tools for the OPBL process. This process encourages social interaction and communication of students, in turn, facilitating the integration of collective intelligence or the creation, sharing, and exchange of knowledge. Data collected from 425 nursing students who studied at seven nursing colleges or medical universities in Taiwan were analyzed using the partial least squares (PLSs) technique. The results indicate that social identification is a crucial antecedent of KSB. Relationship quality plays a vital role in shaping the effects of interpersonal trust and relationship commitment (RC) on KSB during internship periods. The findings can contribute to theoretical discussions and enhance the effectiveness of KSB in the literature of internship and non-internship in the higher education field.",16641078,PSYCHOLOGY
10.3389/feduc.2021.681873,Psychometric Properties of the Elementary Social Behavior Assessment in Swedish Primary School: A Teacher Rated Index of Students’ Prosocial School Behaviors,"This study examined the psychometric properties of a Swedish language adaption of the teacher-rated Elementary Social Behavior Assessment (ESBA), which provides an index of students’ prosocial school behaviors. Participants were eight teachers (two teachers per school in four schools) who rated their students (N = 143 children, M age = 8 years old). The ESBA factor structure was tested with Confirmatory Factor Analysis in a series of models. The two- and three-factor models showed better fit. ESBA showed high internal consistency at the observed level. ESBA’s psychometric properties show initial promise as a tool to help Swedish teachers to support students’ prosocial skills development.",2504284X,EDUCATION
10.3389/fonc.2021.668247,PI3K Promotes Basal Cell Carcinoma Growth Through Kinase-Induced p21 Degradation,"Basal cell carcinoma (BCC) is a locally invasive epithelial cancer that is primarily driven by the Hedgehog (HH) pathway. Advanced BCCs are a critical subset of BCCs that frequently acquire resistance to Smoothened (SMO) inhibitors and identifying pathways that bypass SMO could provide alternative treatments for patients with advanced or metastatic BCC. Here, we use a combination of RNA-sequencing analysis of advanced human BCC tumor-normal pairs and immunostaining of human and mouse BCC samples to identify a PI3K pathway expression signature in BCC. Pharmacological inhibition of PI3K activity in BCC cells significantly reduces cell proliferation and HH signaling. However, treatment of Ptch1fl/fl; Gli1-CreERT2 mouse BCCs with the PI3K inhibitor BKM120 results in a reduction of tumor cell growth with no significant effect on HH signaling. Downstream PI3K components aPKC and Akt1 showed a reduction in active protein, whereas their substrate, cyclin-dependent kinase inhibitor p21, showed a concomitant increase in protein stability. Our results suggest that PI3K promotes BCC tumor growth by kinase-induced p21 degradation without altering HH signaling.",2234943X,ONCOLOGY
10.3389/fpsyg.2021.687404,"Past, Present, and Future of Impulse Buying Research Methods: A Systematic Literature Review","Impulse buying (IB) represents a pivotal subject in consumer psychology. A general agreement on its core elements and their relationship is arguably established. So far, however, there has been little discussion about how to assess impulse purchases, leading to a potential divergence of practise from theory and complexities in cross-study comparability. This systematic literature review investigates the research methods and metrics employed in high-quality literature to evaluate impulse shopping behaviours across different environments, including online, offline, and multichannel settings. Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) criteria, the literature search has been conducted on databases relevant for scientific literature, including Scopus, Web of Science, and ProQuest. Fifty-four articles were included in this systematic review. Findings show the existence of four methods to investigate IB, namely quantitative self-reports, laboratory investigations, fieldwork observations, and qualitative interviews. A comparison of the four methods in terms of fit highlights that self-reports and interviews provide a significant contribution in assessing the cognitive facet of impulse purchasing. Laboratory investigations and fieldwork observation find a better fit with the conative and visceral facets of impulsive buying. Considering the major role of affective charges occurring during impulse shopping, complementary research approaches, and metrics belonging to applied psychophysiology and consumer neuroscience are examined. Three opportunities for future research are discussed, including theory building and refinement, understanding individual differences, and honing behavioural predictions.",16641078,PSYCHOLOGY
10.3389/feduc.2021.681952,Assessing the Social Validity of the SAFMEDS Strategy From the Perspective of Teachers and Children,"The Say-All-Fast-Minute-Every-Day-Shuffled (SAFMEDS) strategy promotes fluency across several skills and contexts. However, few studies have reported the social validity key stakeholders associate with using the strategy in schools. Assessing social validity may provide us with some insight into factors that may affect engagement, implementation fidelity, and persistent use of the intervention after the termination of a research study. Study 1 details the findings from a survey completed by teachers who have used the strategy in their schools (N = 55). Using thematic analysis, we identified three themes: 1) factors that promote and limit progress, 2) confidence, and 3) inherent advantages of the SAFMEDS strategy. These themes encapsulate teachers experiences of implementing the strategy under the real-word conditions of the classroom and the accompanying advantages and potential challenges they face. Within study 2, we discuss themes arising from interviews with children (N = 26) about their views and experiences of using the SAFMEDS strategy. These children had used the strategy with their teacher for one academic year to promote fast and accurate recall of arithmetic facts. Analysis of these transcripts revealed five further themes relating to children’s engagement with the strategy: 1) enjoyment, 2) data, 3) sense of achievement, 4) skills, and 5) home use. Collectively these themes have potential impact with regards to future training and support models for the SAFMEDS strategy.",2504284X,EDUCATION
10.3389/frai.2021.679459,Users’ Responsiveness to Persuasive Techniques in Recommender Systems,"Understanding user’s behavior and their interactions with artificial-intelligent-based systems is as important as analyzing the performance of the algorithms used in these systems. For instance, in the Recommender Systems domain, the accuracy of the recommendation algorithm was the ultimate goal for most systems designers. However, researchers and practitioners have realized that providing accurate recommendations is insufficient to enhance users’ acceptance. A recommender system needs to focus on other factors that enhance its interactions with the users. Recent researches suggest augmenting these systems with persuasive capabilities. Persuasive features lead to increasing users’ acceptance of the recommendations, which, in turn, enhances users’ experience with these systems. Nonetheless, the literature still lacks a comprehensive view of the actual effect of persuasive principles on recommender users. To fill this gap, this study diagnoses how users of different characteristics get influenced by various persuasive principles that a recommender system uses. The study considers four users’ aspects: age, gender, culture (continent), and personality traits. The paper also investigates the impact of the context (or application domain) on the influence of the persuasive principles. Two application domains (namely eCommerce and Movie recommendations) are considered. A within-subject user study was conducted. The analysis of (279) responses revealed that persuasive principles have the potential to enhance users’ experience with recommender systems. The study also shows that, among the considered factors, culture, personality traits, and the domain of recommendations have a higher impact on the influence of persuasive principles than other factors. Based on the analysis of the results, the study provides insights and guidelines for recommender systems designers. These guidelines can be used as a reference for designing recommender systems with users’ experience in mind. We suggest that considering the results presented in this paper could help to improve recommender-users interaction.",26248212,AI
10.1007/s00432-021-03735-y,Anti-tumour effect of neo-antigen-reactive T cells induced by RNA mutanome vaccine in mouse lung cancer,"Purpose: Mutation-specific T-cell response to epithelial cancers and T-cell-based immunotherapy has been successfully used to treat several human solid cancers. We aimed to investigate the anti-tumour effect of neo-antigen-reactive T(NRT) cells induced by RNA mutanome vaccine, which may serve as a feasible and effective therapeutic approach for lung cancer. Methods: We predicted candidate neo-antigens according to the mutant gene analysis by sequencing the mouse Lewis cells and C57BL/6 mouse tail tissue. RNA vaccine was prepared with the neo-antigens as the template. We assessed antitumor efficacy, cytokine secretion and pathological changes after adoptive transfer of NRT cells in vitro and vivo experiments. Results: We identified 10 non-synonymous somatic mutations and successfully generated NRT cells. The percentage of T-cell activation proportion was increased from 0.072% in conventional T cells to 9.96% in NRT cells. Interferon-γ secretion augmented from 17.8 to 24.2% as well. As an in vivo model, adoptive NRT cell infusion could promote active T-cell infiltration into the tumour tissue and could delay tumour progression. Conclusion: NRT cells induced by RNA mutanome vaccine exert a significant anti-tumour effect in mouse lung cancer, and adoptive NRT cell therapy might be considered a feasible, effective therapeutic approach for lung cancer.",14321335,ONCOLOGY
10.3390/ejihpe12110111,Internet Risk Perception: Development and Validation of a Scale for Adults,"Despite the importance of Internet risk perception, no instrument currently exists that measures this awareness in the Spanish population. The goal of this study was to provide information on studies of the validity and reliability of the Internet Risk Perception (IRP) Scale for adult Spanish citizens. We began with a literature review and validation using a mixed panel with 20 participants. We analyzed the degree to which the subjects agreed or disagreed with the criteria evaluated, including contributions for improving the instrument, and performed a pilot test with 517 adults aged 18 to 77. Construct reliability and validity were analyzed using various statistical analyses. The results from the confirmatory factor analysis showed a sufficient accuracy of the data with parameters that indicated an excellent fit for all items. The Spanish version of the scale for adults is a reliable and valid instrument for use in studies that investigate Internet risk perception in people over 18 years of age.",22549625,PSYCHOLOGY
10.1007/s44196-023-00259-w,Adaptively Directed Image Restoration Using Resilient Backpropagation Neural Network,"In this modern era, visual data transmission, processing, and analysis play a vital role in daily life. Image denoising is the process of approximately estimating the original version of a degraded image. The presence of unexpected noise (e.g., fixed, random, and Gaussian) is the root cause of degradation, which has been reduced to some extent by many linear and non-linear filters based on a median value. The real issue is developing a strategy that should be generalized enough to effectively restore an image corrupted with multi-nature noise. Many researchers have developed novel concepts, but their tactics must acquire the highest performance in this area. This article proposes a constrained strategy for this problem, i.e., an adaptively directed denoising filter (ADD filter) based on a neural network. It consists of three major stages: training, filtering, and enhancing. First, we train a feed-forward back-propagation neural network on noisy and noise-free pixels for effective differentiation. Second, we apply a one-pass selective filter to the noisy image. The objective of this one-pass filter is to minimize noise using an adaptive median or directional filter based on density. Finally, the iterative directional filter is applied to the pre-processed image to enhance its visual quality. The extensive experiments depict that the proposed system has achieved better subjective results and improved local (structural similarity) and global (peak signal-to-noise ratio or mean square error) statistical measures.",18756883,AI
10.1007/s00432-023-04779-y,Neoadjuvant chemoradiotherapy versus neoadjuvant chemotherapy alone for patients with locally advanced rectal cancer: a propensity-score-matched analysis combined with SEER validation,"Background: Neoadjuvant therapy followed by radical surgery is recommended for locally advanced rectal cancer (LARC). But radiotherapy can cause potential adverse effects. The therapeutic outcomes, postoperative survival and relapse rates between neoadjuvant chemotherapy (N-CT) and neoadjuvant chemoradiotherapy (N-CRT) patients have rarely been studied. Methods: From February 2012 to April 2015, patients with LARC who underwent N-CT or N-CRT followed by radical surgery at our center were included. Pathologic response, surgical outcomes, postoperative complications and survival outcomes (including overall survival [OS], disease-free survival [DFS], cancer-specific survival [CSS] and locoregional recurrence-free survival [LRFS]) were analyzed and compared. Concurrently, the Surveillance, Epidemiology, and End Results Program (SEER) database was used to compare OS in an external source. Results: A total of 256 patients were input into the propensity score-matching (PSM) analysis, and 104 pairs remained after PSM. After PSM, the baseline data were well matched and there was a significantly lower tumor regression grade (TRG) (P < 0.001), more postoperative complications (P = 0.009) (especially anastomotic fistula, P = 0.003) and a longer median hospital stay (P = 0.049) in the N-CRT group than in the N-CT group. No significant difference was observed in OS (P = 0.737), DFS (P = 0.580), CSS (P = 0.920) or LRFS (P = 0.086) between the N-CRT group and the N-CT group. In the SEER database, patients who received N-CT had similar OS in both TNM II (P = 0.315) and TNM III stages (P = 0.090) as those who received N-CRT. Conclusion: N-CT conferred similar survival benefits but caused fewer complications than N-CRT. Thus, it could be an alternative treatment of LARC.",14321335,ONCOLOGY
10.3390/cancers15102715,18F-FDG PET-Derived Volume-Based Parameters to Predict Disease-Free Survival in Patients with Grade III Breast Cancer of Different Molecular Subtypes Candidates to Neoadjuvant Chemotherapy,"We investigated whether baseline [18F] Fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)-derived semiquantitative parameters could predict disease-free survival (DFS) in patients with grade III breast cancer (BC) of different molecular subtypes candidate to neoadjuvant chemotherapy (NAC). For each 18F-FDG-PET/CT scan, the following parameters were calculated in the primary tumor (SUVmax, SUVmean, MTV, TLG) and whole-body (WB_SUVmax, WB_MTV, and WB_TLG). Receiver operating characteristic (ROC) analysis was used to determine the capability to predict DFS and find the optimal threshold for each parameter. Ninety-five grade III breast cancer patients with different molecular types were retrieved from the databases of the University Hospital of Padua and the University Hospital of Ferrara (luminal A: 5; luminal B: 34; luminal B-HER2: 22; HER2-enriched: 7; triple-negative: 27). In luminal B patients, WB_MTV (AUC: 0.75; best cut-off: WB_MTV > 195.33; SS: 55.56%, SP: 100%; p = 0.002) and WB_TLG (AUC: 0.73; best cut-off: WB_TLG > 1066.21; SS: 55.56%, SP: 100%; p = 0.05) were the best predictors of DFS. In luminal B-HER2 patients, WB_SUVmax was the only predictor of DFS (AUC: 0.857; best cut-off: WB_SUVmax > 13.12; SS: 100%; SP: 71.43%; p < 0.001). No parameter significantly affected the prediction of DFS in patients with grade III triple-negative BC. Volume-based parameters, extracted from baseline 18F-FDG PET, seem promising in predicting recurrence in patients with grade III luminal B and luminal B- HER2 breast cancer undergoing NAC.",20726694,ONCOLOGY
10.1186/s40359-023-01167-6,From threat to challenge—Improving medical students’ stress response and communication skills performance through the combination of stress arousal reappraisal and preparatory worked example-based learning when breaking bad news to simulated patients: study protocol for a randomized controlled trial,"Background: Breaking bad news (BBN; e.g., delivering a cancer diagnosis) is perceived as one of the most demanding communication tasks in the medical field and associated with high levels of stress. Physicians’ increased stress in BBN encounters can negatively impact their communication performance, and in the long term, patient-related health outcomes. Although a growing body of literature acknowledges the stressful nature of BBN, little has been done to address this issue. Therefore, there is a need for appropriate tools to help physicians cope with their stress response, so that they can perform BBN at their best. In the present study, we implement the biopsychosocial model of challenge and threat as theoretical framework. According to this model, the balance between perceived situational demands and perceived coping resources determines whether a stressful performance situation, such as BBN, is experienced as challenge (resources > demands) or threat (resources < demands). Using two interventions, we aim to support medical students in shifting towards challenge-oriented stress responses and improved communication performance: (1) stress arousal reappraisal (SAR), which guides individuals to reinterpret their stress arousal as an adaptive and beneficial response for task performance; (2) worked examples (WE), which demonstrate how to BBN in a step-by-step manner, offering structure and promoting skill acquisition. Methods: In a randomized controlled trial with a 2 (SAR vs. control) x 2 (WE vs. control) between-subjects design, we will determine the effects of both interventions on stress response and BBN skills performance in N = 200 third-year medical students during a simulated BBN encounter. To identify students’ stress responses, we will assess their perceived coping resources and task demands, record their cardiovascular activity, and measure salivary parameters before, during, and after BBN encounters. Three trained raters will independently score students’ BBN skills performances. Discussion: Findings will provide unique insights into the psychophysiology of medical students who are tasked with BBN. Parameters can be understood more comprehensively from the challenge and threat perspective and linked to performance outcomes. If proven effective, the evaluated interventions could be incorporated into the curriculum of medical students and facilitate BBN skills acquisition. Trial registration: ClinicalTrials.gov (NCT05037318), September 8, 2021.",20507283,PSYCHOLOGY
10.1007/s44196-023-00248-z,Swarm Exploration Mechanism-Based Distributed Water Wave Optimization,"Using sparrow search hunting mechanism to improve water wave algorithm (WWOSSA), which combines the water wave optimization (WWO) algorithm and the sparrow search algorithm (SSA), has good optimization ability and fast convergence speed. However, it still suffers from insufficient exploration ability and is easy to fall into local optimum. In this study, we propose a new algorithm for distributed population structure, called swarm exploration mechanism-based distributed water wave optimization (DWSA). In DWSA, an information exchange component and an optimal individual evolution component are designed to improve information exchange between individuals. This multi-part information interaction and distributed population structure algorithm can help the population algorithm to establish a balance between exploitation and exploration more effectively. We contrast DWSA with the original algorithms WWOSSA and other meta-heuristics in order to show the effectiveness of DWSA. The test set consists of 22 actual optimization issues from the CEC2011 set and 29 benchmark functions from the CEC2017 benchmark functions. In addition, an experimental comparison of the parameter values introduced in DWSA is included. According to experimental results, the proposed DWSA performs substantially better than its competitors. Assessments of the population diversity and landscape search trajectory also confirmed DWSA’s outstanding convergence.",18756883,AI
10.3390/cancers15102732,Targeting Sphingosine 1-Phosphate Metabolism as a Therapeutic Avenue for Prostate Cancer,"Prostate cancer (PC) is the second most common cancer in men worldwide. More than 65% of men diagnosed with PC are above 65. Patients with localized PC show high long-term survival, however with the disease progression into a metastatic form, it becomes incurable, even after strong radio- and/or chemotherapy. Sphingosine 1-phosphate (S1P) is a bioactive lipid that participates in all the steps of oncogenesis including tumor cell proliferation, survival, migration, invasion, and metastatic spread. The S1P-producing enzymes sphingosine kinases 1 and 2 (SK1 and SK2), and the S1P degrading enzyme S1P lyase (SPL), have been shown to be highly implicated in the onset, development, and therapy resistance of PC during the last 20 years. In this review, the most important studies demonstrating the role of S1P and S1P metabolic partners in PC are discussed. The different in vitro, ex vivo, and in vivo models of PC that were used to demonstrate the implication of S1P metabolism are especially highlighted. Furthermore, the most efficient molecules targeting S1P metabolism that are under preclinical and clinical development for curing PC are summarized. Finally, the possibility of targeting S1P metabolism alone or combined with other therapies in the foreseeable future as an alternative option for PC patients is discussed. Research Strategy: PubMed from INSB was used for article research. First, key words “prostate & sphingosine” were used and 144 articles were found. We also realized other combinations of key words as “prostate cancer bone metastasis” and “prostate cancer treatment”. We used the most recent reviews to illustrate prostate cancer topic and sphingolipid metabolism overview topic.",20726694,ONCOLOGY
10.3390/cancers15102740,Evaluation of Gliomas with Magnetic Resonance Fingerprinting with PET Correlation—A Comparative Study,"Objectives: Advanced MR imaging of brain tumors is still mainly based on qualitative imaging. PET imaging offers additive metabolic information, and MR fingerprinting (MRF) offers a novel approach to quantitative data acquisition. The purpose of this study was to evaluate the ability of MRF to predict tumor regions and grading in combination with PET. Methods: Seventeen patients with histologically verified infiltrating gliomas and available amino-acid PET data were enrolled. ROIs for solid tumor parts (SPo), perifocal edema (ED1), and normal-appearing white matter (NAWM) were selected on conventional MRI sequences and aligned to the MRF and PET images. The predictability of gliomas by region and grading as well as intermodal correlations were assessed. Results: For MRF, we calculated an overall predictability by region (SPo, ED1, and NAWM) for all of the MRF parameters of 76.5%, 47.1%, and 94.1%, respectively. The overall ability to distinguish low- from high-grade gliomas using MRF was 88.9% for LGG and 75% for HGG, with an accuracy of 82.4%, a ppV of 85.71%, and an npV of 80%. PET positivity was found in 13/17 patients for solid tumor parts, and in 3/17 patients for the edema region. However, there was no significant difference in region-specific MRF values between PET positive and PET negative patients. Conclusions: MRF and PET provide quantitative measurements of the tumor tissue characteristics of gliomas, with good predictability. Nonetheless, the results are dissimilar, reflecting the different underlying mechanisms of each method.",20726694,ONCOLOGY
10.1186/s40594-023-00423-w,Analyzing the associations between motivation and academic performance via the mediator variables of specific mathematic cognitive learning strategies in different subject domains of higher education,"Background: There are different teaching methods and learning content in the academic field of mathematics between school and university. Many students fail in their studies when the proportion of mathematics is high. Additionally, dropout rates, due to mathematical performance, are high. However, there are different strategies used to improve mathematical skills. Based on the process model of self-regulated learning, an analysis of the association between motivational aspects in the pre-action phase as well as seven special cognitive learning strategies for mathematics in the action phase was conducted. The variables were compared with student performance. The study drew on data from 548 retrospective interviews of cooperative students, using a cross-sectional research design.Results: The analysis via structural equation modeling shows a direct association between motivational aspects, such as academic self-concept and curiosity, and the seven learning strategies in mathematics. Furthermore, there is a direct effect of academic self-concept on performance. However, the learning strategy of practicing was the only variable with associations to performance. Additionally, the indirect effect of curiosity on performance via practicing is analyzed.Conclusion: It can be seen, that curiosity on its own is not enough to ensure a good level of performance in mathematics. The findings suggest student learning strategies focusing on harnessing their curiosity and on practicing. A high academic self-concept is also relevant to the performance level achieved. Lecturers should create a learning environment to support such student behavior.",21967822,EDUCATION
10.1186/s40594-023-00421-y,Evaluating a complex and sustained STEM engagement programme through the lens of science capital: insights from Northeast England,"Background: STEM education providers increasingly use complex intervention models to redress persistent under-representation in STEM sectors. These intervention models require robust evaluation to determine their effectiveness. The study examines a complex, sustained intervention intended to build science capital in young people aged 11–15 over 3 years, which drew on science capital theory and related research to inform intervention design and evaluation. When evaluation results differed from those anticipated, process evaluation supported authors to interpret these findings. By outlining challenges faced in the evaluation of a complex, sustained STEM outreach intervention, this paper addresses critique that outreach programmes focus too often on short-term and positive findings. Results: Intervention outcomes were assessed using a quantitative questionnaire adapted from science capital research, issued to pupils at the intervention’s baseline (2015), midpoint (2017) and endpoint (2019). Adopting a cohort-based model, the 2015 questionnaire collected a baseline for the Year 7 intervention group (children aged 11–12, N = 464), and established baseline comparator groups for Year 9 (children aged 13–14, N = 556) and Year 11 (children aged 15–16, N = 342). The Year 7 intervention group was re-evaluated again in 2017 when in Year 9 (N = 556), and in 2019 when in Year 11 (N = 349). Analysis explored differences in science capital between the intervention and comparator groups and identified lower composite science capital scores and greater proportions of low- and medium-science capital in the intervention group when compared with the two comparator groups. A rationale for this emerged from the subsequent process evaluation. Conclusions: This study’s main contribution is the provision of nuanced insight into the evaluation of STEM interventions for use by others evaluating in similar circumstances, particularly those adopting sustained or complex delivery models. This paper concludes that assessing the effectiveness of complex interventions cannot rely on quantitative evaluation of outcomes alone. Process evaluation can complement quantitative instruments and aid interventions to better understand variability and interpret results. While this study highlights the value of science capital when designing intervention models, it also illustrates the inherent challenges of using an outcome measure of ‘building science capital’, and quantifying levels over an intervention’s course.",21967822,EDUCATION
10.3390/educsci13050503,Teaching and Learning Optics in High School: From Fermat to Feynman,"In this article, we analyze the basis of a proposal that allows teaching the notions of reflection, refraction, interference and diffraction from a unified perspective, using Fermat’s variational principle, recovered by Richard Feynman in his formulation of the paths sum for quantum mechanics. This allows reconsidering the notions of geometrical and physical optics, using the probabilistic and unified model of quantum mechanics by means of mathematical notions that are accessible to high school students.",22277102,EDUCATION
10.1186/s40359-023-01200-8,The effect of marital satisfaction on the self-assessed depression of husbands and wives: investigating the moderating effects of the number of children and neurotic personality,"Background: Based on the family system theory, there is an interactive relationship in the family, especially the cognitive style and emotional changes of the husband and wife will affect the behavior, cognition and emotion of the partner. Data about the effects of marital relationships on mental health are often paired. Scholars study the effect of individual independent variables on the dependent variables and the effect of spouse independent variables on the dependent variables to explore the actor and partner effect in marital relationships. Methods: This study used the China Family Panel Studies (CFPS) 2018 dataset to collect paired data on the marital satisfaction and self-rated mental health of 9,560 couples. The Actor–Partner Interdependence Moderation Model (APIMoM) was used to analyze whether moderator variables affect the direction and strength of the effect of marital satisfaction on self-rated depression. In the robustness test part, the robustness of the APIMoM model was tested by reanalyzing the independent variables using two kinds of binary codes respectively, and the results showed that the models were robust. Results: Individuals’ marital satisfaction was significantly negatively correlated with their own depression level and with that of their spouse. The number of family members had a positive moderating effect on the results of the wife’s partner effect. Couples who lived in the environment with more family members had lower depression scores. Couples who have more children have higher depression scores. The number of children has a negative moderating effect on the results of partner effect of husbands and wives. The wife’s neurotic personality score has a negative moderating effect on the wife’s actor effect. Conclusions: In terms of measures to prevent depression, women’s mental health should be given more priority than men’s. Living in a larger family with more children is beneficial for couples’ mental health. Efforts to prevent depression in couples should take into account the neurotic character of the members, especially the wife, and design special treatment and preventive measures accordingly. These findings highlight that binary dynamics should be considered in exploring what factors influence the mental health of married couples.",20507283,PSYCHOLOGY
10.1186/s40594-023-00426-7,Face negotiation in graduate school: the decision to conceal or reveal depression among life sciences Ph.D. students in the United States,"Background: Depression is one of the top mental health concerns among biology graduate students and has contributed to the “graduate student mental health crisis” declared in 2018. Several prominent science outlets have called for interventions to improve graduate student mental health, yet it is unclear to what extent graduate students with depression discuss their mental health with others in their Ph.D. programs. While sharing one’s depression may be an integral step to seeking mental health support during graduate school, depression is considered to be a concealable stigmatized identity (CSI) and revealing one’s depression could result in loss of status or discrimination. As such, face negotiation theory, which describes a set of communicative behaviors that individuals use to regulate their social dignity, may help identify what factors influence graduate students’ decisions about whether to reveal their depression in graduate school. In this study, we interviewed 50 Ph.D. students with depression enrolled across 28 life sciences graduate programs across the United States. We examined (1) to what extent graduate students revealed their depression to faculty advisors, graduate students, and undergraduates in their research lab, (2) the reasons why they revealed or concealed their depression, and (3) the consequences and benefits they perceive are associated with revealing depression. We used a hybrid approach of deductive and inductive coding to analyze our data.Results: More than half (58%) of Ph.D. students revealed their depression to at least one faculty advisor, while 74% revealed to at least one graduate student. However, only 37% of graduate students revealed their depression to at least one undergraduate researcher. Graduate students’ decisions to reveal their depression to their peers were driven by positive mutual relationships, while their decisions to reveal to faculty were often based on maintaining dignity by performing preventative or corrective facework. Conversely, graduates performed supportive facework when interacting with undergraduate researchers by revealing their depression as a way to destigmatize struggling with mental health.Conclusions: Life sciences graduate students most commonly revealed their depression to other graduate students, and over half reported discussing depression with their faculty advisor. However, graduate students were reluctant to share their depression with undergraduate researchers. Power dynamics between graduate students and their advisors, their peers, and their undergraduate mentees influenced the reasons they chose to reveal or conceal their depression in each situation. This study provides insights into how to create more inclusive life science graduate programs where students can feel more comfortable discussing their mental health.",21967822,EDUCATION
10.1186/s40359-023-01194-3,Relationship between leadership-member exchange (LMX) and flow at work among medical workers during the COVID-19: the mediating role of job crafting,"Based on relational leadership theory and self-determination theory, this study aims to investigate the relationship between leader-member exchange (LMX), job crafting, and flow at work among medical workers in the context of the COVID-19 pandemic. Participants in the study consisted of 424 hospital employees. The results showed that: (1) the LMX positively predicted flow at work; (2) two types of job crafting (increasing structural job resources and challenging job demands) played a mediating role between the LMX and flow at work; and (3) gender did not moderate these mediating effects as suggested by previous studies. These results indicate that the LMX can not only directly predict flow at work, but also indirectly predict work-related flow through job crafting by increasing structural job resources and challenging job demands, thus providing new insights for enhancing flow experiences of medical workers.",20507283,PSYCHOLOGY
10.3390/ejihpe13050067,"Symptomatic, Alexithymic, and Suicidality-Related Features in Groups of Adolescent Self-Harmers: A Case-Control Study","Non-suicidal self-injury (NSSI) is an increasing phenomenon among both clinical and nonclinical adolescent groups and is associated with several psychopathological symptoms, in addition to being one of the main risk factors for suicidality. Nevertheless, differences between clinical and nonclinical samples of self-harmers in symptom dimensions, alexithymia, suicidality, and NSSI-related variables are still scarcely investigated. The current study aimed to fill this gap by enrolling a sample of Italian girls (age range: 12–19 years) that included 63 self-harmers admitted to mental health outpatient services (clinical group), 44 self-harmers without admission to mental health services (subclinical group), and 231 individuals without an NSSI history (control group). Questionnaires investigating psychopathological symptoms, alexithymia, and NSSI-related variables were administered. The results highlighted that all symptom-related variables and alexithymic traits were more severe in the NSSI groups than in the control group; in particular, self-depreciation, anxiety, psychoticism, and pathological interpersonal relationships were distinguished between the clinical and subclinical groups. Compared to the subclinical group, the clinical group was characterized by higher NSSI frequency, NSSI disclosure, self-punishment as the main reason for engagement in NSSI, and suicidal ideation. These findings were then discussed in terms of clinical practice and primary and secondary prevention in the adolescent population.",22549625,PSYCHOLOGY
10.1186/s40594-023-00424-9,Effectiveness of digital educational game and game design in STEM learning: a meta-analytic review,"Digital educational games exhibit substantial promise in advancing STEM education. Nevertheless, the empirical evidence on both the efficacy of digital game-based learning and its designs in STEM education is characterized by notable inconsistencies. Therefore, the current study aimed to investigate (1) the general effect of digital game-based STEM learning over STEM learning without digital game, and (2) the enhancement effect of added game-design elements against base game versions in STEM learning. Two meta-analyses were conducted in this study. Based on the 136 effect sizes extracted from 86 studies, the first meta-analysis revealed a medium to large general effect of digital game-based STEM learning over conventional STEM learning (g = 0.624, 95% CI [0.457, 0.790]). In addition, digital game-based STEM learning appeared to be differentially effective for different learning outcome, different types of game, and different subject. A total of 44 primary studies and 81 effect sizes were identified in the second meta-analysis. The results revealed a small to medium enhancement effect of added game-design elements over base game versions (g = 0.301, 95% CI [0.163, 0.438]). Furthermore, our results indicated that the game-design elements added for content learning were more effective than those added for gaming experience. Possible explanations for these findings, as well as the limitations and directions for future research were discussed.",21967822,EDUCATION
10.3390/cancers15112886,Unraveling the Role of Epithelial–Mesenchymal Transition in Adenoid Cystic Carcinoma of the Salivary Glands: A Comprehensive Review,"Salivary adenoid cystic carcinoma (SACC) is considered a challenging malignancy; it is characterized by a slow-growing nature, yet a high risk of recurrence and distant metastasis, presenting significant hurdles in its treatment and management. At present, there are no approved targeted agents available for the management of SACC and systemic chemotherapy protocols that have demonstrated efficacy remain to be elucidated. Epithelial–mesenchymal transition (EMT) is a complex process that is closely associated with tumor progression and metastasis, enabling epithelial cells to acquire mesenchymal properties, including increased mobility and invasiveness. Several molecular signaling pathways have been implicated in the regulation of EMT in SACC, and understanding these mechanisms is crucial to identifying new therapeutic targets and developing more effective treatment approaches. This manuscript aims to provide a comprehensive overview of the latest research on the role of EMT in SACC, including the molecular pathways and biomarkers involved in EMT regulation. By highlighting the most recent findings, this review offers insights into potential new therapeutic strategies that could improve the management of SACC patients, especially those with recurrent or metastatic disease.",20726694,ONCOLOGY
10.3390/educsci13060543,"“Not Every Advisor Is for Me, but Some Are”: Black Men’s Academic Advising Experiences during COVID-19",Contemporary research indicates that Black American men encounter multiple obstacles in higher education settings. Understanding the complexities of how Black men perceive and make sense of academic environments requires addressing a number of elements that influence their academic success. The purpose of this study is to investigate the academic advising challenges faced in virtual environments by Black men during the COVID-19 pandemic. This qualitative case study provides detailed accounts of ten Black men navigating academic advising practices in a virtual setting at large research one historically white institution using focus groups as a method of data collection. Implications and suggestions for future research highlight the significance of supporting Black men in virtual academic advising spaces to create equitable and sustainable practices.,22277102,EDUCATION
10.3390/cancers15112919,Application of Biophysical Techniques to Cellular and Molecular Oncology,"Dysregulated cellular processes drive malignant transformation, tumor progression, and metastasis, and affect responses to therapies",20726694,ONCOLOGY
10.1007/s00432-023-04863-3,The influence of selected microRNAs on the expression profile of genes and proteins related to the tumor necrosis factor-alpha signaling pathways in endometrioid endometrial cancer,"Purpose Tumor necrosis factor exerts many adverse biological effects, from cell proliferation to cell death. Accurate diagnosis and treatment are therefore difficult due to many factors influencing tumor necrosis factor-alpha (TNF-α) signaling, including microRNAs (miRNAs), especially in tumors. The aim of the study was to determine the influence of miRNAs on the expression profile of genes and proteins related to TNF-α signaling in endometrial cancer. Methods The material consisted of 45 endometrioid endometrial cancer and 45 normal endometrium tissue samples. Gene expression was determined with microarrays and then validated for TNF-α, tumor necrosis factor receptor 1 (TNFR1) and 2 (TNFR2), caveolin 1 (CAV1), nuclear factor kappa B subunit 1 (NFKB1), and TGF-beta activated kinase 1 (MAP3K7)-binding protein 2 (TAB2) using real-time quantitative reverse transcription reaction (RT-qPCR). The protein concentration was assessed by enzyme-linked immunosorbent assay (ELISA). In addition, differentiating miRNAs were identified using miRNA microarrays and their relationships with TNF-α signaling genes were evaluated using the mirDIP tool. Results TNF-α, TNFR1, TNFR2, CAV1, NFKB1, and TAB2 were upregulated both on the mRNA and protein levels. The decrease in the activity of miR-1207-5p, miR-1910-3p, and miR-940 may be related to CAV1 overexpression. Similarly for miR-572 and NFKB1 as well as miR-939-5p and TNF-α. In turn, miR-3178 may partially inhibit TNFR1 activity up to grade 2 cancer. Conclusion TNF-α signaling, especially the TNF-α/NF-κB axis, is disrupted in endometrial cancer and worsens with disease progression. The observed changes may be the result of miRNAs’ activity in the initial stage of endometrial cancer and its gradual loss in later grades.",14321335,ONCOLOGY
10.3390/educsci13060554,Effects of Curriculum on Environmental Attitudes: A Comparative Analysis of Environmental and Non-Environmental Disciplines,"To satisfy their ever-increasing needs, humans are constantly exerting excessive pressure upon the environment, while now more than ever, the adoption of new development practices to halt environmental degradation is becoming necessary. Graduates from all disciplines should have environmental awareness, because their decisions as future professionals may affect the environment. If, however, we assume that environmental science graduates possess environmental knowledge, it is worth investigating whether this knowledge affects their environmental attitudes. Hence, the aim of this study is to compare the environmental attitudes of students attending environmental and non-environmental studies. To this end, a comparative study on environmental attitudes was conducted between students majoring in forestry and students majoring in literature studies at one of the largest universities in Greece. That is, the environmental attitudes of students whose discipline was closely related to the environment were compared to the attitudes of students whose discipline was unrelated to the environment. The results showed that students from both disciplines had positive environmental attitudes, but forestry students exhibited a discernibly higher level of environmental awareness, which can be ascribed to their participation in environmentally relevant courses. The insights gains from this study could be particularly useful to education policymakers and curriculum practitioners, since they provide evidence for the potential of curriculum content to shape pro-environmental attitudes.",22277102,EDUCATION
10.3390/educsci13060556,Managing Employee Motivation in Slovak Universities from the Perspectives of Time and Age,"Human resources refer to a special and unique field as they are the most valuable but also the most costly factor of production. The aim of the research is to analyze the level of motivation of university teachers in Slovakia in terms of time and age, and to define the motivational needs of university teachers. The method of sociological questioning is used. The collected data from 2016 university teachers from Slovak technical universities are analyzed using the Tukey HSD test. Based on the research results, it can be stated that university teachers are the most motivated by relational and financial motivational factors. There is a significant change in the level of average importance of motivational factors across time (years), but there is no change in their structure. In terms of the age factor, significant differences over time are identified. Finally, Slovak teachers display the need for a more respected social status and a better image of their profession. The research findings will help university managers in raising the level of teachers’ motivation and in designing motivation programs.",22277102,EDUCATION
10.1186/s40594-023-00429-4,Characterizing facilitation practices of learning assistants: an authoritative-to-dialogic spectrum,"Background: Learning assistants (LAs) increase accessibility to instructor–student interactions in large STEM lecture classes. In this research, we used the Formative Assessment Enactment Model developed for K-12 science teachers to characterize LA facilitation practices. The Formative Assessment Enactment Model describes instructor actions as eliciting or advancing student thinking, guided by their purposes and the perspective they center as well as by what they notice about and how they interpret student thinking. Thus, it describes facilitation practices in a holistic way, capturing the way purposes, perspectives, noticing, interpreting, and actions are intertwined and working together to characterize different LA actions. In terms of how perspectives influence actions, eliciting and advancing moves can be enacted either in authoritative ways, driven by one perspective that has authority, or in dialogic ways, driven by multiple perspectives. Dialogic practices are of particular interest because of their potential to empower students and center student thinking. Results: Our analysis of video recordings of LA–student interactions and stimulated recall interviews with 37 introductory physical science lectures’ LAs demonstrates that instead of as a dichotomy between authoritative and dialogic, LA actions exist along a spectrum of authoritative to dialogic based on the perspectives centered. Between the very authoritative perspective that centers on canonically correct science and the very dialogic perspective that centers the perspectives of the students involved in the discussion, we find two intermediary categories. The two new categories encompass a moderately authoritative perspective focused on the LA’s perspective without the claim of being correct and a moderately dialogic perspective focused on ideas from outside the current train of thought such as from students in the class that are not part of the current discussion. Conclusions: This spectrum further adds to theory around authoritative and dialogic practices as it reconsiders what perspectives can drive LA enactment of facilitation other than the perspective of canonically correct science and the perspectives of the students involved in the discussion. This emerging characterization may be used to give LAs and possibly other instructors a tool to intentionally shift between authoritative and dialogic practices. It may also be used to transition towards more student-centered practices.",21967822,EDUCATION
10.1186/s40594-023-00430-x,Measurement in STEM education research: a systematic literature review of trends in the psychometric evidence of scales,"Background: The objective of this systematic review is to identify characteristics, trends, and gaps in measurement in Science, Technology, Engineering, and Mathematics (STEM) education research. Methods: We searched across several peer-reviewed sources, including a book, similar systematic reviews, conference proceedings, one online repository, and four databases that index the major STEM education research journals. We included empirical studies that reported on psychometric development of scales developed on college/university students for the context of post-secondary STEM education in the US. We excluded studies examining scales that ask about specific content knowledge and contain less than three items. Results were synthesized using descriptive statistics. Results: Our final sample included the total number of N = 82 scales across N = 72 studies. Participants in the sampled studies were majority female and White, most scales were developed in an unspecified STEM/science and engineering context, and the most frequently measured construct was attitudes. Internal structure validity emerged as the most prominent validity evidence, with exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) being the most common. Reliability evidence was dominated by internal consistency evidence in the form of Cronbach’s alpha, with other forms being scarcely reported, if at all. Discussion: Limitations include only focusing on scales developed in the United States and in post-secondary contexts, limiting the scope of the systematic review. Our findings demonstrate that when developing scales for STEM education research, many types of psychometric properties, such as differential item functioning, test–retest reliability, and discriminant validity are scarcely reported. Furthermore, many scales only report internal structure validity (EFA and/or CFA) and Cronbach’s alpha, which are not enough evidence alone. We encourage researchers to look towards the full spectrum of psychometric evidence both when choosing scales to use and when developing their own. While constructs such as attitudes and disciplines such as engineering were dominant in our sample, future work can fill in the gaps by developing scales for disciplines, such as geosciences, and examine constructs, such as engagement, self-efficacy, and perceived fit.",21967822,EDUCATION
10.3390/cancers15113056,Risk of Second Primary Malignancies in Melanoma Survivors: A Population-Based Study,"(1) Introduction: The association between melanoma (MM) and the occurrence of second primary neoplasms (SPNs) has been extensively studied, with reported incidence rates ranging from 1.5% to 20%. This study aims to evaluate the occurrence of SPNs in patients with a history of primary MM and to describe the factors that make the risk higher in our population. (2) Material and Methods: We conducted a prospective cohort study and calculated the incidence rates and relative risks (RR) for the development of different SPNs in 529 MM survivors from 1 January 2005 to 1 August 2021. Survival and mortality rates were obtained, and the Cox proportional hazards model was used to determine the demographic and MM-related factors that influence the overall risk. (3) Results: Among the 529 patients included, 89 were diagnosed with SPNs (29 prior to MM diagnosis, 11 synchronous, and 49 after MM), resulting in 62 skin tumors and 37 solid organ tumors. The estimated probability of developing SPNs after MM diagnosis was 4.1% at 1 year, 11% at 5 years, and 19% at 10 years. Older age, primary MM location on the face or neck, and histologic subtype of lentigo maligna mm were significantly associated with a higher risk of SPNs. (4) Conclusions: In our population, the risk of developing SPNs was higher in patients with primary MM located on the face and neck and with the histological subtype of lentigo maligna-MM. Age also independently influences the risk. Understanding these hazard factors can aid in the development of MM guidelines with specific follow-up recommendations for individuals with the highest risk.",20726694,ONCOLOGY
10.3390/cancers15123079,Safety and Feasibility of Vulvar Cancer Treatment with Electrochemotherapy,"Electrochemotherapy is a local ablative therapy used for the treatment of various superficial and deep-seated tumors. Electrochemotherapy involves the application of electric pulses locally to tumors to destabilize cell membranes and facilitate the entry of cytotoxic drugs, thereby enhancing their cytotoxicity locally. The aim of our study is to investigate the safety and feasibility of electrochemotherapy in patients with vulvar cancer recurrence used for nonpalliative purposes. Ten patients with single local vulvar cancer recurrence were treated with intravenous bleomycin, followed by a local application of electric pulses (electrochemotherapy) to the tumor. Adverse events were determined using the National Cancer Institute’s Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. The feasibility of treating vulvar cancer with electrochemotherapy was determined by an appropriate selection of electrodes based on the size and location of the tumor with safety margins included. Electrochemotherapy was feasible in all patients. No electrochemotherapy-related or other serious adverse events occurred. Our data suggest that electrochemotherapy is a feasible and safe technique for the treatment of vulvar cancer recurrence for nonpalliative purposes. Based on our results, electrochemotherapy might be a viable therapeutic tool for patients who would otherwise undergo surgery involving a mutilation of the external genitalia.",20726694,ONCOLOGY
10.3390/cancers15123084,Endoscopic Resection of Early Gastric Cancer and Pre-Malignant Gastric Lesions,"Early gastric cancer comprises gastric malignancies that are confined to the mucosa or submucosa, irrespective of lymph node metastasis. Endoscopic resection is currently pivotal for the management of such early lesions, and it is the recommended treatment for tumors presenting a very low risk of lymph node metastasis. In general, these lesions consist of two groups of differentiated mucosal adenocarcinomas: non-ulcerated lesions (regardless of their size) and small ulcerated lesions. Endoscopic submucosal dissection is the technique of choice in most cases. This procedure has high rates of complete histological resection while maintaining gastric anatomy and its functions, resulting in fewer adverse events than surgery and having a lesser impact on patient-reported quality of life. Nonetheless, approximately 20% of resected lesions do not fulfill curative criteria and demand further treatment, highlighting the importance of patient selection. Additionally, the preservation of the stomach results in a moderate risk of metachronous lesions, which underlines the need for surveillance. We review the current evidence regarding the endoscopic treatment of early gastric cancer, including the short-and long-term results and management after resection.",20726694,ONCOLOGY
10.1186/s40594-023-00427-6,Which STEM careers are most appealing? Examining high school students’ preferences and motivational beliefs for different STEM career choices,"Background: Decades of research have examined what motivates students to pursue careers in science, technology, engineering, and mathematics (STEM) fields, but STEM careers are a broad category encompassing hundreds of distinct vocations. The present study examined high school students’ relative preferences for pursuing some types of STEM careers over others and explored what motivational beliefs (defined in accordance with situated expectancy value theory) most influenced students’ relative career preferences. A secondary goal was to examine whether there were differences in any patterns as a function of students’ intersecting gender and racial/ethnic identities. A large sample of high school students (N = 526) completed an online survey during class time about their beliefs regarding fifteen different STEM career categories.Results: Students’ career preferences could be classified into four groups: appealing, unappealing, polarizing, or overlooked. The last category was the most common. Students primarily selected reasons related to utility and attainment value in influencing their choices of most- and least-preferred careers. However, within this category, beliefs about helping others were stronger influences on choosing most-preferred careers, whereas concerns about fitting in were more influential for choosing least-preferred careers. Gender and racial/ethnic comparisons suggest differentiation in how students think about the appeal of various career paths as early as high school.Implications: Findings shed light on how students come to perceive some STEM career paths as relatively more appealing than others, with attention to gender and racial/ethnic differences in these processes. Findings also point to specific and actionable ideas for how teachers, counselors, and administrators can target career education to cultivate students’ interest in STEM career paths, where there are particular needs.",21967822,EDUCATION
10.1007/s00432-023-04958-x,Expression of pyroptosis-related genes are correlated with immune microenvironment and predict prognosis in ESCA,"Objectives: Pyroptosis-related genes (PRGs) are abnormally expressed in a variety of gastrointestinal tumors, this study aimed to investigate the role of pyroptosis genes in assessing the prognosis of esophageal cancer (ESCA). Methods: Through consensus clustering, we identified two subtypes associated with PRGs. After Lasso regression and multivariate Cox regression analysis, a polygenic signature based on six prognostic PRGS was constructed. Afterwards, we combined the risk score with clinical predictors to construct and validate a PRGs-associated ESCA prognostic model. Results: Through analysis, we Successfully constructed and validated a PRGs-associated ESCA prognostic model that predicts ESCA survival and correlates with the tumor immune microenvironment. Conclusion: Based on PRGs features, we established a new ESCA hierarchical model. This model has important clinical implications for ESCA patients, both in terms of assessing prognosis and in terms of targeted and immunotherapy.",14321335,ONCOLOGY
10.3390/ejihpe13060079,Burnout of Greek Teachers: Measurement Invariance and Differences across Individual Characteristics,"Burnout (BT) is a vital determinant of work effectiveness and a well-studied psychological construct. The dominant theoretical perspectives have defined BT via the proposed dimensional structures and have provided the corresponding instruments for measuring them. The present endeavor adopts the Oldenburg Burnout Inventory (OLBI), as its purpose is to examine the psychometric properties of a short version for the Greek teachers and to find differences across their individual characteristics. The Greek short version of OLBI comprises two dimensions: Disengagement (four items) and Exhaustion (five items), with reliability measures utilizing Cronbach’s alpha and McDonald’s omega: Exhaustion (α = 0.810/ω = 0.823) and Disengagement (α = 0.742/ω = 0.756). Confirmatory factor analysis showed an adequate fit of the measurement model: χ2 = 320.291, df = 26, p < 0.001; CFI = 0.970; TLI = 0.958; RMSEA = 0.068; 90% CI of RMSEA = [0.062; 0.075]; SRMR = 0.067; NFI = 0.967; GFI = 0.986]. The proposed model is extracted after two studies (N1 = 134, N2 = 2437). The novel aspect of this endeavor is the measurement invariance explored across selected demographic variables. The findings supporting the measurement invariance make an essential contribution to the field, and the implications for educational research are provided along with a concise presentation of theoretical issues.",22549625,PSYCHOLOGY
10.1007/s44196-023-00282-x,An Efficient Multilevel Threshold Segmentation Method for Breast Cancer Imaging Based on Metaheuristics Algorithms: Analysis and Validations,"Breast cancer is a hazardous disease that should be seriously tackled to reduce its danger in all aspects of the world. Therefore, several imaging ways to detect this disease were considered, but the produced images need to be accurately processed to effectively detect it. Image segmentation is an indispensable step in image processing to segment the homogenous regions that have similar features such as brightness, color, texture, contrast, form, and size. Several techniques like region-based, threshold-based, edge-based, and feature-based clustering have been developed for image segmentation; however, thresholding, which is divided into two classes: bilevel and multilevel, won the highest attention by the researchers due to its simplicity, ease of use and accuracy. The multilevel thresholding-based image segmentation is difficult to be tackled using traditional techniques, especially with increasing the threshold level; therefore, the researchers pay attention to the metaheuristic algorithms which could overcome several hard problems in a reasonable time. In this paper, a new hybrid metaheuristic algorithm based on integrating the jellyfish search algorithm with an effective improvement method is proposed for segmenting the color images of breast cancer, namely the hybrid jellyfish search algorithm HJSO. Experiments are extensively performed to appear the superiority of the proposed algorithm, including validating its performance using various breast cancer images and conducting an extensive comparison with several rival algorithms to explore its effectiveness. The experimental findings, including various performance metrics like fitness values, CPU time, Peak signal-to-noise ratio (PSNR), standard deviation, Features similarity index (FSIM), and Structural similarity index (SSIM), totally show the efficiency of HJSO.",18756883,AI
10.1186/s40594-023-00431-w,Applicant qualifications and characteristics in STEM faculty hiring: an analysis of faculty and administrator perspectives,"Background: The lack of racial diversity in science, technology, engineering, and mathematics (STEM) disciplines is perhaps one of the most challenging issues in the United States higher education system. The issue is not only concerning diverse students, but also diverse faculty members. One important contributing factor is the faculty hiring process. To make progress toward equity in hiring decisions, it is necessary to better understand how applicants are considered and evaluated. In this paper, we describe and present our study based on a survey of current STEM faculty members and administrators who examined applicant qualifications and characteristics in STEM faculty hiring decisions. Results: There are three key findings of the present research. First, we found that faculty members placed different levels of importance on characteristics and qualifications for tenure track hiring and non-tenure track hiring. For example, items related to research were more important when evaluating tenure track applicants, whereas items related to teaching and diversity were more important when evaluating non-tenure track applicants. Second, faculty members’ institutional classification, position, and personal identities (e.g., gender, race/ethnicity) had an impact on their evaluation criteria. For instance, we found men considered some diversity-related items more important than women. Third, faculty members rated the importance of qualifications with diversity, equity, and inclusion (DEI)-related constructs significantly lower than qualifications that did not specify DEI-related constructs, and this trend held for both tenure track and non-tenure track faculty hiring. Conclusions: This study was an attempt to address the issue of diversity in STEM faculty hiring at institutions of higher education by examining how applicant characteristics are considered and evaluated in faculty hiring practices. Emphasizing research reputation and postdoctoral reputation while neglecting institutional diversity and equitable and inclusive teaching, research, and service stunt progress toward racial diversity because biases—both implicit and explicit, both positive and negative—still exist. Our results were consistent with research on bias in recruitment, revealing that affinity bias, confirmation bias, and halo bias exist in the faculty hiring process. These biases contribute to inequities in hiring, and need to be addressed before we can reach, sustain, and grow desired levels of diversity.",21967822,EDUCATION
10.1186/s40594-023-00425-8,A meta-analytic investigation of the impact of middle school STEM education: where are all the students of color?,"Background: Integrated science, technology, engineering, and mathematics (STEM) education initiatives are becoming an increasingly popular approach to narrow the opportunity gap among underrepresented minority (i.e., Black, Hispanic, and first-generation) students. However, there are limited studies on the impact of exposure to integrated STEM education on academic achievement and an even lesser amount on performance among underrepresented minority (URM) groups. Students exposed to STEM programming in middle school are more likely to pursue a STEM field in college or a STEM-related career. However, despite increases in middle school STEM programming initiatives, STEM college graduation rates have declined, particularly among URM populations. This meta-analysis aims to determine the effectiveness of STEM education in middle school, focusing on URM students. Results: A total of 20 studies containing 45 independent samples met the study criteria. The studies included were published from January 1, 2011 to May 1, 2022, and identified from the following academic databases: ERIC, Google Scholar, ProQuest Dissertations and Theses, and SCOPUS. Integrated STEM programming was most impactful when: engineering was incorporated into science courses and at full STEM integration, occurring over one academic year (d = 0.89) and occurring in 8th grade (d = 1.55). Overall, the effect size estimate demonstrated heterogeneity, with a large positive significant effect across the studies (d = 0.558, 95% CI [0.514–0.603], p < 0.001), indicating a significant impact on student achievement. The most notable finding was the lack of empirical studies involving URM groups, with only one effect size estimate reported for Black students and other minority groups and 40 effect size estimates for non-minority groups revealing a non-significant difference in effect size estimates. Conclusions: Students benefit from STEM program participation, with the average STEM student outperforming approximately 70% of their same-age, same-grade peers not participating in STEM programming. In particular, URM students benefit even more from quality integrated STEM education initiatives, given one caveat—students must be given the opportunity. We conclude that the issue is not that URM students are not academically benefiting from middle school integrated STEM education programs, based on the available research—they are merely not participating. We highlight the need and suggest interventions for providing collaborative and focused attention on the societal and cultural factors impacting URM student participation and retention in integrated STEM education programs.",21967822,EDUCATION
10.3390/ejihpe13060080,"Relationship between the Health Literacy and Self-Medication Behavior of Primary Health Care Clientele in the Hail Region, Saudi Arabia: Implications for Public Health","Background and aim: Because they are unaware of the potential adverse effects of medications, people frequently self-medicate as a form of self-care. This study aimed to investigate the factors associated with health literacy and the propensity to self-medicate among the primary healthcare clientele of the city of Hail, Saudi Arabia. Methods: This research employed a cross-sectional approach with the participation of 383 primary health center clientele of the Hail Region of Saudi Arabia. Participation was enacted via convenience sampling from December 2022 to February 2023. The data were collected using a self-administered questionnaire. The investigation utilized descriptive statistics as well as multiple linear regression and correlation for the data analysis. Results: Participants who were aged 30 years and above, single, had a college degree, were non-Saudi, had a white-collar occupation and received information from the internet/Google/YouTube had a significant relationship (p < 0.05) with health literacy. On the self-medication scale (SMS), there were significant relationships with age, marital status, educational level and occupation (p < 0.05). The nationality and source of information factors related to health had a positively significant effect on health literacy (p < 0.01), while middle age (24–29 years) had a positive effect on the self-medication scores (p < 0.01). There was a significant positive correlation between the health literacy screening scale (BRIEF) and the self-medication scale (SMS) scores (r = 421, p < 0.001). Conclusion: Age of 30 years old or above, single status, a college degree, non-Saudi status, white-collar occupation and receiving information from the internet/Google/YouTube were all significant for health literacy. There were also significant relationships with the SMS scores for age, marital status, educational level and occupation. The factors affecting health literacy were older participant age, nationality and the source of information regarding health. Conversely, among the participants, being in the middle-aged group (24–29 years) was a factor that affected their self-medication scores. There was a significant positive correlation between the health literacy screening scale (BRIEF) and the self-medication scale (SMS).",22549625,PSYCHOLOGY
10.3390/ejihpe13060081,“It’s Easy to Put Oneself in the Shoes of Others.” Results of a School Study in Geography Lessons on Working with Authentic Personal Narratives in Comparison to Factual Texts,"Texts represent the most frequently used medium in geography teaching, although they do not belong to leading subject-specific media. Despite their undisputed didactic importance, they have not yet been sufficiently researched. In this article, we consider the use of authentic and personal narratives in geography lessons. We first show their theoretical potential for realistic, multi-perspective and motivating teaching. Then, we present a school study in which the use of authentic, personal narratives was investigated in comparison to a factual text. The areas of investigation were the students’ understanding of the content of a geographical topic, their memory performance and their motivation to work. The results show that authentic, personal narratives are better suited than factual texts to convey a topic to pupils in a multi-perspective and differentiated way. They also confirm their potential to empathise better with other people and to understand their actions through changes in perspective. Regarding recall performance, however, the results show no difference between the two groups. Finally, the results of the school study are considered in the context of forming suggestions for the use of authentic, personal narratives in geography lessons.",22549625,PSYCHOLOGY
10.3390/cancers15123241,LIN28B and Let-7 in Diffuse Midline Glioma: A Review,"Diffuse midline glioma (DMG) is the most lethal of all childhood cancers. DMGs are driven by histone-tail-mutation-mediated epigenetic dysregulation and partner mutations in genes controlling proliferation and migration. One result of this epigenetic and genetic landscape is the overexpression of LIN28B RNA binding protein. In other systems, LIN28B has been shown to prevent let-7 microRNA biogenesis; however, let-7, when available, faithfully suppresses tumorigenic pathways and induces cellular maturation by preventing the translation of numerous oncogenes. Here, we review the current literature on LIN28A/B and the let-7 family and describe their role in gliomagenesis. Future research is then recommended, with a focus on the mechanisms of LIN28B overexpression and localization in DMG.",20726694,ONCOLOGY
10.3390/ejihpe13070084,Value of Care: An Exploratory Qualitative Study with Doctors and Patients,"The concept of value in healthcare is mainly based on economic and financial aspects. However, the literature has emphasised the need to investigate value from other perspectives. The present study aimed to explore the views of physicians and patients on the value of healthcare, and to examine in depth the psychosocial and organisational elements that have emerged but that need to be investigated more. Therefore, two qualitative studies were performed, in which 69 physicians and 111 patients participated. The data were analysed using content analysis and text mining using t-lab software. The results revealed common elements between the two healthcare actors that constitute value in healthcare, including competence, professionalism, and soft skills like communication and empathy. Furthermore, the importance of functioning health services and effective organisational culture in local healthcare and investment emerged. These findings can guide healthcare organisations to consider the potential psychosocial factors related to value in healthcare, which affect organisation in terms of costs and healthcare relationships. In addition, these findings are a first step in filling the gap found in the literature regarding the consideration of value from a non-economic perspective and the difficulty of defining and measuring it.",22549625,PSYCHOLOGY
10.3390/cancers15133267,"Recent Advances in Deep Learning and Medical Imaging for Head and Neck Cancer Treatment: MRI, CT, and PET Scans","Deep learning techniques have been developed for analyzing head and neck cancer imaging. This review covers deep learning applications in cancer imaging, emphasizing tumor detection, segmentation, classification, and response prediction. In particular, advanced deep learning techniques, such as convolutional autoencoders, generative adversarial networks (GANs), and transformer models, as well as the limitations of traditional imaging and the complementary roles of deep learning and traditional techniques in cancer management are discussed. Integration of radiomics, radiogenomics, and deep learning enables predictive models that aid in clinical decision-making. Challenges include standardization, algorithm interpretability, and clinical validation. Key gaps and controversies involve model generalizability across different imaging modalities and tumor types and the role of human expertise in the AI era. This review seeks to encourage advancements in deep learning applications for head and neck cancer management, ultimately enhancing patient care and outcomes.",20726694,ONCOLOGY
10.1007/s00432-023-05007-3,The different clonal origins of metachronous and synchronous metastases,"Background Metastases are the leading cause of mortality in cancer patients. Linear and parallel are the two prominent models of metastatic progression. Metastases can be detected synchronously along with the primary tumor or metachronously, following treatment of localized disease. The aim of the study was to determine whether synchronous metastases (SM) and metachronous metastases (MM) differ only in lead-time or stem from different biological processes. Materials and methods We retrospectively studied the chest CTs of 791 patients inflicted by eleven malignancy types that were treated in our institution in the years 2010–2020. Patient’s population included 396 with SM and 395 with MM. The diameter of 15,427 lung metastases was measured. Clonal origin was deduced from the linear/parallel ratio (LPR)-a computerized analysis of metastases diameters. LPR of 1 suggests pure linear dissemination and − 1 pure parallel. Results Patients with MM were significantly older (average of 62.9 vs 60.7 years, p = 0.02), and higher percentage of them were males (58.7% vs 51.1%, p = 0.03). Median overall survival of patients with MM and SM was remarkably similar (23 months and 26 months respectively, p = 0.774) when calculated from the time of metastases diagnosis. Parallel dissemination (LPR ≤ 0) was found in 35.4% of patients with MM compared to only 19.8% of the patients with SM (p < 0.00001). Conclusion Patients with SM and MM differ in demography and in clonal origin. Different therapeutic approaches may be considered in these two conditions.",14321335,ONCOLOGY
10.3390/ejihpe13070085,"The 3 × 2 Achievement Goals in the Education, Sport, and Occupation Literatures: A Systematic Review with Meta-Analysis","Achievement goal theory has been a dominant motivation framework since the 1980s. The 3 × 2 achievement goal framework emerged in the literature in 2011. We aimed to conduct a systematic review with meta-analysis following the PRISMA guidelines of the 3 × 2 achievement goal research in education, sport, and occupation settings. We retrieved articles from searching EBSCOhost and Google Scholar platforms. Eligible articles contained the 3 × 2 achievement goal in education, sport, or occupation, were published in a peer-reviewed journal, and provided mean data or correlate data. We tested hypotheses concerned with (1) the overall pattern of achievement goal endorsement, (2) achievement goal differences by domain (education, sport) and compulsory nature of the domains or sub-domains, and (3) achievement goal relationships with correlates (e.g., learning strategies, motivations, performance). After screening, 56 articles met all inclusion criteria, providing 58 samples across education (n = 44), sport (n = 10), and occupation (n = 4) settings with 35,031 unique participants from 15 countries. Participants endorsed the task- and self-approach goals more than the counterpart avoidance goals, other-avoidance goals more than other-approach goals, and the intercorrelations and reliability coefficients were acceptable. Minimal impact results from examining within and across study bias statistics. Of importance, the domain (i.e., education, sport) and the compulsory nature of the domain or sub-domains (i.e., primary-secondary education, sport) moderated goal endorsement (group mixed-effects p < 0.05, g values medium to very large). These groupings also moderated the other goal differences. Concerning our correlates analyses, most meta-analyzed correlations among the achievement goals and correlates were small in meaningfulness with the largest correlations (0.30–0.42) between the approach goals merged and the task- and self-approach goals and facilitative learning strategies and desired motivations. In conclusion, the 3 × 2 achievement goals literature is diverse. Furthering the study and application of this model requires overcoming inherent limitations (i.e., consistent response scale sets), teasing out differences between the task- and self-goals, measuring performance outcomes, and cross-cultural collaborations.",22549625,PSYCHOLOGY
10.1186/s40594-023-00433-8,How well-intentioned white male physicists maintain ignorance of inequity and justify inaction,"Background: We present an analysis of interviews with 27 self-identified progressive white-male physics faculty and graduate students discussing race and gender in physics. White cis men dominate most STEM fields and are particularly overrepresented in positions of status and influence (i.e., full professors, chairs, deans, etc.), positioning them as a potentially powerful demographic for enacting systemic reform. Despite their proclaimed outrage at and interest in addressing inequity, they frequently engage in patterns of belief, speech and (in)action that ultimately support the status quo of white male privilege in opposition to their intentions. Results: The white male physicists we interviewed used numerous discourses which support racist and sexist norms and position them as powerless to disrupt their own privilege. We present and discuss three overarching themes, seen in our data, demonstrating how highly educated, well-intentioned people of privilege maintain their power and privilege despite their own intentions: (1) denying inequity is physically near them; (2) locating causes of inequity in large societal systems over which they have little influence; and (3) justifying inaction. Conclusions: Despite being progressively minded and highly educated, these men are frequently complicit in racism and sexism. We end with recommendations for helping cis men engage the power they hold to better work with marginalized people to disrupt inequity.",21967822,EDUCATION
10.3390/educsci13070649,The Gender Gap in STEM Careers: An Inter-Regional and Transgenerational Experimental Study to Identify the Low Presence of Women,"Currently, the number of job offers in STEM careers (Science, Technology, Engineering and Mathematics) is growing up, but by contrast, the number of graduates in these fields is decreasing, particularly women graduates. Consequently, if we do not promote the training of women in STEM careers, the gender gap, far from narrowing, will continue to widen. This paper presents the research carried out in the ALAS project (Accompanying girLs towArds STEM careers), which consists of an experimental analysis based on a multi-model study to discover the possible causes of this low participation of women in STEM fields. The models used are the (1) expectancy–value theory of motivation, (2) social role theory, and (3) gender stereotypes theory. Additionally, participatory workshops have been carried out, with the aim of capturing the students’ reactions when they are introduced to STEM practices. The surveyed target groups range from primary education groups up to university graduates and enterprise employees, including both students and teachers. The obtained results show that there are still social patterns that make young people differentiate certain types of activities based on gender, especially at secondary school age. Nevertheless, the findings reveal that beyond the three studied models, a key factor in young people’s decision to be enrolled in STEM careers is their educational environment.",22277102,EDUCATION
10.3390/educsci13070654,‘A Different Voice’ in Peer Feedback: Gender Specificity in Students’ Willingness to Provide Peer Feedback,"In the context of the efforts to reach equity in the classroom, peer feedback (PFB) is used, among other participative learning methods, as it is considered to minimize gender differences. Yet, recent studies have reported gender discrepancies in students’ willingness to provide feedback to their peers. Building on Gilligan’s theory of moral development, we tried to refine the source of this difference. We conducted a semi-experimental study during which education students of both genders performing a PFB activity in a face-to-face course were asked to fill out a questionnaire. This allowed us to estimate the link between, on the one hand, the comfort in providing PFB and the willingness to provide PFB, and on the other hand, personal characteristics like self-esteem, self-efficacy, and empathic concern, and intellectual characteristics like self-efficacy in the learned discipline and the proficiency to write and understand feedback. The linear regression analysis of 57 students’ answers to the questionnaire did not reveal gender differences in comfort in providing PFB and willingness to do so, but showed that the comfort in providing PFB was linked to cognitive proficiency in students of both genders, whereas the willingness to provide PFB was independent of any other variables in men and linked to self-esteem, empathic concern, and comfort in providing feedback in women. This result indicates a differential sensitivity to social factors in male and female students, aligning with Gilligan’s model of women’s ‘ethics of care’. Possible applications in education would be the use of PFB to train women in self-esteem or, inversely, the improvement of psychological safety in PFB exercises in groups including female students.",22277102,EDUCATION
10.1007/s44196-023-00288-5,A Hybrid Deep Learning Method to Extract Multi-features from Reviews and User–Item Relations for Rating Prediction,"Currently, the Internet is widely used for shopping. Online reviews have become a crucial factor in helping people to make purchasing decisions. However, the large amount of data overwhelms most users, leading to the problem of information overload. To address this issue, researchers have proposed recommender systems as a solution. The most commonly used method is the collaborative filtering method, which analyzes users’ purchase history or behavior to make recommendations. In addition to user ratings, by analyzing users’ comments and the relationships between users and items more precise preferences can be obtained. In this study, the aspect-based rating prediction with a hybrid deep learning method (ARPH) is proposed. It consists of five parts: aspect detection, sentiment and semantic analysis, user preference analysis, graph attention network analysis, and rating prediction. It initially extracts the implicit aspect features and aspects’ sentiment–semantic features from user and item reviews. The convolutional neural network and matrix factorization methods are then used to generate the predicted ratings of items. Additionally, a graph attention network was built to calculate the predicted ratings based on the relationships between users and items. Finally, a multilayer perceptron was used to automatically adjust the weights for integrating these two predicted ratings. Our method utilizes user–item relationships to predict ratings when there are fewer user reviews. Conversely, the features derived from textual reviews were employed for rating prediction. The experimental results showed that extracting different features is useful in representing user and product preferences. The proposed method effectively improved the accuracy of the rating predictions.",18756883,AI
10.1186/s40594-023-00436-5,Pathways of opportunity in STEM: comparative investigation of degree attainment across different demographic groups at a large research institution,"Background: We used an opportunity gap framework to analyze the pathways through which students enter into and depart from science, technology, engineering, and mathematics (STEM) degrees in an R1 higher education institution and to better understand the demographic disparities in STEM degree attainment. Results: We found disparities in 6-year STEM graduation rates on the basis of gender, race/ethnicity, and parental education level. Using mediation analysis, we showed that the gender disparity in STEM degree attainment was explained by disparities in aspiration: a gender disparity in students’ intent to pursue STEM at the beginning of college; women were less likely to graduate with STEM degrees because they were less likely to intend to pursue STEM degrees. However, disparities in STEM degree attainment across race/ethnicities and parental education level were largely explained by disparities in attrition: persons excluded because of their ethnicity or race (PEERs) and first generation students were less likely to graduate with STEM degrees due to fewer academic opportunities provided prior to college (estimated using college entrance exams scores) and more academic challenges during college as captured by first year GPAs. Conclusions: Our results reinforce the idea that patterns of departure from STEM pathways differ among marginalized groups. To promote and retain students in STEM, it is critical that we understand these differing patterns and consider structural efforts to support students at different stages in their education.",21967822,EDUCATION
10.1186/s40359-023-01234-y,“I wanted to hide but also to be found”: the high school experiences of young adults who grew up in the same home as a sibling with depression,"Background: Depression is a mental health condition that can have far-reaching consequences for the entire family, not just for the affected individual. Siblings are particularly vulnerable in that the unremitting stress and guilt at home can affect multiple aspects of their lives, including relationships, added responsibilities, and health. This pressure may affect siblings’ own emotional well-being and academic success. Most studies in this field have examined the impact of depression on the affected adolescents or their parents, whereas few have examined the impact on siblings. Sibling studies have been limited by lack of sample homogeneity, especially in the context of coping in high school. This study sought to examine the retrospective experiences of young adults who lived in the same house as a sibling with depression while they were in high school. Methods: This qualitative study examined 21 young adults (aged 18–29) who grew up with a sibling with depression. In-depth, semi-structured interviews were conducted from May to September 2022. The interviews were recorded and transcribed and underwent thematic analysis. Results: Three main themes emerged from the interviews: (1) “School as a place of refuge”: The perspective of participants who grew up with a sibling with depression regarding their high school experience. (2) “I wanted the adults at school to see me”: Relations between research participants and the school educational staff. (3) “I was afraid people would relate to me as the sibling of a crazy person”: Participants’ relationships with their peers. Conclusions: This study sheds light on the experiences of adolescents who grew up with a sibling with depression. The findings point to feelings of being invisible, self-nullification, avoiding sharing with others, and transparency. The participants were afraid that if their peers found out about their sibling they would also be stigmatized and alienated. The study shows that adolescents living with a sibling with depression need support at school.",20507283,PSYCHOLOGY
10.3390/educsci13070677,How Co-Teaching May Contribute to Inclusion in Mathematics Education: A Systematic Literature Review,"This systematic literature review focuses on co-teaching and inclusion in mathematics education. Co-teaching, in which two or more teachers share responsibility for students’ mathematical learning, can cater to students in need of special education. Through a narrative synthesis of 15 articles found through searches in 5 databases, this study investigates what characterizes co-teaching and how it contributes to students’ inclusion in mathematics education. The review was conducted by identifying the focus, specifying review questions, determining studies to include, deciding on data to extract, and reporting the results. The findings show that co-teaching can contribute to spatial inclusion in mathematics education, implying that all students can be taught in the same classroom. Furthermore, co-teaching that contributes to social and didactical inclusion addresses all students’ mathematical learning if it is flexibly organized. Therefore, students struggling to gain access to mathematics and those requiring extra challenges in mathematics learning can benefit from this teaching model.",22277102,EDUCATION
10.1007/s44196-023-00287-6,SEML: Self-Supervised Information-Enhanced Meta-learning for Few-Shot Text Classification,"Training a deep-learning text classification model usually requires a large amount of labeled data, yet labeling data are usually labor-intensive and time-consuming. Few-shot text classification focuses on predicting unknown samples using only a few labeled samples. Recently, metric-based meta-learning methods have achieved promising results in few-shot text classification. They use episodic training in labeled samples to enhance the model’s generalization ability. However, existing models only focus on learning from a few labeled samples but neglect to learn from a large number of unlabeled samples. In this paper, we exploit the knowledge learned by the model in unlabeled samples to improve the generalization performance of the meta-network. Specifically, we introduce a novel knowledge distillation method that expands and enriches the meta-learning representation with self-supervised information. Meanwhile, we design a graph aggregation method that efficiently interacts the query set information with the support set information in each task and outputs a more discriminative representation. We conducted experiments on three public few-shot text classification datasets. The experimental results show that our model performs better than the state-of-the-art models in 5-way 1-shot and 5-way 5-shot cases.",18756883,AI
10.1186/s40359-023-01243-x,Pros & cons: impacts of social media on mental health,"The use of social media significantly impacts mental health. It can enhance connection, increase self-esteem, and improve a sense of belonging. But it can also lead to tremendous stress, pressure to compare oneself to others, and increased sadness and isolation. Mindful use is essential to social media consumption.",20507283,PSYCHOLOGY
10.1186/s40359-023-01240-0,Media screen time use and mental health in school aged children during the pandemic,"Children’s screen time activity has increased significantly during the pandemic. Extended school closures and heightened parent stress are associated with children’s behavioural difficulties and time spent watching screens. The primary aim of this study was to determine which school and household factors were associated with challenging behaviours in Canadian schoolchildren during the COVID-19 pandemic. This longitudinal survey study examined the association amongst screen time, internalizing and externalizing behaviours in school-aged children at two time points over the 2020–2021 academic school year. Parents completed survey measures on their parental involvement, stress levels, and their child’s screen time use as well as their emotional and behavioural difficulties. Children’s average daily screen time was 4.40 h (SE = 18.45) at baseline and 3.89 h (SE = 16.70) at 1-year follow up, with no significant change across the school year (p = .316). Increased screen time use was associated with a greater incidence of internalizing behaviours in children (p = .03). Children who spent more time on screens and who were in households with parents reporting higher stress levels had increased internalizing behaviours (p < .001). No association between screen time use and externalizing behaviours was evident; however, parent stress was positively associated with children’s externalizing behaviours (p < .001). Children’s screen time use has remained high during the pandemic and is associated with anxious and depressive symptoms. Children who spent more time on screens and who were in households with parents reporting higher stress levels had increased internalizing behaviours. Parent stress was positively associated with children’s externalizing behaviours. Targeted family intervention plans focused on reducing parent stress and screen time use may aid in improving children’s mental health during the ongoing pandemic.",20507283,PSYCHOLOGY
10.1186/s40359-023-01225-z,Savoring life during pandemic: an online intervention to promote well-being in emerging adults,"Background: Savoring, that is the ability to create and increase positive emotions, represents a promising approach to enhance subjective well-being (SWB) in emerging adults. This controlled study aims to investigate the preliminary effects of a self-help e-savoring intervention on increasing savoring beliefs and strategies and SWB in times of the COVID-19 pandemic. Methods: Forty-nine emerging adult participants were recruited using the snowball sampling method. The experimental group (n = 23) completed six online exercises (two exercises per week for three weeks) while the control group (n = 26) did not receive the intervention. Both groups filled out online questionnaires before and after the intervention. User experience and perceived usefulness of the intervention were assessed for the experimental group. Results: A repeated measures analysis of variance (ANOVA) revealed a significant increase for the experimental group in savoring beliefs (especially toward the present and the future) and in positive emotions compared to the control group. The perspicuity, attractiveness, and efficiency of the online platform were very positively evaluated, and most participants rated the intervention as useful. Conclusions: The results of this preliminary study together with the high level of adherence and the appreciation for the intervention indicate the potential of promoting online savoring and positive emotions in emerging adults. Future research could evaluate its long-term effects and verify its results with other age groups.",20507283,PSYCHOLOGY
10.1186/s40594-023-00434-7,Fostering computational thinking through unplugged activities: A systematic literature review and meta-analysis,"Unplugged activities as a low-cost solution to foster computational thinking (CT) skills seem to be a trend in recent years. However, current evidence of the effectiveness of unplugged activities in promoting students’ CT skills has been inconsistent. To understand the potential of unplugged activities on computational thinking skills, a systematic review and meta-analysis were conducted. Our review of 49 studies examined the influence of unplugged activities to improve students’ CT skills in K–12 education between 2006 and 2022. The literature review showed that studies on CT skills were mainly (81.64%) conducted in computer science and STEM education, with board and card games being the most common unplugged activities for fostering CT skills in K–12 education. CT diagnostic tools (36.37%) were frequently used as assessment tools. A follow-up meta-analysis of 13 studies with 16 effect sizes showed a generally large overall effect size (Hedges’s g = 1.028, 95% CI [0.641, 1.415], p < 0.001) for the use of unplugged activities in promoting students’ CT skills. The analysis of several moderator variables (i.e., grade level, class size, intervention duration, and learning tools) and their possible effects on CT skills indicated that unplugged activities are a promising instructional strategy for enhancing students’ CT skills. Taken together, the results highlight the affordances of unplugged pedagogy for promoting CT skills in K–12 education. Recommendations for policies, practice, and research are provided accordingly.",21967822,EDUCATION
10.1007/s00432-023-05108-z,Effect of differences in O-RADS lexicon interpretation between senior and junior sonologists on O-RADS classification and diagnostic performance,"Purpose To assess the consistency of Ovarian-Adnexal Reporting and Data System (O-RADS) lexicon interpretation between senior and junior sonologists and to investigate its impact on O-RADS classification and diagnostic performance. Methods We prospectively studied 620 patients with adnexal lesions, all of whom underwent transvaginal or transrectal ultrasound performed by a senior sonologist (R1) who selected the O-RADS lexicon description and O-RADS category for the lesion after the examination. Meanwhile, the junior sonologist (R2) analyzed the images retained by R1 and divided the lesion in the same way. Pathological findings were used as a reference standard. kappa (к) statistics were used to assess the interobserver agreement. Results Of the 620 adnexal lesions, 532 were benign and 88 were malignant. When using the O-RADS lexicon, R1 and R2 had almost perfect agreement regarding lesion category, external contour of solid lesions, presence of papillary inside cystic lesions, and fluid echogenicity (к: 0.81–1.00). Substantial agreement in solid components, acoustic shadow, vascularity and O-RADS categories (к: 0.61–0.80). Consistency in classifying classic benign lesions in the O-RADS category was only moderate (к = 0.535). No significant difference in diagnostic performance between them using O-RADS (P = 0.1211). Conclusion There was good agreement between senior and junior sonologists in the interpretation of the O-RADS lexicon and in the classification of O-RADS, except for a moderate agreement in the interpretation and classification of classic benign lesions. Differences in O-RADS category delineation between sonologists had no significant effect on the diagnostic performance of O-RADS.",14321335,ONCOLOGY
10.3390/cancers15143582,Study of Alternative Imaging Methods for In Vivo Boron Neutron Capture Therapy,"Boron Neutron Capture Therapy (BNCT) is an innovative and highly selective treatment against cancer. Nowadays, in vivo boron dosimetry is an important method to carry out such therapy in clinical environments. In this work, different imaging methods were tested for dosimetry and tumor monitoring in BNCT based on a Compton camera detector. A dedicated dataset was generated through Monte Carlo tools to study the imaging capabilities. We first applied the Maximum Likelihood Expectation Maximization (MLEM) iterative method to study dosimetry tomography. As well, two methods based on morphological filtering and deep learning techniques with Convolutional Neural Networks (CNN), respectively, were studied for tumor monitoring. Furthermore, clinical aspects such as the dependence on the boron concentration ratio in image reconstruction and the stretching effect along the detector position axis were analyzed. A simulated spherical gamma source was studied in several conditions (different detector distances and boron concentration ratios) using MLEM. This approach proved the possibility of monitoring the boron dose. Tumor monitoring using the CNN method shows promising results that could be enhanced by increasing the training dataset.",20726694,ONCOLOGY
10.3390/ai4030026,"Predictive Analytics with a Transdisciplinary Framework in Promoting Patient-Centric Care of Polychronic Conditions: Trends, Challenges, and Solutions","Context. This commentary is based on an innovative approach to the development of predictive analytics. It is centered on the development of predictive models for varying stages of chronic disease through integrating all types of datasets, adds various new features to a theoretically driven data warehousing, creates purpose-specific prediction models, and integrates multi-criteria predictions of chronic disease progression based on a biomedical evolutionary learning platform. After merging across-center databases based on the risk factors identified from modeling the predictors of chronic disease progression, the collaborative investigators could conduct multi-center verification of the predictive model and further develop a clinical decision support system coupled with visualization of a shared decision-making feature for patient care. The Study Problem. The success of health services management research is dependent upon the stability of pattern detection and the usefulness of nosological classification formulated from big-data-to-knowledge research on chronic conditions. However, longitudinal observations with multiple waves of predictors and outcomes are needed to capture the evolution of polychronic conditions. Motivation. The transitional probabilities could be estimated from big-data analysis with further verification. Simulation or predictive models could then generate a useful explanatory pathogenesis of the end-stage-disorder or outcomes. Hence, the clinical decision support system for patient-centered interventions could be systematically designed and executed. Methodology. A customized algorithm for polychronic conditions coupled with constraints-oriented reasoning approaches is suggested. Based on theoretical specifications of causal inquiries, we could mitigate the effects of multiple confounding factors in conducting evaluation research on the determinants of patient care outcomes. This is what we consider as the mechanism for avoiding the black-box expression in the formulation of predictive analytics. The remaining task is to gather new data to verify the practical utility of the proposed and validated predictive equation(s). More specifically, this includes two approaches guiding future research on chronic disease and care management: (1) To develop a biomedical evolutionary learning platform to predict the risk of polychronic conditions at various stages, especially for predicting the micro- and macro-cardiovascular complications experienced by patients with Type 2 diabetes for multidisciplinary care; and (2) to formulate appropriate prescriptive intervention services, such as patient-centered care management interventions for a high-risk group of patients with polychronic conditions. Conclusions. The commentary has identified trends, challenges, and solutions in conducting innovative AI-based healthcare research that can improve understandings of disease-state transitions from diabetes to other chronic polychronic conditions. Hence, better predictive models could be further formulated to expand from inductive (problem solving) to deductive (theory based and hypothesis testing) inquiries in care management research.",26732688,AI
10.3390/ejihpe13070094,Examining the Influence of Exploration and Parental Education Attainment on Students’ Acceptance of Collectivist Values,"Exploration can help students access a wider range of information and make connections among values within the natural and social world. This study investigated the relationship between students’ previous exploration of their surroundings and their acceptance of collectivist values in the context of China. A sample of 343 college students was analyzed based on the Bayesian Mindsponge Framework to explore this relationship. The results revealed a positive association between students’ prior exploration of surroundings and their degree of collectivist orientation. Furthermore, parental education attainment was found to negatively moderate this association, albeit with a small effect size. These findings contribute to the understanding of how information acquisition influences students’ acceptance of collectivist values and highlight the potential role of the family infosphere in shaping this relationship.",22549625,PSYCHOLOGY
10.1186/s40359-023-01239-7,Parenting profiles: motivation toward health-oriented physical activity and intention to be physically active,"Parents influence their sons’ and daughters’ interest in practicing and maintaining physical activity through parenting patterns. To identify perceived parenting style profiles and examine whether the participants differed in their motivation toward health-oriented physical activity and the intention to be physically active. A sample of 296 participants completed a series of self-report measures and a latent profile analysis (LPA) was performed. Two profiles emerged as the most suitable: profile (a) with average scores in parenting variables, and profile (b) with high scores in parenting variables. The results revealed significant differences in integrated regulation and in amotivation, reporting higher scores for profile (b) in the parenting variables love/affection, hostility/aggression, and indifference/neglect, and average in undifferentiated/rejection and control. The combination of perceived parenting style variables in the profiles seems to influence people’s motivation toward health-oriented physical activity. As such, it is crucial to understand parenting from a multivariate approach, mostly in interventions to adjust parenting styles to the most suitable combination.",20507283,PSYCHOLOGY
10.3390/cancers15143633,Comparative Analysis of Photon Stereotactic Radiotherapy and Carbon-Ion Radiotherapy for Elderly Patients with Stage I Non-Small-Cell Lung Cancer: A Multicenter Retrospective Study,"The emergence of an aging society and technological advances have made radiotherapy, especially stereotactic body radiotherapy (SBRT), a common alternative to surgery for elderly patients with early stage non-small-cell lung cancer (NSCLC). Carbon-ion radiotherapy (CIRT) is also an attractive treatment option with potentially lower toxicity for elderly patients with comorbidities. We compared the clinical outcomes of the two modalities using Japanese multicenter data. SBRT (n = 420) and single-fraction CIRT (n = 70) data for patients with stage I NSCLC from 20 centers were retrospectively analyzed. Contiguous patients ≥ 80 years of age were enrolled, and overall survival (OS), disease-specific survival (DSS), local control (LC), and adverse event rates were compared. The median age was 83 years in both groups and the median follow-up periods were 28.5 and 42.7 months for SBRT and CIRT, respectively. The 3-year OS, DSS, and LC rates were 76.0% vs. 72.3% (p = 0.21), 87.5% vs. 81.6% (p = 0.46), and 79.2% vs. 78.2% (p = 0.87), respectively, for the SBRT vs. CIRT groups. Regarding toxicity, 2.9% of the SBRT group developed grade ≥ 3 radiation pneumonitis, whereas none of the CIRT group developed grade ≥ 2 radiation pneumonitis. SBRT and CIRT in elderly patients showed similar survival and LC rates, although CIRT was associated with less severe radiation pneumonitis.",20726694,ONCOLOGY
10.1007/s00432-023-05046-w,"Risk prediction of second primary malignancies after gynecological malignant neoplasms resection with and without radiation therapy: a population-based surveillance, epidemiology, and end results (SEER) analysis","Purpose: The association between post-resection radiotherapy for primary gynecological malignant neoplasms (GMNs) and the development of secondary primary malignancies (SPMs) remains a subject of debate. This study represents the first population-based analysis employing a multivariate competitive risk model to assess risk factors for this relationship and to develop a comprehensive competing-risk nomogram for quantitatively predicting SPM probabilities. Materials and methods: In our study, data on patients with primary GMNs were retrospectively collected from the Epidemiology, Surveillance and End Results (SEER) database from 1973 to 2015. The incidence of secondary malignant tumors diagnosed at least six months after GMN diagnosis was compared to determine potential risk factors for SPMs in GMN patients using the Fine and Gray proportional sub-distribution hazard model. A competing-risk nomogram was constructed to quantify SPM probabilities. Results: A total of 109,537 patients with GMNs were included in the study, with 76,675 and 32,862 GMN patients in the training and verification sets, respectively. The competing-risk model analysis identified age, primary tumor location, tumor grade, disease stage, chemotherapy, and radiation as risk factors for SPMs in GMN patients. Calibration curves and ROC curves in both training and verification cohorts demonstrated the predictive accuracy of the established nomogram, which exhibited a good ability to predict SPM occurrence. Conclusions: This study presents the nomogram developed for quantitatively predicting SPM probabilities in GMN patients for the first time. The constructed nomogram can assist clinicians in designing personalized treatment strategies and facilitate clinical decision-making processes.",14321335,ONCOLOGY
10.3390/ejihpe13070096,The Antecedents of the Technology Acceptance Model in Microentrepreneurs’ Intention to Use Social Networking Sites,"Social media platforms offer significant growth opportunities for enterprises, particularly microenterprises, due to the chance to establish direct contact with customers. Drawing on the Technology-Acceptance Model (TAM), in the present study, we investigate the psychological reasons that lead microentrepreneurs to use Social Networking Sites (SNSs) for their business. In doing so, we also extend TAM by taking into account entrepreneurs’ personalities (e.g., extraversion and openness to experience) and their perceived risk. We collected data by examining 247 microentrepreneurs engaged in the production of handmade objects. Our results confirm that of all the TAM behavioral antecedents tested, perceived usefulness and attitude toward SNSs’ usage for business proved to be the best predictors of the intention to use SNSs for business activity. The results also indicate that extraversion, openness to experience, and perceived risk, as external factors, significantly affect the TAM constructs. We discuss implications and suggestions for future research.",22549625,PSYCHOLOGY
10.1186/s40594-023-00441-8,Math anxiety affects career choices during development,"Background: Links between math anxiety and the choice of a math-intensive career might change over development and differ by gender. The study included three research populations: primary school (N = 87, 48 females, mean age = 10.2), high school (N = 107, 61 females, mean age = 15.7), and university students (N = 100, 53 females, mean age = 27.4). Students completed a math anxiety questionnaire and reported their desired career choice. Results: Findings suggest that math anxiety directly predicted the career choice math intensity for high school and university students, but not primary school students. Gender had a direct effect on younger students, as female students attending primary and high school preferred careers with a lower math intensity. The effect of gender on career choice math intensity for university students was not direct but mediated by math anxiety. Conclusions: It is crucial to identify young students with math anxiety and provide appropriate math anxiety reduction programs to reduce the cumulative effect of math anxiety on academic achievement and career choice.",21967822,EDUCATION
10.3390/educsci13070740,How Effective Is Entrepreneurship Education in Schools? An Empirical Study of the New Curriculum in Spain,"This research analyzes the results of an entrepreneurship education program focused on knowledge and attitudes in 1036 students of secondary education, high school, and vocational training, differentiated into two groups, control and experimental. It analyzes the outcomes after incorporating entrepreneurship content into the school curriculum and participating in a program of entrepreneurial potential, which develops creativity, leadership, personal control, achievement motivation, and problem-solving. Non-parametric statistics were used to assess the influence of the acquisition of entrepreneurial knowledge on the gender, age, school ownership, and socio-educational level of the parents. This study shows that students with a positive attitude towards entrepreneurship improve their entrepreneurial knowledge and that the impact is more significant if they participate in the specific program. The results are not significant for the variables gender, school type, and parents’ level of education, but they are significant for age and school level. The effectiveness of including content on entrepreneurship in the curriculum and the specific program is ratified. It is proposed to reinforce education in entrepreneurial knowledge that strengthens the students’ identity and future entrepreneurial intention.",22277102,EDUCATION
10.3390/ai4030027,Training Artificial Neural Networks Using a Global Optimization Method That Utilizes Neural Networks,"Perhaps one of the best-known machine learning models is the artificial neural network, where a number of parameters must be adjusted to learn a wide range of practical problems from areas such as physics, chemistry, medicine, etc. Such problems can be reduced to pattern recognition problems and then modeled from artificial neural networks, whether these problems are classification problems or regression problems. To achieve the goal of neural networks, they must be trained by appropriately adjusting their parameters using some global optimization methods. In this work, the application of a recent global minimization technique is suggested for the adjustment of neural network parameters. In this technique, an approximation of the objective function to be minimized is created using artificial neural networks and then sampling is performed from the approximation function and not the original one. Therefore, in the present work, learning of the parameters of artificial neural networks is performed using other neural networks. The new training method was tested on a series of well-known problems, a comparative study was conducted against other neural network parameter tuning techniques, and the results were more than promising. From what was seen after performing the experiments and comparing the proposed technique with others that have been used for classification datasets as well as regression datasets, there was a significant difference in the performance of the proposed technique, starting with 30% for classification datasets and reaching 50% for regression problems. However, the proposed technique, because it presupposes the use of global optimization techniques involving artificial neural networks, may require significantly higher execution time than other techniques.",26732688,AI
10.1007/s00432-023-05141-y,Impact of encorafenib on survival of patients with BRAFV600E-mutant metastatic colorectal cancer in a real-world setting,"Purpose: Patients with BRAFV600E-mutant metastatic colorectal cancer (mCRC) have a dismal prognosis. The best strategies in these patients remain elusive. Against this background, we report the clinical course of patients with BRAFV600E-mutant mCRC to retrieve the best treatment strategy. Patients and methods: Clinico-pathological data were extracted from the electronic health records. Kaplan–Meier method was used to estimate overall (OS) and progression-free survival (PFS). Objective response rate (ORR) was assessed according to RECIST 1.1. Results: In total, 51 patients were enrolled. FOLFOXIRI was administered to 12 patients; 29 patients received FOLFOX or FOLFIRI as first-line treatment. Median OS was 17.6 months. Median PFS with FOLFOXIRI (13.0 months) was significantly prolonged (HR 0.325) as compared to FOLFOX/FOLFIRI (4.3 months). However, this failed to translate into an OS benefit (p = 0.433). Interestingly, addition of a monoclonal antibody to chemotherapy associated with superior OS (HR 0.523). A total of 64.7% patients received further-line therapy, which included a BRAF inhibitor in 17 patients. Targeted therapy associated with very favourable OS (25.1 months). Conclusion: Patients with BRAFV600E-mutated mCRC benefit from the addition of an antibody to first-line chemotherapy. Further-line treatment including a BRAF inhibitor has a dramatic impact on survival.",14321335,ONCOLOGY
10.3390/educsci13070754,“The Work I Do Matters”: Cultivating a STEM Counterspace for Black Girls through Social-Emotional Development and Culturally Sustaining Pedagogies,"Central to culturally sustaining pedagogy (CSP) is the notion that we sustain what we love by decentering the white gaze. Elevating CSP and the five core social-emotional learning competencies, we honed in on how Black and Brown girls developed knowledge and skills to manage their emotions, achieve goals, show empathy, and maintain healthy relationships within the context of a single-gender summer STEM program. These opportunities to engage in critical conversations to learn, unlearn, and relearn, while showing up as their full and authentic selves, are not often afforded in traditional STEM classes. This paper focuses on dialogue and interactions amongst four program participants—Samira, Rita, Brandy, and Joy. Critical discourse analysis was employed to challenge the dominance and reproduction of discourses by examining social contexts and systemic structures that they addressed in conversation. Findings revealed the importance of cultivating trusting and intentional learning spaces for Black and Brown girls to engage in open dialogue and critique oppressive discourses. It also displayed the significance of leaning into difficult conversations and pluralism to help adolescent girls realize the complexities of culture while also promoting joy and social-emotional development. Creating spaces that affirm Black and Brown girls matter; their contributions and work that they do matter.",22277102,EDUCATION
10.1007/s00432-023-05127-w,A nomogram incorporating Ki67 to predict survival of acral melanoma,"Background: The proliferation marker Ki67 is associated with the progression and prognosis of melanoma. However, its prognostic impact on acral melanoma (AM) remains unclear. Methods: A total of 314 AM patients were enrolled from a cohort of 5758 patients with melanoma at Peking University Cancer Hospital between 2006 and 2018. The patients were divided into Ki67 high- and low-expressing groups using a cut-off value of 30%. The associations between Ki67 and clinicopathologic characteristics as well as survival were analyzed. Cox proportional regression analysis was used to establish a nomogram to predict the survival probabilities of AM. Results: Among 314 patients, the Ki67-high group (Ki67 ≥ 30%) included 49.4% of patients at diagnosis. Patients in the Ki67-high group had lower median melanoma-specific survival (MSS) than those in the Ki67-low group (60.7 months vs. not reached, p < 0.001). In multivariate analyses, Ki67, lymph node metastasis and primary site were independent prognostic factors for MSS. The nomogram showed that Ki67 had the fourth greatest impact on survival, following Breslow thickness, lymph node metastasis and primary site. The C-index of the nomogram was 0.765 and 0.758 in the training and validation cohort, respectively. Area under the curve values were both near 0.8 in the training and validation cohorts. Net reclassification improvement and integrated discrimination improvement demonstrated that the predictive nomogram performed better than the traditional AJCC staging system. Conclusion: Ki67 expression is an independent prognostic factor for MSS in AM. A predictive model incorporating Ki67 and clinical factors was constructed to predict the prognosis of AM.",14321335,ONCOLOGY
10.3390/ejihpe13070100,Using the DREAM Methodology for Course Assessment in the Field of ICT-Enabled Education for Sustainability,"This study explores the application of the DREAM methodology for course assessment in three South East Asian universities aiming to embed sustainability and sustainable development goals (SDGs) in multiple academic disciplines enabled by information and communication technologies (ICTs). A mixing of content and thematic analysis was used, which aligns with the underpinning philosophy of the Diagnosing, Reviewing/Reflecting, Explaining, Assessing, Managing (DREAM) methodology. The DREAM methodology integrates five processes, starting from diagnosing, to reviewing/reflecting, explaining, assessing, and, finally, managing. Results show that merging semantic and latent themes has contributed to uncovering what messages students’ narratives convey and provided a space for focusing both on the surface and explicit meanings of the data as well as on theory building and policy making. They also show the effectiveness of the DREAM methodology in constructing new knowledge and generating meaningful interpretations and suggestions to teacher educators and other academic teaching staff, as well as higher education institutions’ policymakers and planners.",22549625,PSYCHOLOGY
10.3390/ai4030028,Federated Learning for IoT Intrusion Detection,"The number of Internet of Things (IoT) devices has increased considerably in the past few years, resulting in a large growth of cyber attacks on IoT infrastructure. As part of a defense in depth approach to cybersecurity, intrusion detection systems (IDSs) have acquired a key role in attempting to detect malicious activities efficiently. Most modern approaches to IDS in IoT are based on machine learning (ML) techniques. The majority of these are centralized, which implies the sharing of data from source devices to a central server for classification. This presents potentially crucial issues related to privacy of user data as well as challenges in data transfers due to their volumes. In this article, we evaluate the use of federated learning (FL) as a method to implement intrusion detection in IoT environments. FL is an alternative, distributed method to centralized ML models, which has seen a surge of interest in IoT intrusion detection recently. In our implementation, we evaluate FL using a shallow artificial neural network (ANN) as the shared model and federated averaging (FedAvg) as the aggregation algorithm. The experiments are completed on the ToN_IoT and CICIDS2017 datasets in binary and multiclass classification. Classification is performed by the distributed devices using their own data. No sharing of data occurs among participants, maintaining data privacy. When compared against a centralized approach, results have shown that a collaborative FL IDS can be an efficient alternative, in terms of accuracy, precision, recall and F1-score, making it a viable option as an IoT IDS. Additionally, with these results as baseline, we have evaluated alternative aggregation algorithms, namely FedAvgM, FedAdam and FedAdagrad, in the same setting by using the Flower FL framework. The results from the evaluation show that, in our scenario, FedAvg and FedAvgM tend to perform better compared to the two adaptive algorithms, FedAdam and FedAdagrad.",26732688,AI
10.1186/s40594-023-00442-7,Embracing a culture of talk: STEM teachers’ engagement in small-group discussions about photovoltaics,"Background: Small-group discussions are well established as an effective pedagogical tool to promote student learning in STEM classrooms. However, there are a variety of factors that influence how and to what extent K-12 teachers use small-group discussions in their classrooms, including both their own STEM content knowledge and their perceived ability to facilitate discussions. We designed the present study to specifically target these two factors in the context of photovoltaics, an interdisciplinary field at the intersection of all STEM disciplines with potential to yield widespread benefits related to the use of solar technologies as a sustainable, renewable energy source. Teachers engaged in a series of small-group discussions based on photovoltaic source material (e.g., scientific articles) to build both their STEM content knowledge and capability with discussions, promoting their potential to design and deliver STEM instruction in their own classrooms using small-group discussion.Results: Overall, teachers productively engaged in rich STEM talk as they spent most of the time in the discussion asking authentic questions about photovoltaic topics in alignment with a variety of science and engineering disciplinary core ideas, responding to the questions with rich, elaborative talk, and taking on ownership of the discussions. Teachers also evidenced increases in their photovoltaic knowledge and their perceived capability to facilitate discussions. Finally, most teachers’ end-of-program lesson plans included the use of small-group discussions, and a subsample of teachers who completed a follow-up interview one year after the summer program reported greater enactment of discussion in their STEM classrooms.Conclusion: Our manuscript forwards an important contribution that draws from a practice-based approach to professional development in a way that not only better prepares teachers on what to teach (i.e., through enhanced PV content knowledge), but it also supports their ability to implement this instruction into their classrooms more effectively (i.e., though the use of small-group discussion). As such, this manuscript illustrates an innovative pedagogical approach for potential use in supporting teacher education and informs ways to enable teachers to build enhanced curricula for their STEM students.",21967822,EDUCATION
10.3390/cancers15153810,Characterization of DoTc2 4510—Identifying HPV16 Presence in a Cervical Carcinoma Cell Line Previously Considered to Be HPV-Negative,"Cervical cancer is the fourth leading cause of cancer deaths in women, with over 340,000 women dying from this disease in 2020. Almost all cases have an underlying persistent infection with an oncogenic high-risk type of human papillomavirus (HPV), mainly HPV16. While cervical squamous cell carcinoma is hardly ever HPV-negative, a small subset of adenocarcinoma exhibits absence of HPV, even after disproval of false-negative testing results due to low viral load. This proportion is evident in many cervical cancer studies and is reflected in the repertoire of model cell lines commonly used in research. As the viral origin of cervical cancer makes it a disease preventable and potentially treatable by immunotherapeutic approaches, it is the focus of many studies. For pertinent research, both a broad set of HPV-infected cervical carcinoma models are required, as well as stringent negative controls. A ubiquitously used HPV-negative cervical adenocarcinoma cell line is C-33A. Another cervical cancer cell line is available for purchase from the American Type Culture Collection (ATCC), namely DoTc2 4510, described to be HPV-negative and thus as a model for a rare gynecological malignancy. Here, we present findings proving that DoTc2 4510 is, in fact, an HPV16-positive cell line. This we assessed using a highly sensitive nested multiplex PCR protocol adapted for the identification of 12 carcinogenic HPV types and a second PCR targeting the HPV16 oncogenes E6 and E7. Subsequently, the protein expression of E6 and E7 was examined, as well as the expression of their target proteins p53, p21, and p16INK4a, to assess E6/E7 functionality. Finally, to attest to the survival dependence of DoTc2 4510 cells on HPV16, we performed an HPV16 E6/E7-targeted siRNA knock-down, which indeed led to senescence induction. Together, these findings demonstrate that DoTc2 4510 is an HPV16-transformed cell line.",20726694,ONCOLOGY
10.3390/cancers15153812,Update in Lung Cancer Molecular Pathology: Technological Advances and Clinical Practice,"This Special Issue of eleven articles, including six original works and five reviews, demonstrates the modern heterogenous approach to lung cancer by means of various methodologies from international experts from various countries",20726694,ONCOLOGY
10.1007/s44196-023-00300-y,Hermite–Hadamard-type Inequalities for $$\hbar$$-preinvex Interval-Valued Functions via Fractional Integral,We present a comprehensive study on Hermite–Hadamard-type inequalities for interval-valued functions that are $$\hbar$$,18756883,AI
10.3390/ai4030029,High-Performance and Lightweight AI Model for Robot Vacuum Cleaners with Low Bitwidth Strong Non-Uniform Quantization,"Artificial intelligence (AI) plays a critical role in the operation of robot vacuum cleaners, enabling them to intelligently navigate to clean and avoid indoor obstacles. Due to limited computational resources, manufacturers must balance performance and cost. This necessitates the development of lightweight AI models that can achieve high performance. Traditional uniform weight quantization assigns the same number of levels to all weights, regardless of their distribution or importance. Consequently, this lack of adaptability may lead to sub-optimal quantization results, as the quantization levels do not align with the statistical properties of the weights. To address this challenge, in this work, we propose a new technique called low bitwidth strong non-uniform quantization, which largely reduces the memory footprint of AI models while maintaining high accuracy. Our proposed non-uniform quantization method, as opposed to traditional uniform quantization, aims to align with the actual weight distribution of well-trained neural network models. The proposed quantization scheme builds upon the observation of weight distribution characteristics in AI models and aims to leverage this knowledge to enhance the efficiency of neural network implementations. Additionally, we adjust the input image size to reduce the computational and memory demands of AI models. The goal is to identify an appropriate image size and its corresponding AI models that can be used in resource-constrained robot vacuum cleaners while still achieving acceptable accuracy on the object classification task. Experimental results indicate that when compared to the state-of-the-art AI models in the literature, the proposed AI model achieves a 2-fold decrease in memory usage from 15.51 MB down to 7.68 MB while maintaining the same accuracy of around 93%. In addition, the proposed non-uniform quantization model reduces memory usage by 20 times (from 15.51 MB down to 0.78 MB) with a slight accuracy drop of 3.11% (the classification accuracy is still above 90%). Thus, our proposed high-performance and lightweight AI model strikes an excellent balance between model complexity, classification accuracy, and computational resources for robot vacuum cleaners.",26732688,AI
10.1007/s00432-023-04975-w,Metastasis pattern and prognosis of large cell neuroendocrine carcinoma: a population-based study,"Purpose: As a rare type of tumor, the metastasis pattern of large cell neuroendocrine carcinoma (LCNEC) is still unclear. Our aim was to investigate metastatic patterns and develop a predictive model of prognosis in patients with advanced LCNEC. Methods: Patients of LCNEC diagnosed between 2010–2015 from the Surveillance, Epidemiology and End Results (SEER) database were retrospectively included. Chi-square test was used for baseline characteristics analysis. Survival differences were assessed using Kaplan–Meier curves. Independent prognostic factors identified by multivariate Cox proportional risk model were used for the construction of nomogram. Results: 557 eligible patients with metastasis LCNEC (median (IQR), 64 (56 to 72) years; 323 males) were included in this research. Among patients with isolated metastases, brain metastases had the highest incidence (29.4%), and multisite metastases had worse OS (HR: 2.020: 95% CI 1.413–2.888; P < 0.001) and LCSS (HR: 2.144, 95% CI 1.480–3.104; P < 0.001) in all age groups. Independent prognostic indicators including age, race, T stage, N stage, chemotherapy, radiotherapy and metastatic site were used for the construction of nomogram. Concordance index (C-index) and decision-curve analyses (DCAs) showed higher accuracy and net clinical benefit of nomogram compared to the 7th TNM staging system (OS: 0.692 vs 0.555; P < 0.001; LCSS: 0.693 vs 0.555; P < 0.001). Conclusions: We firstly established a novel comprehensive nomogram to predict the prognosis of metastasis LCNEC. The prognostic model demonstrated excellent accuracy and predictive performance. Chemotherapy and metastasis pattern were the two strongest predictive variables. Close follow-up of patients with LCNEC is necessary to make individualized treatment decisions according to different metastasis patterns.",14321335,ONCOLOGY
10.3390/ai4030030,Improving Alzheimer’s Disease and Brain Tumor Detection Using Deep Learning with Particle Swarm Optimization,"Convolutional Neural Networks (CNNs) have exhibited remarkable potential in effectively tackling the intricate task of classifying MRI images, specifically in Alzheimer’s disease detection and brain tumor identification. While CNNs optimize their parameters automatically through training processes, finding the optimal values for these parameters can still be a challenging task due to the complexity of the search space and the potential for suboptimal results. Consequently, researchers often encounter difficulties determining the ideal parameter settings for CNNs. This challenge necessitates using trial-and-error methods or expert judgment, as the search for the best combination of parameters involves exploring a vast space of possibilities. Despite the automatic optimization during training, the process does not guarantee finding the globally-optimal parameter values. Hence, researchers often rely on iterative experimentation and expert knowledge to fine-tune these parameters and maximize CNN performance. This poses a significant obstacle in developing real-world applications that leverage CNNs for MRI image analysis. This paper presents a new hybrid model that combines the Particle Swarm Optimization (PSO) algorithm with CNNs to enhance detection and classification capabilities. Our method utilizes the PSO algorithm to determine the optimal configuration of CNN hyper-parameters. Subsequently, these optimized parameters are applied to the CNN architectures for classification. As a result, our hybrid model exhibits improved prediction accuracy for brain diseases while reducing the loss of function value. To evaluate the performance of our proposed model, we conducted experiments using three benchmark datasets. Two datasets were utilized for Alzheimer’s disease: the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and an international dataset from Kaggle. The third dataset focused on brain tumors. The experimental assessment demonstrated the superiority of our proposed model, achieving unprecedented accuracy rates of 98.50%, 98.83%, and 97.12% for the datasets mentioned earlier, respectively.",26732688,AI
10.1007/s44196-023-00294-7,An Integrated Fermatean Fuzzy Multi-attribute Evaluation of Digital Technologies for Circular Public Sector Supply Chains,"The barriers to implementing circular supply chains are well explored, but very little is provided to understand how these barriers play in public sector supply chains. Consequently, the role of digital technologies in addressing these barriers in the circularity of supply chains in the public sector remains a gap. Thus, this study bridges these gaps by evaluating digital technologies according to their relevance in addressing the identified barriers. In particular, eight domain experts who have sufficient knowledge and expertise in the domains of the public sector and circular economy were asked to elicit judgments in order to (1) set a threshold that defines the list of barriers that are significant to supply chains in the public sector, (2) obtain the priority weights of these barriers through the criteria importance through intercriteria correlation (CRITIC), and (3) rank the identified digital technologies based on their relevance in addressing the identified barriers in public sector supply chains using combinative distance-based assessment (CODAS) method, all under a Fermatean fuzzy set environment to account for epistemic uncertainties in judgment elicitation processes. This novel integration of the CRITIC and CODAS methods augmented by Fermatean fuzzy sets forms the methodological contribution of this work. Findings show that barriers associated with regulations restricting the collection of wastes, poor demand or acceptance for environmentally superior technologies, lack of expertise, technology, and information, operational risk, immature recycling technologies, and information sharing and communication were considered critical in managing circular public sector supply chains. The analysis also revealed that ripple effect modeling, simulation, and artificial intelligence are the priority digital technologies. These digital technologies offer efficiency and flexibility to decision-makers in analyzing complex and dynamic scenarios before the deployment of any circularity initiative, providing crucial information in its design and implementation. This paper outlines several managerial insights and offers possible agenda for future research.",18756883,AI
10.1007/s00432-023-05063-9,Impact of the COVID-19 pandemic on oncological care in Germany: rapid review,"Objectives The COVID-19 pandemic affected medical care for chronic diseases. This study aimed to systematically assess the pandemic impact on oncological care in Germany using a rapid review. Methods MEDLINE, Embase, study and preprint registries and study bibliographies were searched for studies published between 2020 and 2 November 2022. Inclusion was based on the PCC framework: population (cancer), concept (oncological care) and context (COVID-19 pandemic in Germany). Studies were selected after title/abstract and full-text screening by two authors. Extracted data were synthesized using descriptive statistics or narratively. Risk of bias was assessed and summarized using descriptive statistics. Results Overall, 77 records (59 peer-reviewed studies and 18 reports) with administrative, cancer registry and survey data were included. Disruptions in oncological care were reported and varied according to pandemic-related factors (e.g., pandemic stage) and other (non-pandemic) factors (e.g., care details). During higher restriction periods fewer consultations and non-urgent surgeries, and delayed diagnosis and screening were consistently reported. Heterogeneous results were reported for treatment types other than surgery (e.g., psychosocial care) and aftercare, while ongoing care remained mostly unchanged. The risk of bias was on average moderate. Conclusions Disruptions in oncological care were reported during the COVID-19 pandemic in Germany. Such disruptions probably depended on factors that were insufficiently controlled for in statistical analyses and evidence quality was on average only moderate. Research focus on patient outcomes (e.g., longer term consequences of disruptions) and pandemic management by healthcare systems is potentially relevant for future pandemics or health emergencies.",14321335,ONCOLOGY
10.1007/s00432-023-05172-5,Construction and validation of prognostic nomogram and clinical characteristics for ovarian endometrioid carcinoma: an SEER-based cohort study,"Background: Ovarian endometrioid carcinoma (OEC) is the second most commonly occurring ovarian epithelial malignancy, but the associated prognostic factors remain obscure. This study aimed to analyze independent prognostic factors for patients with OEC and to develop and validate a nomogram to predict the overall survival (OS) of these patients. Methods: Clinical information of patients with OEC (2000–2019) was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox analyses were used to identify independent prognostic factors, and nomogram models were constructed using independent prognostic factors. Receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA) were used to verify the accuracy and validity of the nomogram. Kaplan–Meier curves were used to compare the differences in OS and cancer-specific survival (CSS) among subgroups. Results: A total of 4628 patients with OEC were included, being divided into training (n = 3238) and validation (n = 1390) sets (7:3 ratio). On multivariate Cox analysis, AJCC stage, age, tumor size, differentiation, chemotherapy, and lymph node resection were significant predictors of survival outcomes (P < 0.05). Resection of 1–3 lymph nodes in early-stage OEC patients did not significantly prolong OS (P > 0.05), but resection of ≥ 4 lymph nodes in early-stage improved OS and CSS (P < 0.05). The OS of early-stage patients was not related to whether or not they received chemotherapy (P > 0.05). Lymph node resection and chemotherapy significantly improved the prognosis of patients with advanced OEC (P < 0.05). The c-index of nomogram prediction model was 0.782. ROC with good discrimination, calibration plots with high consistency, and DCA with large net benefit rate result in large clinical value. Conclusion: AJCC stage, differentiation, tumor size, age, chemotherapy, and lymph node dissection were prognostic factors of OEC. The constructed nomogram prediction model can effectively predict the prognosis of OEC patients and improve the accuracy of clinical decision-making.",14321335,ONCOLOGY
10.3390/educsci13080778,Parent Chats in Education System: During and after the Pandemic Outbreak,"Digital technology has significantly changed the face of education by, among other things, creating many communication channels between the participants in the process. This study reveals the role of parent chat rooms in supporting the learning process. The pandemic experience has shown that parent chat rooms can serve a controlling and regulatory function, noting problems and inconsistencies in the learning system. The chats contain background routine messages related to informing and “events”, that is, messages of bewilderment, resistance, elation, and other emotional reactions. A total of 143 chats were analyzed, and 326 communication events were identified. During the regular period, the basic topics, including chat rules and regulations (22%), homework (20%), school activities and holidays (24%), and behavioral problems (24%), were evenly distributed, while during the distance learning period, the assignment problems (36%) and technical problems (28%) came to the fore. In the traditional offline period, parents are not direct participants in the educational process, so the information in the chats sometimes comes in a one-sided or distorted form; however, parental activity can serve to improve the educational system and monitor the processes taking place.",22277102,EDUCATION
10.3390/ai4030031,Applying Few-Shot Learning for In-the-Wild Camera-Trap Species Classification,"Few-shot learning (FSL) describes the challenge of learning a new task using a minimum amount of labeled data, and we have observed significant progress made in this area. In this paper, we explore the effectiveness of the FSL theory by considering a real-world problem where labels are hard to obtain. To assist a large study on chimpanzee hunting activities, we aim to classify various animal species that appear in our in-the-wild camera traps located in Senegal. Using the philosophy of FSL, we aim to train an FSL network to learn to separate animal species using large public datasets and implement the network on our data with its novel species/classes and unseen environments, needing only to label a few images per new species. Here, we first discuss constraints and challenges caused by having in-the-wild uncurated data, which are often not addressed in benchmark FSL datasets. Considering these new challenges, we create two experiments and corresponding evaluation metrics to determine a network’s usefulness in a real-world implementation scenario. We then compare results from various FSL networks, and describe how factors may affect a network’s potential real-world usefulness. We consider network design factors such as distance metrics or extra pre-training, and examine their roles in a real-world implementation setting. We also consider additional factors such as support set selection and ease of implementation, which are usually ignored when a benchmark dataset has been established.",26732688,AI
10.1186/s40359-023-01257-5,Mental illness stigma among indigenous communities in Bangladesh: a cross-sectional study,"Background: Mental illnesses stigma is a universal and transcultural phenomenon. While mental illnesses stigma is pervasive in Bangladesh, very little research exists on stigma toward mental illnesses among indigenous communities. This study aimed to investigate the prevailing stigma and the risk factors among different indigenous communities in the Chattogram Hill Tracts (CHT) in Bangladesh. Methods: A cross-sectional survey was carried out and participants were recruited purposively from Rangamati, a South-Eastern district of Bangladesh in the CHT. Participants from various indigenous communities including Chakma, Marma, Rakhine, Tripura, and Pangkhua were recruited. The 28- item Bangla translated version of the Mental Illnesses Stigma Scale was used. Independent-samples t-test, ANOVA, and multiple regression were performed. Results: The results indicate evidence of a gender difference with females reporting more stigma than their male counterparts. Age, gender, socioeconomic status, and monthly income are associated with stigma among indigenous people. Further analyses of the subscales indicated significant differences among sociodemographic variables. Conclusions: The results provide an insight into the prevailing stigma and associate risk factors among indigenous communities. The results may help inform anti-stigma interventions targeting indigenous communities in Bangladesh.",20507283,PSYCHOLOGY
10.1007/s44196-023-00297-4,An Interval-Valued Pythagorean Fuzzy AHP and COPRAS Hybrid Methods for the Supplier Selection Problem,"Companies must be able to identify their suppliers appropriately and effectively in order to survive in the competitive market conditions. In order to fulfill and surpass the expectations of the consumers and clients, companies need to interact with the relevant suppliers. It is a tough manner for companies to select the best supplier from a large number of relevant alternatives. The selection process of the appropriate supplier involves multiple interacting and competing factors. Generally, the selection process and its results cause a waste of time and money. For this purpose, MCDM methodologies are utilized to manage this complex process efficiently. MCDMs allows for consistent and accurate decision-making as well as the selection of the most appropriate supplier. MCDM is one the most preferred tool to select the best alternative under the conflicting and competitive criteria when the evaluations are made in crisp numbers. Therefore, MCDM methods are preferred in various applications in academia and real life. However, the evaluations could not be always possible with crisp numbers, especially in vague environments or evaluations needs qualitative data. This study is one of the first to combine the AHP and COPRAS supplier selection methods with interval-valued Pythagorean fuzzy (IPF) logic. The effectiveness of these IPF-AHP and IPF-COPRAS evaluations for the supplier selection problem is compared and examined. The experimental results of case scenarios show that IPF is an effective way to apply in decision-making applications. In addition, sensitivity analysis is conducted to evaluate the proposed methodologies. According to sensitivity analysis, the IPF-AHP and IPF-COPRAS be able to illustrate the effects of small changings in criteria weights. Therefore, companies can use the IPF-AHP and IPF-COPRAS to assist their decision-makers in identifying and selecting the best suppliers.",18756883,AI
10.3390/ejihpe13080103,Positive and Negative Impacts of Gamification on the Fitness Industry,"Gamification features to motivate individuals to exercise have become a trend in the fitness sector that is gaining popularity. It is based on the idea that adding fun and competitive components to workout routines will inspire people to achieve their fitness objectives and maintain a healthy lifestyle. This research study attempts to analyze the literature that explores this concept of gamification in detail, and create a picture of how its implementation has changed fitness and healthy habits. This research incorporated the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach as its research methodology. Search strategy used a set of inclusion-exclusion criteria that helped us examine through hundreds of articles identified in the Web of Science and SCOPUS databases. After exclusive and inclusion criteria, 48 articles were selected to be reviewed in detail. Results have indicated that gamification strategy is a supporting factor to overcome the difficulties of executing exercises. Also, to improve the willingness towards fitness regimens.",22549625,PSYCHOLOGY
10.3390/ejihpe13080104,Personality Traits and Physical Activity: Insights from German University Students,"This study explores the intriguing relationship between personality traits, self-rated fitness (SRF), and physical activity (PA) variables among German university students (N = 4244) and sheds light on the impact of personality on adherence to PA guidelines. Employing an online cross-sectional study, the short-form of the Big Five Inventory-2 assessed five domains of personality traits (Extraversion, Negative Emotionality, Agreeableness, Conscientiousness, and Open-Mindedness). PA, including sitting time, was assessed using the International Physical Activity Questionnaire (short-form). SRF and muscle-strengthening activities (MSA) were assessed with one item each. Multiple linear and logistic regression analyses examined associations of individual personality trait domains and all domains combined with SFR, PA variables, and adherence to PA guidelines, controlling for sociodemographic, behavioral, and (mental) health covariates. Most reliably, Extraversion and Conscientiousness revealed positive associations with PA variables, while Negative Emotionality yielded inverse relationships with PA variables. For instance, each unit increase in Extraversion corresponded to an additional 17 min of weekly MSA. On the contrary, daily sitting time was unrelated to personality. Of note, high Open-Mindedness was associated with lower odds for adhering to current PA guidelines. The findings have implications for developing targeted interventions that promote a physically active lifestyle and support students’ well-being and academic success.",22549625,PSYCHOLOGY
10.3390/cancers15153973,Abrogating Metastatic Properties of Triple-Negative Breast Cancer Cells by EGFR and PI3K Dual Inhibitors,"Triple-negative breast cancer (TNBC) is a devastating BC subtype. Its aggressiveness, allied to the lack of well-defined molecular targets, usually culminates in the appearance of metastases that account for poor prognosis, particularly when they develop in the brain. Nevertheless, TNBC has been associated with epidermal growth factor receptor (EGFR) overexpression, leading to downstream phosphoinositide 3-kinase (PI3K) signaling activation. We aimed to unravel novel drug candidates for TNBC treatment based on EGFR and/or PI3K inhibition. Using a highly metastatic TNBC cell line with brain tropism (MDA-MB-231 Br4) and a library of 27 drug candidates in silico predicted to inhibit EGFR, PI3K, or EGFR plus PI3K, and to cross the blood–brain barrier, we evaluated the effects on cell viability. The half maximal inhibitory concentration (IC50) of the most cytotoxic ones was established, and cell cycle and death, as well as migration and EGFR pathway intervenient, were further evaluated. Two dual inhibitors emerged as the most promising drugs, with the ability to modulate cell cycle, death, migration and proliferation, morphology, and PI3K/AKT cascade players such as myocyte enhancer factor 2C (MEF2C) and forkhead box P1 (FOXP1). This work revealed EGFR/PI3K dual inhibitors as strong candidates to tackle brain metastatic TNBC cells.",20726694,ONCOLOGY
10.1007/s00432-023-05133-y,Glial cell-derived soluble factors increase the metastatic potential of pancreatic adenocarcinoma cells and induce epithelial-to-mesenchymal transition,"Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive types of cancer, characterized by the spreading of highly metastatic cancer cells, including invasion into surrounding nerves and perineural spaces. Nerves, in turn, can invade the tumor tissue and, through the secretion of neurotrophic factors, chemokines, and cytokines, contribute to PDAC progression. However, the contribution of the nerve-associated glial cells to PDAC progression is not well characterized. Methods: Two murine PDAC cell lines were cultured with the conditioned media (CM) of primary enteric glial cells or IMS32 Schwann cells (SCs). Different properties of PDAC cells, such as invasiveness, migratory capacity, and resistance to gemcitabine, were measured by RT-qPCR, microscopy, and MTT assays. Using a neuronal cell line, the observed effects were confirmed to be specific to the glial lineage. Results: Compared to the control medium, PDAC cells in the glial cell-conditioned medium showed increased invasiveness and migratory capacity. These cells showed reduced E-cadherin and increased N-cadherin and Vimentin levels, all markers of epithelial–mesenchymal transition (EMT). Primary enteric glial cell CM inhibited the proliferation of PDAC cells but preserved their viability, upregulated transcription factor Snail, and increased their resistance to gemcitabine. The conditioned medium generated from the IMS32 SCs produced comparable results. Conclusion: Our data suggest that glial cells can increase the metastatic potential of PDAC cells by increasing their migratory capacity and inducing epithelial-to-mesenchymal transition, a re-programming that many solid tumors use to undergo metastasis. Glial cell-conditioned medium also increased the chemoresistance of PDAC cells. These findings may have implications for future therapeutic strategies, such as targeting glial cell-derived factor signaling in PDAC.",14321335,ONCOLOGY
10.1007/s00432-023-05323-8,Construction of the survival nomograms for colon cancer patients of different ages based on the SEER database,"Introduction: Three nomograms for predicting the outcomes of early- and late-onset colon cancer (COCA) among patients not stratified by age were constructed using data in the Epidemiology and End Results (SEER) database (1975–2019). The accuracy of the nomogram was then assessed. Method: Clinical data of 6107 patients with COCA were obtained from the SEER database. The patients were randomly divided into training and validation cohorts in a ratio of 7:3. Univariate and multivariate COX analyses of factors that could independently impact the prognosis of COCA were performed, and the corresponding nomograms for early-onset and late-onset COCA were constructed. Calibration curves, ROC curves, and C-index were used to determine the predictive accuracy. The discriminatory ability of the nomograms to assess their clinical utility, which was compared with the TNM staging system of the 8th edition of AJCC, was verified using survival analysis. Result: Tumor primary site, ethnicity, and serum carcinoembryonic antigen (CEA) level significantly impacted the prognosis of colon cancer. Race, brain metastasis, and CEA were independent factors for predicting COCA prognosis. C-index, ROC, and calibration curves demonstrated that the three nomograms were accurate and superior to the traditional TNM staging system. Among the three nomograms, the early-onset COCA nomogram had the highest predictive accuracy, followed by that of colon cancer not stratified by age. Conclusion: Three nomograms for patients not stratified by age, early-onset colon cancer, and late-onset colon cancer were constructed. The accuracies of the nomograms were good and were all superior to the conventional TNM staging system. The early- and late-onset COCA nomograms are useful for clinical management and individualized treatment of COCA patients at different ages.",14321335,ONCOLOGY
10.1007/s44196-023-00316-4,RETRACTED ARTICLE: Research on the Prediction of the Inauguration Development Direction of College Students’ Entrepreneurship Education Based on Educational Data Mining,"In many related studies, educational data mining technology has been proven to play an important role in predicting the development direction of entrepreneurship education for college students. To further improve the accuracy of the prediction, we chose the grey prediction model as the basic prediction model and automatically optimized the weighting method to improve the model. To solve the problem of predicting the development direction of students’ employment in the guidance of entrepreneurship and employment in colleges and universities, the study selects the grey prediction model as the basic prediction model and chooses the automatic optimization and weighting method to improve the model. Meanwhile, the study establishes a variable system containing six dimensions: academic achievement; physical and mental development; cultural, physical, and artistic quantified status; ideological and political quantified status; scientific and technological innovation quantified status; social work quantified status. The final study used the actual prediction test to analyze the prediction effect. We have selected a variable system consisting of six dimensions, which are the results of extensive research. These dimensions include academic achievement, physical and mental development, cultural/sports/art quantitative status, ideological and political quantitative status, technological innovation quantitative status, and social work quantitative status. Each dimension provides us with important predictions about student entrepreneurship and employment. The results show that the model designed by the survey has only two cases of error in the prediction of 20 actual samples. At the same time, there is no prediction error in the two prediction directions of entrepreneurship and social employment. This shows that the model designed by the study is stable and accurate, and the prediction results are more reliable in the prediction directions of entrepreneurship and social employment. Compared with other relevant research results, our model performs well in predicting accuracy, especially in predicting entrepreneurial and social employment directions, without any prediction errors, indicating that our model has superior performance in predicting stability and accuracy compared to other studies.",18756883,AI
10.1007/s44196-023-00321-7,RETRACTED ARTICLE: E-commerce User Recommendation Algorithm Based on Social Relationship Characteristics and Improved K-Means Algorithm,"In the era of the Internet, information data continue to accumulate, and the explosive growth of network information explosion leads to the reduction of the accuracy of users’ access to information. To enhance the user experience and purchasing desire of e-commerce users, a e-commerce user recommendation algorithm based on social relationship characteristics and improved K-means algorithm is proposed. It combines the Automatic Time Division Dynamic Topic Model based on adaptive time slice division for building a strength calculation model in view of the characteristics of social relations. Then, it proposes an e-commerce user recommendation algorithm in view of the improved K-means algorithm to improve the accuracy of topic feature extraction and user recommendation. The experiment illustrates that there is no fluctuation in the clustering function of the improved K-means algorithm, and the highest, lowest, and average accuracy remain consistent under the three datasets, with average accuracy of 78.9%, 84.5%, and 95.9%, respectively. The community discovery-based friend recommendation algorithm presented in the study has the highest accuracy, illustrating that improving the K-means algorithm can further improve recommendation accuracy. The accuracy of the feature extraction method in view of alternative cost is 0.63, which improves the accuracy by about 9%. The results indicate that this study can provide technical support for user recommendations on e-commerce platforms.",18756883,AI
10.1186/s40359-023-01288-y,Qualitative insights from a randomized clinical trial of a mother–child emotional preparation program for preschool-aged children,"Background: Early life stress and adversity conveys risk for emotional, behavioral, and developmental disorders. To address this risk in the preschool population, Mother–Child Emotional Preparation (MCEP) was tested as an in-school dyadic intervention for facilitating mother–child emotional connection through mother–child calming cycles. In a computer-generated block randomized controlled trial enrolling preschool-aged children and their mothers, in partnership with an early childhood learning center, we at Columbia University Irving Medical Center tested effects of MCEP across multiple domains. Within this RCT we designed a qualitative sub-study to understand how MCEP aligns with calming cycle theory and its impact on mothers and the mother–child relationship. Methods: A qualitative researcher observed 14 group MCEP sessions consisting of nurture specialists facilitating reciprocal calming interactions through shared emotional expression between mothers and their preschool-aged children. We conducted two waves of participant interviews in English or Spanish, per participant preference. Participants (n = 8) were majority Hispanic at or below the federal poverty level. Group session observations were coded and analyzed for frequency, co-occurrence, variance by session, and alignment with calming cycle theory, incorporating demographic variables and attendance. Interview transcripts were translated from Spanish to English if needed, then coded and analyzed using thematic analysis. Results: Qualitative analysis revealed mothers’ experiences of MCEP. Data demonstrated that calming position and emotional expression were mutually supportive, and that barriers to connection were calming cycle entry-points, not barriers. At the group level, supported by nurture specialists, fellow participants helped each other progress through calming cycles. Moreover, MCEP adapted to meet individual dyad needs, and mothers described its far-reaching impact. Conclusions: Qualitative methods show that MCEP helps mother–child dyads emotionally connect through the calming cycle and fills a gap in early childhood education services. This study generated insights for quantitative studies and suggested implications for MCEP dissemination. Trial registration: ClinicalTrials.gov, NCT03908268, Registered April 9, 2019—Retrospectively registered.",20507283,PSYCHOLOGY
10.1186/s40594-023-00446-3,"Possibilities and pitfalls of practitioners in trying to apply change theory as viewed through the lens of Reinholz, White, and Andrews “Change theory in STEM higher education: a systematic review”",,21967822,EDUCATION
10.1007/s00432-023-05297-7,High expression of NOLC1 as an independent prognostic factor for survival in patients with colorectal cancer,"Background As a phosphorylated protein, NOLC1 is mainly located in the nucleus and is highly expressed in a variety of tumors, participating in the regulation of cell proliferation and aging. This study further investigated the role of NOLC1 in colorectal cancer tumors, aiming to provide sufficient scientific evidence for the clinical treatment of colorectal cancer. Methods We used TCGA, GEO, TNMplot, GEPIA, and other databases to explore the expression level of NOLC1 in colorectal cancer patients, as well as the correlation between the clinical characteristics of colorectal cancer patients and their expression, and conducted the prognostic analysis. Immunohistofluorescence (IHF) staining verified the analytical results. Subsequently, KEGG and GO enrichment analysis was used to identify the potential molecular mechanism of NOLC1 promoting the occurrence and development of colorectal cancer. The influence of NOLC1 expression on the immune microenvironment of colorectal cancer patients was further investigated using the TIMER database. GDSC database analysis was used to screen out possible anti-colorectal cancer drugs against NOLC1. Finally, we demonstrated the effect of NOLC1 on the activity and migration of colorectal cancer cells by Edu Cell proliferation assay and Wound Healing assay in vitro. Results Our results suggest that NOLC1 is overexpressed in colorectal cancer, and that overexpression of NOLC1 is associated with relevant clinical features. NOLC1, as an independent risk factor affecting the prognosis of colorectal cancer patients, can lead to a poor prognosis of colorectal cancer. In addition, NOLC1 may be associated with MCM10, HELLS, NOC3L, and other genes through participating in Wnt signaling pathways and jointly regulate the occurrence and development of colorectal cancer under the influence of the tumor microenvironment and many other influencing factors. Related to NOLC1: Selumetinib, Imatinib, and targeted drugs such as Lapatinib have potential value in the clinical application of colorectal cancer. NOLC1 enhances the proliferation and migration of colorectal cancer cells. Conclusions High expression of NOLC1 as an independent prognostic factor for survival in patients with colorectal cancer. NOLC1 enhances the proliferation and migration of colorectal cancer cells. Further studies and clinical trials are needed to confirm the role of NOLC1 in the development and progression of colorectal cancer.",14321335,ONCOLOGY
10.3390/educsci13090914,Emotions Matter: A Systematic Review and Meta-Analysis of the Detection and Classification of Students’ Emotions in STEM during Online Learning,"In recent years, the rapid growth of online learning has highlighted the need for effective methods to monitor and improve student experiences. Emotions play a crucial role in shaping students’ engagement, motivation, and satisfaction in online learning environments, particularly in complex STEM subjects. In this context, sentiment analysis has emerged as a promising tool to detect and classify emotions expressed in textual and visual forms. This study offers an extensive literature review using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) technique on the role of sentiment analysis in student satisfaction and online learning in STEM subjects. The review analyses the applicability, challenges, and limitations of text- and facial-based sentiment analysis techniques in educational settings by reviewing 57 peer-reviewed research articles out of 236 articles, published between 2015 and 2023, initially identified through a comprehensive search strategy. Through an extensive search and scrutiny process, these articles were selected based on their relevance and contribution to the topic. The review’s findings indicate that sentiment analysis holds significant potential for improving student experiences, encouraging personalised learning, and promoting satisfaction in the online learning environment. Educators and administrators can gain valuable insights into students’ emotions and perceptions by employing computational techniques to analyse and interpret emotions expressed in text and facial expressions. However, the review also identifies several challenges and limitations associated with sentiment analysis in educational settings. These challenges include the need for accurate emotion detection and interpretation, addressing cultural and linguistic variations, ensuring data privacy and ethics, and a reliance on high-quality data sources. Despite these challenges, the review highlights the immense potential of sentiment analysis in transforming online learning experiences in STEM subjects and recommends further research and development in this area.",22277102,EDUCATION
10.3390/ejihpe13090126,"Impacts of a COVID-19 Educational Video: Evaluation of the Influence of Race, Gender, Political Affiliation, Study Major, and Age on Vaccine Acceptance among University Students","Background: The World Health Organization (WHO) warns that vaccine hesitancy is an ongoing major global health threat. While vaccination against severe acute respiratory syndrome coronavirus (SARS-CoV-2) proves to be an effective strategy in protecting against the disease, vaccine hesitancy represents a major barrier to stopping the spread of the virus. Willingness for vaccination can be influenced by several factors, including education level and health literacy. Although several studies demonstrate the value of video educational programs in improving coronavirus disease 2019 (COVID-19) vaccine knowledge and acceptance, no studies to date have evaluated if race, gender, and other demographic factors impact the influence of an educational video on COVID-19 vaccine knowledge and hesitancy among university students in the United States (U.S.). Aims: This study was conducted to determine the impact of an educational video on U.S. university undergraduate students’ COVID-19 vaccine perception and acceptance. It also aims to evaluate whether demographic factors affect the influence of the video. Methods: An online survey was used to measure perceived understanding and acceptance of COVID-19 vaccines before and after viewing a video regarding the effectiveness and safety of COVID-19 vaccinations. The impact of demographic factors on the Video Influence Score was analyzed. Key results: After viewing the video, respondents’ (n = 285) perceived awareness and acceptance of COVID-19 vaccines significantly increased (p < 0.05). In addition, gender, political party affiliation, age, study major, and influenza vaccination history did not significantly impact the Video Influence Score (p > 0.05). However, African American/Black respondents (3.81 ± 4.24) were significantly more influenced by the video compared to respondents of other races (p < 0.05), such as White/Caucasian (1.91 ± 3.75), Hispanic/Latino (0.17 ± 3.67), Asian (0.29 ± 1.53), and Indigenous American (0.64 ± 2.52). Conclusions: This study suggests the potential impact of an educational video on COVID-19 vaccine perception and acceptance among university students. Despite limitations such as a modest survey response rate, this study provides valuable insight concerning the influential factors affecting vaccine acceptance in diverse student populations. Future studies are warranted to explore how student response to vaccine educational videos may vary depending on students’ racial and cultural backgrounds. Implications: A targeted educational video to promote vaccine acceptance is a valuable tool for public health campaigns to combat vaccine hesitancy. The study also highlights the importance of tailoring interventions to specific demographic groups such as considering racial factors to maximize the impact of educational interventions on vaccine attitudes.",22549625,PSYCHOLOGY
10.3390/cancers15184493,Treatment of Clival Chordomas: A 20-Year Experience and Systematic Literature Review,"Clival chordomas are rare but aggressive skull base tumors that pose significant treatment challenges and portend dismal prognosis. The aim of this study was to highlight the advantages and limitations of available treatments, to furnish prognostic indicators, and to shed light on novel therapeutic strategies. We conducted a retrospective study of clival chordomas that were surgically treated at our institution from 2003 to 2022; for comparison purposes, we provided a systematic review of published surgical series and, finally, we reviewed the most recent advancements in molecular research. A total of 42 patients underwent 85 surgeries; median follow-up was 15.8 years, overall survival rate was 49.9% at 10 years; meanwhile, progression-free survival was 26.6% at 10 years. A significantly improved survival was observed in younger patients (<50 years), in tumors with Ki67 ≤ 5% and when adjuvant radiotherapy was performed. To conclude, clival chordomas are aggressive tumors in which surgery and radiotherapy play a fundamental role while molecular targeted drugs still have an ancillary position. Recognizing risk factors for recurrence and performing a molecular characterization of more aggressive lesions may be the key to future effective treatment.",20726694,ONCOLOGY
10.1186/s40594-023-00445-4,"Validity, acceptability, and procedural issues of selection methods for graduate study admissions in the fields of science, technology, engineering, and mathematics: a mapping review","This review presents the first comprehensive synthesis of available research on selection methods for STEM graduate study admissions. Ten categories of graduate selection methods emerged. Each category was critically appraised against the following evaluative quality principles: predictive validity and reliability, acceptability, procedural issues, and cost-effectiveness. The findings advance the field of graduate selective admissions by (a) detecting selection methods and study success dimensions that are specific for STEM admissions, (b) including research evidence both on cognitive and noncognitive selection methods, and (c) showing the importance of accounting for all four evaluative quality principles in practice. Overall, this synthesis allows admissions committees to choose which selection methods to use and which essential aspects of their implementation to account for.",21967822,EDUCATION
10.1186/s40594-023-00448-1,The role of media in influencing students’ STEM career interest,"Background: Digital media are pervasive in the lives of young people and provide opportunities for them to learn about STEM. Multiple theories argue that the STEM media environment may shape how youth see a STEM career in their future. Yet, little is known about how pre-college digital media consumption may be related to students’ STEM career interest at the beginning of college. The wide variety of STEM media also raises the question of potentially different effects and pathways by media type. In this study, we collected a nationally representative sample of more than 15,000 students in their first year in U.S. colleges and universities. We asked about their career interests at the beginning of college and also asked them to retrospectively report their STEM media consumption during high school. Results: We found that watching STEM-related TV and online videos, as well as playing STEM-related video games during high school, were positively associated with students’ STEM career interests at the beginning of college. However, we also found that STEM media consumption did not impact directly on STEM career interest, but acted through two intermediaries: STEM identity (I and others see me as a STEM person) and three personal career outcome expectations: a high interest in self-development (enhancement and use of talents), and low interests in material status (money, fame, power) and in interpersonal relationships (helping, and working with, other people). Conclusions: This study finds that STEM media have a significant effect in fostering STEM career interest, with most of the effect coming from STEM TV, STEM video viewing, and STEM video games. The effect is mediated mainly through students’ identity and, to a lesser extent, through personal values, such as self-development, material, and interpersonal relationship values. This study suggests that media communication should be mindful of how different platforms may deliver nuanced and varied messages of what STEM careers may afford and who can succeed in STEM.",21967822,EDUCATION
10.3390/educsci13090930,The Role and Motivation of Pre-Service Teacher (PST) Mentors from Pro-Social to Cognitive-Effective Perspectives,"The purpose of this quantitative descriptive study is to shed light on the driving forces of the mentor’s positions in teacher training processes in Israel. The research is based on an exploratory cross-sectional study which included 170 preservice teacher mentors in the north of Israel. The mentoring position, despite its importance, is often unappreciated, even by the mentors themselves. It is barely rewarded, in money, status, or prestige. The current study focuses on the internal motivation of mentors for choosing to serve in this role in addition to their main role as classroom teachers. In this regard, the theory of cognitive-effective perspective can help us to understand the reasons behind these motivations. Our findings indicate that mentors exhibit internal motivation from the pro-social and cognitive-effective perspectives. The average score for attitudes was M = 2.92 (SD ± 0.42). The total score was higher for the cognitive components than for the effective ones (M = 2.98, SD ± 0.44, and M = 2.85, SD ± 0.52, respectively). The main motivations of the mentors were based on their strong desire to improve the level of teaching in Israel. Contributing to the future of education was a dominant part of their personal educational philosophy. These insights depict the mentor as a pillar of the teacher training community in Israel. Our findings also indicate that, while a supportive school climate and autonomy in the mentor’s role are factors that promote mentoring practices, a lack of theoretical knowledge about teacher training and a lack of clarity about the mentors’ responsibilities are factors that hinder such practices. It is important to address these factors in order to enhance the desirable variables while decreasing the undesirable ones, in order to translate educational philosophy into stable and sustainable improved teacher training processes.",22277102,EDUCATION
10.1007/s00432-023-05365-y,Prevalence of mutations in common tumour types in Northern England and comparable utility of national and international Trial Finders,"Purpose: Tumour genomic profiling is of increasing importance in early phase trials to match patients to targeted therapeutics. Mutations vary by demographic group; however, regional differences are not characterised. This was investigated by comparing mutation prevalence for common cancers presenting to Newcastle Experimental Cancer Medicine Centre (ECMC) to The Cancer Genome Atlas (TCGA) and utility of trial matching modalities. Methods: Detailed clinicogenomic data were obtained for patients presenting September 2017–December 2020. Prevalence of mutations in lung, colorectal, breast and prostate cancer was compared to TCGA GDC Data Portal. Experimental Cancer (EC) Trial Finder utility in matching trials was compared to a Molecular Tumour Board (MTB) and commercial sequencing reports. Results: Of 311 patients with advanced cancer, this consisted of lung (n = 131, 42.1%), colorectal (n = 44, 14.1%), breast (n = 36, 11.6%) and prostate (n = 18, 5.6%). More than one mutation was identified in the majority (n = 260, 84%). Significant prevalence differences compared to TCGA were identified, including a high prevalence of EGFR in lung (P = 0.001); RB1 in breast (P = 0.0002); and multiple mutations in prostate cancer. EC Trial Finder demonstrated significantly different utility than sequencing reports in identifying trials (P = 0.007). Conclusions: Regional differences in mutations may exist with advanced stage accounting for prevalence of specific mutations. A national Trial Finder shows utility in finding targeted trials whilst commercial sequencing reports may over-report ‘actionable’ mutations. Understanding local prevalence and trial availability could increase enrolment onto matched early phase trials.",14321335,ONCOLOGY
10.3390/cancers15184549,Salvage High-Dose-Rate Interventional Radiotherapy (Brachytherapy) Combined with Surgery for Regionally Relapsed Head and Neck Cancers,"(1) Background: to report on the use of high-dose-rate (HDR) interventional radiotherapy (brachytherapy, IRT) as a salvage treatment for patients with regionally relapsed head and neck cancers. (2) Methods: A retrospective study of 60 patients treated with HDR-IRT for loco-regionally relapsed head and neck cancers at our institution (2016–2020). Treatment procedure, results, and related toxicities were collected. Local and overall survival outcomes were analyzed. (3) Results: The median follow-up was 22.4 months. Twenty-nine (48.3%) patients had locoregional recurrences with a median time of 28.9 months. The local-recurrence free-survival was 88.1% and 37.3% at 3 years and 5 years. At the last follow-up, 21 patients were alive and the median time to death was 24 months. The overall survival was 39.2% and 16.6% at 3 years and 5 years. Collectively, there were 28 events of grade ≥ 3 late toxicities recorded in 21 patients (35%). (4) Conclusions: Salvage HDR-IRT combined with surgery offers a second-line curative treatment option for regionally relapsed head and neck cancers with acceptable outcomes and toxicities.",20726694,ONCOLOGY
10.3390/cancers15184567,Negative Survival Impact of Occult Lymph Node Involvement in Small HER2-Positive Early Breast Cancer Treated by Up-Front Surgery,"(1) Background: The independent negative prognostic value of isolated tumor cells or micro-metastases in axillary lymph nodes has been established in triple-negative breast cancers (BC). However, the prognostic significance of pN0(i+) or pN1mi in HER2-positive BCs treated by primary surgery remains unexplored. Therefore, our objective was to investigate the impact of pN0(i+) or pN1mi in HER2-positive BC patients undergoing up-front surgery on their outcomes. (2) Methods: We retrospectively analyzed 23,650 patients treated in 13 French cancer centers from 1991 to 2013. pN status was categorized as pN0, pN0(i+), pN1mi, and pNmacro. The effect of pN0(i+) or pN1mi on outcomes was investigated both in the entire cohort of patients and in pT1a-b tumors. (3) Results: Of 1771 HER2-positive BC patients included, pN status distributed as follows: 1047 pN0 (59.1%), 60 pN0(i+) (3.4%), 118 pN1mi (6.7%), and 546 pN1 macro-metastases (30.8%). pN status was significantly associated with sentinel lymph node biopsy, axillary lymph node dissection, age, ER status, tumor grade, and size, lymphovascular invasion, adjuvant systemic therapy (ACt), and radiation therapy. With 61 months median follow-up (mean 63.2; CI 95% 61.5–64.9), only pN1 with macro-metastases was independently associated with a negative impact on overall, disease-free, recurrence-free, and metastasis-free survivals in multivariate analysis. In the pT1a-b subgroup including 474 patients, RFS was significantly decreased in multivariate analysis for pT1b BC without ACt (HR 2.365, 1.04–5.36, p = 0.039) and for pN0(i+)/pN1mi patients (HR 2.518, 1.03–6.14, p = 0.042). (4) Conclusions: Survival outcomes were not adversely affected by pN0(i+) and pN1mi in patients with HER2-positive BC. However, in the case of pT1a-b HER2-positive BC, a negative impact on RFS was observed specifically for patients with pN0(i+) and pN1mi diseases, particularly among those with pT1b tumors without ACt. Our findings highlight the importance of considering the pN0(i+) and pN1mi status in the decision-making process when discussing trastuzumab-based ACt for these patients.",20726694,ONCOLOGY
10.3390/ejihpe13090138,Body-Related Attentional Bias in Adolescents Affected by Idiopathic Scoliosis,"Attentional biases toward body-related information increase body dissatisfaction. This can lead at-risk populations to develop psychopathologies. This phenomenon has not been extensively studied in girls affected by idiopathic scoliosis. This work aimed to study the cognitive processes that could contribute to the worsening and maintaining of body image disorders in adolescent idiopathic scoliosis. Twenty-eight girls were recruited and tested for body image dissatisfaction through the Scoliosis-Research-Society-22-revised (SRS-22r) questionnaire. Attentional biases towards disease-related body parts were assessed using a computerized visual match-to-sample task: girls were asked to answer as fast and accurately as possible to find the picture matching a target by pressing a button on a computer keyboard. Reaction times (RTs) and accuracy were collected as outcome variables and compared within and between groups and conditions. Lower scores in SRS-22r self-image, function, and total score were observed in scoliosis compared to the control group (p-value < 0.01). Faster response times (p-value = 0.02) and higher accuracy (p-value = 0.02) were detected in the scoliosis group when processing shoulders and backs (i.e., disease-relevant body parts). A self-body advantage effect emerged in the scoliosis group, showing higher accuracy when answering self-body stimuli compared to others’ bodies stimuli (p-value = 0.04). These results provide evidence of body image dissatisfaction and attentional bias towards disease-relevant body parts in girls with scoliosis, requiring clinical attention as highly predisposing to psychopathologies.",22549625,PSYCHOLOGY
10.3390/educsci13090963,Guidelines for Supporting a Community of Inquiry through Graded Online Discussion Forums in Higher Education,"Graded online discussion forums allow students to interact with course content, peers, and instructors. These discussions have the potential to enhance students’ learning experiences significantly. By adding graded online discussions to an online structured Master’s program in Education, it was necessary to determine the value of these discussions and their contribution to creating an online community. The purpose of this study, therefore, was to determine how a community of inquiry could support graded online discussions. The study used the Community of Inquiry theoretical framework as its basis. A qualitative exploratory case study design was used, involving eleven purposefully selected participants who were enrolled for a structured master’s program in Education. Data were collected from two sources: feedback from students on their experiences of the online discussions, and the actual online discussions. The data were analyzed using the six-phase thematic analysis approach following a deductive approach. This study revealed that these discussions supported students’ learning and created an online learning community promoting social, cognitive, and teaching presences. These findings have implications for practice. Firstly, fostering social presence is essential for online discussions because it leads to increased engagement, motivation, a sense of belonging, and collaboration. Secondly, online discussions need to be designed with clear guidelines, structured questions, and discussion opportunities. Lastly, online discussions designed to promote cognitive presence challenge students, encourage debate, and assist them in gaining the needed knowledge and higher order thinking skills. Based on these findings, the unique contribution of this study is to provide guidelines for fostering discussion forum participation within the Community of Inquiry (COI) framework. The suggested guidelines can serve as a resource to facilitate effective graded discussion forums in higher education contexts.",22277102,EDUCATION
10.3390/educsci13090961,Supporting Emergent Writing in Preschool Classrooms: Results of a Professional Development Program,"Emergent writing is a key component of early literacy development and contributes to later school success, yet it receives little attention in most preschool classrooms. This paper presents results of a quasi-experimental study of a teacher professional development package that included writing as one of four focal areas. The study was conducted in 15 Head Start classrooms located in the U.S. state of Hawaiʻi. The participants were 39 lead and assistant teachers and 240 children. Intervention teachers had higher quality writing environments and overall classroom environments, while intervention children showed better outcomes on emergent reading and upper case letter knowledge. Emergent writing was assessed only in the intervention group, where children showed large gains along with changes in code-related skills needed for invented spelling. Results are discussed in terms of recommended practices for early writing instruction and teacher professional development.",22277102,EDUCATION
10.3390/cancers15184627,Neo-Adjuvant Treatment in Primary Resectable Pancreatic Cancer: A Systematic Review and PRISMA-Compliant Updated Metanalysis of Oncological Outcomes,"Background: Despite advances in treatment, the prognosis of resectable pancreatic adenocarcinoma remains poor. Neoadjuvant therapy (NAT) has gained great interest in hopes of improving survival. However, the results of available studies based on different treatment approaches, such as chemotherapy and chemoradiotherapy, showed contrasting results. The aim of this systematic review and meta-analysis is to clarify the benefit of NAT compared to upfront surgery (US) in primarily resectable pancreatic adenocarcinoma. Methods: A PRISMA literature review identified 139 studies, of which 15 were finally included in the systematic review and meta-analysis. All data from eligible articles was summarized in a systematic summary and then used for the meta-analysis. Specifically, we used HR for OS and DFS and risk estimates (odds ratios) for the R0 resection rate and the N+ rate. The risk of bias was correctly assessed according to the nature of the studies included. Results: From the pooled HRs, OS for NAT patients was better, with an HR for death of 0.80 (95% CI: 0.72–0.90) at a significance level of less than 1%. In the sub-group analysis, no difference was found between patients treated with chemoradiotherapy or chemotherapy exclusively. The meta-analysis of seven studies that reported DFS for NAT resulted in a pooled HR for progression of 0.66 (95% CI: 0.56–0.79) with a significance level of less than 1%. A significantly lower risk of positive lymph nodes (OR: 0.45; 95% CI: 0.32–0.63) and an improved R0 resection rate (OR: 1.70; 95% CI: 1.23–2.36) were also found in patients treated with NAT, despite high heterogeneity. Conclusions: NAT is associated with improved survival for patients with resectable pancreatic adenocarcinoma; however, the optimal treatment strategy has yet to be defined, and further studies are required.",20726694,ONCOLOGY
10.3390/cancers15194679,Glucocorticoid Receptor Activation in Lobular Breast Cancer Is Associated with Reduced Cell Proliferation and Promotion of Metastases,"Estrogen receptor-positive (ER+) invasive lobular breast cancer (ILC) comprises about ~15% of breast cancer. ILC’s unique genotypic (loss of wild type E-cadherin expression) and phenotypic (small individual round cancer cells that grow in discontinuous nests) are thought to contribute to a distinctive pattern of metastases to serosal membranes. Unlike invasive ductal carcinoma (IDC), ILC metastases often intercalate into the mesothelial layer of the peritoneum and other serosal surfaces. While ER activity is a known driver of ILC proliferation, very little is known about how additional nuclear receptors contribute to ILC’s distinctive biology. In ER+ IDC, we showed previously that glucocorticoid receptor (GR) activity inhibits pro-proliferative gene expression and cell proliferation. Here we examined ER+ ILC models and found that GR activation similarly reduces S-phase entry gene expression and ILC proliferation. While slowing tumor growth rate, our data also suggest that GR activation results in an enhanced metastatic phenotype through increasing integrin-encoding gene expression, extracellular matrix protein adhesion, and mesothelial cell clearance. Moreover, in an intraductal mouse mammary gland model of ILC, we found that GR expression is associated with increased bone metastases despite slowed primary mammary tumor growth. Taken together, our findings suggest GR-mediated gene expression may contribute to the unusual characteristics of ILC biology.",20726694,ONCOLOGY
10.3390/cancers15194700,A Single-Center Study of the Impact of the COVID-19 Pandemic on the Organization of Healthcare Service Delivery to Patients with Head and Neck Cancer,"The aim of this study was to identify and assess the impact of the COVID-19 pandemic on the diagnosis and treatment of head and neck cancer (HNC) patients of the Department of Otolaryngology, Head and Neck Surgery of the 4th Military Teaching Hospital in Wroclaw for whom oncological treatment was planned by a cancer case board between March 2018 and February 2022. We analysed the medical records of 625 patients. In order to verify whether the relationships between the analysed features were statistically significant, the chi-square test of independence and the Student’s t-test for independent samples were used (p < 0.05). Our analysis showed that the impact of the pandemic on the organization of health service delivery to HNC patients was not uniform. The largest difference in the number of formulated treatment plans was observed at the beginning of the pandemic (22.1% reduction compared with the year before the pandemic). During the pandemic, the proportion of patients admitted on the basis of a DILO (diagnosis and oncological treatment) card issued by a primary care physician, instead of a regular referral to hospital, issued also by a primary care physician, was significantly higher compared with the that during the pre-pandemic period. The majority of cancer patients with a oncological treatment planned during the pandemic lived in urban areas. During the pandemic, the number of patients with more-advanced-stage cancer, assessed on the basis of the type of planned treatment (radical vs. palliative), did not increase compared with that during the pre-pandemic period. However, our follow-up period was quite short. It is necessary to intensify activities aimed at promoting health and increasing health awareness in people living in rural areas and setting long-term priorities and objectives for health policies at the national, regional and local levels, with particular focus on this group of people.",20726694,ONCOLOGY
10.1007/s44196-023-00328-0,Self-Supervised Learning for Industrial Image Anomaly Detection by Simulating Anomalous Samples,"Industrial image anomaly detection (AD) is a critical issue that has been investigated in different research areas. Many works have attempted to detect anomalies by simulating anomalous samples. However, how to simulate abnormal samples remains a significant challenge. In this study, a method for simulating anomalous samples is designed. First, for the object category, patch extraction and patch paste are designed to ensure that the extracted image patches come from the objects and are pasted to the objects in the image. Second, based on the statistical analysis of various anomalies’ presence, a combination of data augmentation is proposed to cover various anomalies as much as possible. The method is evaluated on MVTec AD and BTAD datasets; the experimental results demonstrate that our method achieves an overall detection AUC of 97.6% in MVTec AD datasets, outperforming the baseline by 1.5%, and the improvement over VT-ADL method is 4.3% on the BTAD datasets, demonstrating our method’s effectiveness and generalization.",18756883,AI
10.1007/s00432-023-05399-2,Enhancing prognostic accuracy: a SEER-based analysis for overall and cancer-specific survival prediction in cervical adenocarcinoma patients,"Background: Cervical adenocarcinoma (CA) is the second most prevalent histological subtype of cervical cancer, following cervical squamous cell carcinoma (CSCC). As stated in the guidelines provided by the National Comprehensive Cancer Network, they are staged and treated similarly. However, compared with CSCC patients, CA patients are more prone to lymph node metastasis and recurrence with a poorer prognosis. The objective of this research was to discover prognostic indicators and develop nomograms that can be utilized to anticipate the overall survival (OS) and cancer-specific survival (CSS) of patients diagnosed with CA. Methods: Using the Surveillance, Epidemiology, and End Result (SEER) database, individuals with CA who received their diagnosis between 2004 and 2015 were identified. A total cohort (n = 4485) was randomly classified into two separate groups in a 3:2 ratio, to form a training cohort (n = 2679) and a testing cohort (n = 1806). Overall survival (OS) was the primary outcome measure and cancer-specific survival (CSS) was the secondary outcome measure. Univariate and multivariate Cox analyses were employed to select significant independent factors and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was utilized to develop predictive nomogram models. The predictive accuracy and discriminatory ability of the nomogram were assessed by employing metrics such as the calibration curve, receiver operating characteristic (ROC) curve, and the concordance index (C-index). Results: Age, Tumor Node Metastasis stages (T, N, and M), SEER stage, grade, and tumor size were assessed as common independent predictors of both OS and CSS. The C-index value of the nomograms for predicting OS was 0.832 (95% CI 0.817–0.847) in the training cohort and 0.823 (95% CI 0.805–0.841) in the testing cohort. Conclusion: We developed and verified nomogram models for predicting 1-, 3- and 5-year OS and CSS among patients with cervical adenocarcinoma. These models exhibited excellent performance in prognostic prediction, providing support and assisting clinicians in assessing survival prognosis and devising personalized treatments for CA patients.",14321335,ONCOLOGY
10.1007/s00432-023-05350-5,Clinical characteristics of sarcoma patients: a population-based data analysis from a German clinical cancer registry,"Purpose: Sarcomas are a heterogeneous group of malignant neoplasms with a wide range of histological types and occur in almost any anatomic site and side. This study evaluated the prognostic factors in sarcoma patients based on German clinical cancer registry data. Methods: The German clinical cancer register of Saxony-Anhalt was used for all data analyses. Sarcoma cases of all clinical or pathological T-stages (T1a–T4c), all N-stages (N0-3) and M-stages (0–1b) corresponding to the Union for International Cancer Control (UICC) stages I to IVB were considered. In our analyses, 787 cases diagnosed between 2005 and 2022 were included. Further, we assessed the association of cancer-related parameters with mortality and hazard ratios (HR) from the Cox proportional hazard models. We included sex, age at diagnosis, histological grade, T-, N- and M-stages, tumor size, tumor localization and tumor side as parameters in our regression models. Results: The majority of sarcoma patients were diagnosed with leiomyosarcoma (12%), liposarcoma (11%), angiosarcoma (5.3%) and myxofibrosarcoma (2.7%). In our univariate regression models, tumors localized in more than one location, head, face and neck region as well as the pelvis and lower extremity were associated with increased mortality risk (more than one location: HR 7.10, 95% CI 2.20–22.9; head, face and neck: HR 1.35, 95% CI 0.89–2.06; pelvis: HR 1.27, 95% CI 0.86–1.89; lower extremity: HR 1.44, 95% CI 1.05–1.96). Higher histological grades, UICC-grades and TNM-stages were related to a higher mortality risk. Differing histological subtypes had significant influence on overall survival and progression-free survival. Patients diagnosed with fibromyxoid sarcoma, rhabdomyosarcoma and angiosarcoma were related to higher mortality risk compared to other histological subtypes (fibromyxoid sarcoma: HR 5.2, 95% CI 0.71–38.1; rhabdomyosarcoma: HR 2.93, 95% CI 1.44–6.00; angiosarcoma: HR 1.07, 95% CI 0.53–2.18). Conclusions: Histological grade, tumor size, nodal and distant metastasis, tumor localization and histological subtype were determined as prognostic factors in terms of survival.",14321335,ONCOLOGY
10.1186/s40594-023-00450-7,Gender gap in STEM pathways: the role of secondary curricula in a highly differentiated school system—the case of Chile,"Background: STEM fields are instrumental in increasing the technological and innovative capacity of the economy. As women are underrepresented in the STEM workforce, diverse strategies have been implemented to boost their preparedness and interest in these fields, including early exposure to academic and vocational STEM courses. Using the case of Chile’s highly differentiated school system, this paper examines the role of secondary curricula on students’ enrollment and persistence in STEM programs offered by vocational postsecondary institutions and universities. In doing so, we seek to identify whether exposure to STEM courses within the academic or vocational tracks translates into fewer gender differences in STEM higher education.Results: Our results reveal that upper-secondary tracks connected to STEM courses are positively associated with enrollment in STEM higher education and, to some degree, persistence. More specifically, exposure to STEM courses in the academic track is the most effective path to boost chances of enrolling in STEM university programs but has no connection to later persistence. In contrast, applied STEM courses within the vocational tracks perform better in the case of STEM programs in postsecondary vocational institutions both in enrollment and persistence. However, this STEM pipeline significantly amplifies gender gaps as males benefit more than women from early exposure to applied STEM courses. We also found that other indirect routes, such as enrolling in STEM university programs from the vocational track with applied STEM courses, boost female participation in these programs, helping reduce gender gaps.Conclusions: While secondary STEM courses attract more female students to STEM higher education, they alone are insufficient to achieve gender equality in STEM fields as gender gaps widen in the more effective routes. In highly differentiated school systems, policymakers and high school leaders should offer increased support to women interested in STEM studies and careers across all secondary tracks to boost female participation in STEM fields. At the same time, all high school students should be able to select both academic and applied STEM courses as a part of their non-mandatory curriculum.",21967822,EDUCATION
10.3390/ai4040040,Unveiling the Transparency of Prediction Models for Spatial PM2.5 over Singapore: Comparison of Different Machine Learning Approaches with eXplainable Artificial Intelligence,"Aerosols play a crucial role in the climate system due to direct and indirect effects, such as scattering and absorbing radiant energy. They also have adverse effects on visibility and human health. Humans are exposed to fine PM2.5, which has adverse health impacts related to cardiovascular and respiratory-related diseases. Long-term trends in PM concentrations are influenced by emissions and meteorological variations, while meteorological factors primarily drive short-term variations. Factors such as vegetation cover, relative humidity, temperature, and wind speed impact the divergence in the PM2.5 concentrations on the surface. Machine learning proved to be a good predictor of air quality. This study focuses on predicting PM2.5 with these parameters as input for spatial and temporal information. The work analyzes the in situ observations for PM2.5 over Singapore for seven years (2014–2021) at five locations, and these datasets are used for spatial prediction of PM2.5. The study aims to provide a novel framework based on temporal-based prediction using Random Forest (RF), Gradient Boosting (GB) regression, and Tree-based Pipeline Optimization Tool (TP) Auto ML works based on meta-heuristic via genetic algorithm. TP produced reasonable Global Performance Index values; 7.4 was the highest GPI value in August 2016, and the lowest was −0.6 in June 2019. This indicates the positive performance of the TP model; even the negative values are less than other models, denoting less pessimistic predictions. The outcomes are explained with the eXplainable Artificial Intelligence (XAI) techniques which help to investigate the fidelity of feature importance of the machine learning models to extract information regarding the rhythmic shift of the PM2.5 pattern.",26732688,AI
10.3390/ai4040041,A General Machine Learning Model for Assessing Fruit Quality Using Deep Image Features,"Fruit quality is a critical factor in the produce industry, affecting producers, distributors, consumers, and the economy. High-quality fruits are more appealing, nutritious, and safe, boosting consumer satisfaction and revenue for producers. Artificial intelligence can aid in assessing the quality of fruit using images. This paper presents a general machine learning model for assessing fruit quality using deep image features. This model leverages the learning capabilities of the recent successful networks for image classification called vision transformers (ViT). The ViT model is built and trained with a combination of various fruit datasets and taught to distinguish between good and rotten fruit images based on their visual appearance and not predefined quality attributes. The general model demonstrated impressive results in accurately identifying the quality of various fruits, such as apples (with a 99.50% accuracy), cucumbers (99%), grapes (100%), kakis (99.50%), oranges (99.50%), papayas (98%), peaches (98%), tomatoes (99.50%), and watermelons (98%). However, it showed slightly lower performance in identifying guavas (97%), lemons (97%), limes (97.50%), mangoes (97.50%), pears (97%), and pomegranates (97%).",26732688,AI
10.1186/s40359-023-01325-w,"The association between social support provision, psychological capital, subjective well-being and sense of indebtedness among undergraduates with low socioeconomic status","Background: Social support consists of receipt and provision in the interpersonal exchange process. Many studies have explored and verified the effect of received social support. This study focuses on whether and when social support provision can benefit the providers’ positive psychological capital and subjective well-being. Methods: A sample of 732 Chinese undergraduates with low socioeconomic status completed questionnaires on social support provision, psychological capital, life satisfaction, positive affect, negative affect, and sense of indebtedness. Results: The correlation and regression analyses showed that impoverished college students’ social support provision was positively associated with life satisfaction, positive affect, and psychological capital and negatively associated with negative affect. The interaction between the sense of indebtedness and social support provision was negatively associated with life satisfaction, positive affect, and psychological capital, not significantly associated with negative affect. Conclusion: The results demonstrated that giving social support can be as beneficial as receiving social support, and the sense of indebtedness can limit the benefits. Individuals with a lower sense of indebtedness are more likely to benefit from social support provision. The findings have implications for marginalized groups’ subjective well-being and positive psychological capital and show the necessity of guiding individuals to provide social support while maintaining their autonomy.",20507283,PSYCHOLOGY
10.3390/educsci13100993,Teacher Development for Equitable Mathematics Classrooms: Reflecting on Experience in the Context of Performativity,"In this article, we chart the development of one of us—Sue Hough—from a teacher who wanted students to understand to one who gained new critical understandings of student thinking, pedagogy, and the very nature of mathematics. We comment on the role of research interventions and learning communities in this development, with a particular focus on Sue’s encounter with Realistic Mathematics Education and the connections it makes between informal and formal mathematics through the pedagogy of guided reinvention. Development towards teaching that enables all learners to make sense of mathematics requires fundamental changes in pedagogic practice and a reconceptualisation of progress. Bringing about such radical change relies on one further aspect of Sue’s story—the freedom to experiment and learn as a teacher. We note the remoteness of this possibility in a climate of performativity and marketised education, and we discuss the implications of Sue’s journey for our pedagogical responsibilities in professional development today.",22277102,EDUCATION
10.3390/educsci13100996,"Homework’s Implications for the Well-Being of Primary School Pupils—Perceptions of Children, Parents, and Teachers","Teachers and educational researchers explore various approaches to make homework more engaging and enjoyable, intending to improve the well-being and academic performance of primary school students. The study aimed to identify practices with positive and negative effects on students’ well-being when doing homework. The views of those involved in giving, doing, and assessing homework were captured from three perspectives, namely, teachers, students, and parents. In May–June 2022, six online focus groups were conducted with the participation of 13 teachers, 11 parents, and 16 primary school students from a Romanian school. The thematic analysis identified the homework that the children (do not) like; their reactions when they receive, do, and are assessed for such homework; and suggestions on how to improve the homework. The results revealed that homework assignments that make young schoolchildren feel capable, effective, appreciated, and rewarded; homework done in teams in the form of competitions or games; parental involvement in collaborative homework; and homework with creative elements are effective ways that contribute to the well-being of primary school pupils when doing homework. Repetitive, lengthy, tedious, overloaded homework generates frustration, discouragement, and emotional reactions such as crying, abandonment, anxiety, and sleep deprivation.",22277102,EDUCATION
10.1186/s40359-023-01335-8,Transdiagnostic phenomena of psychopathology in the context of the RDoC: protocol of a multimodal cross-sectional study,"In the past, affective and cognitive processes related to psychopathology have been examined within the boundaries of phenotype-based diagnostic labels, which has led to inconsistent findings regarding their underlying operating principles. Investigating these processes dimensionally in healthy individuals and by means of multiple modalities may provide additional insights into the psychological and neuronal mechanisms at their core. The transdiagnostic phenomena Neuroticism and Rumination are known to be closely linked. However, the exact nature of their relationship remains to be elucidated. The same applies to the associations between Hedonic Capacity, Negativity Bias and different Emotion Regulation strategies. This multimodal cross-sectional study examines the relationship of the transdiagnostic phenomena Neuroticism and Rumination as well as Hedonic Capacity, the Negativity Bias and Emotion Regulation from a RDoC (Research Domain Criteria) perspective. A total of 120 currently healthy subjects (past 12 months) will complete several questionnaires regarding personality, emotion regulation, hedonic capacity, and psychopathologies as well as functional magnetic resonance imaging (fMRI) during cognitive and emotional processing, to obtain data on the circuit, behavioral and self-report level. This study aims to contribute to the understanding of the relationship between cognitive and affective processes associated with psychopathologies as well as their neuronal correlates. Ultimately, a grounded understanding of these processes could guide improvement of diagnostic labels and treatments. Limitations include the cross-sectional design and the limited variability in psychopathology scores due to the restriction of the sample to currently healthy subjects.",20507283,PSYCHOLOGY
10.3390/ejihpe13100150,A Qualitative Study to Explore the Life Experiences of Older Adults in Oman,"Background: Reminiscence studies and life reviews have a number of proven advantages. Future generations gain by learning from elders’ life experiences, as do older adults themselves who share their memories. Despite Oman’s sizable geriatric population, research on older individuals’ life experiences is scarce. Therefore, this study aimed to explore the life experiences of older Omani individuals across their many life stages, from childhood to the present. Methods: This was a qualitative study design. Convenience sampling was employed and conducted from December 2021 to October 2022. A total of 13 Omani older adults (9 females and 4 males), with an average age of 68 years, were recruited for this study (response rate = 34%). Socio-demographic and life review information was gathered according to a set of semi-structured guiding questions. The responses were then captured on audio recordings, which underwent transcription and translation. Thematic analysis techniques were applied to the extracted data. Results: Three main themes were evident in this study’s findings: childhood memories, friendships, and relationships, as well as the elders’ past. Additionally, older adults passed on a number of gems of wisdom to be shared with the younger generations. Conclusions: This study aided in revealing the resiliency, social connections, and life reflections of Omani older adults. These themes can guide the creation of age-inclusive laws, social support initiatives, and healthcare services specifically designed to satisfy the special requirements and ambitions of the elderly population. Based on these themes, this study recommended that the local community or society build a more sympathetic and compassionate atmosphere that honors and respects the accomplishments of this essential group by recognizing and comprehending the complex experiences of older adults. In addition, future studies could explore particular aspects of these older experiences and pinpoint solutions to improve their quality of life and wellbeing.",22549625,PSYCHOLOGY
10.1186/s40359-023-01345-6,"PsyCARE study: assessing impact, cost-effectiveness, and transdiagnostic factors of the Italian ministry of health’s “psychological bonus” policy","Background: The prevalence of anxiety and depression disorders is surging worldwide, prompting a pressing demand for psychological interventions, especially in less severe cases. Responding to this need, the Italian government implemented the “Psychological Bonus” (PB) policy, allotting 25 million euros for mental health support. This policy entitles individuals to a minimum of four to twelve psychological sessions. In collaboration with the National Board of Italian Psychologists, our study assesses this policy’s effectiveness. Indeed, the PsyCARE study aims to examine the utilization of the Psychological Bonus, evaluate its impact on adult and adolescent participants’ psychological well-being through pre- and post-intervention assessments and six-month follow-up, and conduct a longitudinal cost-effectiveness analysis of this policy. A secondary aim is to investigate the influence of these interventions on transdiagnostic factors, including emotion regulation and epistemic trust. Methods: The study involves licensed psychotherapists and their patients, both adults and adolescents, benefiting from the Psychological Bonus. Data collection is underway and set to conclude in December 2023. Psychotherapists will provide diagnostic information and assess patient functioning. In addition, patients will be evaluated on mental health aspects such as clinical symptoms, emotion regulation, epistemic trust, and quality of life. We will employ linear mixed-effects models to analyze the outcomes, accounting for both fixed and random effects to capture the hierarchical structure of the data. Discussion: We anticipate the study’s findings will highlight reduced psychological distress and improved quality of life for participants and demonstrate the Psychological Bonus policy’s cost-effectiveness. The study will gather data on the role of specific versus nonspecific therapeutic factors in psychotherapy while adopting a patient-tailored approach to identify effective therapeutic elements and examine transdiagnostic factors. Overall, this study’s findings will guide future measures within the Italian healthcare system, fostering a psychological health culture and providing valuable insights to the broader public. Study registration:",20507283,PSYCHOLOGY
10.1186/s40359-023-01302-3,Assessment of the mind-body connection: preliminary psychometric evidence for a new self-report questionnaire,"Objectives: While interoceptive self-report scales provide a foundation for measuring the mind-body connection, they variably consider other important factors that could influence interpretations of internal bodily sensations and perceptions related to mind-body integration. The proposed Body-Mind Connection Questionnaire (BMCQ) aimed to operationalise the notion that this construct involves three major components: (a) Interoceptive Attention, (b) Sensation-Emotion Articulation, and (c) Body-Mind Values. Methods: Following panel review and piloting with the target population, the developed BMCQ was evaluated in 316 participants (189 identifying as female) aged 18-50 (MAge=30.78), alongside established self-report measures of interoceptive sensibility, body awareness, sensory processing sensitivity, and alexithymia. We examined the BMCQ factor structure through exploratory factor analysis and analysed convergent and discriminant validity. Results: Exploratory factor analysis supported three scales of the BMCQ, which explained 54.03% of variance. Factor loadings (>0.44) and reliability indices (0.74 to 0.85) were acceptable. Inter-scale correlations suggested that the scales are distinct but related (rs=0.38 to 0.59). BMCQ scales were supported by convergent (r=0.33 to 0.67) and discriminant evidence (rs=0.01 to 0.39, p range n.s. to <.05). Conclusions: Preliminary psychometric properties indicate that the BMCQ is multidimensional and consists of three constructs that differentially relate to theoretically associated measures. Interoceptive Attention, Sensation-Emotion Articulation, and Body-Mind Values may serve as a basis for efficiently assessing the mind-body connection more holistically, which could be useful for developing interventions aimed at enhancing mind-body integration.",20507283,PSYCHOLOGY
10.3390/ejihpe13100153,Assessing the Relationship between Prosocial Behavior and Well-Being: Basic Psychological Need as the Mediator,"Previous research has established a positive link between prosocial behavior (PB) and psychological well-being. However, limited studies have explored the relationship between PB and well-being (WB), particularly among vocational students. Furthermore, the underlying mechanisms, including mediating factors, remain understudied in this context. This study aimed to investigate the association between PB and WB among vocational students while examining the mediating role of basic psychological needs. A sample of 221 vocational students (mean age = 19.68 years, SD = 1.57) completed anonymous questionnaires assessing PB, basic psychological needs, and WB. The results revealed a positive correlation between PB and WB in vocational students (r = 0.22, p < 0.01), with basic psychological needs partially mediating this relationship (β = 0.14, t = 10.85, p < 0.001, 95% CI = (0.18, 0.23)). These findings enhance our understanding of the association between PB and vocational students’ WB, shed light on the mechanisms involved, and offer insights into promoting the well-being of vocational students.",22549625,PSYCHOLOGY
10.3390/ejihpe13100156,Meaning in Life and Loneliness as Mediators between COVID-19 Anxiety and Life Satisfaction in the Post-Pandemic among the General Population in Turkey: A Serial Mediation Model,"The COVID-19 pandemic has impacted global society, leading to negative well-being and mental health outcomes. However, little is known about how COVID-19-related anxiety affects life satisfaction through psychological factors. This study examined the mediating roles of meaning in life and loneliness in the relationship between COVID-19 anxiety and life satisfaction in 333 Turkish general population (59.2% females; Mage = 33.9 ± 7.8). Participants completed measures of COVID-19 anxiety, life satisfaction, meaning in life, and loneliness. The results showed that COVID-19 anxiety predicted meaning in life, loneliness, and life satisfaction. Meaning in life predicted loneliness and life satisfaction, while loneliness predicted life satisfaction. Serial mediation analysis revealed that COVID-19 anxiety predicts life satisfaction through meaning in life and loneliness, even after controlling for age and gender. These findings contribute to our understanding of the underlying mechanisms between COVID-19 anxiety and life satisfaction, with implications for future research and practice.",22549625,PSYCHOLOGY
10.3390/ai4040045,Algorithms for All: Can AI in the Mortgage Market Expand Access to Homeownership?,"Artificial intelligence (AI) is transforming the mortgage market at every stage of the value chain. In this paper, we examine the potential for the mortgage industry to leverage AI to overcome the historical and systemic barriers to homeownership for members of Black, Brown, and lower-income communities. We begin by proposing societal, ethical, legal, and practical criteria that should be considered in the development and implementation of AI models. Based on this framework, we discuss the applications of AI that are transforming the mortgage market, including digital marketing, the inclusion of non-traditional “big data” in credit scoring algorithms, AI property valuation, and loan underwriting models. We conclude that although the current AI models may reflect the same biases that have existed historically in the mortgage market, opportunities exist for proactive, responsible AI model development designed to remove the systemic barriers to mortgage credit access.",26732688,AI
10.1007/s00432-023-05441-3,Hedgehog pathway in sarcoma: from preclinical mechanism to clinical application,"Sarcomas are a diverse group of malignant neoplasms of mesenchymal origin. They develop rarely, but due to poor prognosis, they are a challenging and significant clinical problem. Currently, available therapeutic options have very limited activity. A better understating of sarcomas’ pathogenesis may help develop more effective therapies in the future. The Sonic hedgehog (Shh) signaling pathway is involved in both embryonic development and mature tissue repair and carcinogenesis. Shh pathway inhibitors are presently used in the treatment of basal cell carcinoma. Its increased activity has been demonstrated in many sarcomas, including osteosarcoma, Ewing sarcoma, chondrosarcoma, rhabdomyosarcoma, leiomyosarcoma, and malignant rhabdoid tumor. In vitro studies have demonstrated the effectiveness of inhibitors of the Hedgehog pathway in inhibiting proliferation in those sarcomas in which the components of the pathway are overexpressed. These results were confirmed by in vivo studies, which additionally proved the influence of Shh pathway inhibitors on limiting the metastatic potential of sarcoma cells. However, until now, the efficacy of sarcomas treatment with Shh pathway inhibitors has not been established in clinical trials. The reason for that may be the non-canonical activation of the pathway or interactions with other signaling pathways, such as Wnt or Notch. In this review, we present the Shh signaling pathway's role in the pathogenesis of sarcomas, including both canonical and non-canonical signaling. We also propose how this knowledge could be potentially translated into clinics.",14321335,ONCOLOGY
10.1007/s00432-023-05446-y,Contributing and limiting factors to guideline-adherent therapy in senior and elderly breast cancer patients: a questionnaire-based cross-sectional study using clinical and cancer registry data in Germany,"Purpose: Elderly cancer patients are less likely to be treated in accordance with evidence-based guideline recommendations. This study examines patient-related factors associated with deviations from guideline recommendations. Methods: Using medical documentation and cancer registry data, we investigated the treatment courses of female breast cancer patients aged 50 and older in Germany regarding compliance with German guidelines. Participants completed a questionnaire querying factors hypothesized to be associated with guideline adherence. We conducted univariate analyses to explore the data and select variables for multivariate logistic regression to estimate adjusted odds ratios. Results: Of 1150 participants, 206 (17.9%) were treated in deviation from guideline recommendations. Patients 70 years and older were more likely to be treated deviating from guideline recommendations than patients 50–69 years old (OR: 2.07; 95% CI: 1.52–2.80). Patients aged 50–69 years who reported that quality of life guided their treatment decision were more likely to be treated in deviation from guideline recommendations (AOR: 2.08; 95% CI: 1.11–3.92) than the elderly. In older patients, higher age was associated with an increased chance of receiving guideline-discordant care (AOR: 1.06; 95% CI: 1.01–1.11), as was depression diagnosed prior to cancer (AOR: 1.84; 95% CI: 1.00–3.40). Conclusion: Reasons for deviations from guideline recommendations in breast cancer patients differ by age. In decision-making concerning elderly patients, particular attention should be paid to those with pre-existing depressive disorders. Adequately addressing their needs and concerns could prevent inappropriate deviations from guideline recommendations.",14321335,ONCOLOGY
10.3390/ejihpe13100158,From Policies to Practices: Factors Related to the Use of Inclusive Practices in Portugal,"Inclusion is considered a foundation for quality education, and teachers’ inclusive practices are essential for success in mainstream classrooms. Portugal has been making progressive improvements in its policies for inclusive education, although there is little consistency in school practices within or between schools. Moreover, data identifying the personal and career variables relevant to teachers’ inclusive practices in Portugal are scarce. Therefore, the purpose of this study was to determine the relationship between teachers’ inclusive practices and personal and career-based characteristics, including gender, level of teaching, years of experience, roles performed at school, and perception of inclusive resources. The participants were 924 teachers who worked in private and public schools in Portugal. Regression analysis showed that perceived inclusive resources, level of teaching, and gender predicted variance in inclusive practices. Mean difference analyses revealed that teachers at the lower levels of teaching, females, and teachers reporting more inclusive resources had the highest scores for inclusive practices. These findings are discussed in terms of their practical relevance for inclusive school systems.",22549625,PSYCHOLOGY
10.3390/ai4040046,From Trustworthy Principles to a Trustworthy Development Process: The Need and Elements of Trusted Development of AI Systems,"The current endeavor of moving AI ethics from theory to practice can frequently be observed in academia and industry and indicates a major achievement in the theoretical understanding of responsible AI. Its practical application, however, currently poses challenges, as mechanisms for translating the proposed principles into easily feasible actions are often considered unclear and not ready for practice. In particular, a lack of uniform, standardized approaches that are aligned with regulatory provisions is often highlighted by practitioners as a major drawback to the practical realization of AI governance. To address these challenges, we propose a stronger shift in focus from solely the trustworthiness of AI products to the perceived trustworthiness of the development process by introducing a concept for a trustworthy development process for AI systems. We derive this process from a semi-systematic literature analysis of common AI governance documents to identify the most prominent measures for operationalizing responsible AI and compare them to implications for AI providers from EU-centered regulatory frameworks. Assessing the resulting process along derived characteristics of trustworthy processes shows that, while clarity is often mentioned as a major drawback, and many AI providers tend to wait for finalized regulations before reacting, the summarized landscape of proposed AI governance mechanisms can already cover many of the binding and non-binding demands circulating similar activities to address fundamental risks. Furthermore, while many factors of procedural trustworthiness are already fulfilled, limitations are seen particularly due to the vagueness of currently proposed measures, calling for a detailing of measures based on use cases and the system’s context.",26732688,AI
10.1186/s40359-023-01373-2,A psychometric study of an executive function assessment instrument (TDI-FE),"Background: This study aims to present and discuss the psychometric properties of executive functions, which were measured using the TDI-FE instrument. The analysis encompasses its internal structure, potential sensitivity to fatigue factors, relationships with external criteria, and diagnostic accuracy. Methods: The study sample comprised 382 students from Brazil, aged 6–8 years. Child development variables were screened using the TDI-FE and gold standard tests (Cancellation Attention and Trail Making Tests). The proposed scale comprised four activities: a test with fruit images with three tasks, and one memory game. Results: The one-factor model of EF of the TDI-FE failed to fit to the data. However, fit substantially improved once a latent fatigue factor was controlled in the model. The latent factor of EF assessed by the TDI-FE tasks was coherently associated with a series of external variables, including two popular collateral measures of EF. The diagnostic accuracy was reasonable, and a cut-off of 37 points produced 70% of sensitivity and 60% of specificity. Conclusion: Results indicated that the TDI-FE demonstrated sound psychometric properties and diagnostic accuracy, then consisting of an efficient alternative for the assessment of EFs in early childhood education. The study also proved the need to control for response biases such as fatigue in the latent variable models of EF. The TDI-FE is notable because of its low cost and easy application, and it might fulfill a need for instruments for individuals from different contexts at this stage of development in Brazil.",20507283,PSYCHOLOGY
10.3390/cancers15205002,Modulatory Properties of Aloe secundiflora’s Methanolic Extracts on Targeted Genes in Colorectal Cancer Management,"Colon tumors have a very complicated and poorly understood pathogenesis. Plant-based organic compounds might provide a novel source for cancer treatment with a sufficient novel mode of action. The objective of this study was to analyze and evaluate the efficacy of Aloe secundiflora’s (AS) methanolic extracts on the expression of CASPS9, 5-LOX, Bcl2, Bcl-xL, and COX-2 in colorectal cancer (CRC) management. Caco-2 cell lines were used in the experimental study. In the serial exhaustive extraction (SEE) method, methanol was utilized as the extraction solvent. Upon treatment of CASPS9 with the methanolic extracts, the expression of the genes was progressively upregulated, thus, dose-dependently increasing the rate of apoptosis. On the other hand, the expressions of 5-LOX, Bcl2, and Bcl-xL were variably downregulated in a dose-dependent manner. This is a unique novel study that evaluated the effects of AS methanolic extracts in vitro on CRC cell lines using different dosage concentrations. We, therefore, recommend the utilization of AS and the application of methanol as the extraction solvent of choice for maximum modulatory benefits in CRC management. In addition, we suggest research on the specific metabolites in AS involved in the modulatory pathways that suppress the development of CRC and potential metastases.",20726694,ONCOLOGY
10.3390/cancers15205014,The Carcinogenic Potential of Bisphenol A in the Liver Based on Transcriptomic Studies,"Bisphenol A (BPA) is an environmental toxin widely used in the production of polycarbonate plastics. A correlation exists between BPA tissue contamination and the occurrence of pathological conditions, including cancer. First-passage detoxification of high BPA amounts in the liver promotes hepatotoxicity and morphological alterations of this organ, but there is a lack of knowledge about the molecular mechanisms underlying these phenomena. This prompted us to investigate changes in the liver transcriptomics of 3-month-old female mice exposed to BPA (50 mg/kg) in drinking water for 3 months. Five female mice served as controls. The animals were euthanized, the livers were collected, and RNA was extracted to perform RNA-seq analysis. The multistep transcriptomic bioinformatics revealed 120 differentially expressed genes (DEGs) in the BPA-exposed samples. Gene Ontology (GO) annotations indicated that DEGs have been assigned to many biological processes, including “macromolecule modification” and “protein metabolic process”. Several of the revealed DEGs have been linked to the pathogenesis of severe metabolic liver disorders and malignant tumors, in particular hepatocellular carcinoma. Data from this study suggest that BPA has a significant impact on gene expression in the liver, which is predictive of the carcinogenic potential of this compound in this organ.",20726694,ONCOLOGY
10.1007/s44196-023-00341-3,A Multiclustering Evolutionary Hyperrectangle-Based Algorithm,"Clustering is a grouping technique that has long been used to relate data homogeneously. With the huge growth of complex datasets from different sources in the last decade, new paradigms have emerged. Multiclustering is a new concept within clustering that attempts to simultaneously generate multiple clusters that are bound to be different from each other, allowing to analyze and discover hidden patterns in the dataset compared to single clustering methods. This paper presents a hybrid methodology based on an evolutionary approach with the concepts of hyperrectangle for multiclustering, called MultiCHCClust. The algorithm is applied in a post-processing stage and it improves the results obtained for a clustering algorithm with respect to the partitioning of the dataset and the optimization of the number of partitions, achieving a high degree of compactness and separation of the partitioned dataset as can be observed in a complete experimental study.",18756883,AI
10.3390/ai4040047,Deep Learning Performance Characterization on GPUs for Various Quantization Frameworks,"Deep learning is employed in many applications, such as computer vision, natural language processing, robotics, and recommender systems. Large and complex neural networks lead to high accuracy; however, they adversely affect many aspects of deep learning performance, such as training time, latency, throughput, energy consumption, and memory usage in the training and inference stages. To solve these challenges, various optimization techniques and frameworks have been developed for the efficient performance of deep learning models in the training and inference stages. Although optimization techniques such as quantization have been studied thoroughly in the past, less work has been done to study the performance of frameworks that provide quantization techniques. In this paper, we have used different performance metrics to study the performance of various quantization frameworks, including TensorFlow automatic mixed precision and TensorRT. These performance metrics include training time and memory utilization in the training stage along with latency and throughput for graphics processing units (GPUs) in the inference stage. We have applied the automatic mixed precision (AMP) technique during the training stage using the TensorFlow framework, while for inference we have utilized the TensorRT framework for the post-training quantization technique using the TensorFlow TensorRT (TF-TRT) application programming interface (API).We performed model profiling for different deep learning models, datasets, image sizes, and batch sizes for both the training and inference stages, the results of which can help developers and researchers to devise and deploy efficient deep learning models for GPUs.",26732688,AI
10.3390/educsci13101047,The Contribution of Educational Psychology to South African Preservice Teacher Training and Learner Support,"Teacher education programmes are developed around the theoretical and practical understanding of child development, learning, assessment, behaviour management and motivation, which are areas of expertise in educational psychology. This paper aims to (a) critically investigate the contribution of educational psychology in the training of preservice teachers at South African universities and (b) understand the distribution of educational psychologists in public schools to support teaching and learning. A narrative literature review and email requests for unpublished documents from four educational psychologists were used as methods to collect literature in order to answer the following questions: What contribution does educational psychology make to training preservice teachers at public universities in South Africa? What contributions do educational psychologists make to support learners in South African public schools? Analysis was carried out by identifying recurring patterns in the literature reviewed. This study found that of the 26 public universities in South Africa, there are only 6 universities that offer educational psychology programmes. Educational psychology programmes in higher education institutions are in decline, leading to a decrease in the number of qualified educational psychologists. This decline negatively affects the involvement of educational psychologists in training preservice teachers in educational psychology modules or courses. Therefore, the inclusion of educational psychology as a core or fundamental module in the curriculum of preservice teachers to avoid dependence on the decreasing number of educational psychologists in higher education institutions is key. An increase in teacher training programmes in higher education should be merged with an equal increase in educational psychology core or fundamental courses in the curriculum of preservice teachers.",22277102,EDUCATION
10.1186/s40359-023-01383-0,"Structural modeling of EFL/ESL teachers’ physical activity, mental health, psychological well-being, and self-efficacy","Background: Physical activity (PA) is known to positively affect individuals’ mental and physical health, especially those who experience high levels of stress, such as teachers. Previous studies have examined the relationship between teachers’ PA, mental health, and well-being. Still, there is a lack of research on the direct and indirect effects of PA and self-efficacy. Purpose: This study aimed to investigate the structural relationship between teachers’ PA, mental health, well-being, and self-efficacy among ESL/EFL teachers. A total of 364 Chinese English language teachers were selected through convenience sampling. Mental health, physical activity, psychological well-being, and self-efficacy instruments were used. Methodology: The data was analyzed using Smart PLS software, and the hypothesized model was evaluated. The results indicated an acceptable level of divergent and convergent validity and goodness of fit. Results: The findings revealed that PA directly predicts teachers’ mental health and well-being, but the direct structural relationship between teachers’ PA and self-efficacy was not confirmed. However, the results showed that teachers’ PA contributes to their self-efficacy by enhancing their mental and psychological well-being. The total effect of teachers’ PA on their self-efficacy was significant. Additionally, mental health and psychological well-being strongly influenced teachers’ self-efficacy. Conclusion: In conclusion, regular weekly physical activity can help EFL/ESL teachers foster their mental health, psychological well-being, and self-efficacy. These findings have theoretical and practical significance for teachers, trainers, and educational psychologists.",20507283,PSYCHOLOGY
10.3390/educsci13101050,Earning Your Way into General Education: Perceptions about Autism Influence Classroom Placement,"The language used by teachers, school staff, and parents to talk about autistic students can send either positive or negative messages to other school staff, parents, and all students—with or without autism—about autistic students. Ultimately, these messages also extend to autistic people. Using qualitative focus group methods, we talked to parents, teachers, administrators, and other school staff to better understand how people speak about the inclusion of autistic students in general education classrooms in public schools. Overall, we found that many of our participants thought (1) autistic students need to earn their way into general education classrooms, unlike their peers without disabilities, (2) segregating students with disabilities away from their peers without disabilities is acceptable, and sometimes preferable, in school settings, and (3) there is power in inclusive education opportunities for students with and without disabilities in school settings. The findings from this study suggest that inclusive opportunities for autistic students were largely driven by stakeholder mindsets. These results should encourage school staff to think about and reflect on how they talk about autistic students in inclusive settings with the ultimate goal of creating more welcoming inclusive environments for autistic students.",22277102,EDUCATION
10.3390/educsci13101053,“I’d Rather Do It Single-Handed”—Nursing Students’ Struggles with Group Assignments: A Qualitative Study,"This study, framed by the GRPI (Goal, Role, Process, and Interaction) teamwork model, explores team dynamics among nursing students in performing group assignments, utilizing a qualitative research design. Twenty-three nursing students from Year 1 to Year 4 at a nursing school in Macau were invited. Semi-structured personal interviews were carried out. In addition, three teachers who were involved in instructing and assessing group assignments of nursing students were also interviewed. Data were analyzed using inductive and deductive approaches. The study found that although the barriers to accomplishing effective teamwork were embedded into the four dimensions of the DRPI model, they were interplayed. Communication was fundamental for teamwork, thus leading to a modified DRPI model. Teammates did not equally share the workload. Despite interpersonal conflicts among teammates, nursing students managed to stay in superficial harmony with their peers. They became more familiar with teamwork while advancing into their senior years but with decreased group communications. This study highlights various factors preventing students from transferring individualism to team players. Teaming is not an equal learning opportunity for teammates. Culturally upheld value of harmony prevails in the interpersonal relationships of the team members, which may compromise the teamwork spirit cultivation expectations from the teachers.",22277102,EDUCATION
10.3390/cancers15205087,The Different Roles of MET in the Development and Treatment of Cancer,This Special Issue features contributions from leading international researchers in the field of MET (hepatocyte growth factor (HGF) receptor) biology and therapeutics,20726694,ONCOLOGY
10.1186/s40594-023-00454-3,Integrating artificial intelligence into science lessons: teachers’ experiences and views,"Background: In the midst of digital transformation, schools are transforming their classrooms as they prepare students for a world increasingly automated by new technologies, including artificial intelligence (AI). During curricular implementation, it has not made sense to teachers to teach AI as a stand-alone subject as it is not a traditional discipline in schools. As such, subject matter teachers may need to take on the responsibility of integrating AI content into discipline-based lessons to help students make connections and see its relevance rather than present AI as separate content. This paper reports on a study that piloted a new lesson package in science classrooms to introduce students to the idea of AI. Specifically, the AI-integrated science lesson package, designed by the research team, provided an extended activity that used the same context as an existing lesson activity. Three science teachers from different schools piloted the lesson package with small groups of students and provided feedback on the materials and implementation. Findings: The findings revealed the teachers’ perceptions of integrating AI into science lessons in terms of the connection between AI and science, challenges when implementing the AI lesson package and recommendations on improvements. First, the teachers perceived that AI and science have similarities in developing accurate models with quality data and using simplified reasoning, while they thought that AI and science play complementary roles when solving scientific problems. Second, the teachers thought that the biggest challenge in implementing the lesson package was a lack of confidence in content mastery, while the package would be challenging to get buy-in from teachers regarding curriculum adaptation and targeting the appropriate audience. Considering these challenges, they recommended that comprehensive AI resources be provided to teachers, while this package can be employed for science enrichment programs after-school. Conclusions: The study has implications for curriculum writers who design lesson packages that introduce AI in science classrooms and for science teachers who wish to contribute to the development of AI literacy for teachers and the extension of the range of school science and STEM to students.",21967822,EDUCATION
10.3390/educsci13111070,"The Past, the Present, and the Future of the Evolution of Mixed Reality in Teacher Education","The authors in this article provide a historical view (past) on the development of mixed reality (MR) simulation in teacher education as well as a brief history of simulation from other fields along with foundational knowledge on the evolution of simulation. The authors provide a systematic review of the current state (present) of the research in MR for teacher education within the past 5 years aligned with the research question “What are the uses, practices, and outcomes of MR simulation in teacher preparation?”. Three themes were identified, i.e., simulation to this point is designed by teacher educators, feedback matters in impacting outcomes, and practice is safe and reflective for those who prepare teachers in these environments. A summary is provided of these key articles and the findings. The authors conclude the article by sharing the potential evolution (future) of aspects of the model of MR, focusing on the use of AI agents and multi-modal data collection, including biometric signals, providing insights into simulation in teacher education.",22277102,EDUCATION
10.1186/s40359-023-01389-8,Examining specific and non-specific symptoms of the best-fitting posttraumatic stress disorder model in conflict-exposed adolescents,"Background: The 5th revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) construes PTSD symptoms into 4 clusters (intrusion, avoidance, negative alterations in cognitions and mood, alterations in arousal and reactivity; Model 1). However, recent literature has shown that this symptom structure does not best represent PTSD. Unfortunately, the findings of studies investigating the proposed alternative models are from consensus. Adding to the complexity of the issue of symptom-grouping models is the identification of specific and non-specific symptoms of PTSD. The present study aims to address these gaps by identifying the best-fitting PTSD model and subsequently examining what symptoms are considered specific and non-specific to PTSD in adolescent-survivors of armed political conflict and violence. Methods: The study utilized a sample of 641 adolescent victim survivors. We conducted CFA analyses and compared nested models through the scaled χ2 difference test, while comparison of non-nested models was done using the Bayesian information criterion (BIC). The best-fitted model was used in the consequent analysis, where we statistically controlled for the effect of non-specific psychological distress on PTSD by comparing the factor loadings and factor correlations before and after accounting for distress using the Aroian z-test. Results: The results provide support for the 7-factor hybrid model of PTSD over other proposed models for the current sample. Moreover, the data reveal that only 7 items could be construed as core symptoms, while the rest of the symptoms can be considered non-PTSD specific. Conclusions: Overall, the findings provide support for the validity of the hybrid PTSD model among political conflict-exposed adolescents. The results also show that the DSM-5 PTSD has both specific and non-specific features in the present sample of conflict-exposed adolescents. This has potential implications for theory, practice, and treatment of the disorder.",20507283,PSYCHOLOGY
10.1007/s00432-023-05470-y,Diagnostic accuracy of contrast-enhanced computed tomography in assessing cervical lymph node status in patients with oral squamous cell carcinoma,"Objective: Accurate preoperative prediction of lymph node (LN) status plays a pivotal role in determining the extension of neck dissection (ND) required for patients with oral squamous cell carcinoma (OSCC). This study aims to evaluate the diagnostic accuracy of contrast-enhanced computed tomography (CT) in detecting LN metastases (LNMs) and to explore clinicopathological factors associated with its reliability. Methods: Data from 239 patients with primary OSCC who underwent preoperative CT and subsequent radical surgery involving ND were retrospectively reviewed. Suspicious LNs were categorized into three groups: accentuated (< 10 mm), enlarged (≥ 10 mm), and melted. Statistical analysis encompassing correlation and comparative analysis, and determination of sensitivity, specificity, PPV, and NPV were performed. Results: Overall, sensitivity was significantly higher in the accentuated LNs group (83.54%) compared to the melted LNs group (39.24%, p < 0.05, t test). Conversely, specificity was significantly higher in the melted LNs group (98.19%) compared to the accentuated LNs group (55.15%, p < 0.05, t test). Accentuated LNs exhibited a false negative rate of 13.00%. False positive rates were 51.80%, 30.26% and 8.82%, respectively. Diagnostic accuracy for detecting LNMs in level IIa and IIb exceeded that of level III. Patients with solely accentuated LNs were more likely to have a small, well-differentiated tumor. However, no distinctions emerged in terms of the occurrence of T4 tumors among the three groups. Conclusion: CT proves sufficient to predict LNMs in patients with OSCC. Looking ahead, the potential integration of artificial intelligence and deep learning holds promise to further enhance the reliability of CT in LNMs detection. However, this prospect necessitates further investigation.",14321335,ONCOLOGY
10.3390/educsci13111076,Attitude Construction toward Invasive Species through an Eco-Humanist Approach: A Case Study of the Lesser Kestrel and the Myna,"The green school in northern Israel has embraced an eco-humanist approach with the aim of mitigating the animosity displayed by fifth-grade students towards invasive species. This antipathy arose due to the negative impact of these invasive species on a local species that the students were monitoring as a component of their environmental education curriculum. Therefore, the purpose of this study was to examine to what extent, if at all, there is a difference in the ethical attitude of the 188 fifth-grade students (10–11 years old) towards the conflict between the Lesser Kestrel (local species) and the Myna (invader species) and the solution to this conflict following the change to an eco-humanist teaching approach. The study, based on content analysis methodology of written self-reflection, and thematic analysis indicated that the fifth-graders’ knowledge was not adversely affected, but the solutions they proposed for resolving the conflict between the Myna and the Lesser Kestrel were more holistic, ethical, and moral after adopting the eco-humanist approach. Eco-humanism encourages an ethical attitude and environmental responsibility toward nature’s fate, including invasive species.",22277102,EDUCATION
10.3390/ejihpe13110164,"Motivational Influences on Health, Well-Being, and Lifestyle: Validation of the Spanish Version of the Treatment Self-Regulation Questionnaire in Four Health Domains","Background: Motivation is a central concept in self-determination theory (SDT). The Treatment Self-Regulation Questionnaire (TSRQ), which assesses motivation (autonomous, controlled, etc.), has been widely used. However, less is known about its applicability to samples such as college students, who may be at risk of having unhealthy behavior in many areas (including smoking, poor dietary habits, alcohol, or tobacco consumption). As this population is transitioning to adulthood, research is needed to understand motivation and changing health patterns. In addition, the lack of instruments for this population in Spain has made the measurement validation process a priority. The purpose of this psychometric study was to adapt the TSRQ to Spanish college students and to examine its structural and validity across four health domains. Methods: Two samples of Spanish college students (n = 347 and n = 244) agreed to participate in the study. Participants completed a booklet containing measures of motivation, well-being, general health, anxiety, depression, and lifestyle. Results: CFA supported a five-dimensional structure in each domain. Reliability values were also adequate for each questionnaire. Regarding other sources of validity, statistically significant relationships between self-determination, health, and well-being were clearly confirmed, and autonomy was a significant predictor of lifestyle. Conclusions: The Spanish version of the TSRQ showed adequate psychometric properties (dimensionality and internal structure, reliability, and validity evidence regarding its relationships with other constructs) in college students. The Spanish TSRQ will provide future research aimed to understand the motivational role in college students’ health behavior and well-being.",22549625,PSYCHOLOGY
10.1186/s40594-023-00453-4,Authentic STEM education through modelling: an international Delphi study,"Background: The literature asserts that science, technology, engineering, and mathematics (STEM) education needs to be authentic. Although models and modelling provide a basis from which to increase authenticity by bridging the STEM disciplines, the idea of authentic STEM education remains challenging to define. In response, the aim of this study is to identify consensus on significant elements of authentic STEM education through models and modelling. Views were gathered anonymously over three rounds of questions with an expert panel. Responses were subjected to a multimethod analysis that pursued identification, consensus, and stability in the panel’s revealed propositions and themes around authentic STEM education through modelling. Results: The panel reached high consensus concerning the potential of STEM education to support learning across traditional subject borders through authentic problem solving. The panel also consented that modelling is indispensable for achieving real-world relevance in STEM education, and that model-based integrated STEM education approaches provide opportunities for authentic problem solving. Furthermore, results showed that integrating individual STEM subjects during teaching, in terms of including disciplinary knowledge and skills, requires specialised competence. Here, technology and engineering subjects tended to implicitly underpin communicated teaching activities aimed at STEM integration. Conclusions and implications: The panellists stress that STEM disciplines should be taught collaboratively at the same time as they are not in favour of STEM as a subject of its own but rather as a cooperation that maintains the integrity of each individual subject. Many respondents mentioned integrated STEM projects that included modelling and engineering design, although they were not specifically labelled as engineering projects. Thus, real-world STEM education scenarios are often viewed as being primarily technology and engineering based. The panel responses also implicate a need for multiple definitions of authenticity for different educational levels because a great deal of uncertainty surrounding authenticity seems to originate from the concept implying different meanings for different STEM audiences. These international Delphi findings can potentially inform integrated STEM classroom interventions, teacher education development, educational resource and curriculum design.",21967822,EDUCATION
10.1007/s44196-023-00350-2,Hybrid Sine Cosine Algorithm with Integrated Roulette Wheel Selection and Opposition-Based Learning for Engineering Optimization Problems,"The sine cosine algorithm (SCA) is widely recognized for its efficacy in solving optimization problems, although it encounters challenges in striking a balance between exploration and exploitation. To improve these limitations, a novel model, termed the novel sine cosine algorithm (nSCA), is introduced. In this advanced model, the roulette wheel selection (RWS) mechanism and opposition-based learning (OBL) techniques are integrated to augment its global optimization capabilities. A meticulous evaluation of nSCA performance has been carried out in comparison with state-of-the-art optimization algorithms, including multi-verse optimizer (MVO), salp swarm algorithm (SSA), moth-flame optimization (MFO), grasshopper optimization algorithm (GOA), and whale optimization algorithm (WOA), in addition to the original SCA. This comparative analysis was conducted across a wide array of 23 classical test functions and 29 CEC2017 benchmark functions, thereby facilitating a comprehensive assessment. Further validation of nSCA utility has been achieved through its deployment in five distinct engineering optimization case studies. Its effectiveness and relevance in addressing real-world optimization issues have thus been emphasized. Across all conducted tests and practical applications, nSCA was found to outperform its competitors consistently, furnishing more effective solutions to both theoretical and applied optimization problems.",18756883,AI
10.3390/educsci13111085,“A Common Danger Unites”: Reflecting on Lecturers’ Higher Education Experiences during the COVID-19 Pandemic Using an Ethnographic Fictional Analysis,"The sudden transition of Higher Education (HE) from predominately face-to-face to online delivery during the COVID-19 pandemic lockdowns placed many lecturers in unfamiliar situations. This study aimed to explore and represent the experiences of lecturers working in HE during this time. We used a storytelling approach to represent an amalgamation of experiences collated from lecturers. Data were collected using (i) a focus group interview, (ii) reflections on our experiences, and (iii) experiences alluded to by academics via online blogs. The data were presented using an ethnographic fiction. Salient experiences detailed throughout the ethnographic fiction include (i) challenges building a community between colleagues, academics, and students; (ii) concerns regarding the capacity of institutions and staff to deliver online; (iii) a lack of synergy between the expectations of staff to fulfil duties and the reality of being able to do so in time; (iv) the challenges of engaging students; (v) concerns regarding the accessibility of online learning for a diverse body of students; and (vi) challenges with work–life balance. The ethnographic fiction provides a voice for HE lecturers who candidly shared their experiences of working during the pandemic. Stakeholders are encouraged to develop their own interpretations of the story and apply these to policy and practice.",22277102,EDUCATION
10.3390/educsci13111089,Conceptions of Portuguese Science Teachers on the Concept of Ecoethics,"Ecoethics is a philosophical subject that studies the moral relationship of human beings concerning the environment and its non-human components. Education for ecoethics addresses issues of how to live, how to make environmental choices, and how to think about the consequences of human activities. It is important that, firstly, the concept of ecoethics is clear to all involved, including teachers and students. Knowing that teachers’ conceptions strongly influence their practice, and since no studies with teachers in active service were found, it was considered pertinent to investigate the conceptions of Portuguese Biology and Geology teachers about the concept of ecoethics. For data collection, a questionnaire was applied at a national level, with a related open-ended question. Categories of analysis were defined a priori and then the responses were classified based on those categories. The main results show that most respondents define ecoethics as ethics applied to the environment; almost a tenth relate the concept to issues concerning the preservation of life or the quality of life. Given the influence of teachers on students’ education, a focus on teachers’ training in ecoethics is essential as a starting point for an effective approach to ecoethics issues that can contribute to solving environmental problems.",22277102,EDUCATION
10.3390/educsci13111094,"Enhancing English Acquisition: Effects of among us Game-Based Gamification on Language Competence, Motivation, Attention, and Attitude towards the English Subject","This study aimed to ascertain if there was a significant impact on the acquisition of English language competence, motivation, attention, and emotions towards English as a Second Language (ESL) after the development of gamification based on the famous Among us game with primary education students aged 7–8 years (n = 24) from a state school in Ciudad Real (Castilla-La Mancha). An experimental method with a pretest–post-test design was considered, in which the control group followed a transmission instructional model, and the experimental group underwent an eight-session gamified experience using Information and Communication Technologies (ICT). Four ad hoc tests were designed and implemented to assess writing, reading, speaking, and listening skills, while various test adaptations were used to measure attention and motivation variables. The results show that gamification helped to improve the variables analyzed, showing significant enhancements in reading from the experimental group, as well as a more positive attitude towards the English subject, increased active participation, and fewer negative inclinations towards mistakes. The study suggests that incorporating gamification can have a positive impact on learning outcomes and may serve as a means of bridging linguistic inequalities and promoting equitable access to language learning opportunities. However, further research is necessary to explore the potential of gamification in this regard.",22277102,EDUCATION
10.3390/educsci13111100,Maintaining Tensions: Braiding as an Analogy for Mathematics Teacher Educators’ Political Work,"Although the field of mathematics education has made gains in centering the need for justice-oriented approaches and antiracist teaching practices in teacher education, much of this work remains in its infancy. Moreover, research focused on this area highlights teacher candidates’ knowledge and dispositions and often ignores the role of the mathematics teacher educators facilitating the process. We contend that mathematics teacher educators must pay more attention to how intersectional identities, contexts, Mirror Tests, and principles of Rehumanizing Mathematics manifest in teacher education to better understand how teacher candidates develop political knowledge in teaching mathematics. To this end, we introduce a framework of considerations, which we call a compass, that identifies four dimensions (or strands) and offers guiding questions for mathematics teacher educators to consider. We offer examples from a multi-site research study to illuminate each dimension and build the case for the necessity of braiding the four strands together as we engage in this line of work. Implications for practice and future research are discussed.",22277102,EDUCATION
10.3390/ejihpe13110172,Does Equine Interaction Facilitate Emotional Safety and Learning for College Students within an Agricultural-Based Classroom?,"Effective teaching requires an educational environment that promotes learning, and yet, developing such an environment can be challenging within today’s agricultural-based classroom for educators due to the trend to a more virtual teaching format and less hands-on learning. Animal interaction, particularly equine activities, has been shown to assist educators in the development of an emotionally safe environment for promoting learning. However, research is lacking as to whether the interaction with the animal needs to be direct or indirect within the collegiate educational environment to observe benefits. Therefore, the objective of this study was to determine the impact of equine interaction, both direct and indirect, within an educational environment on the emotional safety and learning for the college student within the agricultural-based classroom. Three course types were observed within the agricultural-based educational environment that included courses with no equine interaction (Group A) and courses with equine interaction, both direct (Group B) and indirect (Group C) interaction with the horse. Indirect interaction included items such as observation of equine handling via a video or gaining knowledge from reading online materials, but not engaging in direct, hands-on activities with the horse. Development of emotional safety within the students enrolled within these courses was measured using a self-reporting emotional safety evaluation. Due to the structure of the scale, a decrease in emotional safety indicated a positive change. Learning, both development of semantic and procedural memory, was measured using a student-completed knowledge examination and an instructor-completed skill evaluation, respectively. While significant improvement in emotional safety was not observed within any of the course types, a weak negative correlation was found between emotional safety and semantic memory for students enrolled in equine courses, both direct (R = −0.55, R2 = 0.28) and indirect (R = −0.25, R2 = 0.06) interaction, finding as emotional safety scores lowered to the ideal range that knowledge improved. In addition, students within equine courses showed semantic memory development in specific areas of equine sciences (Group B: Grooming/Tacking, p = 0.03; Group C: Equine Behavior, p = 0.04) and direct equine interaction resulted in development of equine-based procedural memory in all four skill areas measured within the study (p = 0.00). As such, learning is promoted through equine interaction, whether direct or indirect interaction, within the agricultural-based classroom, suggesting that both forms of equine interaction can be a valuable educational tool for the instructor within the collegiate setting.",22549625,PSYCHOLOGY
10.1186/s40594-023-00455-2,Exploring the multifaceted roles of mathematics learning in predicting students' computational thinking competency,"Background: There exist shared competencies between computational thinking (CT) and mathematics, and these two domains also mutually benefit from various teaching approaches. However, the linkages between mathematics and computational thinking lack robust empirical support, particularly from student-centered learning perspectives. Our study aimed to enhance our understanding of the connections between students' mathematics learning and computational thinking. To assess students' mathematics learning, we measured their beliefs about mathematics learning and their level of mathematical literacy (ML). Our hypothesis posited that students' beliefs concerning mathematics learning, encompassing their views on the nature of mathematics and their attitude towards the subject, can both directly and indirectly influence their CT, with ML serving as a mediating factor. Our data were gathered through surveys and tests administered to eighth- and ninth-grade students. Data were analyzed using partial least squares–structural equation modeling (PLS–SEM).Results: The evaluation of the measurement model indicated strong internal consistency for each construct. Both convergent and discriminant validity were also established. Upon assessing the structural model, it was found that beliefs about the nature of mathematics positively predicted attitudes towards mathematics, and this belief also indirectly predicted ML through positive attitudes towards mathematics. In addition, ML directly and positively predicted both CT subscales. Notably, a comprehensive mediating effect of ML on beliefs about mathematics learning and CT was identified in the analysis.Conclusions: This study advances the understanding of the relationships between mathematics learning and CT. We have further confirmed the importance of mathematical literacy in predicting CT and its mediating role between beliefs about mathematics learning and CT. It is suggested that teachers could promote students’ CT competence by enhancing their mathematical literacy or integrating mathematics and CT into the same learning activities. Finally, we propose that upcoming investigations treat CT assessments as formative constructs, diverging from their reflective counterparts.",21967822,EDUCATION
10.3390/ejihpe13110177,Assessment and Psychometric Properties of the 21-Item Depression Anxiety Stress Scale (DASS-21) among Portuguese Higher Education Students during the COVID-19 Pandemic,"The COVID-19 pandemic has caused substantial disruptions in the lives of higher education students, with detrimental repercussions for academic performance and overall mental health. Therefore, we aimed to evaluate the prevalence of depression, anxiety, and stress symptoms among Portuguese higher education students during the first wave of the coronavirus pandemic and investigate DASS-21’s psychometric characteristics and whether it functions effectively during a pandemic. A convenience sampling procedure was used to recruit 1522 participants (75.1% women and 79.2% undergraduate students) for this cross-sectional research. Participants completed an e-survey created using DASS-21. The results revealed a considerable prevalence of symptoms of depression [≥10] (N = 434, 28.5%), anxiety [≥7] (N = 551, 36.2%), and stress [≥11] (N = 544, 35.7%). Confirmatory factor analysis (CFA) revealed the scale’s three-factor structure, which matched the three DASS-21 subscales. Subsequently, the heterotrait–monotrait (HTMT) correlation ratio evaluated the scale’s discriminant validity, which was relatively good. Cronbach’s alpha measured the internal consistency of the DASS subscales, which was excellent (Cronbach’s α > 0.90). DASS-21 was shown to be a reliable and appropriate measure for assessing students’ mental health. Furthermore, DASS-21 is recommended for use by academics and healthcare professionals in measuring students’ psychological distress. Further validation studies of this scale are needed with larger and more representative samples.",22549625,PSYCHOLOGY
10.1186/s40359-023-01401-1,The psychometric property of a short-form of the Social Axioms Survey (SAS II),"Background: Social Axioms are generalized beliefs and broad assumptions about the world, guiding behaviors across various social situations. Social Axioms are usually assessed by Social Axioms Survey II (SAS II). Nevertheless, the length of the scale may limit its usefulness in studies with strict time constraint. The present study aimed at developing a shorter version. Methods: A survey was conducted among 455 college students. First, we performed psychometric evaluation on the full item version of SAS II to identify items with superior psychometric properties for a brief version of SAS II. Second, we validated the psychometric properties of the brief version of SAS II. Results: A 20-item version of SAS II (SAS II-20) was developed, and it demonstrated adequate reliability and validity. The correlations between SAS II-20 and personality variables, cognitive flexibility, interpersonal trust, locus of control, and paranormal beliefs were consistent with past studies. Conclusions: SAS II-20 is psychometrically acceptable and provides a time-efficient measurement tool for investigating social beliefs.",20507283,PSYCHOLOGY
10.3390/ejihpe13110179,(No) Effects of a Self-Kindness Intervention on Self-Esteem and Visual Self-Perception: An Eye-Tracking Investigation on the Time-Course of Self-Face Viewing,"Previous research has suggested a favorable impact of self-kindness on subjective well-being. The present experiment investigated the effects of an app-assisted self-kindness intervention for increasing self-esteem and self-face gaze, and for decreasing depression. We explored self-face processing via a time-course analysis of eye-tracking data. Eighty participants (56 female, 24 male; mean age: 23.2 years) were randomly allocated to one of two intervention groups, each receiving daily instructions to enhance either self-kindness or relaxation (active control). Following a one-week intervention period, both groups reported improved self-esteem (p = .035, ηpart2 = .068) and reduced depression (p < .001, ηpart2 = .17). The duration of self-face gaze increased in both groups (p < .001, ηpart2 = .21). Self-face processing was characterized by an early automatic attention bias toward the self-face, with a subsequent reduction in self-face bias, followed in turn by an attentional self-face reapproach, and then a stable self-face bias. We thus identified a complex temporal pattern of self-face inspection, which was not specifically altered by the intervention. This research sheds light on the potential for app-assisted interventions to positively impact psychological well-being, while also highlighting the complexity of self-face processing dynamics in this context. In the future, we propose the inclusion of personalized self-kindness statements, which may amplify the benefits of these interventions.",22549625,PSYCHOLOGY
10.3390/ejihpe13110183,“I Am on Top!”: An Interactive Intervention Program to Promote Self-Regulation Processes in the Prevention of the Use of Doping in Sports High Schools,"The use of substances to improve sports performance is a widespread phenomenon among adolescents. Several anti-doping programs have been developed, mainly based on knowledge-based evidence. The main aim of the present study was to implement an anti-doping intervention in sports high school students, based on a psychological framework, such as Socio-Cognitive Theory, through the development of a Serious Game (SG), i.e., digital learning based on the game. The experimental design included an intervention group (n = 167; F = 37.7%; Meanage = 17.5 years; SD = 0.58) and a control group (n = 112; F = 42%; Meanage = 17.6; SD = 1). Both of the groups completed the same questionnaire on two different occasions (i.e., time 1 and time 2) for measuring doping intention, self-regulatory efficacy to resist social pressure for the use of substances, moral disengagement, and doping knowledge. Data were analyzed through repeated measures of Group X Time ANOVA, demonstrating some degree of efficacy of the intervention, in particular in terms of the decrease in doping intention and the strengthening of doping knowledge. Moreover, the study demonstrated that the score obtained during the implementation of the SG could partially represent a coherent measure of the participants’ beliefs regarding doping. These results could be considered a starting point for future research to better develop technological anti-doping interventions.",22549625,PSYCHOLOGY
10.1186/s40359-023-01417-7,Impulsivity and sensitivity to reward as mediating factors of the negative relationship between emotional intelligence and health-related risk-taking: evidence from a sample of university students,"Better abilities in emotional intelligence (EI) have been linked to a decreased tendency to engage in health-related risk behaviour. However, the processes underlying this relationship are still unclear. The aim of this research was to examine the role of impulsivity and sensitivity to reward as mediating factors in the relationship between EI and health risk-taking. Two hundred and fifty participants (Mage = 23.60, age range = 18–59; SD = 6.67; 71.60% women) were assessed on ability EI levels, risk-taking in health contexts, impulsivity, and sensitivity to reward. Unlike previous studies in the literature, we employed a performance-based ability measure to assess EI (Mayer-Salovey-Caruso Emotional Intelligence Test, MSCEIT). The results confirmed the negative relationship between EI and health risk-taking and revealed the existence of a significant negative indirect effect of EI on health-risk taking through various dimensions of impulsivity and sensitivity to reward. EI abilities —particularly the ability to manage emotions— were associated with lower levels of impulsivity under positive and negative emotional states, a better management of the tendency towards sensation seeking, and a decreased emotional reactivity to rewards. The present research provides a better understanding of the processes underlying the negative relationship between EI and health risk-taking. Our findings suggest that having higher levels of EI abilities would allow for a more objective evaluation of risk scenarios and a more appropriate and safer decision making through its influence on the levels of impulsivity and emotional reactivity to rewards. Practical implications, limitations, and future lines of research are discussed.",20507283,PSYCHOLOGY
10.1007/s00432-023-05488-2,"A case report of two instances of colorectal hepatoid adenocarcinoma, accompanied by a comprehensive literature review","Objective: The study aimed to explore the clinical and pathological characteristics, survival outcomes, and prognostic factors of colorectal hepatoid adenocarcinoma. Methods: We performed two cases of colorectal hepatoid adenocarcinoma treated at the Oncology Department of the First Affiliated Hospital of Nanchang University. We also reviewed literature up to the present and performed a retrospective study of colorectal hepatoid adenocarcinoma. Results: Among the 39 patients included in this study, 28 had primary tumors in the colon, 9 in the rectum, and 2 in the rectosigmoid junction. The median age was 52 years (range 31–75 years); 28 patients (71.8%) were male. Out of the 32 patients for whom survival data were available, 24 patients succumbed to disease-related causes. The median overall survival of 32 patients was 8 months, with 1-year and 2-year overall survival rates of 31.0% and 16.0%, respectively. Univariate analysis revealed that depth of infiltration, presence of liver metastases, TNM stage, and the completeness of surgical resection were significantly associated with the overall survival period of colorectal hepatoid adenocarcinoma. Conclusion: Colorectal hepatoid adenocarcinoma exhibits a high degree of aggressiveness and poor prognosis. The major strategy for early-stage HAC was radical surgery and chemoradiotherapy demonstrates limited efficacy for extending survival.",14321335,ONCOLOGY
10.1186/s40359-023-01360-7,Post-traumatic growth and influencing factors among parents of premature infants: a cross-sectional study,"Background: Post-traumatic growth is a positive psychological change that may aid recovery in individuals experiencing trauma. Owing to the lack of research in the area of parental care for premature infants, we decided to explore the levels and factors influencing post-traumatic growth among parents of premature infants in neonatal intensive care units. We believe that these findings will help reassess existing care practices so that healthcare providers can promptly identify negative emotions and take necessary measures to help develop the potential to enhance post-traumatic growth. Methods: A cross-sectional survey was conducted using convenience sampling between February and September 2022. Data were analysed using independent sample t-tests and one-way analysis of variance (ANOVA). Bivariate correlations were analysed using the Pearson’s or Spearman’s method, and related factors were analysed using multiple linear regression. We followed the SRQR checklist throughout the study period. Results: A total of 217 patients were effectively treated, with a recovery rate of 98.64%. Univariate analysis showed that the length of hospital stay, presence of only one child, parents’ age, marital status, education level, working status, and per capita monthly familial income were influencing factors. Bivariate analysis showed that post-traumatic growth was moderately and positively correlated with perceived social support, rumination, and family resilience. Multiple linear regression showed that purposeful contemplation, family resilience, education, family support, age, and marital status entered into the regression equation and together accounted for 47.4% of the total variation. Conclusions: It is necessary to pay attention to post-traumatic growth and familial stability in these families, provide aid in building a good support system, and encourage parents to mobilise their family and favourable factors to increase post-traumatic growth levels.",20507283,PSYCHOLOGY
10.3390/cancers15225376,"The Influence of the Exposome in the Cutaneous Squamous Cell Carcinoma, a Multicenter Case–Control Study","Introduction: The concept of exposome refers to the total of harmful and beneficial environmental exposures that can help predict the organism’s biological responses over time. Ultraviolet radiation (UVR) from sun exposure has been recognized as the main etiological agent of skin cancer, and squamous cell carcinoma (SCC) is one most commonly associated with chronic exposure. However, in recent years, evidence suggests that lifestyle, environmental pollution, and contaminants in water and food can have an influence. Objectives: To study the relationship between SCC and sun exposure, pollution, stress, and lifestyle in a Spanish cohort. Materials and Method: A multicenter case–control study was carried out in which 13 dermatologists from different regions of Spain recruited cases and controls between April 2020 and August 2022. The group of cases were patients diagnosed with SCC and, as a control group, people who attended Dermatology consultations as companions with no history of skin cancer. Results: A total of 62 patients with SCC and 126 controls were included (62.9% males, median age 76.46 (10.1) and 33.3%, median age 55.7 (15), respectively). The SCC group had experienced more outside work than the controls (75% vs. 22.4%, p < 0.001), less recreational exposure (sunbathing, p = 0.05, and outdoor sports, p = 0.01), and a lower annual income (p = 0.01), with an increase in tobacco exposure (p < 0.001), without differences in other carcinogens, such as ionizing radiation or chemical exposure. The control group had a higher daily screentime use (p < 0.001) and practiced more relaxation activities (p = 0.03). A higher linolenic acid intake and lower coffee consumption were the only dietary variables associated with SCC (p < 0.05). Some chronic medications (anxiolytics, antidepressants, beta-blockers, statins, hydrochlorothiazide, ACE inhibitors, metformin, and omeprazole) were also statistically associated with SCC. Statistical significance for all aforementioned variables was maintained in the multivariate analysis (p < 0.05). Conclusions: The study found a significant association between SCC and multiple exposome-related factors in addition to chronic sun exposure in the Spanish population. Primary prevention strategies should target specific populations, such as outdoor workers promoting sun-safe behaviors and stress-reducing activities, in addition to adequate skin photoprotection in patients under certain medications associated with SCC.",20726694,ONCOLOGY
10.1186/s40594-023-00457-0,"Motivational climate predicts effort and achievement in a large computer science course: examining differences across sexes, races/ethnicities, and academic majors","Background: The motivational climate within a course has been shown to be an important predictor of students’ engagement and course ratings. Because little is known about how students’ perceptions of the motivational climate in a computer science (CS) course vary by sex, race/ethnicity, and academic major, we investigated these questions: (1) To what extent do students’ achievement and perceptions of motivational climate, cost, ease, and effort vary by sex, race/ethnicity, or major? and (2) To what extent do the relationships between students’ achievement and perceptions of motivational climate, cost, and effort vary by sex, race/ethnicity, and major? Participants were enrolled in a large CS course at a large public university in the southeastern U.S. A survey was administered to 981 students in the course over three years. Path analyses and one-way MANOVAs and ANOVAs were conducted to examine differences between groups. Results: Students’ perceptions of empowerment, usefulness, interest, and caring were similar across sexes and races/ethnicities. However, women and Asian students reported lower success expectancies. Students in the same academic major as the course topic (i.e., CS) generally reported higher perceptions of the motivational climate than students who did not major or minor in the course topic. Final grades in the course did not vary by sex or race/ethnicity, except that the White and Asian students obtained higher grades than the Black students. Across sex, race/ethnicity, and major, students’ perceptions of the motivational climate were positively related to effort, which was positively related to achievement. Conclusions: One implication is that females, Asian students, and non-CS students may need more support, or different types of support, to help them believe that they can succeed in computer science courses. On average, these students were less confident in their abilities to succeed in the course and were more likely to report that they did not have the time needed to do well in the course. A second implication for instructors is that it may be possible to increase students’ effort and achievement by increasing students’ perceptions of the five key constructs in the MUSIC Model of Motivation: eMpowerment, Usefulness, Success, Interest, and Caring.",21967822,EDUCATION
10.3390/cancers15225408,Predictors of Neurological Worsening after Resection of Spinal Meningiomas,"Background: Due to the slow-growing nature of spinal meningiomas, they are mostly asymptomatic for a long time, and become symptomatic after the compression of the spinal cord or nerve roots. The aim of this study was to identify predictors for a poor clinical outcome after the surgical resection of spinal meningiomas and thereby to allow a preoperative identification of high-risk spinal meningiomas. Methods: Data acquisition was conducted as a single-center retrospective analysis. From 1 January 2004 to 31 December 2019, 121 patients who underwent surgical resection of a spinal meningioma were reviewed. Clinical and radiological data (such as tumor size, location, occupation ratio of the spinal canal, and the degree of spinal cord compression) were assessed. The functional clinical findings of the patients were recorded using the Karnofsky Performance Score, modified McCormick scale, and Frankel scale preoperatively, at discharge, and 3–6 months after surgery. Results: The mean patient age was 66 ± 13 years. A total of 104 (86%) patients were female and 17 (14%) were male. The thoracic spine (68%) was the most common location, followed by the cervical (29%) and lumbar (3%) spine. Preoperatively, 11.7% of patients were categorized as McCormick 1, 35.8% as 2, 39.2% as 3, 11.7% as 4, and 1.7% as 5. The neurological function of the patients with a functional deficit prior to surgery improved in 46% of the patients, remained unchanged in 52%, and worsened in 2% at discharge. At early follow-up, the proportions were 54%, 28%, and 5%, respectively. Preoperative Frankel scale was a significant predictor of a postoperative deterioration. Patients with Frankel score A to C preoperatively had a 9.2 times higher chance of clinical deterioration postoperatively (OR = 9.16). We found that the Frankel scale weakly correlated with the degree of spinal cord compression. In this study, other radiological parameters, such as the degree of cord compression and spinal canal occupation ratio, did not show a significant effect on the outcome. Conclusions: Surgery of intraspinal meningiomas can be considered safe. Neurological function improves in a large proportion of patients after surgery. However, a relevant preoperative deficit according to the Frankel scale (grade A–C) was a significant predictor of a postoperative neurological deterioration.",20726694,ONCOLOGY
10.3390/educsci13111154,College Student Mental Health and Wellbeing Prior to and during the COVID-19 Pandemic,"Student mental health was a growing concern globally prior to the onset of the COVID-19 pandemic. The aim of this study was to assess the impact of the pandemic and associated restrictions on the psychological wellbeing of college students. Baseline data were collected pre-pandemic in September 2019 among students attending a university in Northern Ireland and an Institute of Technology in the Republic of Ireland. Surveys were also conducted with this cohort during the pandemic, at the start of the academic years 2020 and 2021 (499 students fully completed all three waves). A follow-up survey was conducted at the end of their third year, in summer 2022 (n = 229). High levels of mental health problems were already present among students commencing college. The subsequent pandemic had a very negative impact on student’s academic experience and other aspects of life. Rates of depression (PHQ-9) increased significantly from the onset of the pandemic and remained high. Anxiety (GAD-7) initially decreased but then escalated at the end of college. The study highlights the importance of early intervention and makes recommendations for addressing the needs of students during times of stress. Additional supports may be required to deal with the long-lasting impact of the pandemic.",22277102,EDUCATION
10.3390/cancers15225466,Epidemiology of Neuroendocrine Neoplasms and Results of Their Treatment with [177Lu]Lu-DOTA-TATE or [177Lu]Lu-DOTA-TATE and [90Y]Y-DOTA-TATE—A Six-Year Experience in High-Reference Polish Neuroendocrine Neoplasm Center,"Neuroendocrine neoplasms (NENs) are a group of neoplasms arising from neuroendocrine cells. The worldwide incidence and prevalence of the NENs are estimated to be 6/100,000 and 35/100,000, respectively. Those numbers are increasing every decade, requiring higher and higher diagnosis and treatment costs. Radioligand therapy (RLT) using beta-emitting radioisotopes is an efficient and relatively safe method of treatment, typically used as a second-line treatment. RLT tolerability is higher than other available pharmacotherapies (chemotherapy or tyrosine kinase inhibitors). Recent studies show an increase in overall survival among patients treated with RLT. The present study aimed to learn the epidemiology of NENs in Poland and assess the effectiveness of RLT in a high-reference center. A prospective analysis of 167 patients treated with RLT in one of Poland’s highest-reference NEN centers was performed. The analysis covered 66 months of observation (1 December 2017–30 May 2023), during which 479 RLT single administrations of radioisotope were given. The standard procedure was to give four courses of [177Lu]Lu-DOTA-TATE alone, or tandem therapy—[177Lu]Lu-DOTA-TATE and [90Y]Y-DOTA-TATE. Grading analysis showed that most patients had non-functioning G2 NEN with a mean Ki-67 of 6.05% (SD ± 6.41). The most common primary tumor location was the pancreas. Over two-thirds of patients did undergo surgery due to primary tumors or distant metastases. The majority of patients were using lanreotide as a chronically injected somatostatin analog. Median progression-free survival (PFS) on somatostatin analogs was 21.0 (IQR = 29.0) months. Directly after the last course of RLT, disease stabilization was noted in 69.46% of patients, partial regression was noted in 20.36% of patients, complete regression was noted in 0.60% of patients, and progression was noted in 9.58% of patients. In long-term follow-up, the median observation time among patients who underwent four treatment cycles (n = 108) was 29.8 (IQR = 23.9) months. Stabilization of the disease was observed in 55.56% of the patients and progression was observed in 26.85% of the patients, while 17.59% of patients died. Median PFS was 29.3 (IQR 23.9), and the median OS was 34.0 months (IQR 16.0). The mean age of NEN diagnosis is the sixth decade of life. It takes almost three years from NEN diagnosis to the start of RLT. In long-term observation, RLT leads to disease stabilization in over half of the patients with progressive disease. No differences in PFS or OS depend on the radioisotope used for RLT. In Poland, organized coordination of NEN treatment in high-reference centers ensures the continuity of patient care.",20726694,ONCOLOGY
10.3390/ai4040050,Enhancing Tuta absoluta Detection on Tomato Plants: Ensemble Techniques and Deep Learning,"Early detection and efficient management practices to control Tuta absoluta (Meyrick) infestation is crucial for safeguarding tomato production yield and minimizing economic losses. This study investigates the detection of T. absoluta infestation on tomato plants using object detection models combined with ensemble techniques. Additionally, this study highlights the importance of utilizing a dataset captured in real settings in open-field and greenhouse environments to address the complexity of real-life challenges in object detection of plant health scenarios. The effectiveness of deep-learning-based models, including Faster R-CNN and RetinaNet, was evaluated in terms of detecting T. absoluta damage. The initial model evaluations revealed diminishing performance levels across various model configurations, including different backbones and heads. To enhance detection predictions and improve mean Average Precision (mAP) scores, ensemble techniques were applied such as Non-Maximum Suppression (NMS), Soft Non-Maximum Suppression (Soft NMS), Non-Maximum Weighted (NMW), and Weighted Boxes Fusion (WBF). The outcomes shown that the WBF technique significantly improved the mAP scores, resulting in a 20% improvement from 0.58 (max mAP from individual models) to 0.70. The results of this study contribute to the field of agricultural pest detection by emphasizing the potential of deep learning and ensemble techniques in improving the accuracy and reliability of object detection models.",26732688,AI
10.1007/s00432-023-05482-8,"Niosomal formulation of mefenamic acid for enhanced cancer targeting; preparation, characterization and biodistribution study using radiolabeling technique","Background: This work aimed to prepare niosomal formulations of an anticancer agent [mefenamic acid (MEF)] to enhance its cancer targeting.131I was utilized as a radiolabeling isotope to study the radio-kinetics of MEF niosomes.Methods: niosomal formulations were prepared by the ether injection method and assessed for entrapment efficiency (EE%), zeta potential (ZP), polydispersity index (PDI) and particle size (PS). MEF was labeled with131I by direct electrophilic substitution reaction through optimization of radiolabeling-related parameters. In the radio-kinetic study, the optimal131I-MEF niosomal formula was administered intravenously (I.V.) to solid tumor-bearing mice and compared to I.V.131I-MEF solution as a control.Results: the average PS and ZP values of the optimal formulation were 247.23 ± 2.32 nm and − 28.3 ± 1.21, respectively. The highest131I-MEF labeling yield was 98.7 ± 0.8%. The biodistribution study revealed that the highest tumor uptake of131I-MEF niosomal formula and131I-MEF solution at 60 min post-injection were 2.73 and 1.94% ID/g, respectively.Conclusion: MEF-loaded niosomes could be a hopeful candidate in cancer treatment due to their potent tumor uptake. Such high targeting was attributed to passive targeting of the nanosized niosomes and confirmed by radiokinetic evaluation.",14321335,ONCOLOGY
10.1007/s44196-023-00357-9,Research on the Prediction of Tire Radial Load Based on 1D CNN and BiGRU,"As an important indicator of vehicle systems, tire load is a key factor in the structural design and safety assessment of vehicles. Direct measurement methods for tire loads are expensive and complicated, while conventional load identification methods are limited by low accuracy and poor robustness. This study aimed to propose a radial load identification method for rubber-tired vehicles based on a one-dimensional convolutional neural network (1D CNN) and bidirectional gated recurrent unit (BiGRU). Considering a priori information of the radial load data of tires and based on the observability of the vehicle vibration system, the proposed method selected feature sets and then retained the effective feature subsets through feature selection to construct samples with multiple time steps as input and with a single time step as output for network training. In doing so, the load prediction results were obtained, and the theoretical model was modified by integrating prediction accuracy, generalization performance, and robustness. Compared with traditional algorithms, the proposed method could effectively reduce the error of load identification, improve adaptability under different operating conditions, and handle the measurement error of different noise levels, which are of practical application value in the engineering field.",18756883,AI
10.3390/cancers15235532,Real-World Systemic Treatment Patterns after Atezolizumab and Bevacizumab in Patients with Hepatocellular Carcinoma in the United States,"Real-world (RW) evidence is needed to evaluate atezolizumab plus bevacizumab (atezo + bev) utilization for hepatocellular carcinoma (HCC) in clinical practice. This retrospective cohort study used administrative claims databases to evaluate treatment patterns in individuals with HCC ≥18 years of age who were initiated on atezo + bev between June 2020 and June 2022. The endpoints of this study were the proportion of individuals who discontinued atezo + bev and received subsequent systemic therapies, time to discontinuation (TTD), and time to next treatment. Overall, 825 individuals were eligible (median age 67 years; 80% male). Over a median follow-up of 15.3 months, most (72%) discontinued atezo + bev, with a median TTD of 3.5 months. A minority (19%) received subsequent therapies, with the most common second-line agents being lenvatinib (6%), cabozantinib (4%), and nivolumab (4%). The median time from index to next treatment post-atezo + bev was 5.4 months. Further research is needed to identify the patients who are most likely to benefit from atezo + bev as well as later-line HCC therapies to optimize overall survival.",20726694,ONCOLOGY
10.3390/educsci13121174,Wicked from the Start: Educational Impediments to Teaching about Climate Change (and How Geography Education Can Help),"Climate change is a wicked problem, defying simple resolution. Education in various forms and at various levels has sought to improve understanding and stimulate climate change action in young people. There exists, however, a certain wickedness in education systems as well that makes climate change education difficult to enact successfully. These include an unsupportive education environment where academic standards related to climate change are missing, the lack of an inquiry-based pedagogy that can be well-suited to investigating topics like climate change with no easy answers, and ill-prepared teachers who do not fully know both the physical science and social aspects of the topic. A review of education standards in the United States and the literature on the latter two issues is used to make the argument that it is the geography classroom that can serve as the best unifying space that is most supportive of holistic and meaningful climate change education. This future is possible should we be successful in amending standards, pedagogy, and teacher preparation.",22277102,EDUCATION
10.1186/s40594-023-00458-z,STEM education institutional change projects: examining enacted approaches through the lens of the Four Categories of Change Strategies Model,"Background: Enacting STEM education reform is a complex task and there are a variety of approaches that might be selected by change agents. When working on an institutional change project to impact multiple parts of the STEM education system, teams of change agents may select multiple strategies and tactics to enact at one time and over multiple years of a project. However, the literature lacks studies which document and analyze strategies and tactics used by change project teams in a way that can be useful for other change agents. The current study seeks to fill this gap by investigating National Science Foundation-funded change initiatives at three public research universities focused on encouraging the adoption of evidenced-based instructional practices by STEM faculty in order to understand the strategies used within and across projects.Results: Qualitative framework analysis using the lens of the Henderson et al. (Journal of Research in Science Teaching 48(8): 952–984, 2011. Four Categories of Change Strategies Model showed that institutional projects enact a wide range of tactics that span the four strategies represented in the four categories of the model both across institutions and within each institution. The analysis documents a number of change tactics not previously described by the model and offers expanded definitions of the change processes that operate within each category in the context of institutional change projects.Conclusion: This descriptive work advances our understanding of the breadth and depth of actions taken by institutional change initiatives and provides insights into types of variations that might be observed based on different institutional contexts. The current analysis both affirms the value of the original model and identifies expanded ways to think about the four categories within the context of institutional change projects.",21967822,EDUCATION
10.3390/cancers15235555,"Diffuse Gliomas with FGFR3-TACC3 Fusions: Oncogenic Mechanisms, Hallmarks, and Therapeutic Perspectives","In 2012, whole-transcriptome sequencing analysis led to the discovery of recurrent fusions involving the FGFR3 and TACC3 genes as the main oncological driver in a subset of human glioblastomas. Since then, FGFR3-TACC3 fusions have been identified in several other solid cancers. Further studies dissected the oncogenic mechanisms of the fusion protein and its complex interplay with cancer cell metabolism. FGFR3-TACC3 fusion-driven gliomas emerged as a defined subgroup with specific clinical, histological, and molecular features. Several FGFR inhibitors were tested in FGFR3-TACC3 fusion-positive gliomas and proved some efficacy, although inferior to the results seen in other FGFR3-TACC3 fusion-driven cancers. In this review, we summarize and discuss the state-of-the-art knowledge resulting from a 10-year research effort in the field, its clinical implications for glioma patients, the potential reasons for targeted therapy failures, and the perspective of emerging treatments.",20726694,ONCOLOGY
10.1007/s44196-023-00360-0,RETRACTED ARTICLE: Dual Siamese Anchor Points Adaptive Tracker with Transformer for RGBT Tracking,"Due to environmental conditions, such as rainy days, foggy days, and dim lighting, objects in visible light images are not prominently displayed, leading to an easy loss of targets during tracking. In recent years, many RGB visible light trackers have achieved significant success in addressing visual tracking challenges. However, these trackers perform poorly when tracking targets under special conditions, such as occlusions and low-light scenarios. In contrast, objects in thermal infrared images are more distinct in poor lighting conditions. Given this characteristic, researchers have shown increased interest in the development of trackers that combine thermal infrared and visible light imagery. However, some mainstream RGBT (red–green–blue and thermal) algorithms, such as MANET and ADNET, are based on the anchor-based theory, requiring consideration of anchor box sizes and introducing a substantial number of hyperparameters. This can lead to suboptimal performance when tracking dynamically changing targets. Moreover, these models rely on convolutional neural networks for feature extraction, which have limitations in capturing global features. In this paper, we introduce a novel training network model called DAPAT, which combines the anchor-free concept with Transformer theory. DAPAT differs from previous models in several ways. Specifically, we have designed a straightforward model to extract precise global features from template and search images. We have also incorporated two enhancement modules into the model to improve template and search images of different sizes while suppressing the impact of non-target images. We employ a dual-stream feature fusion network to reduce the loss of image feature information due to feature correlation operations. Finally, we compare the performance of the tracking model proposed in this paper with some advanced RGBT trackers on three data sets (RGBT234, RGBT210, and GTOT). The test results demonstrate that our tracker exhibits improvements in robustness and success rate, among other performance aspects.",18756883,AI
10.3390/cancers15235584,Treatment and Outcomes of Radiation-Induced Soft Tissue Sarcomas of the Extremities and Trunk—A Systematic Review of the Literature,"Introduction: Radiation-induced soft tissue sarcomas (RISs) are rare secondary malignancies with a dire prognosis. The literature on the management of these tumors remains scarce due to their low incidence. Our systematic review sought to assess the treatment alternatives and outcomes of patients with RIS. Methods: A systematic review was conducted following the PRISMA guidelines. Our study was registered in PROSPERO (ID: CRD42023438415). Quality assessment was performed using the STROBE checklist. Weighted means for both continuous and categorical values were calculated. Results: Twenty-one studies comprising 1371 patients with RIS were included. The mean latency period from radiation to RIS diagnosis was 14 years, and the mean radiation dose delivered to the primary malignancy was 29.2 Gy. The most common histological type was undifferentiated pleomorphic sarcoma (42.2%), and 64% of all tumors were high-grade. The trunk was the most common location (59%), followed by extremities (21%) and pelvis (11%). Surgery was performed in 68% of patients and, among those with an appendicular tumor, the majority (74%) underwent limb-salvage surgery. Negative margins were attained in 58% of patients. Chemotherapy and radiotherapy were administered in 29% and 15% of patients, respectively. The mean 5-year overall survival was 45%, and the local recurrence and metastasis rates were 39% and 27%, respectively. Conclusions: In our study, the most common treatment was surgical resection, with RT and chemotherapy being administered in less than one third of patients. Patients with RIS exhibited poor oncologic outcomes. Future studies should compare RIS with de novo STS while controlling for confounders.",20726694,ONCOLOGY
10.3390/educsci13121189,Successful School Leadership in New Zealand: A Scoping Review,"This article examines the available evidence on what it means to be a successful school leader within the current educational landscape in Aotearoa, New Zealand. It provides a nuanced understanding of common success factors and the contribution of the school principal’s leadership to that success in context. A set of factors that shaped their behaviour and actions is presented that draws attention to cultural relationships and contextual awareness, emphasising not only students’ academic success, but also students’ cultures as vehicles for learning and social change. Findings from this article provide insights into how successful school leaders consider their entire school as a complex system with interconnected parts and build social infrastructures that nurture partnerships with multiple stakeholders.",22277102,EDUCATION
10.3390/ejihpe13120191,"Nomophobia and Its Association with Depression, Anxiety and Stress (DASS Scale), among Young Adults in Greece","Smartphones with their numerous applications have become essential daily equipment, prompting scientific research to deal with the impact of their use on psychosocial health. Under this spectrum, the aim of the present cross-sectional study was to examine the association between nomophobia and the negative emotional states of depression, anxiety, and stress, in relation to self-esteem and sociodemographic data, among the young adult population. The study sample consisted of 1408 young adults aged 18–25 years, participating on a voluntary basis with an online anonymous questionnaire. Data were collected through the “Nomophobia Questionnaire (NMP-Q)”, “Depression Anxiety Stress Scales—short form (DASS-21)”, and Rosenberg Self-Esteem Scale (RSES). The questionnaire also included socio-demographic characteristics and smartphone use variables. Data analysis showed that women were identified with severe depression and stress to a greater extent than men (63.3% vs. 55.1% for depression and 18.1% vs. 13.8% for stress scale). With respect to nomophobia, participants with severe levels of nomophobia also exhibited severe levels of negative emotional states in all DASS components, i.e., 40.6% in depression, 73.7% in anxiety, and 32.7% in stress (all p values < 0.001). Participants with severe levels of depression and anxiety were very often checking their phone and used it in all daily activities. Moreover, correlation analysis revealed that self-esteem had a moderating effect on the relationship between nomophobia and DASS, a fact that modifies the association between the involved variables: stronger relationships appeared between nomophobia and DASS components in individuals with normal/high self-esteem than in individuals with low self-esteem.",22549625,PSYCHOLOGY
10.1007/s00432-023-05505-4,SNP array genomic analysis of matched pairs of brain and liver metastases in primary colorectal cancer,"Purpose Brain metastasis formation is a rare and late event in colorectal cancer (CRC) patients and associated with poor survival. In contrast to other metastatic sites, the knowledge on chromosomal aberrations in brain metastases is very limited. Methods Therefore, we carried out single nucleotide polymorphism (SNP) array analyses on matched primary CRC and brain metastases of four patients as well as on liver metastases of three patients. Results Brain metastases showed more chromosomal aberrations than primary tumors or liver metastases. Commonly occurring aberrations were gain of 8q11.1-q24.3 (primary CRC), gain of 13q12.13-q12.3 (liver metastases), and gain of 20q11.1-q13.33 (brain metastases). Furthermore, we found one copy-neutral loss of heterozygosity (cn-LOH) region on chromosome 3 in primary CRC, three cn-LOH regions in liver metastases and 23 cn-LOH regions in brain metastases, comprising 26 previously undescribed sites. Conclusion The more frequent occurrence of cn-LOHs and subsequently affected genes in brain metastases shed light on the pathophysiology of brain metastasis formation. Further pairwise genetic analyses between primary tumors and their metastases will help to define the role of affected genes in cn-LOH regions.",14321335,ONCOLOGY
10.3389/feduc.2023.1279921,Models of classroom assessment for course-based research experiences,"Course-based research pedagogy involves positioning students as contributors to authentic research projects as part of an engaging educational experience that promotes their learning and persistence in science. To develop a model for assessing and grading students engaged in this type of learning experience, the assessment aims and practices of a community of experienced course-based research instructors were collected and analyzed. This approach defines four aims of course-based research assessment—(1) Assessing Laboratory Work and Scientific Thinking; (2) Evaluating Mastery of Concepts, Quantitative Thinking and Skills; (3) Appraising Forms of Scientific Communication; and (4) Metacognition of Learning—along with a set of practices for each aim. These aims and practices of assessment were then integrated with previously developed models of course-based research instruction to reveal an assessment program in which instructors provide extensive feedback to support productive student engagement in research while grading those aspects of research that are necessary for the student to succeed. Assessment conducted in this way delicately balances the need to facilitate students’ ongoing research with the requirement of a final grade without undercutting the important aims of a CRE education.",2504284X,EDUCATION
10.3390/cancers15235646,Towards Cancer Nanoradiopharmaceuticals—Radioisotope Nanocarrier System for Prostate Cancer Theranostics Based on Radiation-Synthesized Polymer Nanogels,"Despite the tremendous development of oncology, prostate cancer remains a debilitating malignancy. One of the most promising approaches to addressing this issue is to exploit the advancements of nanomedicine in combination with well-established nuclear medicine and radiotherapy. Following this idea, we have developed a radioisotope nanocarrier platform of electron-beam-synthesized nanogels based on poly(acrylic acid). We have developed a functionalization protocol, showing the very high (>97%) efficiency of the conjugation in targeting a ligand–bombesin derivative. This engineered peptide can bind gastrin-releasing peptide receptors overexpressed in prostate cancer cells; moreover, it bears a radioisotope-chelating moiety. Our nanoplatform exhibits very promising performance in vitro; the radiolabeled nanocarriers maintained high radiochemical purity of >90% in both the labeling buffer and human serum for up to 14 days. The application of the targeted nanocarrier allowed also effective and specific uptake in PC-3 prostate cancer cells, up to almost 30% after 4 h, which is a statistically significant improvement in comparison to carrier-free radiolabeled peptides. Although our system requires further studies for more promising results in vivo, our study represents a vital advancement in radionanomedicine—one of many steps that will lead to effective therapy for castration-resistant prostate cancer.",20726694,ONCOLOGY
10.3390/educsci13121203,Closing the Gap: Automated Distractor Generation in Japanese Language Testing,"Recent advances in natural language processing have increased interest in automatic question generation, particularly in education (e.g., math, biology, law, medicine, and languages) due to its efficiency in assessing comprehension. Specifically, multiple-choice questions have become popular, especially in standardized language proficiency tests. However, manually creating high-quality tests is time-consuming and challenging. Distractor generation, a critical aspect of multiple-choice question creation, is often overlooked, yet it plays a crucial role in test quality. Generating appropriate distractors requires ensuring they are incorrect but related to the correct answer (semantically or contextually), are grammatically correct, and of similar length to the target word. While various languages have seen research in automatic distractor generation, Japanese has received limited attention. This paper addresses this gap by automatically generating cloze tests, including distractors, for Japanese language proficiency tests, evaluating the generated questions’ quality, difficulty, and preferred distractor types, and comparing them to human-made questions through automatic and manual evaluations.",22277102,EDUCATION
10.1007/s44196-023-00372-w,Group-Fusion One-Dimensional Convolutional Neural Network for Ballistic Target High-Resolution Range Profile Recognition with Layer-Wise Auxiliary Classifiers,"Ballistic missile defense systems require accurate target recognition technology. Effective feature extraction is crucial for this purpose. The deep convolutional neural network (CNN) has proven to be an effective method for recognizing high-resolution range profiles (HRRPs) of ballistic targets. It excels in perceiving local features and extracting robust features. However, the standard CNN's fully connected manner results in high computational complexity, which is unsuitable for deployment in real-time missile defense systems with stringent performance requirements. To address the issue of computational complexity in HRRP recognition based on the standard one-dimensional CNN (1DCNN), we propose a lightweight network called group-fusion 1DCNN with layer-wise auxiliary classifiers (GFAC-1DCNN). GFAC-1DCNN employs group convolution (G-Conv) instead of standard convolution to effectively reduce model complexity. Simply using G-Conv, however, may decrease model recognition accuracy due to the lack of information flow between feature maps generated by each G-Conv. To overcome this limitation, we introduce a linear fusion layer to combine the output features of G-Convs, thereby improving recognition accuracy. Additionally, besides the main classifier at the deepest layer, we construct layer-wise auxiliary classifiers for different hierarchical features. The results from all classifiers are then fused for comprehensive target recognition. Extensive experiments demonstrate that GFAC-1DCNN with such simple and effective techniques achieves higher overall testing accuracy than state-of-the-art ballistic target HRRP recognition models, while significantly reducing model complexity. It also exhibits a higher recall rate for warhead recognition compared to other methods. Based on these compelling results, we believe this work is valuable in reducing workload and enhancing missile interception rates in missile defense systems.",18756883,AI
10.3390/ejihpe13120200,Prevention of Work Absence Due to Back Pain: A Network Meta-Analysis,"This paper reviewed the most effective strategies for preventing work absence due to back pain (BP) and BP episodes (the number of people reporting back pain). We searched randomized controlled trials (RCTs) of prevention strategies for BP from previous meta-analyses, PubMed, CENTRAL, and Embase and conducted a network meta-analysis. Thirteen RCTs (2033 participants) were included. Low- to high-quality evidence showed that exercise combined with ergonomics, education, back belts, and education combined with ergonomics did not prevent sickness absenteeism or BP episodes. There was moderate-quality evidence that exercise, especially resistance exercise, was the best prevention strategy to reduce the number of people reporting absenteeism due to BP (risk ratio [RR] = 0.10; 95% CI: 0.01 to 0.69). Moderate-quality evidence suggested that resistance and stretching exercises combined with education was the best prevention strategy to reduce pain (RR = 0.80; 95% CI: 0.67 to 0.96) and the number of absenteeism days for BP (standardized mean difference [SMD] = −0.39; 95% CI: −0.77 to −0.02). In conclusion, exercise, especially resistance and stretching exercises, and exercise combined with education were ranked as the best interventions to prevent sickness absenteeism and BP episodes.",22549625,PSYCHOLOGY
10.3390/cancers15245790,Therapeutic Targeting of Glioblastoma and the Interactions with Its Microenvironment,"Glioblastoma (GBM) is the most common primary malignant brain tumour, and it confers a dismal prognosis despite intensive multimodal treatments. Whilst historically, research has focussed on the evolution of GBM tumour cells themselves, there is growing recognition of the importance of studying the tumour microenvironment (TME). Improved characterisation of the interaction between GBM cells and the TME has led to a better understanding of therapeutic resistance and the identification of potential targets to block these escape mechanisms. This review describes the network of cells within the TME and proposes treatment strategies for simultaneously targeting GBM cells, the surrounding immune cells, and the crosstalk between them.",20726694,ONCOLOGY
10.1186/s40359-023-01466-y,Mental health professionals’ perspectives on the relevance of religion and spirituality to mental health care,"Background: A large body of evidence indicates that spiritual and religious backgrounds, beliefs, and practices (SRBBPs) are related to better psychological health. Spirituality and religion (R/S) are also important aspects of multicultural diversity. There is evidence that clients would like to talk about their spirituality, and that including it in assessment and treatment planning can be beneficial. However, the extent to which practicing mental health professionals view SRBBPs as relevant to mental health and clinical practice is unclear. Methods: A survey examining several aspects of addressing SRBBPs in clinical practice was distributed to 894 professionals across mental health disciplines, including psychiatry, psychology, social work, marriage family therapy, licensed professional counselors, certified chemical dependency counselors, and psychiatric mental health nurses. Results: 89% of mental health professionals agreed that clinicians should receive training in R/S competencies. There were no differences between mental health disciplines in ratings of importance of such training. Younger individuals and those who identify as more spiritual were more likely to consider R/S training as important. Although 47.1% of professionals had not received much R/S training, many perceived themselves to be highly competent in R/S clinical integration practices (57.8% considered themselves able to display them very much or completely). In addition, respondents with more R/S training evaluated themselves as more proficient in R/S clinical integration. Nearly two-thirds (65.2%) of respondents reported encountering few to no barriers to engaging in R/S competent mental health care. Conclusions: There is a growing consensus among mental health care professionals that mental health professionals should be trained in R/S competencies. Strong agreement exists that basic R/S competencies include respect, empathy, examination of bias, and routine assessment of R/S in mental health care. Four in five of those surveyed agree that more active competencies, such as identifying and addressing religious and spiritual struggles and problems and helping clients explore and access R/S strengths and resources should be included, whereas one in five report less comfort with these competencies.",20507283,PSYCHOLOGY
10.3390/ai5010001,A Time Window Analysis for Time-Critical Decision Systems with Applications on Sports Climbing,"Human monitoring systems are already utilized in various fields like assisted living, healthcare or sport and fitness. They are able to support in everyday life or act as a pre-warning system. We developed a system to monitor the ascent of a sport climber. It is integrated in a belay device. This paper presents the first time series analysis regarding the fall of a climber utilizing such a system. A Convolutional Neural Network handles the feature engineering part of the sensor information as well as the classification of the task at hand. In this way, the time is implicitly considered by the network. An analysis regarding the size of the time window was carried out with a focus on exploring the respective results. The neural network models were then tested against an already-existing principle based on a mechanical mechanism. We show that the size of the time window is a decisive factor in a time critical system. Depending on the size of the window, the mechanical principle was able to outperform the neural network. Nevertheless, most of our models outperformed the basic principle and returned promising results in predicting the fall of a climber within up to 91.8 ms.",26732688,AI
10.3390/ai5010002,A Time Series Approach to Smart City Transformation: The Problem of Air Pollution in Brescia,"Air pollution is a paramount issue, influenced by a combination of natural and anthropogenic sources, various diffusion modes, and profound repercussions for the environment and human health. Herein, the power of time series data becomes evident, as it proves indispensable for capturing pollutant concentrations over time. These data unveil critical insights, including trends, seasonal and cyclical patterns, and the crucial property of stationarity. Brescia, a town located in Northern Italy, faces the pressing challenge of air pollution. To enhance its status as a smart city and address this concern effectively, statistical methods employed in time series analysis play a pivotal role. This article is dedicated to examining how ARIMA and LSTM models can empower Brescia as a smart city by fitting and forecasting specific pollution forms. These models have established themselves as effective tools for predicting future pollution levels. Notably, the intricate nature of the phenomena becomes apparent through the high variability of particulate matter. Even during extraordinary events like the COVID-19 lockdown, where substantial reductions in emissions were observed, the analysis revealed that this reduction did not proportionally decrease PM2.5 and PM10 concentrations. This underscores the complex nature of the issue and the need for advanced data-driven solutions to make Brescia a truly smart city.",26732688,AI
10.3390/cancers16010027,Overexpression of Growth Differentiation Factor 15 in Glioblastoma Stem Cells Promotes Their Radioresistance,"GSCs play an important role in GBM recurrence. Understanding the resistance mechanisms in these cells is therefore crucial for radiation therapy optimization. In this study, using patient-derived GSCs, we demonstrate that GDF15, a cytokine belonging to the TGF-β superfamily, is regulated by irradiation (IR) and the transcription factor WWTR1/TAZ. Blocking WWTR1/TAZ using specific siRNAs significantly reduces GDF15 basal expression and reverses the upregulation of this cytokine induced by IR. Furthermore, we demonstrate that GDF15 plays an important role in GSC radioresistance. Targeting GDF15 expression by siRNA in GSCs expressing high levels of GDF15 sensitizes the cells to IR. In addition, we also found that GDF15 expression is critical for GSC spheroid formation, as GDF15 knockdown significantly reduces the number of GSC neurospheres. This study suggests that GDF15 targeting in combination with radiotherapy may be a feasible approach in patients with GBM.",20726694,ONCOLOGY
10.3390/ejihpe14010002,"Preschool Teachers’ Cognitions, Emotions, and Tolerance toward Children’s Hypothetical Social Behaviors in the Classroom","Teachers’ tolerance toward children’s social behaviors is, in part, guided by teachers’ cognitions and emotions. Few studies have examined the associations between teachers’ cognitions, emotions, and tolerance toward children’s social behaviors. This study aimed to (1) describe the cognitions, emotions, and tolerance of Portuguese preschool teachers toward children’s shy, physically and relationally aggressive, rough-and-tumble play, exuberant, and unsociable behaviors at preschool, depending on children’s sex; and (2) examine the direct and indirect associations (via teachers’ emotions) between teachers’ cognitions and tolerance toward children’s social behaviors, depending on children’s sex. One hundred and seven preschool teachers completed the Child Behaviors Vignettes. Preschool teachers displayed more negative views toward children’s physical and relational aggression, reported positive perspectives toward children’s rough play and mixed attitudes toward children’s exuberance, and differentiated shy from unsociable behaviors. Direct associations between teachers’ cognitions and tolerance were found only for physical aggression. Teachers’ anticipation of negative peer costs and academic performance appear to exert an indirect influence on teachers’ tolerance toward physical aggression and unsociability, via increased levels of worry. These findings highlight the role of teachers’ emotions for tolerance toward children’s social behaviors and the need to enhance their self-awareness.",22549625,PSYCHOLOGY
10.3390/educsci14010006,Embedding Civil Engineering Understanding through the Use of Interactive Virtual Reality,"Recent skills surveys of engineering graduates have highlighted a deficit in critical thinking among graduates. A possible solution to this is to increase the number of hands-on exercises in the curriculum. This could be carried out through the integration of 3D learning tools, specifically a virtual reality (VR) program, to effectively teach civil engineering practical studies and allow repeatable and measurable exercises for students. This study aims to assess the suitability of the VR program as an additional resource alongside existing learning exercises or a substitute for hands-on experiments when needed. The methodology involved creating a VR program, compatible with VR headsets to replicate an engineering experiment, namely the loading of a concrete beam to observe its failure. Students’ understanding of the virtual experiment was evaluated through end-of-experiment questions. The findings indicate that the VR learning tool was successful in enhancing students’ understanding of the civil engineering experiment. The immersive and interactive nature of VR contributed to a solid grasp of the concepts presented, proving its potential as a valuable educational resource. By leveraging VR technology, educational institutions can provide an engaging and effective alternative to traditional laboratory sessions, ensuring uninterrupted and high-quality learning experiences for civil engineering students.",22277102,EDUCATION
10.1007/s44196-023-00374-8,Convolution Neural Network Bidirectional Long Short-Term Memory for Heartbeat Arrhythmia Classification,"Arrhythmia is a heart condition that poses a severe threat to life and requires prompt medical attention. One of the challenges in detecting arrhythmias accurately is that incorrect diagnoses can have severe consequences. In light of this, it is critical to develop a solution that is both effective and reliable. In this study, we propose a residual Convolution Neural Network Bidirectional Long Short-Term Memory (DeepResidualBiLSTM) model for classifying Arrhythmia types, which addresses the vanishing gradient problem and captures the relevant features in the signals’ long dependencies. The model is characterized by its simplicity, stability, and ability to extract meaningful features effectively. Using two well-known datasets, the experimental results demonstrate exceptional accuracy, precision, and recall values of approximately 99.4% at the early stage of 20 epoch training. Furthermore, the model demonstrates a remarkable ability to discriminate between Arrhythmia classes under varying thresholds using the ROC curve metric, with a high value, in most cases, of 100% for accurately detecting positive cases.",18756883,AI
10.1007/s44196-023-00376-6,Semantic Adversarial Attacks on Face Recognition Through Significant Attributes,"Face recognition systems are susceptible to adversarial attacks, where adversarial facial images are generated without awareness of the intrinsic attributes of the images in existing works. They change only a single attribute indiscriminately. To this end, we propose a new Semantic Adversarial Attack using StarGAN (SAA-StarGAN), which manipulates the facial attributes that are significant for each image. Specifically, we apply the cosine similarity or probability score to predict the most significant attributes. In the probability score method, we train the face verification model to perform an attribute prediction task to get a class probability score for each attribute. Then, we calculate the degree of change in the probability value in an image before and after altering the attribute. Therefore, we perform the prediction process and then alter either one or more of the most significant facial attributes under white-box or black-box settings. Experimental results illustrate that SAA-StarGAN outperforms transformation-based, gradient-based, stealthy-based, and patch-based attacks under impersonation and dodging attacks. Besides, our method achieves high attack success rates on various models in the black-box setting. In the end, the experiments confirm that the prediction of the most important attributes significantly impacts the success of adversarial attacks in both white-box and black-box settings and could improve the transferability of the generated adversarial examples.",18756883,AI
10.3390/ejihpe14010004,The Individual Work Performance Questionnaire: Psychometric Properties of the Italian Version,"Individual work performance can be defined as individual behaviour capable of generating value and a competitive advantage for the organization. Furthermore, this construct is linked to other fundamental variables that constitute worker well-being, such as job satisfaction and engagement. Although important, a complete measure of individual work performance is still lacking in the Italian context. The objective of this work is to validate the Individual Work Performance Questionnaire (IWPQ) within the Italian organisational context. The IWPQ is a multi-dimensional construct consisting of task performance, contextual performance, and counterproductive work behavior. To investigate the psychometric properties of the Italian IWPQ, 1053 participants were enrolled, whose ages ranged between 19 and 69 years. EFA, CFA, and MCFA analyses were performed to test the structural factors of the IWPQ. The results supported the validity of the IWPQ in the Italian context; the final structure consisted of 17 items. Multigroup confirmatory factor analysis showed that the factor solution was invariant across both gender and occupational categories and found evidence of metric, uniqueness, scalar, and structural invariance. Convergent validity was also tested and demonstrated. Adequate studies on the importance of individual performance can be used to better understand and distinguish the different components affecting performance.",22549625,PSYCHOLOGY
10.3390/ejihpe14010006,"Physical Activity Time, Alcohol Consumption, Mediterranean Diet, and Anxiety in Education Science Students","Student lifestyles change during university. This research aimed to classify university students according to their levels of physical activity, alcohol consumption, adherence to the Mediterranean diet, and anxiety and studied the relationships between the variables using a multigroup equation model according to gender. The sample was composed of 549 participants (M = 23.06; S.D. = 6.22), of whom 409 were women and 140 were men. Validated and adapted instruments such as the Beck Anxiety Inventory, the PREDIMED Questionnaire, and the Alcohol Use Disorder Identification Test were used. The data revealed four clusters through Ward’s method and the k-means method. Regarding the exploratory model, differences were found in the effects of the variables according to sex. In conclusion, alcohol consumption was positively associated with the Mediterranean diet, and physical activity was negatively associated with the Mediterranean diet and anxiety.",22549625,PSYCHOLOGY
10.3390/educsci14010028,Learning about the Coexistence between Nature and Humans in Elementary Science Education: Developing Lessons Using Folktales That Reflect Ancestors’ Views on Nature,"Understanding the coexistence between nature and humans is a basic concept required in modern society. In this study, we verify the effectiveness of folktales as teaching material in science education by incorporating folktales into the fifth-grade elementary school science unit, “Functions of Running Water and Changes in the Land”. We investigate the effects of folktales that express ancestors’ perspectives on nature on pupils’ ideas about the coexistence between nature and humans. Additionally, we explore the possibility of using folktales in science education. In November 2017, an experimental group (74 participants) explored the coexistence between nature and humans through folktales, while a control group (60 participants) explored this coexistence through discussion activities. These experiments were conducted in fifth-grade classrooms at elementary schools in Hiroshima Prefecture, western Japan. Our results indicate that for some pupils in the experimental group, exposure to their ancestors’ views of nature helped them develop and refine their ideas about their connection to and relationship with the river. Folktales vividly depict the nature of the past in the places where the pupils live, offering a glimpse into their ancestors’ different views on nature that differ from present-day views. It is considered that, by coming into contact with the folktale, pupils were able to enter a situation that transcended time, allowing them to think about and empathize with the people who lived with the river. It is suggested that this connection is related to the results described above.",22277102,EDUCATION
10.3390/cancers16010125,SIRT1 Promotes Cisplatin Resistance in Bladder Cancer via Beclin1 Deacetylation-Mediated Autophagy,"Autophagy-dependent cisplatin resistance poses a challenge in bladder cancer treatment. SIRT1, a protein deacetylase, is involved in autophagy regulation. However, the precise mechanism through which SIRT1 mediates cisplatin resistance in bladder cancer via autophagy remains unclear. In this study, we developed a cisplatin-resistant T24/DDP cell line to investigate this mechanism. The apoptosis rate and cell viability were assessed using flow cytometry and the CCK8 method. The expression levels of the relevant RNA and protein were determined using RT-qPCR and a Western blot analysis, respectively. Immunoprecipitation was utilized to validate the interaction between SIRT1 and Beclin1, as well as to determine the acetylation level of Beclin1. The findings indicated the successful construction of the T24/DDP cell line, which exhibited autophagy-dependent cisplatin resistance. Inhibiting autophagy significantly reduced the drug resistance index of these cells. The T24/DDP cell line showed a high SIRT1 expression level. The overexpression of SIRT1 activated autophagy, thereby further promoting cisplatin resistance in the T24/DDP cell line. Conversely, inhibiting autophagy counteracted the cisplatin-resistance-promoting effects of SIRT1. Silencing SIRT1 led to increased acetylation of Beclin1, the inhibition of autophagy, and a reduction in the cisplatin resistance of the T24/DDP cell line. Introducing a double mutation (lysine 430 and 437 to arginine, 2KR) in Beclin-1 inhibited acetylation and activated autophagy, effectively reversing the decreased cisplatin resistance resulting from SIRT1 silencing. In summary, our study elucidated that SIRT1 promotes cisplatin resistance in human bladder cancer T24 cells through Beclin1-deacetylation-mediated autophagy activation. These findings suggest a potential new strategy for reversing cisplatin resistance in bladder cancer.",20726694,ONCOLOGY
10.3390/ejihpe14010007,Big Five Personality Traits and Compulsive Buying: The Mediating Role of Self-Esteem,"The inter-relationships between the Big Five personality traits, self-esteem, and compulsive buying are supported by strong empirical evidence. What is yet unknown is to what extent self-esteem can channel the influence of personality traits on compulsive buying. The main objective of this study is to explore the possible mediating role of self-esteem in the link between the Big Five personality traits and compulsive buying. Path analysis results, using a sample of 487 university students, generally confirm the suitability of the proposed model in which self-esteem mediated the effects of the Big Five personality traits (neuroticism, extraversion, agreeableness, openness to experience, and conscientiousness) on compulsive buying. Moreover, a direct effect of neuroticism and conscientiousness on compulsive buying was found. Finally, based on the finding that self-esteem acts as a necessary filter in the analysis of the five factors–compulsive buying relationship, several action-oriented guidelines for the prevention or intervention of this behavioral problem are suggested.",22549625,PSYCHOLOGY
10.3390/educsci14010058,"Grief (Work) Is Heart (Work): A Critical Race Feminista Epistolary Exchange as an Offering on Death, Grief, and Well-Being to Academia","This article centers around my work as a critical race feminista; an academic experiencing consistent attacks on the scholarship I produce while also being a tía (aunt), an active griever, and a godmother to my eldest nephew, Solano Garcia. This is the first time that my nephew and I will have shared our most private papelitos guardados (intimate guarded papers). In this article, we respond to the paucity of Black, Indigenous, and People of Color-centered death, grief, and well-being in academia. Using a critical race feminist epistolary methodology, we document our epistolary exchanges that contain dehumanizing attempts on our bodymindspirit matrices as active grievers of color confronting the premature death of my brother, who died at the age of 37 in the summer of 2021. Unlike the ‘western’ psychotherapeutic tradition of overcoming death and grief, we stake a claim, sit with it, and affirm it as an ongoing process. We argue that recognizing and affirming death and grief is a life-making process that creates spaces for healing through our epistolary offerings. This article aims to offer BIPOC faculty, staff, students, and their families life-affirming strategies towards radical self-care, love, and intergenerational collective healing within a sociopolitical context that operates as a surveillance mechanism.",22277102,EDUCATION
10.3390/ejihpe14010010,"Family Functioning Styles and Exercise Addiction: Disengaged, Enmeshed, and Rigid Family Patterns Are Associated with Exercise Addiction","Physical exercise is a widely recommended practice for promoting health, but for some individuals, this activity can result in pathological and morbid behaviour. Therefore, the study of the factors contributing to the onset, development, and progression of exercise addiction is particularly relevant. Within this framework, the present study assessed the effect of family functioning, body image concerns, age, and gender on exercise addiction. A sample of 300 regular exercisers (Mage = 30.3 years, SD = 11.6; 69.7% females, 30.3% males) participated in the study and completed the Family Adaptability and Cohesion Evaluation Scales–IV, Body Image Concern Inventory, and Exercise Addiction Inventory. Data were analysed by implementing a series of moderated moderated-mediations. Results showed that three significant models were relevant. First, positive associations of disengaged (p < 0.05), enmeshed (p < 0.05), and rigid (p < 0.01) family functioning with exercise addiction were found. Furthermore, body image concerns mediated all these relationships, and the interaction between gender and age significantly moderated the effects of body image concerns on exercise addiction (p < 0.05). Such data may be useful for a deeper understanding of the variables associated with the development of exercise addiction, suggesting key elements on which it might be useful to focus in clinical and/or preventive activity.",22549625,PSYCHOLOGY
10.3390/ejihpe14010011,Academic Success at Social Costs: An Exploratory Study on Social Networks of Chinese Students under Academic Streaming,"In universities that require students to reside in dormitories, there are two types of social networks—study/classroom-based and social/dorm room-based. The academic streaming system may disrupt study/classroom connections, but its impact on students’ social networks is unknown. Using self-reported surveys, this study examines ego network measures of network sizes, turnover, multiplexity, and diversity among 382 students (44% female, 56% male). Surveys were administered before and after the university employed a first-semester grade-point average to demote or promote students into an honours college. Follow-up interviews were conducted with 11 honours students staying within their track and 11 students who were re-streamed to the non-honours track. Quantitative results showed that students in the non-honours college and who remained there had increasingly overlapping friendship circles between study and social environments, along with more diverse social connections, indicating stronger networks. In contrast, honours participants experienced fewer overlapping networks across domains and less dispersed social ties, especially after the academic replacement process. Qualitative results showed that the honours students faced a trade-off between academic success and social engagement in maintaining their elite status. Re-streamed students experienced otherness in social groups and decreased psychological wellbeing. This study contributes to the application of network analysis in education and provides insights into the unintended consequences of educational practice on students’ social networks.",22549625,PSYCHOLOGY
10.1186/s40359-024-01524-z,Psychometric properties of principals’ attitudes toward inclusive education (PATIE) scale: Arabic version,"Inclusive education is critical for the successful integration of students with disabilities into general education schools, and principals’ attitudes play a crucial role in this process. Despite the recognized significance of attitudes, there remains a gap in understanding these attitudes among principals in Arabic-speaking regions concerning inclusive education practices. This study aims to bridge this gap by validating and assessing the reliability of the Arabic version of the Principals’ Attitudes Toward Inclusive Education (PATIE) scale. To measure these attitudes in the Arab region, the current study validated and assessed the reliability of the Arabic version of the Principals’ Attitudes Toward Inclusive Education (PATIE) scale using a sample of 391 principals from schools that have in place inclusion programs for students with disabilities. Confirmatory factor analysis (CFA) was employed to validate the scale’s structural, discriminant, and convergent validity, while Cronbach’s alpha and composite reliability (CR) were utilized to evaluate the scale’s reliability. The results demonstrated the strong validity and reliability of the Arabic version of the PATIE, with all five factors displaying good reliability. These findings suggest that the scale can effectively measure attitudes toward inclusive education in Arabic-speaking countries. This study’s implications for research and practice are significant, as they underscore the importance of positive attitudes among principals in promoting inclusive education and provide a validated tool for measuring these attitudes.",20507283,PSYCHOLOGY
10.3390/ai5010012,Bibliometric Mining of Research Trends in Machine Learning,"We present a method, including tool support, for bibliometric mining of trends in large and dynamic research areas. The method is applied to the machine learning research area for the years 2013 to 2022. A total number of 398,782 documents from Scopus were analyzed. A taxonomy containing 26 research directions within machine learning was defined by four experts with the help of a Python program and existing taxonomies. The trends in terms of productivity, growth rate, and citations were analyzed for the research directions in the taxonomy. Our results show that the two directions, Applications and Algorithms, are the largest, and that the direction Convolutional Neural Networks is the one that grows the fastest and has the highest average number of citations per document. It also turns out that there is a clear correlation between the growth rate and the average number of citations per document, i.e., documents in fast-growing research directions have more citations. The trends for machine learning research in four geographic regions (North America, Europe, the BRICS countries, and The Rest of the World) were also analyzed. The number of documents during the time period considered is approximately the same for all regions. BRICS has the highest growth rate, and, on average, North America has the highest number of citations per document. Using our tool and method, we expect that one could perform a similar study in some other large and dynamic research area in a relatively short time.",26732688,AI
10.3390/ai5010013,"Enhancing Thermo-Acoustic Waste Heat Recovery through Machine Learning: A Comparative Analysis of Artificial Neural Network–Particle Swarm Optimization, Adaptive Neuro Fuzzy Inference System, and Artificial Neural Network Models","Waste heat recovery stands out as a promising technique for tackling both energy shortages and environmental pollution. Currently, this valuable resource, generated through processes like fuel combustion or chemical reactions, is often dissipated into the environment, despite its potential to significantly contribute to the economy. To harness this untapped potential, a traveling-wave thermo-acoustic generator has been designed and subjected to comprehensive experimental analysis. Fifty-two data corresponding to different working conditions of the system were extracted to build ANN, ANFIS, and ANN-PSO models. Evaluation of performance metrics reveals that the ANN-PSO model demonstrates the highest predictive accuracy (R2=0.9959), particularly in relation to output voltage. This research demonstrates the potential of machine learning techniques for the analysis of thermo-acoustic systems. In doing so, it is possible to obtain an insight into nonlinearities inherent to thermo-acoustic systems. This advancement empowers researchers to forecast the performance characteristics of alternative configurations with a heightened level of precision.",26732688,AI
10.1186/s40359-023-01506-7,Basic counseling skills in psychology and teaching: validation of a short version of the counselor activity self-efficacy scales,"Background: Counseling self-efficacy is a relevant measure to examine trainees’ beliefs about their counseling skills. This study aimed to validate three scales of the revised German version of the Counselor Activity Self-Efficacy Scales (CASES-R) measuring basic counseling skills. To ascertain the scales’ sensitivity to change, counseling self-efficacy was assessed before and after specific training. Method: The sample comprised 163 university students enrolled either in psychology or education. Students were examined before and after participating in training focusing on basic counseling skills. We applied confirmatory factor analysis and tested internal consistency, convergent validity, and criterion validity. Results: Confirmatory factor analysis supported the three-factor structure of the CASES-R scales for basic counseling skills. The scales provided acceptable to good internal consistency (α = 0.77 − 0.87). Significant relations with general self-efficacy (r =.23, p <.01) provided first indication for convergent validity. We also found a significant correlation of the CASES-R with positive affect (r =.22), and significant correlations of some subscales with empathetic concern (r =.16 −.21) and mastery goal orientation (r =.16), overall supporting criterion validity. The CASES-R scales proved to be sensitive to change, as participants’ scores were higher after (M = 6.18, SD = 1.05) than before (M = 5.37, SD = 1.16) counseling training (F(1, 309) = 42.27, p <.001). Conclusion: We found support for the proposed factor structure and reliability of the German version of the three CASES-R scales, indicating its suitability for use in basic counseling settings. Future research should further examine the scales’ validity.",20507283,PSYCHOLOGY
10.1186/s40359-024-01519-w,The interrelationships between Chinese learners’ trait emotional intelligence and teachers’ emotional support in learners’ engagement,"Background: One noteworthy concern within the realm of education is the level of engagement demonstrated by students. Among the factor that can have a crucial role in this domain is teacher support, especially emotional support which has an impact on several aspects of learners’ education. Furthermore, various studies have investigated the relationship between Emotional Intelligence (EI) and learners’ engagement. Methods: Accordingly, this study investigated the possible role of trait EI and the emotional support of teachers and how these constructs may work to associate learners’ engagement. For this objective, a total of 309 Chinese students across different colleges and universities in 5 provinces of Beijing, Shanghai, Jiangsu, Hubei, and Shaanxi were enrolled. They were 126 females and 183 males, with ages ranging from 18 to 30 years old (Mean = 24.6). Results: The results of this research through running Structural Equation Modeling (SEM) demonstrated that teachers’ emotional support and trait EI both can associate students’ learning engagement. The final measurement model shows that about 73% of changes in learners’ engagement can be associated by their trait EI and teachers’ emotional support. Conclusions: This study underscores the importance of emotional support from teachers and the trait of EI in relation to students’ engagement in learning. Both factors were shown to play a significant role in associating student engagement. Moreover, this study could potentially have wider impacts on members of academic teams.",20507283,PSYCHOLOGY
10.1007/s00432-023-05530-3,Efficacy and safety of first-line therapy in patients with HER2-positive advanced breast cancer: a network meta-analysis of randomized controlled trials,"Purpose: The numerous first-line treatment regimens for human epidermal growth factor receptor 2 (HER2)-positive advanced breast cancer (ABC) necessitate a comprehensive evaluation to inform clinical decision-making. We conducted a Bayesian network meta-analysis (NMA) to compare the efficacy and safety of different interventions. Methods: We systematically searched for relevant randomized controlled trials (RCTs) in Pubmed, Embase, Cochrane Library and online abstracts from inception to June 1, 2023. NMA was performed to calculate and analyze progression-free survival (PFS), overall survival (OS), objective response rate (ORR), and adverse events of grade 3 or higher (≥ 3 AEs). Results: Out of the 10,313 manuscripts retrieved, we included 28 RCTs involving 11,680 patients. Regarding PFS and ORR, the combination of trastuzumab with tyrosine kinase inhibitors (TKIs) was more favorable than dual-targeted therapy. If only using trastuzumab, combination chemotherapy is superior to monochemotherapy in terms of PFS. It is important to note that the addition of anthracycline did not result in improved PFS. For patients with hormone receptor-positive HER2-positive diseases, dual-targeted combined with endocrine therapy showed better benefit in terms of PFS compared to dual-targeted alone, but it did not reach statistical significance. The comprehensive analysis of PFS and ≥ 3 AEs indicates that monochemotherapy combined with dual-targeted therapy still has the optimal balance between efficacy and safety. Conclusion: Monochemotherapy (Docetaxel) plus dual-target (Trastuzumab and Pertuzumab) therapy remains the optimal choice among all first-line treatment options for ABC. The combination of trastuzumab with TKIs (Pyrotinib) demonstrated a significant improvement in PFS and ORR, but further data are warranted to confirm the survival benefit.",14321335,ONCOLOGY
10.3390/cancers16030476,Prediction of Patient Outcomes in Locally Advanced Cervical Carcinoma Following Chemoradiotherapy—Comparative Effectiveness of Magnetic Resonance Imaging and 2-Deoxy-2-[18F]fluoro-D-glucose Imaging,"Purpose: To evaluate the utility and comparative effectiveness of three five-point qualitative scoring systems for assessing response on PET-CT and MRI imaging individually and in combination, following curative-intent chemoradiotherapy (CRT) in locally advanced cervical cancer (LACC). Their performance in the prediction of subsequent patient outcomes was also assessed; Methods: Ninety-seven patients with histologically confirmed LACC treated with CRT using standard institutional protocols at a single centre who underwent PET-CT and MRI at staging and post treatment were identified retrospectively from an institutional database. The post-CRT imaging studies were independently reviewed, and response assessed using five-point scoring tools for T2WI, DWI, and FDG PET-CT. Patient characteristics, staging, treatment, and follow-up details including progression-free survival (PFS) and overall survival (OS) outcomes were collected. To compare diagnostic performance metrics, a two-proportion z-test was employed. A Kaplan–Meier analysis (Mantel–Cox log-rank) was performed. Results: The T2WI (p < 0.00001, p < 0.00001) and DWI response scores (p < 0.00001, p = 0.0002) had higher specificity and accuracy than the PET-CT. The T2WI score had the highest positive predictive value (PPV), while the negative predictive value (NPV) was consistent across modalities. The combined MR scores maintained high NPV, PPV, specificity, and sensitivity, and the PET/MR consensus scores showed superior diagnostic accuracy and specificity compared to the PET-CT score alone (p = 0.02926, p = 0.0083). The Kaplan–Meier analysis revealed significant differences in the PFS based on the T2WI (p < 0.001), DWI (p < 0.001), combined MR (p = 0.003), and PET-CT/MR consensus scores (p < 0.001) and in the OS for the T2WI (p < 0.001), DWI (p < 0.001), and combined MR scores (p = 0.031) between responders and non-responders. Conclusion: Post-CRT response assessment using qualitative MR scoring and/or consensus PET-CT and MRI scoring was a better predictor of outcome compared to PET-CT assessment alone. This requires validation in a larger prospective study but offers the potential to help stratify patient follow-up in the future.",20726694,ONCOLOGY
10.3390/educsci14020116,Transitioning to Success: The Link between E-CTE and College Preparation for Students with Learning Disabilities in the United States,"In recent years, there has been a specific call to not only increase the number of engineering-trained individuals but also to address the lack of diversity in science, technology, engineering and mathematics (STEM) fields, including individuals with disabilities. In particular, students with learning disabilities (SWLDs) make up a large portion of all students and are, therefore, a crucial population on which to focus educational and career progression efforts. One potential means of promoting persistence along the STEM pipeline—engineering specifically—is through engineering career and technical education (E-CTE) coursework in high school. Using a nationally representative dataset, we explore how E-CTE participation links to college preparation and transition activities for SWLDs, including math SAT performance, dual credit course participation, college application, and FAFSA completion. Under our more rigorous school fixed-effects models, we find that E-CTE participation is associated with beneficial results across each of our outcomes. The implications are discussed.",22277102,EDUCATION
10.3390/ai5010014,MultiWave-Net: An Optimized Spatiotemporal Network for Abnormal Action Recognition Using Wavelet-Based Channel Augmentation,"Human behavior is regarded as one of the most complex notions present nowadays, due to the large magnitude of possibilities. These behaviors and actions can be distinguished as normal and abnormal. However, abnormal behavior is a vast spectrum, so in this work, abnormal behavior is regarded as human aggression or in another context when car accidents occur on the road. As this behavior can negatively affect the surrounding traffic participants, such as vehicles and other pedestrians, it is crucial to monitor such behavior. Given the current prevalent spread of cameras everywhere with different types, they can be used to classify and monitor such behavior. Accordingly, this work proposes a new optimized model based on a novel integrated wavelet-based channel augmentation unit for classifying human behavior in various scenes, having a total number of trainable parameters of 5.3 m with an average inference time of 0.09 s. The model has been trained and evaluated on four public datasets: Real Live Violence Situations (RLVS), Highway Incident Detection (HWID), Movie Fights, and Hockey Fights. The proposed technique achieved accuracies in the range of 92% to 99.5% across the used benchmark datasets. Comprehensive analysis and comparisons between different versions of the model and the state-of-the-art have been performed to confirm the model’s performance in terms of accuracy and efficiency. The proposed model has higher accuracy with an average of 4.97%, and higher efficiency by reducing the number of parameters by around 139.1 m compared to other models trained and tested on the same benchmark datasets.",26732688,AI
10.3390/ejihpe14020019,Mid-Term and Long-Lasting Psycho–Cognitive Benefits of Bidomain Training Intervention in Elderly Individuals with Mild Cognitive Impairment,"Background: This study investigated whether combining simultaneous physical and cognitive training yields superior cognitive outcomes compared with aerobic training alone in individuals with mild cognitive impairment (MCI) and whether these benefits persist after four weeks of detraining. Methods: Forty-four people with MCI (11 males and 33 females) aged 65 to 75 years were randomly assigned to an 8-week, twice-weekly program of either aerobic training (AT group, n = 15), aerobic training combined with cognitive games (ACT group, n = 15), or simply reading for controls (CG group, n = 14). Selective attention (Stroop), problem-solving (Hanoi Tower), and working memory (Digit Span) tasks were used to assess cognitive performances at baseline, in the 4th (W4) and 8th weeks (W8) of training, and after 4 weeks of rest (W12). Results: Both training interventions induced beneficial effects on all tested cognitive performance at W4 (except for the number of moves in the Hanoi tower task) and W8 (all p <0.001), with the ACT group exhibiting a more pronounced positive impact than the AT group (p < 0.05). This advantage was specifically observed at W8 in tasks such as the Stroop and Tower of Hanoi (% gain ≈40% vs. ≈30% for ACT and AT, respectively) and the digit span test (% gain ≈13% vs. ≈10% for ACT and AT, respectively). These cognitive improvements in both groups, with the greater ones in ACT, persisted even after four weeks of detraining, as evidenced by the absence of a significant difference between W8 and W12 (p > 0.05). Concerning neuropsychological assessments, comparable beneficial effects were recorded following both training regimens (all p < 0.05 from pre- to post-intervention). The control group did not show any significant improvement in most of the cognitive tasks. Conclusions: The greater mid-term and long-lasting effects of combined simultaneous physical–cognitive training underscores its potential as a cost-effective intervention for the prevention and management of cognitive decline. While these results are valuable in guiding optimal physical and mental activity recommendations for adults with MCI, further neurophysiological-based studies are essential to offer robust support and deepen our understanding of the mechanisms underlying these promising findings.",22549625,PSYCHOLOGY
10.1007/s00432-023-05555-8,Patient–physician communication about cancer-related fatigue: a survey of patient-perceived barriers,"Purpose: Cancer-related fatigue is a subjective, distressing, and common sequela of cancer which is often disregarded and underdiagnosed. Fatigue is assessed by self-report requiring communication between patient and physician. In this study, we investigated the patients’ perspective on the patient–physician communication about fatigue. Methods: On average five months after diagnosis 1179 cancer patients, recruited in Germany, completed a survey as part of the LIFT project. The survey included questions on sociodemographic data, fatigue, depression, fatigue management, patient–physician communication, and communication barriers. Data were analyzed descriptively and using logistic regression analyses. Results: Half of the participants reported that their physician had never asked them whether they felt exhausted. Patients undergoing chemo-, radio-, or immunotherapy were more likely to be asked about fatigue, while older age and major depression decreased the likelihood. Sixty-four percent of the patients felt impeded by communication barriers. Common barriers were not knowing who to turn to for fatigue (39%), time constraints (31%), and the fear of being perceived as weak (22%). Almost half of the participants indicated that their physicians were not appreciative and did not deal adequately with fatigue-related questions. Conclusion: This study revealed gaps in the patient–physician communication regarding cancer-related fatigue. Contrary to guideline recommendations a minority of physicians addressed fatigue. On the other hand, cancer patients felt reluctant to bring up this topic due to structural barriers and fears. Physicians should routinely address fatigue and adopt a communication style which encourages patients to likewise state their symptoms and raise their questions. Trial registration: Clinicaltrials.gov, identifier: NCT04921644. Registered in June 2021.",14321335,ONCOLOGY
10.1007/s00432-024-05610-y,Prediction of positive pulmonary nodules based on machine learning algorithm combined with central carbon metabolism data,"Background: Lung cancer causes a huge disease burden, and early detection of positive pulmonary nodules (PPNs) as an early sign of lung cancer is extremely important for effective intervention. It is necessary to develop PPNs risk recognizer based on machine learning algorithm combined with central carbon metabolomics. Methods: The study included 2248 participants at high risk for lung cancer from the Ma'anshan Community Lung Cancer Screening cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to screen 18 central carbon-related metabolites in plasma, recursive feature elimination (RFE) was used to select all 42 features, followed by five machine learning algorithms for model development. The performance of the model was evaluated using area under the receiver operator characteristic curve (AUC), accuracy, precision, recall, and F1 scores. In addition, SHapley Additive exPlanations (SHAP) was performed to assess the interpretability of the final selected model and to gain insight into the impact of features on the predicted results. Results: Finally, the two prediction models based on the random forest (RF) algorithm performed best, with AUC values of 0.87 and 0.83, respectively, better than other models. We found that homogentisic acid, fumaric acid, maleic acid, hippuric acid, gluconic acid, and succinic acid played a significant role in both PPNs prediction model and NPNs vs PPNs model, while 2-oxadipic acid only played a role in the former model and phosphopyruvate only played a role in the NPNs vs PPNs model. This model demonstrates the potential of central carbon metabolism for PPNs risk prediction and identification. Conclusion: We developed a series of predictive models for PPNs, which can help in the early detection of PPNs and thus reduce the risk of lung cancer.",14321335,ONCOLOGY
10.1007/s00432-023-05562-9,Early port site and peritoneal metastasis following robot-assisted radical cystectomy: a rare case report,Radical cystectomy with pelvic lymph node dissection is the recommended treatment for managing muscle-invasive carcinoma of the urinary bladder. Early recurrence is observed in only about 4.1% of cases. Port-site metastasis following robot-assisted radical cystectomy is extremely rare. We encountered a challenging and a rare case of bladder cancer that manifested with port-site and peritoneal metastasis within 6 weeks of surgery.,14321335,ONCOLOGY
10.3390/educsci14020129,The Pernicious Predictability of State-Mandated Tests of Academic Achievement in the United States,"The purpose of this study was to determine the predictiveness of community and family demographic variables related to the development of student academic background knowledge on the percentage of students who pass a state-mandated, commercially prepared, standardized Algebra 1 test in the state of New Jersey, USA. This explanatory, cross-sectional study utilized quantitative methods through hierarchical regression analysis. The results suggest that family demographic variables found in the United States Census data related to the development of student academic background knowledge predicted 75 percent of schools in which students achieved a passing score on a state standardized high school assessment of Algebra 1. We can conclude that construct-irrelevant variance, influenced in part by student background knowledge, can be used to predict standardized test results. The results call into question the use of standardized tests as tools for policy makers and educational leaders to accurately judge student learning or school quality.",22277102,EDUCATION
10.1007/s00432-023-05594-1,Short-term serial circulating tumor DNA assessment predicts therapeutic efficacy for patients with advanced pancreatic cancer,"Purpose We investigated the potential clinical utility of short-term serial KRAS-mutated circulating cell-free tumor DNA (ctDNA) assessment for predicting therapeutic response in patients undergoing first-line chemotherapy for advanced pancreatic cancer. Methods We collected 144 blood samples from 18 patients with locally advanced or metastatic cancer that were undergoing initial first-line chemotherapy of gemcitabine plus nab-paclitaxel (GEM plus nab-PTX). Analysis of KRAS-mutated ctDNA was quantified by digital droplet polymerase chain reaction (ddPCR) as mutant allele frequency (MAF). This study investigated pretreatment KRAS-mutated ctDNA status and ctDNA kinetics every few days (days 1, 3, 5 and 7) after initiation of chemotherapy and their potential as predictive indicators. Results Of the 18 enrolled patients, an increase in KRAS-mutated ctDNA MAF values from day 0–7 after initiation of chemotherapy was significantly associated with disease progression (P < 0.001). Meanwhile, positive pretreatment ctDNA status (MAF ≥ 0.02%) (P = 0.585) and carbohydrate antigen 19-9 (CA19-9) values above the median (P = 0.266) were not associated with disease progression. In univariate analysis, this short-term increase in ctDNA MAF values (day 0–7) was found to be associated with significantly shorter progression free survival (PFS) (hazard ration [HR], 24.234; range, (2.761–212.686); P = 0.0002). Conclusion This short-term ctDNA kinetics assessment may provide predictive information to reflect real-time therapeutic response and lead to effective refinement of regimen in patients with advanced pancreatic cancer undergoing systemic chemotherapy.",14321335,ONCOLOGY
10.1007/s00432-023-05592-3,Exploring the expression and clinical significance of the miR-140-3p-HOXA9 axis in colorectal cancer,"Purpose: This study aims to investigate the expression patterns and clinical significance of miR-140-3p and homeobox A9 (HOXA9) in colorectal cancer (CRC) selected by bioinformatic study, while elucidating their potential interplay. Methods: The microRNA expression profiles of paired colorectal cancer and matched normal tissues were retrieved from the Gene Expression Omnibus Database. Differentially expressed microRNAs and microRNA candidates were filtered and subjected to further analysis. Clinicopathological data, along with paraffin-embedded samples of colorectal tumor tissues were collected to facilitate comprehensive analysis. Expression levels of miR-140-3p and HOXA9 were quantified using qRT-PCR and immunohistochemistry. Survival rates were determined using the Kaplan–Meier method, and the COX regression model was utilized to identify independent prognostic factors that impact the overall prognosis. Results: MiR-140-3p was significantly downregulated in colorectal tumors compared to normal tissue, and HOXA9 was identified as a previously unreported potential downstream target. HOXA9 expression was elevated in tumors compared to normal tissues. Reduced miR-140-3p expression was associated with lymph node metastasis, while high HOXA9 expression correlated with both lymph node metastasis and lympho-vascular invasion. Patients with low miR-140-3p and high HOXA9 expression had a poorer prognosis. HOXA9 was identified as an independent risk factor for CRC patient survival. Conclusion: The miR-140-3p-HOXA9 signaling disruption is closely linked to lymph node metastasis and unfavorable prognosis in CRC. This axis shows promise as a clinical biomarker for predicting the CRC patient survival and a potential therapeutic target.",14321335,ONCOLOGY
10.3390/educsci14020153,Assessing the Linguistic Creativity Domain of Last-Year Compulsory Secondary School Students,"The importance of creativity in the training of people gained special relevance with the PISA Tests of the OECD, which, for the first time, evaluated the general creativity of 15-year-old students in 2022. This descriptive and quantitative study focuses on the evaluation of linguistic creativity, using different classical instruments to measure divergent thinking and adding new ones, such as metaphorical capacity. Participants were 454 students in their last year of secondary education from eight Spanish educational centers. Results indicate moderate performance in divergent thinking tasks, with students exhibiting limitations in generating novel metaphors, often resorting to literal responses. Statistically significant differences according to gender were found in metaphor generation and in the alternate uses task. A correlation study reveals significant associations between metaphor generation and divergent thinking tasks. These highlight the differential role of semantic memory and cognitive processes involved in metaphor generation and divergent thinking. Finally, this study underlines the complexities and multicomponent nature of creativity as a first step to develop educational policies and interventions targeting creativity. Overall, the importance of addressing creativity in a transdisciplinary way and training teachers on techniques to channel creativity are highlighted, such as through the design of challenges or writing workshops.",22277102,EDUCATION
10.1007/s44196-023-00380-w,A Quantum-Like Tensor Compression Sentence Representation Based on Constraint Functions for Semantics Analysis,"To emphasize the semantic impact of local semantic and grammatical information among adjacent words in the input text, we establish a constraint functions-based quantum-like tensor compression sentence representation model by integrating the concept of extending the pure state-based density matrix to the mixed-state projection operator in quantum mechanics. The provided model highlights the semantic significance of mixed word associations in the input text, simultaneously reducing the reliance on information derived solely from dictionary statistics. We combine the correlation coefficient with the attention mechanism to establish the correlation coefficient between words. The quantum-like sentence representation based on pure state density matrix is extended to the projection operator of mixed states. Combining the acquisition of maximum in convex optimization, a constraint functions-based quantum-like text representation pruning model is established to reduce redundant information caused by dimensional expansion of tensor operations. The experimental results on SICK-2014, STS-benchmark, and STS-companion show that the provided model is more effective than the mainstream models in mining semantic information, especially more sensitive to the negative semantics of sentences.",18756883,AI
10.1007/s44196-023-00375-7,A LDA-Based Social Media Data Mining Framework for Plastic Circular Economy,"The mass production of plastic waste has caused an urgent worldwide public health crisis. Although government policies and industrial innovation are the driving forces to meet this challenge, trying to understand public attitudes may improve the efficiency of this process. Social media has become the main ways for the public to obtain information and express opinions and feelings. This motivated us to mine the perceptions and behavioral responses towards plastic usage using social media data. In this paper, we proposed a framework for data collection and analysis based on mainstream media in the UK to obtain public opinions on plastics. An unsupervised machine learning model based on Latent Dirichlet Allocation (LDA) has been employed to analyse and cluster the topics to deal with the lack of annotation of the data contents. An additional dictionary method was then proposed to evaluate the sentiment of the comments. The framework also provides tools to visualise the model and results to stimulate insightful understandings. We validated the framework's effectiveness by applying it to analyse three mainstream social media, where 6 first-level topic categories and 13 second-level topic categories from the comment texts related to plastics have been identified. The results show that public sentiment towards plastic products is generally stable. The spatiotemporal distribution of each topic's sentiment is highly correlated with the number of occurrences.",18756883,AI
10.1186/s40594-024-00466-7,STEM learning opportunities and career aspirations: the interactive effect of students’ self-concept and perceptions of STEM professionals,"Background: Students’ positive perceptions of scientists or engineers have been reported to be positively related to their science, technology, engineering, and mathematics (STEM) career aspirations. However, other research indicates that positive perceptions of experts in these fields might not necessarily lead to students’ pursuit of STEM careers. Self-concept, defined as one’s perceived abilities in specific academic domains, likely plays a moderating role in the relationship between perceptions and career aspirations according to the motivational theory of role modelling. Moreover, students’ perceptions of STEM professionals might be sourced from STEM-related media and school experiences. Therefore, through running a moderated mediation model, this study examined whether and how the influences of media consumption and school STEM learning opportunities on career aspirations would be mediated by perceptions of STEM professionals, and whether the mediation effect would be conditional on students’ self-concept. Methods: Data were collected through an online survey of 608 primary and secondary school students from Hong Kong, and were analysed using structural equation modelling. Results: Results revealed that the students’ positive perceptions of STEM professionals were positively associated with their career aspirations, and mediated the links from media consumption and school opportunities to career aspirations. In addition, this mediated pathway depended on STEM self-concept, such that perceptions of STEM professionals were only linked with STEM career aspirations for adolescents with average or high levels of self-concept. Conclusions: The findings of this study suggest the need to pay attention to the STEM perceptions and self-concept interaction while designing and implementing learning activities to connect a diversity of students with STEM careers. It is not only important to foster students’ self-concept, but also to enrich their knowledge of diverse occupations, so as to help diversify their perceptions that being professionals in these fields is desirable and attainable, and to eventually inspire more student engagement and participation in STEM.",21967822,EDUCATION
10.3389/fonc.2024.1325345,TERT promoter methylation is associated with high expression of TERT and poor prognosis in papillary thyroid cancer,"The telomerase reverse transcriptase (TERT) is overexpressed and associated with poor prognosis in papillary thyroid cancer (PTC), the most common subtype of thyroid cancer. The overexpression of TERT in PTC was partially attributed to transcriptional activation by two hotspot mutations in the core promoter region of this gene. As one of the major epigenetic mechanisms of gene expression regulation, DNA methylation has been proved to regulate several tumor-related genes in PTC. However, the association of TERT promoter DNA methylation with TERT expression and PTC progression is still unclear. By treating PTC cell lines with demethylating agent decitabine, we found that the TERT promoter methylation and the genes’ expression were remarkably decreased. Consistently, PTC patients with TERT hypermethylation had significantly higher TERT expression than patients with TERT hypomethylation. Moreover, TERT hypermethylated patients showed significant higher rates of poor clinical outcomes than patients with TERT hypomethylation. Results from the cox regression analysis showed that the hazard ratios (HRs) of TERT hypermethylation for overall survival, disease-specific survival, disease-free interval (DFI) and progression-free interval (PFI) were 4.81 (95% CI, 1.61-14.41), 8.28 (95% CI, 2.14-32.13), 3.56 (95% CI, 1.24-10.17) and 3.32 (95% CI, 1.64-6.71), respectively. The HRs for DFI and PFI remained significant after adjustment for clinical risk factors. These data suggest that promoter DNA methylation upregulates TERT expression and associates with poor clinical outcomes of PTC, thus holds the potential to be a valuable prognostic marker for PTC risk stratification.",2234943X,ONCOLOGY
10.3389/fonc.2024.1298122,"The safety and efficacy of TACE combined with HAIC, PD-1 inhibitors, and tyrosine kinase inhibitors for unresectable hepatocellular carcinoma: a retrospective study","Objective: To assess the effectiveness and safety of transarterial chemoembolization (TACE) in combination with hepatic artery infusion chemotherapy (HAIC)、PD-1 inhibitors, and tyrosine kinase inhibitors(TKI) for unresectable hepatocellular carcinoma (HCC).Methods: A retrospective analysis was performed on 158 unresectable HCC patients admitted to the First Affiliated Hospital of Nanchang University between May 2019 and October 2022. The patients were split into two groups based on the type of treatment they received: TACE combined with HAIC,PD-1 and TKI group (THPK) and TACE combined with PD-1 and TKI group (TPK). The response was evaluated using modified solid tumor Efficacy Assessment Criteria (mRECIST). Kaplan-Meier curves were used to analyze the overall survival (OS). OS-influencing factors were identified using the Cox proportional risk regression model.Results: Finally, 63 patients who received THPK treatment and 60 patients who had TPK treatment were included. The THPK group had higher DCR (77.78% vs. 55.00%, P=0.007) and ORR (20.63% vs. 13.34%, P=0.282) than the TPK group did. The survival analysis curve also showed that the median OS was substantially longer in the THPK group than in the TPK group (OS: 21 months vs. 14 months, P=0.039). After multivariate Cox regression-corrected analysis, extrahepatic metastases (P=0.002) and methemoglobin >400 (P=0.041) were adverse influences on OS, but the THPK group (relative to the TPK group) was an independent favorable prognostic factor for OS (P=0.027). The results of the subgroup analysis showed that the addition of HAIC therapy to TPK treatment in patients with BCLC stage C, age ≦60 years, ECOG grade 0 and lobular distribution of tumors prolonged overall survival time and improved prognosis. Except for nausea, there was no difference in the adverse events between the two groups.Conclusion: In patients with unresectable HCC, the THPK group had a longer OS and similar adverse events compared to the TPK group. In the future, TACE-HAIC in combination with targeted and immunotherapy may be a more effective therapeutic option for hepatocellular carcinoma that cannot be surgically removed.",2234943X,ONCOLOGY
10.1007/s00432-023-05604-2,Skeletal muscle extramedullary plasmacytoma transformed into plasmablastic plasmacytoma: a case report,"Background Extramedullary plasmacytoma (EMP) is a rare plasma cell malignancy, especially when the tumor originates in skeletal muscle. Plasmablastic plasmacytoma is an anaplastic round cell tumor with highly malignancy and poor prognosis. To date, there have been no reports on the transformation of skeletal muscle EMP into plasmablastic plasmacytoma. Therefore, the diagnosis, treatment, and prognosis of cases of this pathologic transformation are unclear. Case presentation This article reports a case of an elderly male patient who presented with a painless mass in the right calf and was diagnosed with EMP by puncture pathology. Complete remission was obtained after sequential chemoradiotherapy. 6 months later, another puncture was performed due to plasmablastic plasmacytoma multiple distant metastases, and the pathology showed that EMP was transformed to plasmablastic plasmacytoma. Despite aggressive antitumor therapy, the disease continued to deteriorate, and the patient ultimately died of respiratory failure. Conclusion The transformation of EMP into plasmablastic plasmacytoma is very rare, and its diagnosis and treatment require the participation of both experienced pathologists and clinicians. We report this case in order to raise clinicians' awareness of the diagnosis and treatment of EMP and its transformation to plasmablastic plasmacytoma, and to avoid misdiagnosis and underdiagnosis.",14321335,ONCOLOGY
10.3389/fonc.2024.1255618,Monitoring response to neoadjuvant therapy for breast cancer in all treatment phases using an ultrasound deep learning model,"Purpose: The aim of this study was to investigate the value of a deep learning model (DLM) based on breast tumor ultrasound image segmentation in predicting pathological response to neoadjuvant chemotherapy (NAC) in breast cancer.Methods: The dataset contains a total of 1393 ultrasound images of 913 patients from Renmin Hospital of Wuhan University, of which 956 ultrasound images of 856 patients were used as the training set, and 437 ultrasound images of 57 patients underwent NAC were used as the test set. A U-Net-based end-to-end DLM was developed for automatically tumor segmentation and area calculation. The predictive abilities of the DLM, manual segmentation model (MSM), and two traditional ultrasound measurement methods (longest axis model [LAM] and dual-axis model [DAM]) for pathological complete response (pCR) were compared using changes in tumor size ratios to develop receiver operating characteristic curves.Results: The average intersection over union value of the DLM was 0.856. The early-stage ultrasound-predicted area under curve (AUC) values of pCR were not significantly different from those of the intermediate and late stages (p< 0.05). The AUCs for MSM, DLM, LAM and DAM were 0.840, 0.756, 0.778 and 0.796, respectively. There was no significant difference in AUC values of the predictive ability of the four models.Conclusion: Ultrasonography was predictive of pCR in the early stages of NAC. DLM have a similar predictive value to conventional ultrasound for pCR, with an add benefit in effectively improving workflow.",2234943X,ONCOLOGY
10.1186/s40594-024-00464-9,Pre-service elementary teachers’ science and engineering teaching self-efficacy and outcome expectancy: exploring the impacts of efficacy source experiences through varying course modalities,"Background: Teacher efficacy is one of the most influential components for effective instruction, highlighting the importance of providing preservice teachers (PSTs) with opportunities to learn how to teach engineering during their college preparatory coursework. Making space for engineering instruction within science methods coursework could provide opportunities for PSTs to enhance their engineering teaching efficacy but also requires course instructors to give up some time previously devoted to science-focused instruction. The purpose of the current study was to explore how infusing engineering learning opportunities into a science methods course impacts PSTs’ engineering and science teaching efficacy and outcome expectancy. Results: Pre/post-surveys were completed by PSTs enrolled in a Kindergarten-8th grade science methods course offered in four modalities (i.e., face-to-face, hybrid, online, rapid shift online). The course offered multiple engineering-focused learning activities and vicarious experiences. PSTs’ science teaching efficacy beliefs, engineering teaching efficacy beliefs, science teaching outcome expectancy, and engineering teaching outcome expectancy all significantly increased from pre- to post-test. There was no significant difference between efficacy gains based on course modality. The purposeful inclusion of multiple engineering activities and vicarious experiences allows for significant gains in science and engineering teaching efficacy and outcome expectancy regardless of the modality in which the course is taken. Conclusions: This study shows that having varied efficacy source experiences while learning engineering design can result in increased efficacy, even in the absence of field experience and face-to-face coursework, and that the inclusion of these engineering experiences with science methods coursework does not detract from enhancing science teaching efficacy beliefs and outcome expectancy. Further research is needed to more closely examine individual components of science methods courses and the impacts each component has when implemented using different course modalities.",21967822,EDUCATION
10.3390/ai5010018,Automated Classification of User Needs for Beginner User Experience Designers: A Kano Model and Text Analysis Approach Using Deep Learning,"This study introduces a novel tool for classifying user needs in user experience (UX) design, specifically tailored for beginners, with potential applications in education. The tool employs the Kano model, text analysis, and deep learning to classify user needs efficiently into four categories. The data for the study were collected through interviews and web crawling, yielding 19 user needs from Generation Z users (born between 1995 and 2009) of LEGO toys (Billund, Denmark). These needs were then categorized into must-be, one-dimensional, attractive, and indifferent needs through a Kano-based questionnaire survey. A dataset of over 3000 online comments was created through preprocessing and annotating, which was used to train and evaluate seven deep learning models. The most effective model, the Recurrent Convolutional Neural Network (RCNN), was employed to develop a graphical text classification tool that accurately outputs the corresponding category and probability of user input text according to the Kano model. A usability test compared the tool’s performance to the traditional affinity diagram method. The tool outperformed the affinity diagram method in six dimensions and outperformed three qualities of the User Experience Questionnaire (UEQ), indicating a superior UX. The tool also demonstrated a lower perceived workload, as measured using the NASA Task Load Index (NASA-TLX), and received a positive Net Promoter Score (NPS) of 23 from the participants. These findings underscore the potential of this tool as a valuable educational resource in UX design courses. It offers students a more efficient and engaging and less burdensome learning experience while seamlessly integrating artificial intelligence into UX design education. This study provides UX design beginners with a practical and intuitive tool, facilitating a deeper understanding of user needs and innovative design strategies.",26732688,AI
10.3389/fonc.2024.1341233,Effective treatment of advanced lung adenocarcinoma with paraneoplastic leukemoid reaction with Lorlatinib: a case report,"BackgroundLorlatinib is a new generation ALK kinase inhibitor. We describe a 52-year-old patient with ALK-positive advanced lung adenocarcinoma who achieved remission after multi-line therapy combined with paraneoplastic leukemoid reaction treated with Lorlatinib.Case reportA 52-year-old male patient was diagnosed with stage IV right lung adenocarcinoma, ALK: (+), previously received oral Crizotinib and Alectinib. Blood routine showed white blood cells abnormally elevated after disease progression, and maximum white blood cell count was 179.14×10^9/L. The patient was enrolled in study entitled “a phase II, multicenter, open-label, dual-cohort study to evaluate the efficacy and safety of LORLATINIB monotherapy in ALK inhibitor-treated locally advanced or metastatic ALK-positive non-small cell lung cancer patients in China”. With oral Lorlatinib, the white blood cell count decreased from 179.14×10^9/L to normal after two weeks of administration. PFS was 4.5 months. When follow up imaging showed lesions progression, the white blood cell count increased again, diagnosing a paraneoplastic leukemic reaction. OS was 5.2 months.ConclusionIn this case, fourth-line Lorlatinib treatment is effiective in ALK-positive advanced patient with paraneoplastic leukemoid reaction. ClinicalTrials.gov Identifier: NCT03909971",2234943X,ONCOLOGY
10.3389/fonc.2023.1333761,"Case report: Successful treatment of a patient with relapsed/refractory primary central nervous system lymphoma with thiotepa-based induction, autologous stem cell transplantation and maintenance","Despite significant improvements in prognosis, a subset of patients with primary central nervous system lymphoma (PCNSL) remains at high risk for relapse. The treatment of relapsed and refractory (R/R) PCNSL remains a major clinical challenge. Herein, we present a 24-year-old patient with PCNSL who relapsed 4 years after initial diagnosis and subsequently became refractory to high-dose methotrexate (HD-MTX), temozolomide, whole brain radiation therapy (WBRT), ibrutinib, and lenalidomide. She received thiotepa with anti-programmed cell death protein 1 (PD-1) antibody and achieved partial remission and then underwent autologous stem cell transplantation (ASCT) with thiotepa-based conditioning. Post-transplant maintenance with thiotepa and anti-PD-1 at 3-month intervals resulted in a durable complete response (CR) in this case of R/R PCNSL. Our report highlights the important role of thiotepa in the treatment of patients with R/R PCNSL.",2234943X,ONCOLOGY
10.1007/s00432-023-05546-9,The effectiveness of E-health interventions promoting physical activity in cancer survivors: a systematic review and meta-analysis of randomized controlled trials,"Purpose: This systematic review and meta-analysis aimed to identify whether E-health interventions effectively improve physical activity (PA) in cancer survivors. Methods: PubMed, Web of Science, and Cochrane Library databases were searched from inception to October 21, 2023. Randomized controlled trials reporting the effect of E-health interventions on PA among cancer survivors were included. Random-effect models were used to calculate standardized mean differences (SMD) and the 95% confidence interval (CI). Results: In total, 15 trials with 2,291 cancer survivors were included in this meta-analysis. The results showed that E-health interventions improved moderate to vigorous physical activity (MVPA) among cancer survivors (SMD = 0.26, 95% CI 0.08, 0.43, N = 8, p < 0.001, I2 = 37%), as well as moderate physical activity (MPA) (SMD = 0.22, 95% CI 0.05, 0.38, N = 9, p < 0.001, I2 = 28%) and vigorous physical activity (VPA) (SMD = 0.34, 95% CI 0.15, 0.54, N = 6, p < 0.001, I2 = 11%). Conclusion: E-health interventions are effective at promoting PA among cancer survivors. As current research primarily focuses on immediate post-intervention measurements with limited follow-up data, further investigation is required to explore the long-term effects of E-health interventions on PA.",14321335,ONCOLOGY
10.3389/fonc.2024.1302724,Case report: Minimally invasive primary debulking surgery for advanced stage epithelial ovarian cancer,"The surgical management of advanced ovarian cancer has historically emphasized an open technique, but advances in minimally invasive surgery (MIS) have led to its increasing use in ovarian cancer. Most research has focused on the utility of MIS in the interval debulking setting. Here, we present a case of a 38-year-old patient with incidentally diagnosed advanced stage ovarian cancer. We describe the robotic surgery techniques used to achieve complete primary cytoreduction, including resection of disease on the diaphragm. The patient has completed standard adjuvant chemotherapy and maintenance treatment and remains without evidence of disease for more than 2 years. This case details the techniques utilized to achieve complete cytoreduction including trocar placement, robotic instrument preference, and rotation of the robotic boom. This patient has had successful perioperative and oncologic outcomes, and her case highlights the role for minimally invasive primary debulking surgery for select patients with advanced ovarian cancer.",2234943X,ONCOLOGY
10.3389/fonc.2023.1215426,Neurotoxicity-sparing radiotherapy for brain metastases in breast cancer: a narrative review,"Breast cancer brain metastasis (BCBM) has a devastating impact on patient survival, cognitive function and quality of life. Radiotherapy remains the standard management of BM but may result in considerable neurotoxicity. Herein, we describe the current knowledge on methods for reducing radiation-induced cognitive dysfunction in patients with BCBM. A better understanding of the biology and molecular underpinnings of BCBM, as well as more sophisticated prognostic models and individualized treatment approaches, have appeared to enable more effective neuroprotection. The therapeutic armamentarium has expanded from surgery and whole-brain radiotherapy to stereotactic radiosurgery, targeted therapies and immunotherapies, used sequentially or in combination. Advances in neuroimaging have allowed more accurate screening for intracranial metastases, precise targeting of intracranial lesions and the differentiation of the effects of treatment from disease progression. The availability of numerous treatment options for patients with BCBM and multidisciplinary approaches have led to personalized treatment and improved therapeutic outcomes. Ongoing studies may define the optimal sequencing of available and emerging treatment options for patients with BCBM.",2234943X,ONCOLOGY
10.3389/fonc.2023.1272808,Optimization of treatment strategies based on preoperative imaging features and local recurrence areas for locally advanced lower rectal cancer after lateral pelvic lymph node dissection,"Purpose: Local recurrence (LR) is the main cause of treatment failure in locally advanced lower rectal cancer (LALRC). This study evaluated the preoperative risk factors for LR in patients with LALRC to improve the therapeutic strategies.Patients and Methods: LALRC patients who underwent total mesorectal excision (TME) with lateral pelvic lymph node (LPN) dissection (LPND) from January 2012 to December 2019 were reviewed. The log-rank test was used to assess local recurrence-free survival (LRFS), and multivariate Cox regression was used to identify the prognostic risk factors for LRFS. Follow-up imaging data were used to classify LR according to the location.Results: Overall, 376 patients were enrolled, and 8.8% (n=33) of these patients developed LR after surgery. Multivariate analysis identified positive clinical circumferential resection margin (cCRM) as an independent prognostic factor for LRFS (HR: 4.94; 95% CI, 1.75-13.94; P=0.003). The most common sites for LR were the pelvic plexus and internal iliac area (PIA) (54.5%), followed by the central pelvic area (CPA) (39.4%) and obturator area (OA) (6.1%). Following a subgroup analysis, LR in the OA was not associated with positive cCRM. Patients treated with upfront surgery (n=35, 14.1%) had a lower cCRM positive rate when compared with patients treated with neoadjuvant chemoradiotherapy (nCRT) (n=12, 23.5%). However, the LR rate in the nCRT group was still lower (n=28, 36.4%) than that in the upfront surgery group (n=35, 14.%). Among patients with positive cCRM, the LR rate in patients with nCRT remained low (n=3, 10.7%).Conclusion: Positive cCRM is an independent risk factor for LR after TME plus LPND in LALRC patients. LPND is effective and adequate for local control within the OA regardless of cCRM status. However, for LALRC patients with positive cCRM, nCRT should be considered before LPND to further reduce LR in the PIA and CPA.",2234943X,ONCOLOGY
10.1007/s44196-023-00401-8,Segmentation of Lung Lesions through Bilateral Learning Branches to Aggregating Contextual and Local Characteristics,"Detecting and analyzing lung lesion regions using artificial intelligence is of great significance in the medical diagnosis of lung CT images, which can substantially improve the efficiency of doctors. However, segmentation of the inflammatory region in the CT image of the lung remains challenging due to the varied sizes, blurry local details, irregular shapes, and limited sizes of datasets. Faced with these challenges, this paper proposes a novel lung lesion segmentation network that incorporates two feature extraction branches to achieve a balance of speed and accuracy. We first design a context branch (CB) to preserve the scale-invariant global context information by the transformer-like module. Besides, a shallow detail branch (DB) based on a deep aggregation pyramid (DAP) module is designed to provide detailed information. Extensive experiments are conducted on two datasets, including the public COVID-19 dataset and a private dataset. Experimental results demonstrate that the proposed method outperforms state-of-the-art methods. Moreover, the trade-off between accuracy and inference speed is achieved.",18756883,AI
10.1007/s00432-023-05539-8,Approved immune checkpoint inhibitors in hepatocellular carcinoma: a large-scale meta-analysis and systematic review,"A meta-analysis was performed to assess the benefits and safety profile of approved immune checkpoint inhibitors in hepatocellular carcinoma patients. Eligible studies were searched from Cochrane, Embase, and PubMed databases based on a well-established strategy. Following the exclusion of ineligible studies, 12 studies were included in this meta-analysis. Compared with control group, immune checkpoint inhibitors were associated with improved ORR (OR 3.03, 95% CI 2.26–4.05, P < 0.00001), SD (OR 0.77, 95% CI 0.62–0.95, P = 0.02), OS (HR 0.75, 95% CI 0.68–0.83, P < 0.00001), and PFS (HR 0.74, 95% CI 0.63–0.87, P < 0.0003). However, no significant differences were observed in DCR (OR 1.33, 95% CI 0.97–1.81, P = 0.07), PD (OR 0.90, 95% CI 0.67–1.21, P = 0.48), and all caused any-grade adverse events (OR 1.22, 95% CI 0.62–2.39, P = 0. 57), all caused ≥ grade 3 adverse events (OR 1.10, 95% CI 0.97–1.25, P = 0.14), treatment-related any-grade adverse events (OR 1.13, 95% CI 0.55–2.32, P = 0.73), and treatment-related ≥ grade 3 events (OR 0.82, 95% CI 0.34–1.97, P = 0.65) between the two groups. After subgroup analysis conducted, patients in the immune checkpoint inhibitor group compared with targeted drug group showed significant improvements in OS (HR 0.74, 95% CI 0.66–0.84, P < 0.00001) and PFS (HR 0.75, 95% CI 0.61–0.91, P = 0.004). Immune checkpoint inhibitors have demonstrated peculiar benefits in the treatment of HCC with an acceptable safety profile. Compared to targeted drugs, immune checkpoint inhibitors still offer advantages in the treatment of hepatocellular carcinoma. However, there is still considerable room for further improvement.",14321335,ONCOLOGY
10.1007/s44196-024-00404-z,Data Mesh Meets Blockchain,"Effective dataset management is crucial for enterprises to make informed decisions and remain competitive. However, centralized dataset management approaches often result in poor scalability, unclear governance, inaccessible data silos, and duplication of efforts. This paper proposes a distributed blockchain-based framework inspired by the data mesh architecture to address these challenges. Our proposed framework leverages blockchain’s decentralized nature to enable efficient and transparent dataset sharing across enterprise business domains. By turning datasets into digital assets and business domains into peers, our framework utilizes blockchain smart contracts to allow business domains to view, request, and share datasets. In this paper, we describe the details of our framework, and we analyze it from scalability, accessibility, security, and data governance perspectives. To validate our framework, we provide a proof-of-concept implementation with a publicly available source code.",18756883,AI
10.3390/educsci14020183,Investigating the Factors Contributing to the Formation of Secondary School Students’ Interest towards Higher Education Studies,"The present study’s objective constitutes the examination of the prognostic factors that influence the inclination of students in secondary school towards pursuing higher education. To achieve this goal, an existing questionnaire was utilized and appropriately altered to align with the Greek educational system. The survey involved the participation of 301 secondary school students from Piraeus, which comprises one of Greece’s major cities. The outcomes of the research yield substantial endorsement for the principles outlined in the social cognitive career theory. Specifically, the study highlights the significant role of family background, encompassing the educational levels of the parents, the students’ perceptions of the family’s financial situation, and the financial support provided by the family during the students’ academic journey, in shaping the students’ intent towards pursuing higher education. Moreover, the presence of a secure attachment bond between students and their parents suggests a favorable inclination towards higher education. Conversely, students deriving from low-income families are prone to exhibit hesitancy in pursuing higher education. The acquired data reveal a constructive relationship among outcome expectations, social support, as well as the process of students’ interest in developing a desire for higher education. Conversely, factors such as gender and age, as well as the presence of siblings studying in higher education, appear to have little influence in this regard.",22277102,EDUCATION
10.3390/ejihpe14020025,"The Relation of Big Five Personality Traits on Academic Performance, Well-Being and Home Study Satisfaction in Corona Times","Introduction: As a result of the protective measures taken to contain the COVID-19 pandemic, German students experienced home study in the spring of 2020. The present study addressed the relation between coping with the home study situation and personality. Methods: The interrelations of the Big Five factors with students’ well-being, study satisfaction and academic performance were examined in 287 German online participants. Results: The results showed significant positive correlations of positive affect and conscientiousness, as well as of better academic performance and academic satisfaction. For extraversion, a positive supporting effect on the affective level emerged, although previous studies suggested negative influences of extraversion on affect in home study settings in other phases of the pandemic. Furthermore, in contrast, neuroticism showed a negative relation to study satisfaction and mood in home study. Conclusion: In summary, the personalities of students should be considered in order to provide protective measures and avoid negative coping effects.",22549625,PSYCHOLOGY
10.3390/ejihpe14020026,The Linguistic–Cognitive Profile in an Adult Population with Parkinson’s Disease and Deep Brain Stimulation: A Comparative Study,"Introduction. Individuals with Parkinson’s disease (PD) exhibit general impairments, particularly non-motor symptoms that are related to language, communication, and cognition processes. People with this disease may undergo a surgical intervention for the placement of a deep brain stimulation device, which improves their motor symptoms. However, this type of intervention leads to a decline in their linguistic and cognitive abilities that becomes increasingly noticeable as the disease progresses. Objective. The objective of this research was to compare the performance and linguistic–cognitive profile of individuals with Parkinson’s disease who underwent deep brain stimulation treatment based on the stage of the disease. Method. A total of 60 participants who were diagnosed with PD by their reference hospital were selected. These participants were divided into three groups based on the stage of the disease that they were in, forming three groups: a Stage I group (n = 20), a Stage II group (n = 20), and a Stage III group (n = 20). The linguistic–cognitive profile was assessed using the MoCA, ACE-III, and MetAphas tests. The design of this study was established as a quasi-experimental, cross-sectional investigation, and statistical analysis was performed using MANOVA to compare the scores between the study groups. Results. The results indicate that individuals in Stage I exhibit better linguistic and cognitive performance compared to the other groups of participants in Stage II and Stage III, with statistically significant differences (p < 0.05). Conclusion. In conclusion, the progression of PD leads to significant linguistic and cognitive decline in individuals with this disease who have a deep brain stimulation device, greatly limiting the autonomy and quality of life for people with PD.",22549625,PSYCHOLOGY
10.3389/fpsyg.2024.1326170,Intimate relationships and hypnosis: insecure adult attachment affects emotions and absorption during hypnosis,"Introduction Hypnosis research indicates that subjects are not equally hypnotizable. Most studies on hypnotizability focused on the relationships with personality or cognitive variables. At the same time, only a few proposed the contribution of the attachment style, defined as the result of the childhood relationship with the caregivers and influencing the adult relations. Methods In the present investigation, two studies were carried out to test the possible association between adult attachment and hypnotic responsivity. The adult attachment was assessed using the Experiences in Close Relationships-Revised (ECR-R) questionnaire, while hypnosis was assessed through the Harvard Group Scale of Hypnotic Susceptibility (HGSHS:A; Study 1) and the Phenomenology of Consciousness Inventory: Hypnotic Assessment Procedure (PCI-HAP; Study 2) in order to adopt a behavioral and a phenomenological approach, respectively. Results Analyses showed that attachment factors (anxiety and avoidance) were not associated with the level of hypnotizability, whereas it was associated with variations of consciousness during hypnosis, mainly internal dialogue, absorption and negative emotions. Overall, the insecure attachment styles yielded increased mind wandering and restlessness during hypnosis when compared to the secure style. The reason probably lies in the feeling of anxiety or danger of insecurely attached individuals when involved in intimate or confidential relationships. Conclusion These findings clarify a still poorly investigated aspect concerning the influence of attachment style on hypnotic experience and further highlight the need to consider inter-individual differences and the phenomenological perspective when assessing hypnosis and hypnotizability.",16641078,PSYCHOLOGY
10.3390/ejihpe14020027,Portuguese Validation of the TAPQoL: A Health-Related Quality of Life Instrument for Children Aged 0–6 Years,"In Portugal, there are few generic and specific instruments to assess health-related quality of life (HRQoL) in children, especially those of preschool age. This study aimed to adapt and validate the Portuguese version of the Preschool Children Quality of Life Questionnaire (TAPQoL) in a community and clinical sample of children aged 0–6 years. The parents of 409 healthy children and 137 children undergoing treatment for burns and acute lymphoblastic leukemia completed the TAPQoL and were assessed on psychological morbidity and family functioning. Exploratory and confirmatory factor analyses were performed, as well as analysis of the psychometric properties as shown by internal consistency measures, convergent validity, and average variance extracted. Confirmatory factor analysis confirmed an 11-factor structure with good psychometric properties. The current version of the TAPQoL is a valid and reliable instrument for assessing HRQoL in Portuguese preschool children in community and clinical settings.",22549625,PSYCHOLOGY
10.1186/s40359-024-01565-4,The relationship between passion and athlete identity in sport: the mediating and moderating role of dedication,"Background: In addition to the fact that the concept of passion in sports plays a significant role in the formation of the identity concept of athletes, the dedication of athletes to the sports branches they are interested in also has a significant impact on their passion for the sport they are interested in as well as their identity as an athlete. In this direction, the research aims to investigate the role of dedication as a mediator and moderator in the relationship between athlete identity and passion in sport.Methods: The research was designed using the quantitative research technique of relational surveying. As data collection instruments for the research, the athlete identity scale, the passion in sport scale, and the sports commitment scale were utilized. 237 amateur and professional athletes, of which 142 were male and 95 were female (Mage = 22.7), participated voluntarily in the study by random sampling. The data were analyzed with the PROCESS and Jamovi programs in order to examine the direct and indirect effects.Results: Significant effects of sports passion on commitment and athlete identity were found. Since both dedication and athlete identity had a significant effect on passion for sports, it was determined that passion for sports continues to influence athlete identity through the medium of dedication. The moderator significance of medium, high, and low values of devotion was determined.Ethics approval number: 226394, date of registration: 03/11/2022.Conclusion: On the basis of the results of the statistical analyses, it was determined that the concept of dedication has a mediating and moderating effect on the relationship between sports passion and athlete identity.",20507283,PSYCHOLOGY
10.1186/s40594-024-00472-9,"Students’ perspectives on the ‘STEM belonging’ concept at A-level, undergraduate, and postgraduate levels: an examination of gender and ethnicity in student descriptions","Women and ethnic minorities have historically been underrepresented in some STEM fields. It is therefore important to understand the factors influencing students’ persistence in STEM fields, and what STEM belonging means from the voices of socio-demographically diverse students, in order to ensure equity among students in STEM fields and to increase their belonging to this field, which has not been clearly defined in the literature, and there is a lack of agreement about the definition of belonging itself. For this purpose, the perspectives of students in England are brought together in this study in an attempt to better understand the concept of STEM belonging within a broader context of integration. The inductive thematic analysis with the voices of socio-demographically diverse 313 A-level, undergraduate and postgraduate Mathematics, Physics, and Chemistry students showed that compared to male students, it was mostly female, non-binary, non-White, and first-generation students who defined STEM belonging as ‘Feeling safe and comfortable in the STEM community and settings’. This theme was defined by the participants as the group/community/learning environment in which the individual belongs, the interaction with the people in the field, and the comfort that this participation/interaction creates. Students stressed the importance of creating a supportive and welcoming STEM environment so that individuals can feel at home, as well as a safe and comfortable STEM environment for people of all identities, genders, ethnicities, and backgrounds. Based on the participants’ responses, this study also conceptualised the concept of STEM belonging as having four phases: the ‘adaptation phase’, the ‘integration phase’, the ‘continuum phase’, and the ‘transition phase’. These four phases which comprise the STEM belonging concept are consecutive and interconnected. The study concluded that all human beings are connected in a relational way (either strong or weak) and that the concept of STEM belonging develops as a result of interactions with ‘self’ and ‘others’ who have a shared passion and an interest in STEM fields. Although individuals have intrinsic motivation and individual prompts in STEM fields (i.e. resilience, beliefs in their capacity/ability and curiosity, etc.), social determinants (i.e. receiving adequate support from members of the STEM community, social capital and social cohesion, etc.) also play a significant role in influencing individual’s sense of STEM belonging.",21967822,EDUCATION
10.3389/fonc.2024.1302196,Case report: Tall cell carcinoma with reversed polarity of the breast: an additional case and review of the literature,"Objective: The aim of this report was to comprehensively investigate the clinicopathological features, histological characteristics, and differential diagnosis of tall cell carcinoma with reversed polarity of the breast (TCCRP) to enhance the understanding of this tumour for precise therapeutic interventions.Methods: The clinicopathological characteristics and differential diagnosis of a patient with TCCRP were retrospectively analysed, and a systematic literature review was extracted from relevant published studies on PubMed.Results: All patients included in the study were female, with a median age of 51 years. Microscopically, the tumour cells exhibited a solid papillary growth pattern with tall columnar morphology and reversed nuclear polarity. Immunohistochemistry revealed that the tumours were triple-negative breast cancer (negative for ER, PR, and HER-2), with a low Ki-67 proliferation index. Different degrees of expression were observed for CK7, Calretinin, and S-100 markers; however, CK5/6 showed high expression levels.Conclusions: TCCRP is an uncommon invasive carcinoma subtype found in the breast. Its histological morphology resembles that of tall cell subtype papillary thyroid carcinoma. Accurate diagnosis requires the integration of histomorphological assessment along with immunohistochemistry and molecular genetics analysis.",2234943X,ONCOLOGY
10.3389/fonc.2024.1360899,Bibliometric analysis of breast cancer-related lymphedema research trends over the last 2 decades,"Objective As breast cancer cases rise globally, post-mastectomy lymphedema garners increasing scholarly attention. This study aims to conduct a comprehensive bibliometric analysis of Breast Cancer-Related Lymphedema (BCRL) research from 2003 to 2022, identifying trends and providing global research insights for future studies. Method The literature for this analysis was extracted from the Web of Science (WoS) Core Collection, encompassing 1199 publications, including 702 articles and 101 reviews, totaling 803. Using advanced bibliometric tools such as VOSviewer and CiteSpace, quantitative and visual analyses were performed to map collaboration networks, research clusters, and emerging trends. The search strategy included specific terms related to lymphedema, breast cancer, and BCRL, ensuring a comprehensive representation of the research landscape. Results The bibliometric analysis revealed a steady increase in BCRL publications over the studied period, reaching a peak in 2018. The United States emerged as the leading contributor to BCRL literature, with China also demonstrating a significant presence. Collaboration networks were visualized, showcasing the interconnectedness of institutions and researchers globally. Key research hotspots identified include preventive strategies, complex decongestive therapy, and reconstructive interventions. Conclusion In conclusion, this pioneering bibliometric analysis provides a comprehensive overview of BCRL research trends and collaborations globally. The findings contribute valuable insights into the evolution of the field, highlighting areas of focus and emerging research themes. This study serves as a foundational resource for researchers, clinicians, and policymakers, fostering evidence-based practices and interventions for BCRL in the future.",2234943X,ONCOLOGY
10.3389/fpsyg.2023.1345256,Corrigendum: Compassionate pedagogy for neurodiversity in higher education: a conceptual analysis,[This corrects the article DOI: 10.3389/fpsyg.2023.1093290.].,16641078,PSYCHOLOGY
10.3389/fonc.2024.1327691,"Development and validation of serological dynamic risk score to predict outcome in gastric cancer with adjuvant chemotherapy: a multicentre, longitudinal, cohort study","Background: Baseline serological biomarkers have the potential to predict the benefits of adjuvant chemotherapy in patients with gastric cancer. However, the fluctuating nature of postoperative recurrence risk makes precise treatment challenging. We aimed to develop a risk score in real-time predicting outcomes for postoperative GC patients using blood chemistry tests.Materials and methods: This was a retrospective, multicentre, longitudinal cohort study from three cancer centres in China, with a total of 2737 GC patients in the pTNM stage Ib to III. Among them, 1651 patients with at least two serological records were assigned to the training cohort. Model validation was carried out using separate testing data with area under curve (AUC). The least absolute shrinkage and selection operator (LASSO) and random forest-recursive feature elimination (RF-RFE) algorithm were used to select the parameters.Results: The Cox regression model derived six risk factors to construct a composite score (low-risk: 0-2 score; high risk: 3-6 score), including CEA, CA125, CA199, haemoglobin, albumin, and neutrophil to lymphocyte ratio. The risk score accurately predicted mortality in 1000-time bootstrap (AUROCs:0.658; 95% CI: 0.645, 0.670), with the highest AUROC (0.767; 95% CI: 0.743, 0.791) after 1 year since the gastrectomy. In validation dataset, the risk score had an AUROC of 0.586 (95% CI 0.544, 0.628). Furthermore, patients with high risk at 1 month derived significant clinical benefits from adjuvant chemotherapy (P for interaction <0.0001). Compared with the low-low-low risk group, the low-low-high risk group of the long-term state chain (risk state at baseline, 6 months, 1 year) had the worse OS (HR, 6.91; 95%CI: 4.27, 11.19) and DFS (HR, 7.27; 95%CI: 4.55, 11.63).Conclusion: The dynamic risk score is an accurate and user-friendly serological risk assessment tool for predicting outcomes and assisting clinical decisions after gastrectomy.",2234943X,ONCOLOGY
10.1186/s40359-024-01580-5,A test of pre-exposure spacing and multiple context pre-exposure on the mechanisms of latent inhibition of dental fear: A study protocol,"Background: Latent inhibition occurs when exposure to a stimulus prior its direct associative conditioning impairs learning. Results from naturalistic studies suggest that latent inhibition disrupts the learning of dental fear from aversive associative conditioning and thereby reduces the development of dental phobia. Although theory suggests latent inhibition occurs because pre-exposure changes the expected relevance and attention directed to the pre-exposed stimulus, evidence supporting these mechanisms in humans is limited. The aim of this study is to determine if two variables, pre-exposure session spacing and multiple context pre-exposure, potentiate the hypothesized mechanisms of expected relevance and attention and, in turn, increase latent inhibition of dental fear. Methods: In a virtual reality simulation, child and adult community members (ages 6 to 35) will take part in pre-exposure and conditioning trials, followed by short- and long-term tests of learning. A 100ms puff of 60 psi air to a maxillary anterior tooth will serve as the unconditioned stimulus. Pre-exposure session spacing (no spacing vs. sessions spaced) and multiple context pre-exposure (single context vs. multiple contexts) will be between-subject factors. Stimulus type (pre-exposed to-be conditioned stimulus, a non-pre-exposed conditioned stimulus, and an unpaired control stimulus) and trial will serve as within-subject factors. Baseline pain sensitivity will also be measured as a potential moderator. Discussion: It is hypothesized that spaced pre-exposure and pre-exposure in multiple contexts will increase the engagement of the mechanisms of expected relevance and attention and increase the latent inhibition of dental fear. It is expected that the findings will add to theory on fear learning and provide information to aid the design of future interventions that leverage latent inhibition to reduce dental phobia.",20507283,PSYCHOLOGY
10.3389/fpsyg.2024.1298357,"Collectivism, face concern and Chinese-style lurking among university students: the moderating role of trait mindfulness","Introduction This study focuses on understanding the unique causes and mechanisms of “Chinese-style lurking” on WeChat among university students, within a cultural context that emphasizes collectivism and face concern. The research also looks into the moderating role of trait mindfulness. Methods For the confirmation of these phenomena and to validate the theories, a structural equation model was constructed using the Stress-Strain-Outcome (SSO) theory and mindfulness buffering theory. The model was then tested and validated with data from 1,453 valid online surveys. These data were analyzed using the SmartPLS 4.0 software. Results The results indicate that collectivism increases face concern, which in turn escalates online social anxiety. Face concern completely mediates between collectivism and online social anxiety, creating a serial mediation effect between face concern, online social anxiety, and lurking behavior. Additionally, trait mindfulness was found to negatively modulate the pathways from collectivism to face concern and from online social anxiety to lurking. Discussion The findings underscore the influence of traditional Chinese culture on contemporary students' online behavior and provide a new perspective for understanding social media lurking in an Eastern context. The results suggest that a mindfulness-based approach could be used to mitigate the associated silence and anxiety.",16641078,PSYCHOLOGY
10.1007/s44196-024-00419-6,Graph Convolutional Network with Syntactic Dependency for Aspect-Based Sentiment Analysis,"Aspect-based sentiment analysis (ABSA) aims to mine the sentiment tendencies expressed by specific aspect terms. The studies of ABSA mainly focus on the attention-based approaches and the graph neural network approaches based on dependency trees. However, the attention-based methods usually face difficulties in capturing long-distance syntactic dependencies. Additionally, existing approaches using graph neural networks have not made sufficient exploit the syntactic dependencies among aspects and opinions. In this paper, we propose a novel Syntactic Dependency Graph Convolutional Network (SD-GCN) model for ABSA. We employ the Biaffine Attention to model the sentence syntactic dependencies and build syntactic dependency graphs from aspects and emotional words. This allows our SD-GCN to learn both the semantic relationships of aspects and the overall semantic meaning. According to these graphs, the long-distance syntactic dependency relationships are captured by GCNs, which facilitates SD-GCN to capture the syntactic dependencies between aspects and viewpoints more comprehensively, and consequently yields enhanced aspect features. We conduct extensive experiments on four aspect-level sentiment datasets. The experimental results show that our SD-GCN outperforms other methodologies. Moreover, ablation experiments and visualization of attention further substantiate the effectiveness of SD-GCN.",18756883,AI
10.3389/fpsyg.2024.1330437,Reserve-building as a buffer for depression among individuals living with disability: a longitudinal study of current activities related to brain health,"Aims This study examined whether reserve-building activities are associated with attenuated reported depression among people who were disabled from work due to a medical condition as compared to employed, retired, and unemployed participants. Methods This secondary analysis included 771 individuals who provided data at three time points: baseline (late Spring 2020), follow-up 1 (Spring 2021), and follow-up 2 (Fall 2021). The DeltaQuest Reserve-Building Measure assessed current activities related to brain health. An analysis of variance and Pearson correlation coefficients assessed group differences in reserve-building activity scores. Classification and regression tree (CART) modeling investigated factors associated with higher and lower reported depression by employment group. The random effects (RE) models tested two buffering hypotheses: (1) comparing all groups to the employed group and (2) examining within-group effects. Results Engaging in outdoor activities, exercise, and religious/spiritual activities was associated with reduced depression over time in the overall sample. While disabled participants endorsed lower levels of being Active in the World, Outdoor activities, and Exercise and higher levels of Inner Life and Passive Media Consumption than the other employment groups, more reserve-building activities distinguished depression levels in the disabled group's CART models compared to the others. Among the disabled, unemployed, and retired participants, engaging in any reserve-building activities was also associated with lower depression scores, which was distinct from the employed participants. In the RE models that used the employed group as the reference category, only the disabled group's level of depression was buffered by engaging in creative activities. In the within-group RE models, the disabled group's engagement in Religious/Spiritual, Outdoors, and Games was associated with substantially reduced within-group depression, which was different from the other employment groups. In contrast, reserve-building activities were not implicated at all as buffers for employed participants. Conclusion This study revealed a beneficial effect of reserve-building activities on buffering depression over time during the COVID-19 pandemic, particularly for disabled people. It documented that even if such individuals engaged in lesser amounts of such activities as compared to other employment groups, the buffering effect was substantial. Given the low-cost and accessible nature of reserve-building activities, it would be worthwhile to encourage such activities for disabled individuals.",16641078,PSYCHOLOGY
10.1186/s40594-024-00473-8,Using collaborative autoethnography to investigate mentoring relationships for novice engineering education researchers,"Background: The National Science Foundation Research Initiation in Engineering Formation (RIEF) program aims to increase research capacity in the field by providing funding for technical engineering faculty to learn to conduct engineering education research through mentorship by an experienced social science researcher. We use collaborative autoethnography to study the tripartite RIEF mentoring relationship between Julie, an experienced engineering education researcher, and two novice education researchers who have backgrounds in biomedical engineering—Paul, a biomedical engineering faculty member and major professor to the second novice, Deepthi, a graduate student. We ground our work in the cognitive apprenticeship model and Eby and colleagues’ mentoring model. Results: Using data from written reflections and interviews, we explored the role of instrumental and psychosocial supports in our mentoring relationship. In particular, we noted how elements of cognitive apprenticeship such as scaffolding and gradual fading of instrumental supports helped Paul and Deepthi learn qualitative research skills that differed drastically from their biomedical engineering research expertise. We initially conceptualized our tripartite relationship as one where Julie mentored Paul and Paul subsequently mentored Deepthi. Ultimately, we realized that this model was unrealistic because Paul did not yet possess the social science research expertise to mentor another novice. As a result, we changed our model so that Julie mentored both Paul and Deepthi directly. While our mentoring relationship was overall very positive, it has included many moments of miscommunication and misunderstanding. We draw on Lent and Lopez’s idea of relation-inferred self-efficacy to explain some of these missed opportunities for communication and understanding. Conclusions: This paper contributes to the literature on engineering education capacity building by studying mentoring as a mechanism to support technically trained researchers in learning to conduct engineering education research. Our initial mentoring model failed to take into account how challenging it is for mentees to make the paradigm shift from technical engineering to social science research and how that would affect Paul’s ability to mentor Deepthi. Our experiences have implications for expanding research capacity because they raise practical and conceptual issues for experienced and novice engineering education researchers to consider as they form mentoring relationships.",21967822,EDUCATION
10.1186/s40594-024-00474-7,Systemic advantage has a meaningful relationship with grade outcomes in students’ early STEM courses at six research universities,"Background: Large introductory lecture courses are frequently post-secondary students’ first formal interaction with science, technology, engineering, and mathematics (STEM) disciplines. Grade outcomes in these courses are often disparate across student populations, which, in turn, has implications for student retention. This study positions such disparities as a manifestation of systemic inequities along the dimensions of sex, race/ethnicity, income, and first-generation status and investigates the extent to which they are similar across peer institutions.Results: We examined grade outcomes in a selected set of early STEM courses across six large, public, research-intensive universities in the United States over ten years. In this sample of more than 200,000 STEM course enrollments, we find that course grade benefits increase significantly with the number of systemic advantages students possess at all six institutions. The observed trends in academic outcomes versus advantage are strikingly similar across universities despite the fact that we did not control for differences in grading practices, contexts, and instructor and student populations. The findings are concerning given that these courses are often students’ first post-secondary STEM experiences.Conclusions: STEM course grades are typically lower than those in other disciplines; students taking them often pay grade penalties. The systemic advantages some student groups experience are correlated with significant reductions in these grade penalties at all six institutions. The consistency of these findings across institutions and courses supports the claim that inequities in STEM education are a systemic problem, driven by factors that go beyond specific courses or individual institutions. Our work provides a basis for the exploration of contexts where inequities are exacerbated or reduced and can be used to advocate for structural change within STEM education. To cultivate more equitable learning environments, we must reckon with how pervasive structural barriers in STEM courses negatively shape the experiences of marginalized students.",21967822,EDUCATION
10.3390/ejihpe14030033,Psychological Distress and Behavioral Vigilance in Response to Minority Stress and Threat among Members of the Asian American and Pacific Islander Community during the COVID-19 Pandemic,"Stigmatization, hostility, and violence towards the Asian American and Pacific Islander (AAPI) community have increased sharply during the COVID-19 pandemic. It is important to conduct research to promote understanding of the effects of such stigmatization on the AAPI community. Accordingly, the present study used a combined minority stress and integrated threat framework to examine whether factors related to AAPI identity would moderate the relationship between stigmatization/threat associated with AAPI identity and increased psychological distress and behavioral vigilance. AAPI individuals were recruited online from both Turk Prime and Reddit and completed measures of perceived stigmatization; integrated threat; depression, anxiety, and stress; and behavioral vigilance. Perceptions of stigmatization and threat predicted relevant outcomes both as individual predictors and in multivariate analyses. However, factors relating to the strength of AAPI identification did not moderate the effects of stigmatization and threat on psychological distress and behavioral vigilance, which is a result that failed to support this aspect of the broader conceptual model on which this project was based. Instead, these proposed moderators were themselves predicted by stigmatization and threat variables. The implications of these findings for effective interventions to alleviate the negative consequences of anti-Asian stigmatization are discussed.",22549625,PSYCHOLOGY
10.3390/cancers16050944,Characteristics of Early Pancreatic Cancer: Comparison between Stage 1A and Stage 1B Pancreatic Cancer in Multicenter Clinical Data Warehouse Study,"Background: Little is known about the characteristics of early pancreatic cancer. We aimed to identify the characteristics, clues for early detection, and prognostic factors for early pancreatic cancer by analyzing a large number of patients with stage 1 pancreatic cancer. Methods: A clinical data warehouse that includes databases of all the medical records of eight academic institutions was used to select and analyze patients with pancreatic cancer that had been diagnosed from January 2010 to May 2023. Results: In total, 257 stage 1 pancreatic cancer patients were included. There were 134 men (52%), and the average age was 67.2 ± 9.9 years. Compared to patients with stage 1B pancreatic cancer (2–4 cm), patients with stage 1A pancreatic cancer (≤2 cm) had more tumors in the body and tail than in the head (p = 0.028), more new-onset diabetes and less old diabetes (p = 0.010), less jaundice (p = 0.020), more follow-up of IPMN (intraductal papillary mucinous neoplasm, p = 0.029), and more histories of acute pancreatitis (p = 0.013). The pathological findings showed that stage 1A pancreatic cancer involved more IPMNs (p < 0.001) and lower pancreatic intraepithelial neoplasia (p = 0.004). IPMN was present in all 13 pancreatic tumors that were smaller than 1 cm. In multivariate analysis, positive resection margin (odds ratio [OR] 1.536, p = 0.040), venous invasion (OR 1.710, p = 0.010), and perineural invasion (OR 1.968, p = 0.002) were found to be risk factors affecting disease-free survival, while old diabetes (odds ratio [OS] 1.981, p = 0.003) and perineural invasion (OR 2.270, p = 0.003) were found to be risk factors affecting overall survival. Conclusions: IPMN is closely associated with early pancreatic cancer and may provide an opportunity for early detection. The presence of perineural invasion was a crucial prognostic factor for both overall and disease-free survival in patients with stage 1 pancreatic cancer.",20726694,ONCOLOGY
10.3390/educsci14030246,“Who’s the Student at Home?”: Parental Help-Giving Orientation in Learning at Home Predicted using a Parent’s Personal Characteristics,"The present study focuses on the involvement of a parent in their child’s learning processes, particularly, their help-giving orientation while learning at home. The main goal of the study was to identify the connection between the parent’s personal characteristics and the help-giving orientation the parent provides to their child: autonomous vs. dependent (parent as student) help-giving. The sample was collected using online participant recruitment surveys in Israel. In total, 306 parents aged 27–59, who had at least one child in elementary school, answered five questionnaires measuring the research variables: the short grit scale; the satisfaction with life scale; the advice/affect management–overparenting subscale; the parenting sense of competence scale; the parental help-giving orientations scale (PHGOs), and a background questionnaire. The findings identified negative associations between parental personal characteristics (grit, advice/affect management, well-being) and parent-as-student orientation and positive associations between the parent’s characteristics and parental autonomous help-giving orientation, with all of these effects at least partially mediated by parental self-efficacy (indirect effects). The results provide greater insight into the relationship between a parent’s personal characteristics and their choice of assistance to their child and contribute to the knowledge regarding parental involvement in learning at home and educational contexts in general.",22277102,EDUCATION
10.1007/s44196-024-00427-6,Intelligent Vehicle Violation Detection System Under Human–Computer Interaction and Computer Vision,"In view of the current problems of low detection accuracy, poor stability and slow detection speed of intelligent vehicle violation detection systems, this article will use human–computer interaction and computer vision technology to solve the existing problems. First, the picture data required for the experiment is collected through the Bit Vehicle model dataset, and computer vision technology is used for preprocessing. Then, use Kalman filtering to track and study the vehicle to help better predict the trajectory of the vehicle in the area that needs to be detected; finally, use human–computer interaction technology to build the interactive interface of the system and improve the operability of the system. The violation detection system based on computer vision technology has an accuracy of more than 96.86% for the detection of the eight types of violations extracted, and the average detection is 98%. Through computer vision technology, the system can accurately detect and identify vehicle violations in real time, effectively improving the efficiency and safety of traffic management. In addition, the system also pays special attention to the design of human–computer interaction, provides an intuitive and easy-to-use user interface, and enables traffic managers to easily monitor and manage traffic conditions. This innovative intelligent vehicle violation detection system is expected to help the development of traffic management technology in the future.",18756883,AI
10.3390/ejihpe14030035,No End in Sight; Assessing the Impact of Internet Gaming Disorder on Digital Eye Strain Symptoms and Academic Success,"Background: Internet Gaming Disorder (IGD) has been associated with symptoms of Digital Eye Strain (DES) and poor academic performance among adolescent students. The purpose of this study is to assess whether a student’s achievement of a specific academic goal within a short period of time can be directly predicted by symptoms of IGD and DES. Methods: This is a cross-sectional survey of 140 high school graduates who received an examination of visual acuity as a pre-requisite for entering the written admission examinations of law enforcement and military academies. The students completed the Digital Eye Strain Questionnaire (DESQ) and the Ten-Item Internet Gaming Disorder Test (IGDT-10) and stated their own evaluation of their chances for success. They were contacted following their admission examinations, and their success or failure to be admitted was recorded. Results: The students with IGD symptomatology were more likely to present with symptoms of DES. They were also more pessimistic about their chances of success in the subsequent written admission examinations; none succeeded, while the rest of the students recorded an expected rate of success. A combination of IGD and complaints related to the prolonged fixation of the upper body in a specific viewing position was the best predictor variable set for future success in admission examinations. Conclusions: IGD is associated with a failure to achieve academic success. Combining a factor for physical discomfort during prolonged sessions of gaming with the typical criteria for IGD may expand the predictive validity of the construct of gaming disorder.",22549625,PSYCHOLOGY
10.3390/educsci14030252,The Bidirectional Relationship between Meta-Creativity and Academic Performance in University Students,"Creativity has been studied in relation to academic performance, usually from the perspective of the creative result, with fewer studies focusing on the creative process and the student’s awareness of that process, known as meta-creativity. This study aimed to analyze differences in meta-creativity based on academic performance groups (high or low) and determine the predictive power of meta-creativity belonging to the high or low academic performance groups. A total of 172 university students participated. Meta-creativity was assessed using a Meta-Creativity Questionnaire, which evaluated three dimensions (creative motivation, creative leadership, and divergent thinking). Additionally, academic performance was recorded, allowing for the classification of students based on high and low academic performance. The results of the analysis of variance indicated statistically significant differences between students with high and low academic performance in the three dimensions. Discriminant analysis indicated that the dimensions of meta-creativity were able to predict who belonged to the high and low academic performance groups. The model correctly classified 86.6% of the sample. It can be concluded that academic performance is a good indicator of the level of meta-creativity, and, additionally, meta-creativity has a beneficial effect on academic performance. There is a bidirectional relationship between the two variables.",22277102,EDUCATION
10.3389/fonc.2024.1198555,A systematic review and Bayesian meta-analysis assessing intelectin-1 in cancer patients and healthy individuals,"Background Intelectin-1 (ITLN1) is an adipokine with multiple physiological functions, including a role in tumour formation and development. Previous research reported variable ITLN1 levels for cancer patients and healthy individuals. This study aimed to compare ITLN1 concentrations between controls and cancer patients and to determine the adipokine’s physiological level. Methods Five databases were searched in January 2022 for studies that measured the level of ITLN1 in adults that were healthy or diagnosed with any type of cancer. After title, abstract and full-text screening, the methodological quality of the studies was assessed. The extracted data were meta-analysed using the R language and Bayesian statistical techniques. Results Overall, 15 studies compared circulating ITLN1 levels between healthy individuals (n=3424) and cancer patients (n=1538), but no differences were observed between these studies. ITLN1 was not different between groups in an analysis that evaluated high-quality studies only (n=5). The meta-analysis indicated considerably higher ITLN1 levels in gastrointestinal (i.e., colorectal, pancreatic, gastric) cancer compared to controls, while the other cancer types did not demonstrate differences between groups. The mean ITLN1 level of healthy individuals was 234 ± 21ng/ml (n=136), while the average value in high-quality studies (n=52) was 257 ± 31ng/ml. Conclusion Different types of cancer showed different circulating ITLN1 patterns. Circulating ITLN1 concentration was higher in gastrointestinal cancer compared to controls, with strong support from the meta-analytical model. Our analysis also determined the mean ITLN1 level in healthy individuals; this is a crucial starting point for understanding how this cytokine associates with diseases. Two-thirds of the studies were of low methodological quality and thus, future work in this field must focus on improved methods. Systematic review registration identifier CRD42022303406.",2234943X,ONCOLOGY
10.1186/s40359-024-01612-0,Chinese English language learners’ vocabulary retention: Investigating the effectiveness of neuro/metacognitive and socio-cultural strategies,"The acquisition of a rich vocabulary is foundational to language proficiency. In the pedagogical pursuit of effective vocabulary teaching, educators explore diverse methodologies. Researchers investigated the impact of different neurocognitive, metacognitive, and socio-cultural strategies on enhancing vocabulary learning, particularly among Chinese English Language Learners. The study aims to determine the effectiveness of techniques derived from these theories compared to traditional teaching methods in enhancing vocabulary recall and recognition among English language learners. A quasi-experimental pre-test/post-test design was employed for the experimental and control groups, comprising 90 Chinese EFL learners selected from educational institutions in 2022–2023. The experimental group (n = 45) received instruction involving visual imagery, multisensory rotation, circle rotation, and mind mapping over eight sessions, while the control group (n = 45) received traditional teaching methods. Statistical analysis, utilizing covariance and analysis of variance with SPSS software version 22, revealed significant improvements in recall and vocabulary recognition within and between the experimental and control groups. The results indicate that incorporating techniques based on Neuro-Cognitive, Multimedia, Socio-Cultural, and Metacognitive theories positively influences vocabulary recall and recognition. This suggests the efficacy of these innovative methods in enhancing English language learning, highlighting their potential for broader integration into EFL instruction.",20507283,PSYCHOLOGY
10.3390/cancers16051052,"Impact of Primary Tumor Location on Demographics, Resectability, Outcomes, and Quality of Life in Finnish Metastatic Colorectal Cancer Patients (Subgroup Analysis of the RAXO Study)","The primary tumor location (PTL) is associated with the phenotype, metastatic sites, mutations, and outcomes of metastatic colorectal cancer (mCRC) patients, but this has mostly been studied according to sidedness (right vs. left sided). We studied right colon vs. left colon vs. rectal PTL in a real-life study population (n = 1080). Health-related quality of life (HRQoL) was assessed multi-cross-sectionally with QLQ-C30, QLQ-CR29, EQ-5D, and 15D. A chi-square, Kaplan–Meier, and Cox regression were used to compare the groups. The PTL was in the right colon in 310 patients (29%), the left colon in 396 patients (37%), and the rectum in 375 patients (35%). The PTL was associated with distinct differences in metastatic sites during the disease trajectory. The resectability, conversion, and resection rates were lowest in the right colon, followed by the rectum, and were highest in the left colon. Overall survival was shortest for right colon compared with left colon or rectal PTL (median 21 vs. 35 vs. 36 months), with the same trends after metastasectomy or systemic therapy only. PTL also remained statistically significant in a multivariable model. The distribution of symptoms varied according to PTL, especially between the right colon (with general symptoms of metastases) and rectal PTL (with sexual- and bowel-related symptoms). mCRC, according to PTL, behaves differently regarding metastatic sites, resectability of the metastases, outcomes of treatment, and HRQoL.",20726694,ONCOLOGY
10.1186/s40594-024-00475-6,"Beyond STEM attrition: changing career plans within STEM fields in college is associated with lower motivation, certainty, and satisfaction about one’s career","Background: Research and policy often focus on reducing attrition from educational trajectories leading to careers in science, technology, engineering, and mathematics (STEM), but many students change career plans within STEM. This study examined how changing career plans within STEM fields was associated with psychological indicators of career readiness. We conducted a large online survey of undergraduate students (N = 1,727) across 42 courses covering every major STEM discipline at a large U.S. research-intensive public university. Students reported about their career plans, whether plans had changed, motivation for those career plans, and satisfaction with and certainty of persisting with those plans. A trained team of coders classified whether students reported having STEM career plans at the time of the survey and at the beginning of college. Results: Students who said they had changed career plans within STEM fields during college also reported lower motivation for their new career plans, satisfaction with those plans, and certainty of persisting in them, compared to students who retained consistent STEM career plans. With few exceptions, these associations held across students’ gender, race, year in school, and STEM field of study. Within-STEM career plan changes were very common, reported by 55% of fourth-year STEM students. Women reported changing career plans within STEM fields more often than men. Implications: Results suggest that changing career plans within STEM is an important phenomenon to consider in preparing a qualified and diverse STEM workforce. Students who change career plans within STEM fields may need additional supports for their career motivation and satisfaction compared to students who do not change plans.",21967822,EDUCATION
10.1186/s40359-024-01624-w,"Clinical effectiveness, cost-effectiveness and process evaluation of group schema therapy for eating disorders: study protocol for a multicenter randomized controlled trial","Background: Eating disorders (EDs), such as (atypical) Anorexia (AN) and Bulimia Nervosa (BN), are difficult to treat, causing socioeconomic impediments. Although enhanced cognitive behavioral therapy (CBT-E) is widely considered clinically effective, it may not be the most beneficial treatment for (atypical) AN and BN patients who do not show a rapid response after the first 4 weeks (8 sessions) of a CBT-E treatment. Alternatively, group schema therapy (GST) may be a valuable treatment for this ED population. Even though GST for EDs has yielded promising preliminary findings, the current body of evidence requires expansion. On top of that, data on cost-effectiveness is lacking. In light of these gaps, we aim to describe a protocol to examine whether GST is more (1) clinically effective and (2) cost-effective than CBT-E for (atypical) AN and BN patients, who do not show a rapid response after the first 4 weeks of treatment. Additionally, we will conduct (3) process evaluations for both treatments. Methods: Using a multicenter RCT design, 232 Dutch (atypical) AN and BN patients with a CBT-E referral will be recruited from five treatment centers. Clinical effectiveness and cost-effectiveness will be measured before treatment, directly after treatment, at 6 and at 12 months follow-up. In order to rate process evaluation, patient experiences and the degree to which treatments are implemented according to protocol will be measured. In order to assess the quality of life and the achievement of personalized goals, interviews will be conducted at the end of treatment. Data will be analyzed, using a regression-based approach to mixed modelling, multivariate sensitivity analyses and coding trees for qualitative data. We hypothesize GST to be superior to CBT-E in terms of clinical effectiveness and cost-effectiveness for patients who do not show a rapid response to the first 4 weeks of a CBT-E treatment. Discussion: To our knowledge, this is the first study protocol describing a multicenter RCT to explore the three aforementioned objectives. Related risks in performing the study protocol have been outlined. The expected findings may serve as a guide for healthcare stakeholders to optimize ED care trajectories. Trial registration: clinicaltrials.gov (NCT05812950).",20507283,PSYCHOLOGY
10.3389/fpsyg.2024.1327119,Examining the impact of a restorative breath-based intervention “Sudarshan Kriya Yoga” at work: a field experiment,"Background Human capital plays a crucial role in the success of an organization and further contributes to the broader goals of growth and development of society. In this regard, it is essential to ensure the well-being of employees at the workplace. Given the positive impact of yoga on psycho-physiological aspects of health, this study aims to examine the impact of a breath-based yogic intervention, Sudarshan Kriya Yoga (SKY), on stress, anxiety, thriving, general health, emotional well-being, social well-being, and psychological well-being among employees of a leading manufacturing firm in India. Methods Undertaking a randomized-control experiment design (n = 64), we examined the impact of SKY on stress, anxiety, thriving, general health, and emotional, social, and psychological well-being. Two certified instructors conducted the SKY intervention in a retreat format over 3 days. Results The analysis demonstrated positive outcomes across various aspects of participants’ well-being, i.e., it significantly reduced their stress and anxiety and increased the levels of thriving, general health, and emotional, social, and psychological well-being. These findings are valuable for understanding the potential benefits of the SKY intervention. Discussion The findings provide support for considering SKY as a potential well-being intervention for employers at the workplace and society at large. Further exploration, implementation, and research in diverse contexts will be crucial to fully understand the long-term impact and scalability of the SKY intervention in promoting holistic well-being.",16641078,PSYCHOLOGY
10.3390/ai5010020,Few-Shot Fine-Grained Image Classification: A Comprehensive Review,"Few-shot fine-grained image classification (FSFGIC) methods refer to the classification of images (e.g., birds, flowers, and airplanes) belonging to different subclasses of the same species by a small number of labeled samples. Through feature representation learning, FSFGIC methods can make better use of limited sample information, learn more discriminative feature representations, greatly improve the classification accuracy and generalization ability, and thus achieve better results in FSFGIC tasks. In this paper, starting from the definition of FSFGIC, a taxonomy of feature representation learning for FSFGIC is proposed. According to this taxonomy, we discuss key issues on FSFGIC (including data augmentation, local and/or global deep feature representation learning, class representation learning, and task-specific feature representation learning). In addition, the existing popular datasets, current challenges and future development trends of feature representation learning on FSFGIC are also described.",26732688,AI
10.3390/ejihpe14030039,Technology-Supported Behavior Change—Applying Design Thinking to mHealth Application Development,"Non-communicable diseases are the leading cause of global deaths. The risk of their development and progression is increased by modifiable behavioral risk factors. Yet, despite the known benefits of primary and secondary prevention, people often do not follow recommendations for a healthier lifestyle. To this end, mobile health (mHealth) applications offer features for behavioral interventions. Yet, reported user engagement is often low. The objective of the work presented in this article is thus to evaluate the suitability of Design Thinking (DT) as a means to inform the development of an mHealth application that helps increase long-term engagement, and consequently supports individuals in sustainably changing their lifestyle. Applying the DT approach, key user needs and challenges were investigated and used to design a first low-fidelity mHealth application prototype. Think-Aloud analysis, task completion, and post-test interviews were then used to evaluate the prototype and generate early-stage insights. Subsequently, a structured, retrospective analysis of this process, evaluating the insight-generation potential of each step in the DT process cycle, was used to reflect on its suitability to inform mHealth application development. The respective results highlight (1) the distinct value of the DT method, particularly in the early stages of a development project; (2) the strong need for interdisciplinary collaboration in such projects, so as to capture realistic end-user requirements and improve the overall effectiveness of the application design; and (3) the significance of integrating behavioral change theories into the design of mHealth applications, in order to promote long-term engagement.",22549625,PSYCHOLOGY
10.3390/ejihpe14030040,"The Effects of Nature Exposure Therapies on Stress, Depression, and Anxiety Levels: A Systematic Review","Background: Mental well-being plays a pivotal role within the broader spectrum of health and illness, encompassing factors such as stress, depression, and anxiety. Nature-based therapeutic interventions have emerged as a promising approach to addressing these mental health challenges. This study seeks to assess the impact of these interventions on stress, depression, and anxiety levels. Methods: We conducted an extensive search for randomized clinical trials that examined stress, anxiety, and depression levels. The selected studies underwent a rigorous risk-of-bias assessment following the guidelines outlined in the Cochrane Handbook for Systematic Reviews. Results: Our review encompassed findings from eight publications. Among them, two studies measuring cortisol levels revealed significant differences between the pre-test and post-test measurements within the intervention groups. In two studies that employed the Stress Response Inventory, a significant decrease in stress levels was observed within the intervention groups in contrast to the control groups. However, no significant differences were noted in studies that utilized the Restorative Outcome Scale. In the assessment of anxiety and depression levels, three studies employed the Positive and Negative Affect Schedule, while four studies utilized The Profile of Mood States scale; none of these studies demonstrated significant differences. Conclusions: The current body of evidence offers limited support for advocating nature-based therapeutic interventions as a primary approach to reducing stress, depression, and anxiety.",22549625,PSYCHOLOGY
10.3389/fpsyg.2024.1278996,Cross-level transformation of creativity from entrepreneurs to organizations,"With the intensification of competition in the business environment, organizational creativity is increasingly becoming crucial for organizations to build competitive advantages and promote organizational development. For innovative enterprises, their entrepreneurs largely determine the development orientation of the enterprise. They are one of the most critical factors determining the level of corporate innovation, but there need to be more effective creativity transformation path to pursue innovation development. The findings in this study show that entrepreneurial individual creativity has a significant positive effect on organizational creativity, platform leadership mediates the path of creativity transformation across hierarchical levels, and organizational culture has positive moderating effect between platform leadership and organizational creativity. The study results explain the transformation mechanism of creativity from the entrepreneur's perspective, expand the potential transformation path of organizational creativity, and are instructive for enhancing organizational creativity.",16641078,PSYCHOLOGY
10.3389/fpsyg.2024.1307574,Classic and modern models of self-regulated learning: integrative and componential analysis,"Self-regulated learning (SRL) is considered a construct of great heuristic value and has attracted the attention of numerous researchers and inspired influential theoretical models. The objective of the present study was to provide an up-to-date, comparative and integrated description of the theoretical models of SRL used in current empirical research. For this purpose, we conducted a critical review of the scientific literature referring explicitly to any SRL model and we described, compared and integrated the processes and personal and situational dimensions considered in each model. The models have clearly evolved from focusing on cold self-regulation, conscious activity and individual functioning, to emphasising hot self-regulation and considering implicit activity and interindividual functioning. Among empirical research lines based on the most recent models, the following stand out: detailed analysis of SRL during its progress, the manifestation of SRL in diverse instructional formats and the role of affective/motivational self-regulation.",16641078,PSYCHOLOGY
10.3389/fpsyg.2024.1298104,The ripple effect of strain in times of change: how manager emotional exhaustion affects team psychological safety and readiness to change,"Introduction Managers assume a pivotal role during periods of organizational change, yet there exists a notable gap in our understanding of how their emotional exhaustion may impact their capacity to generate readiness to change within their teams. Grounded in the conservation of resources theory (COR), this study explores the crossover effect of managers’ emotional exhaustion on team readiness to change. We expect this to occur through higher levels of laissez-faire leadership, which impacts the teams’ psychological safety. Methodology Data was gathered within a Canadian governmental organization undergoing two significant changes—cultural change and digitalization—with a specific focus on leadership as a pivotal factor in preparing teams for change. Employing surveys from 372 team members and 62 managers affected by this change, we conducted path analysis to empirically test the proposed model across 74 teams and their respective managers. Results Managers’ emotional exhaustion has a negative indirect effect on team readiness to change. The double mediation pathway implies a positive relationship on laissez-faire leadership, which hinders psychological safety. In turn, psychological safety hampers team readiness to change. Conclusion Managers must invest significant resources to fulfill their roles and responsibilities during strategic change. Those who feel exhausted during change may look for ways to protect some of their resources by reducing the time and energy they invest leading their team. This self-preserving resource strategy has detrimental consequences on teams’ effectiveness during change due to an indirect crossover effect that affects the levels of psychological safety on the team.",16641078,PSYCHOLOGY
10.1007/s44196-024-00430-x,Optimizing Placement and Scheduling for VNF by a Multi-objective Optimization Genetic Algorithm,"Virtual network functions (VNFs) have gradually replaced the implementation of traditional network functions. Through efficient placement, the VNF placement technology strives to operate VNFs consistently to the greatest extent possible within restricted resources. Thus, VNF mapping and scheduling tasks can be framed as an optimization problem. Existing research efforts focus only on optimizing the VNFs scheduling or mapping. Besides, the existing methods focus only on one or two objectives. In this work, we proposed addressing the problem of VNFs scheduling and mapping. This work proposed framing the problem of VNFs scheduling and mapping as a multi-objective optimization problem on three objectives, namely (1) minimizing line latency of network link, (2) reducing the processing capacity of each virtual machine, and (3) reducing the processing latency of virtual machines. Then, the proposed VNF-NSGA-III algorithm, an adapted variation of the NSGA-III algorithm, was used to solve this multi-objective problem. Our proposed algorithm has been thoroughly evaluated through a series of experiments on homogeneous and heterogeneous data center environments. The proposed method was compared to several heuristic and recent meta-heuristic methods. The results reveal that the VNF-NSGA-III outperformed the comparison methods.",18756883,AI
10.3389/fpsyg.2024.1305862,Do you say uh or uhm? A cross-linguistic approach to filler particle use in heritage and majority speakers across three languages,"Filler particles like uhm in English or ähm in German show subtle language-specific differences and their variation in form is related to socio-linguistic variables like gender. The use of fillers in a second language has been shown to differ from monolinguals' filler particle use in both frequency and form in different language contexts. This study investigates the language-specific use of filler particles by bilingual heritage speakers in both their languages, looking at the dominant majority language in the society and their minority heritage language spoken at home. This is done based on heritage Russian and German data and majority German and English data from the RUEG corpus. Language-specific fillers were extracted from the corpus and analyzed for their occurrence and segmental form. The frequency analysis suggests an influence of bilingualism, age group, and formality of the situation on the filler frequency across all languages. The number of filler particles is higher in formal, older, and bilingual speech. The form analysis reveals an effect of language and gender on the type of filler particle. The vocalic-nasal filler particles (e.g., uhm) are more frequently found in German and English and in female speech of these languages. Heritage speakers of Russian in contact with German and English show higher use of vocalic-nasal forms also in their Russian while producing similar gender related patterns to monolingual speakers in both their languages. The higher frequency of filler particles in formal situations, older speakers and in bilingual speech, is discussed related to cognitive load which is assumed to be higher in these contexts while speech style which differs between situations and social groups is also considered as explanation. The higher use of vocalic-nasal filler particles in German and English suggests language specific filler particle preferences also related to the socio-linguistic variable gender in these languages. The results from heritage speakers suggest and influence on filler particle form in their heritage language, while also revealing socio-linguistic usage patterns related to gender which are produced by heritage speakers similarly to monolinguals in their respective language.",16641078,PSYCHOLOGY
10.1007/s00432-024-05655-z,"An investigation of the effect of mindfulness-integrated cognitive behavior therapy on demoralization, body image, and sexual function in Iranian women with breast cancer: a randomized controlled trial","Background: Breast cancer is an extremely unpleasant and unbearable experience that can have a profound impact on a person’s life. Compared to other types of cancer, breast cancer has a more severe psychological impact on women. Purpose: This study aimed to investigate the effect of mindfulness-integrated cognitive behavior therapy on demoralization, body image, and sexual function in Iranian women with breast cancer. Method: A sample of 30 women with breast cancer were randomly divided into intervention and control groups. The research was conducted in the oncology division of Imam Reza Hospital in Kermanshah by the clinical trial method with a two-group pretest–posttest design and a 2 month follow-up. Participants in the intervention group received Mindfulness-integrated cognitive behavior therapy for eight sessions. The intervention was carried out individually in weekly 60 min sessions. While the control group received self-help treatment (through an educational book). A demographic questionnaire, Demoralization Scale (DS-II), Body Image Scale (BIS), and Female Sexual Function Index (FSFI) were used to collect data. For data analysis, means and standard deviations were calculated and repeated measures and the Bonferroni test was conducted using SPSS 26. Results: The results showed the effectiveness of mindfulness-integrated cognitive behavior therapy on demoralization, body image, and sexual function (p < 0.05). Concerning demoralization in the intervention group, the pre-test mean was 16.73 ± 3.33, and it reduced to 11.93 ± 1.49 in the post-test. The body image mean score showed a decreasing trend in the intervention group, from 12.47 ± 1.88 in the pre-test to 8.80 ± 3.21 in the post-test. The mean score for sexual function showed an increasing trend, increasing from 18.06 ± 2.29 in the pre-test to 23.07 ± 0.91 in the post-test. There was no significant difference in the mean score of the post-test compared to the pre-test and follow-up in the control group (p < 0.05). Conclusion: MICBT can be used in conjunction with pharmaceuticals and medical treatments to improve the psychological symptoms of women with breast cancer, according to this study’s results. Trial registration (IRCT20160103025817N6). 2022-04-06.",14321335,ONCOLOGY
10.1007/s44196-024-00431-w,Diagnosis of Gallbladder Disease Using Artificial Intelligence: A Comparative Study,"Gallbladder (GB) disease is a common pathology that needs correct and early diagnosis for the optimum medical treatment. Early diagnosis is crucial as any delay or misdiagnosis can worsen the patient situation. Incorrect diagnosis could also lead to an escalation in patient symptoms and poorer clinical outcomes. The use of Artificial Intelligence (AI) techniques, ranging from Machine Learning (ML) to Deep Learning (DL) to predict disease progression, identify abnormalities, and estimate mortality rates associated with GB disorders has increased over the past decade. To this end, this paper provides a comprehensive overview of the AI approaches used in the diagnosis of GB illnesses. This review compiles and compares relevant papers from the last decade to show how AI might enhance diagnostic precision, speed, and efficiency. Therefore, this survey gives researchers the opportunity to find out both the diagnosis of GB diseases and AI techniques in one place. The maximum accuracy rate by ML was when using SVM with 96.67%, whilst the maximum accuracy rate by DL was by utilising a unique structure of VGG, GoogleNet, ResNet, AlexNet and Inception with 98.77%. This could provide a clear path for further investigations and algorithm’s development to boost diagnostic results to improve the patient’s condition and choose the appropriate treatment.",18756883,AI
10.3390/ejihpe14030046,Duration Perception and Reading in Typically Developing Adults and Adults with Developmental Dyslexia: Implications for Assessment and Intervention,"While the link between beat perception and reading skills is attributed to a general improvement in neural entrainment to speech units, duration perception (DP) is primarily linked to a specific aspect of speech perception, specifially discriminating phonemes of varying lengths. Our previous study found a significant correlation between DP and pseudoword reading in both typically developing (TD) individuals and adults with dyslexia (DD). This suggests that, like beat, DP may also enhance overall speech perception. However, our previous study employed a composite measure that did not discriminate speed from accuracy. In this study, we sought to replicate the link between DP and pseudoword reading in a new sample and explore how it might vary depending on the reading parameter being measured. We analyzed the performance of 60 TD vs. 20 DD adults in DP, word reading and pseudoword reading tasks, analyzing the latter for both speed and accuracy. Indeed, duration skills correlated positively with pseudoword reading accuracy. In TD adults, there was no association between DP and reading speed, whereas DD individuals exhibited slower reading speed alongside improved duration skills. We emphasize the potential usefulness of DP tasks in assessment and early intervention and raise new questions about compensatory strategies adopted by DD adults.",22549625,PSYCHOLOGY
10.1007/s00432-024-05642-4,Diffusion-weighted imaging-based radiomics model using automatic machine learning to differentiate cerebral cystic metastases from brain abscesses,"Objectives: To develop a radiomics model based on diffusion-weighted imaging (DWI) utilizing automated machine learning method to differentiate cerebral cystic metastases from brain abscesses. Materials and methods: A total of 186 patients with cerebral cystic metastases (n = 98) and brain abscesses (n = 88) from two clinical institutions were retrospectively included. The datasets (129 from institution A) were randomly portioned into separate 75% training and 25% internal testing sets. Radiomics features were extracted from DWI images using two subregions of the lesion (cystic core and solid wall). A thorough image preprocessing method was applied to DWI images to ensure the robustness of radiomics features before feature extraction. Then the Tree-based Pipeline Optimization Tool (TPOT) was utilized to search for the best optimized machine learning pipeline, using a fivefold cross-validation in the training set. The external test set (57 from institution B) was used to evaluate the model’s performance. Results: Seven distinct TPOT models were optimized to distinguish between cerebral cystic metastases and abscesses either based on different features combination or using wavelet transform. The optimal model demonstrated an AUC of 1.00, an accuracy of 0.97, sensitivity of 1.00, and specificity of 0.93 in the internal test set, based on the combination of cystic core and solid wall radiomics signature using wavelet transform. In the external test set, this model reached 1.00 AUC, 0.96 accuracy, 1.00 sensitivity, and 0.93 specificity. Conclusion: The DWI-based radiomics model established by TPOT exhibits a promising predictive capacity in distinguishing cerebral cystic metastases from abscesses.",14321335,ONCOLOGY
10.3390/ejihpe14030047,Examining Students’ Acceptance and Use of ChatGPT in Saudi Arabian Higher Education,"This study examines students’ acceptance and use of ChatGPT in Saudi Arabian (SA) higher education, where there is growing interest in the use of this tool since its inauguration in 2022. Quantitative research data, through a self-reporting survey drawing on the “Unified Theory of Acceptance and Use of Technology” (UTAUT2), were collected from 520 students in one of the public universities in SA at the start of the first semester of the study year 2023–2024. The findings of structural equation modeling partially supported the UTAUT and previous research in relation to the significant direct effect of performance expectancy (PE), social influence (SI), and effort expectancy (EE) on behavioral intention (BI) on the use of ChatGPT and the significant direct effect of PE, SI, and BI on actual use of ChatGPT. Nonetheless, the results did not support earlier research in relation to the direct relationship between facilitating conditions (FCs) and both BI and actual use of ChatGPT, which was found to be negative in the first relationship and insignificant in the second one. These findings were because of the absence of resources, support, and aid from external sources in relation to the use of ChatGPT. The results showed partial mediation of BI in the link between PE, SI, and FC and actual use of ChatGPT in education and a full mediation in the link of BI between EE and actual use of ChatGPT in education. The findings provide numerous implications for scholars and higher education institutions in SA, which are also of interest to other institutions in similar contexts.",22549625,PSYCHOLOGY
10.3390/cancers16061189,Early Onset of Lung Cancer in Small Areas as a Signature of Point Pollution Sources,"The impact of air pollution on lung cancer (LC) is difficult to detect in low-populated areas due to the potentially unfocused detection of pollutants and/or limited statistical power. This study identified and measured the harmful effect of pollution in small areas by considering the early onset of LC as a signature of pollution. This novel method requires a Bayesian standard curve calculated from the median age at LC onset and the corresponding median age of reference populations. Similar medians gathered from the area/s under investigation permits a probabilistic comparison with the standard curve. Statistically significant divergences can be interpreted as early or late LC onset. The method is exemplified in the Trieste municipality (northeast Italy) using data from the Friuli Venezia Giulia Cancer Registry (study population) and from the International Agency for Research on Cancer (reference population). Early LC onset has been observed near the pollution sources. Within 600 m of the iron foundry, onset ranged between 3.2 and 7.7 years earlier in men and between 11.7 and 16.8 years earlier in women. Near the shipyard, early onset was around 4 years in men and 7 years in women, while in the industrial area, early onset was 5 years in women only. Examining early LC onset may speed up the investigation of potential environmental hazards.",20726694,ONCOLOGY
10.3390/cancers16061195,CD44 in Bladder Cancer,"The glycoprotein CD44, with its many isoforms and variations in carbohydrate patterning, participates in a diverse set of cellular functions. This fact leads to the protein playing a role in many normal and pathologic cellular processes including a role in cancer progression and metastasis. These same facts make CD44 a strong therapeutic target in many cancer types, including bladder cancer.",20726694,ONCOLOGY
10.1007/s44196-024-00447-2,Retraction Note: Dual Siamese Anchor Points Adaptive Tracker with Transformer for RGBT Tracking,,18756883,AI
10.1186/s40594-024-00471-w,Promoting STEM learning perseverance through recognizing communal goals: understanding the impact of empathy and citizenship,"Background: Previous research has indicated that placing emphasis on communal goals within the field of science, technology, engineering, and mathematics (STEM) education can yield beneficial learning outcomes. However, there remains a relative dearth of investigation into the factors that contribute to the success of STEM education programs integrating communal goals. In the present study, we sought to explore the roles of two constructs that prioritize the interests of others, namely empathy and citizenship, in promoting STEM learning perseverance within the context of a STEM-based community service learning (CSL) program. Specifically, we proposed that empathy would be associated with STEM learning perseverance through its relationship with citizenship, within a sample of 275 secondary school students from Hong Kong who participated in the said program. Results: Using structural equation modeling (SEM), the results revealed that empathy is significantly and positively associated with STEM learning perseverance, both directly and indirectly, through citizenship. The results held even after controlling for the demographic variables of school membership, gender, and age. Conclusions: This research highlights the association between understanding the needs of the community (empathy) and students' desire for community involvement (citizenship), which subsequently influences their perseverance in STEM learning. This relationship is particularly pronounced in educational settings where communal goals are emphasized.",21967822,EDUCATION
10.3389/fonc.2024.1348288,"Assessment of knowledge and perceptions of human papillomavirus vaccine and its determinants among women who have eligible daughters in Debre Berhan City, Ethiopia: a cross-sectional study","Introduction Globally, cervical cancer(CC) is the second most commonly diagnosed cancer and the fourth leading cause of cancer-related deaths in women. Human papillomavirus (HPV) infection is the leading cause of CC. Persistent infection with HPV accounts for 90% of all CC cases. The human papillomavirus vaccine has the great potential to prevent HPV-related infections for millions of women and men. The current study aimed to assess knowledge and perceptions towards the HPV vaccine and its determinants among women who have eligible daughters in Debre Berhan City, Ethiopia. Methods A cross-sectional study was conducted from April 2, 2023, to May 15, 2023. A multistage sampling procedure was used to recruit 607 women participants. Descriptive statistics were used to summarize socio-demographic data. Univariable and multivariable binary logistic regression analyses were performed to measure the associations between the dependent and independent variables. A p-value of <0.05 was considered statistically significant. Results More than three-fourths of the participants, 479 individuals (80%) were currently married, and 243(40.1%) had a diploma or higher education level. Of 456(75.12) participants reported, they had information about cervical cancer. For 449(73.9%) of the participants, television was the main evidence. The majority of 352(59.99%) participants knew the HPV vaccine could be offered to a female child aged 9-14 years old. Only 215(35.4%) participants think the HPV vaccine was safe and effective. Women who had a degree and above educational level were about 9 times more likely to have good knowledge about the HPV vaccine than study participants who did not read and write (AOR=9.21; 95% CI=2.82-12.16; p=0.004). Women who did not have information about the HPV vaccine before this study were about 80% less likely to have a positive perception of the HPV vaccine than participants who had earlier information about the HPV vaccine (AOR=0.8; 95%CI=0.63-0.49; P=003). Conclusion Women had poor knowledge and perceptions about the HPV vaccine. Maternal marital status, age, and having information about the HPV vaccine were the only predictors of women’s knowledge of the HPV vaccine.",2234943X,ONCOLOGY
10.3390/ejihpe14030048,Validation of the Gaming Skills Questionnaire in Adolescence: Effects of Gaming Skills on Cognitive and Affective Functioning,"Given the widespread popularity of videogames, research attempted to assess their effects on cognitive and affective abilities, especially in children and adolescents. Despite numerous correlational studies, robust evidence on the causal relationship between videogames and cognition remains scarce, hindered by the absence of a comprehensive assessment tool for gaming skills across various genres. In a sample of 347 adolescents, this study aimed to develop and validate the Gaming Skill Questionnaire (GSQ) and assess the impact of gaming skills in six different genres (sport, first-person shooters, role-playing games, action-adventure, strategy, and puzzle games) on cognitive and affective abilities of adolescents. The GSQ exhibited strong reliability and validity, highlighting its potential as a valuable tool. Gaming skills positively affected executive function, memory, overall cognition, cognitive flexibility, and emotion recognition, except for empathy. Various game genres had different effects on cognitive and affective abilities, with verbal fluency influenced mainly by sports, executive functions by action, strategy, and puzzle, and emotion recognition positively impacted by action and puzzle but negatively by sports and strategy games. Both age and gaming skills influenced cognitive flexibility, with gaming having a greater effect. These intriguing genre-specific effects on cognitive and affective functioning postulate further research with GSQ’s contribution.",22549625,PSYCHOLOGY
10.3390/ai5010021,Single Image Super Resolution Using Deep Residual Learning,"Single Image Super Resolution (SSIR) is an intriguing research topic in computer vision where the goal is to create high-resolution images from low-resolution ones using innovative techniques. SSIR has numerous applications in fields such as medical/satellite imaging, remote target identification and autonomous vehicles. Compared to interpolation based traditional approaches, deep learning techniques have recently gained attention in SISR due to their superior performance and computational efficiency. This article proposes an Autoencoder based Deep Learning Model for SSIR. The down-sampling part of the Autoencoder mainly uses 3 by 3 convolution and has no subsampling layers. The up-sampling part uses transpose convolution and residual connections from the down sampling part. The model is trained using a subset of the VILRC ImageNet database as well as the RealSR database. Quantitative metrics such as PSNR and SSIM are found to be as high as 76.06 and 0.93 in our testing. We also used qualitative measures such as perceptual quality.",26732688,AI
10.3390/ai5010022,Trust-Aware Reflective Control for Fault-Resilient Dynamic Task Response in Human–Swarm Cooperation,"Due to the complexity of real-world deployments, a robot swarm is required to dynamically respond to tasks such as tracking multiple vehicles and continuously searching for victims. Frequent task assignments eliminate the need for system calibration time, but they also introduce uncertainty from previous tasks, which can undermine swarm performance. Therefore, responding to dynamic tasks presents a significant challenge for a robot swarm compared to handling tasks one at a time. In human–human cooperation, trust plays a crucial role in understanding each other’s performance expectations and adjusting one’s behavior for better cooperation. Taking inspiration from human trust, this paper introduces a trust-aware reflective control method called “Trust-R”. Trust-R, based on a weighted mean subsequence reduced algorithm (WMSR) and human trust modeling, enables a swarm to self-reflect on its performance from a human perspective. It proactively corrects faulty behaviors at an early stage before human intervention, mitigating the negative influence of uncertainty accumulated from dynamic tasks. Three typical task scenarios {Scenario 1: flocking to the assigned destination; Scenario 2: a transition between destinations; and Scenario 3: emergent response} were designed in the real-gravity simulation environment, and a human user study with 145 volunteers was conducted. Trust-R significantly improves both swarm performance and trust in dynamic task scenarios, marking a pivotal step forward in integrating trust dynamics into swarm robotics.",26732688,AI
10.1007/s00432-024-05689-3,Preoperative ultrasound-guided dual localization with titanium clips and carbon nanoparticles for predicting the surgical approach and guiding the resection of Siewert type II esophagogastric junction adenocarcinoma,"Objective: To investigate the superiority of preoperative ultrasound-guided titanium clip and nanocarbon dual localization over traditional methods for determining the surgical approach and guiding resection of Siewert type II adenocarcinoma of the esophagogastric junction (AEG). Method: This study included 66 patients with Siewert type II AEG who were treated at the PLA Joint Logistics Support Force 900th Hospital between September 1, 2021, and September 1, 2023. They were randomly divided into an experimental group (n = 33), in which resection was guided by the dual localization technique, and the routine group (n = 33), in which the localization technique was not used. Surgical approach predictions, proximal esophageal resection lengths, pathological features, and the occurrence of complications were compared between the groups. Result: The use of the dual localization technique resulted in higher accuracy in predicting the surgical approach (96.8% vs. 75.9%, P = 0.02) and shorter proximal esophageal resection lengths (2.39 ± 0.28 cm vs. 2.86 ± 0.39 cm, P < 0.001) in the experimental group as compared to the routine group, while there was no significant difference in the incidence of postoperative complications (22.59% vs. 24.14%, P = 0.88). Conclusion: Preoperative dual localization with titanium clips and carbon nanoparticles is significantly superior to traditional methods and can reliably delineate the actual infiltration boundaries of Siewert type II AEG, guide the surgical approach, and avoid excessive esophageal resection.",14321335,ONCOLOGY
10.3389/fpsyg.2024.1308636,Persisting inhibition biases efficient rule inference under uncertainty,"Introduction Task set inhibition supports optimal switching among tasks by actively suppressing the interference from recently executed competing task sets. It is typically studied in cued task-switching paradigms where there is no uncertainty about the task set or rule to prepare for on each trial. While inhibition has been shown to influence the speed and the accuracy of task execution, affecting task set retrieval, preparation, or implementation in conditions of task set switching, it remains uninvestigated whether it also affects rule selection under uncertainty. Methods We implemented an ad-hoc four-rule card sorting task and categorized the rules selected by participants after a rule shift according to the recency of their last usage. We included a measure of working memory capacity (WMC) to control for its involvement in the rule selection process. Results Participants exhibited a reduced preference for recently abandoned rules than less recently abandoned ones. Furthermore, we found that such a preference was not associated with WMC. Discussion The results suggest that decision-making processes underlying rule inference and selection may be influenced by task-set inhibition, configuring as a conflict adjustment mechanism to the sequential history of rules application.",16641078,PSYCHOLOGY
10.3389/fpsyg.2024.1335536,Eye-movement reveals word order effects on comparative sentences in older adults using a verb-final language,"Objectives This study aimed to examine age-related differences in the comprehension of Korean comparative sentences with varying word orders by employing both offline and online measures, and to investigate how variations in word order affect sentence processing across different age groups. Methods A total of 52 monolingual native Korean speakers, 26 young adults, and 26 older adults, completed a sentence-picture-matching task under two word order conditions: comparative-first and nominative-first. Offline measures included accuracy and response time, while an online method involved eye-tracking within the Visual World Paradigm. Data analyses were performed using linear and generalized linear mixed-effects models. Results Older adults demonstrated lower accuracy and longer response times compared to younger individuals. Distinctive fixation patterns were observed, particularly in the sentential-final phrase, across different age groups. Specifically, nominative-first sentences elicited greater target advantage scores among younger adults, whereas older adults showed higher scores in comparative-first sentences. Conclusion The study highlights the potential of comparative sentences in elucidating age-related changes in sentence comprehension. These differences were evident not only in offline tasks but also in real-time processing, as evidenced by eye-tracking data. The findings suggest distinct processing strategies employed by young and older adults and underscore the importance of considering both syntactic and semantic cues in sentence comprehension.",16641078,PSYCHOLOGY
10.3389/fpsyg.2024.1308098,"Measuring the menu, not the food: “psychometric” data may instead measure “lingometrics” (and miss its greatest potential)","This is a review of a range of empirical studies that use digital text algorithms to predict and model response patterns from humans to Likert-scale items, using texts only as inputs. The studies show that statistics used in construct validation is predictable on sample and individual levels, that this happens across languages and cultures, and that the relationship between variables are often semantic instead of empirical. That is, the relationships among variables are given a priori and evidently computable as such. We explain this by replacing the idea of “nomological networks” with “semantic networks” to designate computable relationships between abstract concepts. Understanding constructs as nodes in semantic networks makes it clear why psychological research has produced constant average explained variance at 42% since 1956. Together, these findings shed new light on the formidable capability of human minds to operate with fast and intersubjectively similar semantic processing. Our review identifies a categorical error present in much psychological research, measuring representations instead of the purportedly represented. We discuss how this has grave consequences for the empirical truth in research using traditional psychometric methods.",16641078,PSYCHOLOGY
10.1007/s00432-024-05650-4,Integrative analysis with machine learning identifies diagnostic and prognostic signatures in neuroblastoma based on differentially DNA methylated enhancers between INSS stage 4 and 4S neuroblastoma,"Introduction: Accumulating evidence demonstrates that aberrant methylation of enhancers is crucial in gene expression profiles across several cancers. However, the latent effect of differently expressed enhancers between INSS stage 4S and 4 neuroblastoma (NB) remains elusive. Methods: We utilized the transcriptome and methylation data of stage 4S and 4 NB patients to perform Enhancer Linking by Methylation/Expression Relationships (ELMER) analysis, discovering a differently expressed motif within 67 enhancers between stage 4S and 4 NB. Harnessing the 67 motif genes, we established the INSS stage related signature (ISRS) by amalgamating 12 and 10 distinct machine learning (ML) algorithms across 113 and 101 ML combinations to precisely diagnose stage 4 NB among all NB patients and to predict the prognosis of NB patients. Based on risk scores calculated by prognostic ISRS, patients were categorized into high and low-risk groups according to median risk score. We conducted comprehensive comparisons between two risk groups, in terms of clinical applications, immune microenvironment, somatic mutations, immunotherapy, chemotherapy and single-cell analysis. Ultimately, we empirically validated the differential expressions of two ISRS model genes, CAMTA2 and FOXD1, through immunochemistry staining. Results: Through leave-one-out cross-validation, in both feature selection and model construction, we selected the random forest algorithm to diagnose stage 4 NB, and Enet algorithm to develop prognostic ISRS, due to their highest average C-index across five NB cohorts. After validations, the ISRS demonstrated a stable predictive capability, outperforming the previously published NB signatures and several clinic variables. We stratified NB patients into high and low-risk group based on median risk score, which showed the low-risk group with a superior survival outcome, an abundant immune infiltration, a decreased mutation landscape, and an enhanced sensitivity to immunotherapy. Single-cell analysis between two risk groups reveals biologically cellular variations underlying ISRS. Finally, we verified the significantly higher protein levels of CAMTA2 and FOXD1 in stage 4S NB, as well as their protective prognosis value in NB. Conclusion: Based on multi-omics data and ML algorithms, we successfully developed the ISRS to enable accurate diagnosis and prognostic stratification in NB, which shed light on molecular mechanisms of spontaneous regression and clinical utilization of ISRS.",14321335,ONCOLOGY
10.3390/educsci14040341,Socio-Economically Disadvantaged Male Students’ Hesitancy to Study Biology in Ireland: Factors Effecting Intent in the Transition to Upper Secondary School,"While it is evident that Ireland has the ambition to widen access to higher education, there are challenges; especially regarding the decision-making process of socio-economically disadvantaged youth when selecting subjects for transition into higher education. This is of particular concern when there are abundant science-related courses in higher education, as well as careers, which are fundamental to the global economy, and a cohort of Ireland’s youth is disadvantaged in choosing this pathway. National statistics highlight the disproportionate participation rate across genders in upper secondary school science education. Extensive research has been invested in exploring supporting female access into male-dominated science fields (e.g., physics) but less so regarding male access into female-dominated science fields (e.g., biology) to achieve gender equity. Thus, this paper uses the Theory of Planned Behaviour as a theoretical framework to examine the possible psychosocial elements affecting the decision-making process of socio-economically disadvantaged male students attending DEIS schools in the Republic of Ireland and their intent to study biology as a subject at the upper secondary school level. Data collected from 344 secondary school-level students from 20 schools across nine Irish counties, and subsequently descriptively analysed, revealed that male students were considerably less likely than female students to choose biology at upper secondary level education. Many male students expressed anxiousness and hopelessness when evaluating the study of biology. Teachers were identified as lead influencers and self-efficacy was highlighted as a significant factor in male affinity to the subject. Finally, higher levels of female students’ intent to study biology at upper second level suggested the familial influence of parents and wider family contributes to their overall perspective on the relevance of science to their future prosperity. Considering the various factors influencing intent, the authors suggest that a targeted pedagogical intervention that includes the promotion of self-efficacy; male student mastery experiences through assessment; emphasis on scientific knowledge; and raising the awareness of the various career pathways that studying biology affords could ameliorate this trend amongst teenage males. Additionally, targeted messaging for parents and the wider family as well as continuous professional development for teachers should be integral to any work conducted in this area.",22277102,EDUCATION
10.1186/s40594-024-00478-3,Prior experiences as students and instructors play a critical role in instructors’ decision to adopt evidence-based instructional practices,"Background: There has been a growing interest in characterizing factors influencing teaching decisions of science, technology, engineering, and mathematics (STEM) instructors in order to address the slow uptake of evidence-based instructional practices (EBIPs). This growing body of research has identified contextual factors (e.g., classroom layout, departmental norms) as primary influencers of STEM instructors’ decision to implement EBIPs in their courses. However, models of influences on instructional practices indicate that context is only one type of factor to consider. Other factors fall at the individual level such as instructors’ past teaching experience and their views on learning. Few studies have been able to explore in depth the role of these individual factors on the adoption of EBIPs since it is challenging to control for contextual features when studying current instructors. Moreover, most studies exploring adoption of EBIPs do not take into account the distinctive features of each EBIP and the influence these features may have on the decision to adopt the EBIP. Rather, studies typically explore barriers and drivers to the implementation of EBIPs in general. In this study, we address these gaps in the literature by conducting an in-depth exploration of individual factors and EBIPs’ features that influence nine future STEM instructors’ decisions to incorporate a selected set of EBIPs in their teaching. Results: We had hypothesized that the future instructors would have different reasoning to support their decisions to adopt or not Peer Instruction and the 5E Model as the two EBIPs have distinctive features. However, our results demonstrate that instructors based their decisions on similar factors. In particular, we found that the main drivers of their decisions were (1) the compatibility of the EBIP with their past experiences as students and instructors as well as teaching values and (2) experiences provided in the pedagogical course they were enrolled in. Conclusions: This study demonstrates that when considering the adoption of EBIPs, there is a need to look beyond solely contextual influences on instructor’s decisions to innovate in their courses and explore individual factors. Moreover, professional development programs should leverage their participants past experiences as students and instructors and provide an opportunity for instructors to experience new EBIPs as learners and instructors.",21967822,EDUCATION
10.1007/s44196-024-00434-7,"Fault Detection, Classification and Localization Along the Power Grid Line Using Optimized Machine Learning Algorithms","Distributed energy generation increases the need for smart grid monitoring, protection, and control. Localization, classification, and fault detection are essential for addressing any problems immediately and resuming the smart grid as soon as possible. Simultaneously, the capacity to swiftly identify smart grid issues utilizing sensor data and easily accessible frequency and voltage data from PMU devices is a prerequisite of this task. Therefore, this paper proposes new methods using fuzzy logic and adaptive fuzzy neural networks as well as machine learning and meta-heuristic algorithms. First, line voltage is used by a fuzzy thresholding method to estimate when a transmission line defect would develop in less than 1.2 clock cycles. Next, features taken from frequency signals in the real-time interval are utilized to classify the type of error using machine learning systems (decision tree algorithm and random forest algorithm) optimized with wild horse meta-heuristic algorithm. To locate the precise problem location, we finally use a neural fuzzy inference system that is capable of adapting to new data. We employ a simulated power transmission system in MATLAB to test our proposed solutions. Mean square error (MSE) and confusion matrix are used to assess the efficiency of a classifier or detector. For the decision tree algorithm method, the detector attained an acceptable MSE of 2.34e−4 and accuracy of 98.1%, and for the random forest algorithm method, an acceptable MSE of 3.54e−6 and accuracy of 100%. Furthermore, the placement error was less than 153.6 m in any direction along the line.",18756883,AI
10.1007/s44196-024-00482-z,Retraction Note: Effectiveness of Mixed Fuzzy Time Window Multi-objective Allocation in E-Commerce Logistics Distribution Path,,18756883,AI
10.1007/s44196-024-00439-2,Hybrid Strategies Based Seagull Optimization Algorithm for Solving Engineering Design Problems,"The seagull optimization algorithm (SOA) is a meta-heuristic algorithm proposed in 2019. It has the advantages of structural simplicity, few parameters and easy implementation. However, it also has some defects including the three main drawbacks of slow convergence speed, simple search method and poor ability of balancing global exploration and local exploitation. Besides, most of the improved SOA algorithms in the literature have not considered the drawbacks of the SOA comprehensively enough. This paper proposes a hybrid strategies based algorithm (ISOA) to overcome the three main drawbacks of the SOA. Firstly, a hyperbolic tangent function is used to adjust the spiral radius. The spiral radius can change dynamically with the iteration of the algorithm, so that the algorithm can converge quickly. Secondly, an adaptive weight factor improves the position updating method by adjusting the proportion of the best individual to balance the global and local search abilities. Finally, to overcome the single search mode, an improved chaotic local search strategy is introduced for secondary search. A comprehensive comparison between the ISOA and other related algorithms is presented, considering twelve test functions and four engineering design problems. The comparison results indicate that the ISOA has an outstanding performance and a significant advantage in solving engineering problems, especially with an average improvement of 14.67% in solving welded beam design problem.",18756883,AI
10.3389/fpsyg.2024.1354129,Exploring a practitioner-athlete relationship and facilitated learning throughout a psychological skills training program,"Psychological skills training (PST) programs have been consistently reported as an important part of preparation for optimal performance in high performance sport. However, there is much less research about the quality and characteristics of the working relationship between a sport psychology practitioner (SPP) and an athlete and, importantly, how that relationship facilitates learning. Therefore, the purpose of the present paper was to explore the working relationship between a SPP and a volleyball player and how that working relationship facilitated the learning processes utilized by this player, as she prepared for the demands of her sport and life. An instrumental case study methodology with a qualitative description approach was employed to illustrate different aspects of the evolving relationship and the athlete’s experiences. The results of this case reflect an approach that combined features of both a directive approach in teaching specific psychological skills and a less directive and more collaborative approach, which, in turn, allowed an athlete to begin to learn how to guide their own learning.",16641078,PSYCHOLOGY
10.3390/educsci14040356,"Centering Educators’ Voices in the Development of Professional Learning for Data-Rich, Place-Based Science Instruction","This self-reflective case study describes our project team’s efforts to promote equity in science professional learning (PL) by centering the voices of educators in the PL design process and within the course itself. We believe that educators’ experiences, priorities, and expertise are essential to developing professional learning that meets the needs of teachers and their students. We have a particular interest in amplifying the voices of those in historically underrepresented communities. Toward that end, we engaged science educators who work with Indigenous students and recent immigrants as collaborators in developing PL to support data-rich, place-based Earth Science instruction. In this case study, we share and critique the practices and tools that we have employed to center educator voices, rather than those of the PL designers and researchers. Our strategies for developing more equitable science professional learning include the use of: (a) equity-focused research methods, such as asset-based needs-sensing questions and peer-to-peer interviews; (b) a humanistic stance toward data-rich science learning, which emphasizes the typically unnamed sociocultural inputs and outputs that permeate all aspects of data; (c) a participatory design process that centers educators’ voices; and (d) a model of professional learning that uses representations of educator and student experiences as objects for reflection.",22277102,EDUCATION
10.3390/ejihpe14040056,The Moderating Effect of Body Appreciation on the Relationship between Self-Esteem and Life Satisfaction,"Background: Although positive associations between life satisfaction, self-esteem, and body image have previously been established, differences in these variables by gender and age have yielded mixed results. Moreover, little is known about the interplay between self-esteem and body appreciation on life satisfaction. This study aims to investigate the moderating effect of body appreciation on the relationship between self-esteem and life satisfaction, considering disparities between females and males and also between emerging adults (before the age of thirty) and older adults. Methods: A cross-sectional online survey was performed in Poland with a sample of 449 adults aged between 18 and 75 (M = 30.41, SD = 12.72), including 68% of women. The survey included the Satisfaction With Life Scale (SWLS), Rosenberg Self-Esteem Scale (RSES), and Body Appreciation Scale (BAS-2). Results: Men scored higher than women in terms of life satisfaction and self-esteem, while older participants (age > 30) scored higher than younger individuals (age ≤ 30) in terms of life satisfaction, self-esteem, and body appreciation. The study confirmed positive and moderate correlations between life satisfaction, self-esteem, and body appreciation. The interactive effect of self-esteem and body appreciation on life satisfaction was also found by controlling for age and gender. Conclusions: Some intervention programs focused on increasing levels of self-esteem and body appreciation should be implemented, especially among women and emerging adults, to improve their well-being.",22549625,PSYCHOLOGY
10.1007/s00432-024-05638-0,Decision regret of cancer patients after radiotherapy: results from a cross-sectional observational study at a large tertiary cancer center in Germany,"Purpose: The decision-making process regarding cancer treatment is emotionally challenging for patients and families, harboring the risk of decision regret. We aimed to explore prevalence and determinants of decision regret following radiotherapy. Methods: This cross-sectional observational study was conducted at a tertiary cancer center to assess decision regret following radiotherapy. The study employed the German version of the Ottawa Decision Regret Scale (DRS) which was validated in the study population. Decision regret was categorized as absent (0 points), mild (1–25 points), and strong (> 25 points). Various psychosocial outcome measures were collected using validated questionnaires to identify factors that may be associated with decision regret. Results: Out of 320 eligible patients, 212 participated, with 207 completing the DRS. Median age at start of radiotherapy was 64 years [interquartile range (IQR), 56–72], genders were balanced (105 female, 102 male), and the most common cancer types were breast (n = 84; 41%), prostate (n = 57; 28%), and head-and-neck cancer (n = 19; 9%). Radiotherapy was applied with curative intention in 188 patients (91%). Median time between last radiotherapy fraction and questionnaire completion was 23 months (IQR, 1–38). DRS comprehensibility was rated as good or very good by 98% (196 of 201) of patients. Decision regret was reported by 43% (n = 90) as absent, 38% (n = 78) as mild, and 18% (n = 38) as strong. In the multiple regression analysis, poor Eastern Cooperative Oncology Group performance status, low social support, and dissatisfaction with care were independent risk factors for higher decision regret after radiotherapy. Conclusions: The German version of the DRS could be used to assess decision regret in a diverse cohort of cancer patients undergoing radiotherapy. Decision regret was prevalent in a considerable proportion of patients. Further studies are necessary to validate these findings and obtain causal factors associated with decision regret after radiotherapy.",14321335,ONCOLOGY
10.1007/s00432-024-05694-6,"Overexpression of Transmembrane Phosphatase with Tensin homology (TPTE) in prostate cancer is clinically significant, suggesting its potential as a valuable biomarker","Purpose Cancer testis antigens (CTAs) are a family of proteins typically expressed in male testicles but overexpressed in various cancer cell types. Transmembrane Phosphatase with Tensin homology (TPTE) is expressed only in the testis of healthy individuals and is a member of the family of CTAs. The current study, for the first time, examined the significance of TPTE expression in prostate cancer (PCa) tissues by generating a novel antibody marker targeting TPTE protein. Methods Polyclonal antibodies were prepared for TPTE-p1 and TPTE-p2 peptides, which are derived from the extracellular domains of TPTE. Anti-TPTE-p2 antibody was then used to study the extent and pattern of TPTE expression in 102 PCa and 48 benign prostatic hyperplasia (BPH) tissue samples by immunohistochemistry. The viability of cancer cell lines (PC-3 and MCF-7 cells) was also evaluated in the presence of anti-TPTE-p2 antibody using the MTT test. Results The immunohistochemical analysis demonstrated a significant increase in cytoplasmic and membrane TPTE expression in the PCa samples compared to the BPH group (both P < 0.0001). Cytoplasmic TPTE expression was positively correlated with Gleason score and PSA levels (P = 0.03 and P = 0.001, respectively). Significant correlations were identified between the levels of PSA and perineural invasion and the membrane expression (P = 0.01, P = 0.04, respectively). Moreover, anti-TPTE-p2 antibody inhibited PC-3 and MCF-7 cells proliferation compared to the control group for 24 h (P < 0.001 and P = 0.001, respectively) as well as for 48 h (P = 0.001 and P = 0.001, respectively). Conclusion Our findings indicate that increased TPTE expression is associated with progression of disease. The ability of anti-TPTE-p2 antibody to recognize and target the TPTE protein makes it a potential biomarker to assess and/or target the PCa.",14321335,ONCOLOGY
10.3390/educsci14040367,"Impact of Gamification on Students’ Learning Outcomes and Academic Performance: A Longitudinal Study Comparing Online, Traditional, and Gamified Learning","This study aims to examine the influence of gamification in students’ learning outcomes and academic performance. A longitudinal study was conducted to compare students’ academic performance in online learning (2020–2021), traditional learning (2021–2022), and gamified learning (2022–2023). The longitudinal study lasted 3 years and a total of 1001 higher education students were involved. Three research questions were set to be explored and students’ viewpoints and experiences were also examined through a questionnaire of 20 questions. This study follows a quantitative research approach. The data refers to students’ academic performance, success rate, excellence rate, withdrawal rate, engagement, motivation, and perspectives. In the laboratory part of the course, gamified learning yielded better outcomes over online learning and traditional learning in success rate (39% and 13%), excellence rate (130% and 23%), average grade (24% and 11%), and retention rate (42% and 36%) respectively. In the theoretical part of the course, gamified learning resulted in better outcomes over online learning and traditional learning in success rate (19% and 14%), in excellence rate (125% and 79%), and in average grade (25% and 12%) respectively. In the overall course, gamified learning yielded better outcomes over online learning and traditional learning in success rate (14% and 14%), in excellence rate (122% and 70%), and in average grade (25% and 17%) respectively. The highest increase was observed in students’ excellence rate. Students highly regarded gamification as an effective educational approach that can increase their learning outcomes, engagement, productivity, and motivation and trigger both their both intrinsic and extrinsic motivation. The learning experience become more enjoyable and students’ basic needs in terms of autonomy, competence and sufficiency, and relatedness and sense of belonging were met. Traditional learning also resulted in better learning outcomes when compared to online learning. Gamification emerged as an effective learning approach which leads to improved learning outcomes and academic performance, learning motivation, engagement, and retention rate over online learning and traditional learning in both theoretical and applied course settings.",22277102,EDUCATION
10.1186/s40359-024-01691-z,A brief version of the Attitudes to Ageing Questionnaire for older Chinese adults: development and psychometric evaluation,"Background: Positive attitudes toward aging are considered essential for achieving psychological well-being in later life. However, there is currently a lack of a concise and comprehensive measurement tool specifically designed to assess attitudes toward aging among the elderly population in China. To address this gap, the present study aimed to develop a brief version of the Attitudes to Ageing Questionnaire tailored to older Chinese individuals and evaluate its psychometric properties. Methods: Initially, a sample of community-dwelling older adults (Sample 1: n = 442, aged 60–88) was utilized to establish a new scale format. Subsequently, two convenience samples (Sample 2: n = 311, aged 60–90; Sample 3: n = 164, aged 60–89) were employed to evaluate the psychometric properties of this scale, including factor structure, internal consistency, test-retest reliability, convergent validity, and discriminant validity. Results: We selected 12 items from the original questionnaire to create the brief scale. The brief scale maintained the three-factor structure of the full-format version, encompassing psychosocial loss, physical change, and psychological growth, and demonstrated adequate psychometric properties. Conclusions: This development process shortens the administration time of the questionnaire while avoiding excessive loss of information. The newly developed scale serves as a reliable and valid assessment tool for measuring attitudes toward aging among older Chinese individuals and is well-suited for implementation in large-scale surveys that utilize an extensive array of questionnaires. This tool can be applied to assessing the effectiveness of interventions aimed at eliminating ageism.",20507283,PSYCHOLOGY
10.1007/s44196-024-00457-0,Analysis of English Classroom Teaching Behavior Mode in Environmental Protection Field Based on Deep Learning,"Learning is to use algorithms to enable machines to learn rules from a large amount of historical data, so as to intelligently identify new samples or predict the future. Deep learning can promote students’ understanding of knowledge, conduct in-depth processing of new knowledge, integrate it with the original knowledge, and apply it to new situations, solve intelligent audio–visual listening from the perspective of deep learning, and focus on cultivating students’ in-depth learning ability and individual differences in innovative thinking. As the main position of ecological education, schools should effectively strengthen the publicity and education of ecological ideas and low-carbon concepts, and integrate them into education and teaching to effectively improve students’ awareness of environmental protection. This study aims to explore the effectiveness of flipped classroom teaching model based on deep learning. Therefore, from the perspective of deep learning, this paper combs the theory of deep learning, constructs a new model of smart classroom, and provides ideas and directions for model reform. In this study, the flipped classroom teaching model based on deep learning was applied to English teaching, and an 8-week teaching experiment was conducted. In addition, this paper believes that it is of great practical significance to carry out environmental protection education with the help of English teaching.",18756883,AI
10.1186/s40594-024-00480-9,When perceived similarity overrides demographic similarity: examining influences on STEM students’ developmental mentor networks,"Background: While dyadic faculty–mentored relationship research currently saturates the mentoring literature, recent developments suggest the need for a broader consideration of a student's mentor network. Research taking a network approach may provide deeper insights into the formation and benefits of mentorship for undergraduate students in science, technology, engineering, and mathematics (STEM) disciplines. Utilizing Developmental Mentor Network Theory and ego-centric social network analysis, this pre-registered study evaluates how the characteristics of mentees and mentors relate to both the content of support and structure of mentor networks in a large sample of White and Hispanic/Latino(a) STEM undergraduates across 12 universities. Results: Results were nuanced but showed that perceived psychological similarity with their mentor(s) predicted both dyadic and network average levels of mentor support (i.e., psychosocial, career, role modeling) and relational satisfaction. Furthermore, results point to homophily and engagement in undergraduate research effects on mentor network structures. Conclusions: These findings highlight the importance of using a network approach to deepen our understanding of the factors (e.g., psychological similarity) that may influence the formation and maintenance of robust and diverse supportive mentoring networks.",21967822,EDUCATION
10.3389/fpsyg.2024.1325600,The strength of conspiracy beliefs versus scientific information: the case of COVID 19 preventive behaviours,"Controlling the spread of COVID-19 requires individuals to adopt preventive behaviours, but conspiracy beliefs about its origin are spreading. The aim of this paper is to better comprehend the strength of conspiracy beliefs versus objective COVID-19 information to predict people’s adherence to protective behaviours (getting vaccinated, being tracked through APPs, and keeping social distance from infected people). Study 1 shows that COVID-19 implicit theories detected in the Pre-study were activated as independent factors that constitute people’s interpretations of the virus origin. These beliefs were related to a lesser intention to engage in preventive behaviours and a higher level of mistrust in institutional information, although some beliefs generate positive expectations about COVID-19 consequences. In Study 2, conducted with a different sample, official COVID-19 information was included as an independent variable, but this new variable did not further explain results. Lastly, Study 3 consisting of both previous samples confirmed that conspiracy beliefs had a direct effect on a lesser willingness to engage in preventive actions, a higher mistrust, and positive expectations about COVID-19 consequences. We conclude that objective COVID-19 information did not buffer the effect of conspiracy beliefs; they interfere with actions to prevent it by taking institutions as scapegoats or complicit with secret powers.",16641078,PSYCHOLOGY
10.3389/fpsyg.2024.1336631,"Predictors of non-suicidal self-injury in adolescents with depressive disorder: the role of alexithymia, childhood trauma, and body investment","Purpose This study analyzes the relationship of alexithymia, childhood trauma, and body investment to non-suicidal self-injury (NSSI) behaviors in adolescents with depressive disorder and whether they have predictive and diagnostic value for non-suicidal self-injury (NSSI) behaviors in adolescents with depressive disorder. Patients and methods A total of 225 patients with a diagnosis of adolescent depressive disorder were included in the study and were divided into two groups according to the DSM-5 criteria: 98 cases without NSSI and 127 cases with NSSI. Compare the demographic data, 24-item Hamilton Depression Scale (HAMD-24), 20-item Toronto Alexithymia Scale (TAS-20), Childhood Trauma Questionnaire-Short Form (CTQ-SF), and Body Investment Scale (BIS) scores between two groups. Binary logistic regression was used to analyze the independent risk factors contributing to NSSI behaviors in adolescents with depression, and establish four predictive models. Based on the models’ predictive probability, the ROC curves were plotted to calculate the value of the predictive diagnostic effect. Results The group without NSSI had lower scores than the group with NSSI on HAMD-24 total score, TAS-20 total score, difficulty identifying feelings, difficulty describing feelings, and externally focused thinking, as well as lower scores on CTQ-SF total score, physical neglect, emotional neglect, physical abuse, and emotional abuse. In contrast, the BIS total score, body image feelings and attitudes, body care, and body protection factor scores were higher for the group without NSSI. The BIS body care factor score and the CTQ-SF emotional abuse factor score were significantly linked with adolescents diagnosed with depressive disorder who exhibited NSSI behaviors. These results provide a good diagnostic model for adolescents with depressive disorder. Conclusion Low levels of body care and childhood emotional abuse may independently contribute to the implementation of NSSI in adolescents with depressive disorder. Body investment and childhood trauma are valuable in diagnosing and predicting NSSI behaviors and should be considered as potentially important factors in clinical treatment.",16641078,PSYCHOLOGY
10.3390/ejihpe14040063,Early Parenting Interactions and First-Time Mothers’ Postnatal Depression and Parental Competence,"Objectives: Schema Therapy, an approach that integrates cognitive-behavioural and attachment principles, helps us understand the impact of early interactions with caregivers on adult mental health. These early interactions can be assessed through Schema Therapy-informed tools; however, these tools have yet to be used with a postnatal population, which represents a period of vulnerability for new mothers. Therefore, the present study aimed to evaluate the impact of positive and negative early parenting interactions on a first-time mother’s mental health and her sense of competence during the postnatal period, using recently revised and newly developed Schema Therapy-informed tools. Design: This is a cross-sectional study. Method: First-time mothers (N = 220) participated in an online survey within 12 months post-birth. Participants completed the Positive Parenting Schema Inventory (PPSI), Young Parenting Inventory—Revised (YPI-R2), Edinburgh Postnatal Depression Scale (EPDS), and Parenting Sense of Competence (PSOC) scale. The data were analysed using hierarchical multiple regression and mediational analysis. Results: Negative early interactions with mothers and fathers led to greater postnatal depressive symptomology, while positive early interactions with mothers led to fewer postnatal depressive symptoms. Mediation analyses revealed that postnatal depressive symptoms mediated early parenting interactions and participants’ sense of parenting competence as a new mother. Conclusions: The protective effects of positive early interactions with caregivers can help first-time mothers’ postnatal emotional adjustment and their sense of competence through diminished postnatal depressive symptoms. However, the enduring effects of negative early interactions with caregivers can contribute to a first-time mother’s risk of developing postnatal depression and negatively affect her sense of parental competence.",22549625,PSYCHOLOGY
10.3390/educsci14040383,Schools’ Challenges in Distance Learning during Emergency Education: Focus Group Methodology,"The present research uses the focus group discussion methodology to report the challenges met by the educational system in distance education during emergency education. It shows the different potentialities of this use. In doing this, it studies the practices used by schools during emergency education. Furthermore, the research verifies the suggestions given by a group of educationists to cope with challenges in emergency education. A focus group of nine participants met in the frame of a Ph.D. course to discuss the issues in which the present research is interested, and the number of discussion sessions was four. The research results indicated that the reasons varied for agreement and disagreement in the FGDs, where these reasons were mostly experience-based, perception-based, affiliation-based, inconsideration-based, compromise-based, and suggestion-based. Moreover, the types of agreement and disagreement were mostly complementary, vis-à-vis agreement-with-objection and agreement-with-advancement. The facilitator performed the following different functions: (1) initiator, (2) caring about the different voices in the FGD, and thus encouraging equity in the FGD, (3) making the discussion smooth, (4) advancing the discussion, (5) and orchestrating the discussion. In addition, the discussion of the participants addressed challenges related to the teachers, to the Ministry of Education, and to the resources. The schools’ and the Ministry of Education’s practices included different actions in an attempt to overcome the challenges of distance education: holding workshops related to distance education, suggesting the schools as places for the teachers to teach their online lessons, and making declarations for the public and families. The suggestions given by the participants to maintain and improve online learning included communicating with the students and holding workshops for the professional development of teachers at regular times. Close relationships between the Ministry of Education, the schools, and the parents were recommended in order to maintain an acceptable level of distance education.",22277102,EDUCATION
10.3389/fpsyg.2024.1254564,Incorporating uncertainty within dynamic interoceptive learning,"Introduction: Interoception, the perception of the internal state of the body, has been shown to be closely linked to emotions and mental health. Of particular interest are interoceptive learning processes that capture associations between environmental cues and body signals as a basis for making homeostatically relevant predictions about the future. One method of measuring respiratory interoceptive learning that has shown promising results is the Breathing Learning Task (BLT). While the original BLT required binary predictions regarding the presence or absence of an upcoming inspiratory resistance, here we extended this paradigm to capture continuous measures of prediction (un)certainty.Methods: Sixteen healthy participants completed the continuous version of the BLT, where they were asked to predict the likelihood of breathing resistances on a continuous scale from 0.0 to 10.0. In order to explain participants' responses, a Rescorla-Wagner model of associative learning was combined with suitable observation models for continuous or binary predictions, respectively. For validation, we compared both models against corresponding null models and examined the correlation between observed and modeled predictions. The model was additionally extended to test whether learning rates differed according to stimuli valence. Finally, summary measures of prediction certainty as well as model estimates for learning rates were considered against interoceptive and mental health questionnaire measures.Results: Our results demonstrated that the continuous model fits closely captured participant behavior using empirical data, and the binarised predictions showed excellent replicability compared to previously collected data. However, the model extension indicated that there were no significant differences between learning rates for negative (i.e. breathing resistance) and positive (i.e. no breathing resistance) stimuli. Finally, significant correlations were found between fatigue severity and both prediction certainty and learning rate, as well as between anxiety sensitivity and prediction certainty.Discussion: These results demonstrate the utility of gathering enriched continuous prediction data in interoceptive learning tasks, and suggest that the updated BLT is a promising paradigm for future investigations into interoceptive learning and potential links to mental health.",16641078,PSYCHOLOGY
10.3389/fpsyg.2024.1340456,"Effects of Baduanjin practice on emotional, attention and cognitive function in acupuncturists: protocol for a clinical randomized controlled neuroimaging trial","Background In Chinese medicine, the mental focus and emotional stability of acupuncturists are key to optimal clinical outcomes. Many renowned acupuncturists utilize Traditional Chinese Qigong practices to enhance their concentration and emotional regulation abilities. Nevertheless, the existing literature lacks comprehensive evidence addressing this matter. Methods This study will enroll 99 acupuncturists and randomly allocate them to one of three groups: Baduanjin, aerobic exercise, or a waiting-list control. The Baduanjin group will undertake 24 weeks of training, with three one-hour sessions weekly. The aerobic group will engage in brisk walking for the same duration and frequency. The control group will not receive any specific training. Assessments of emotion regulation, attention, cognitive functions, finger sensation, and athletic ability will be conducted at baseline (−1 week), mid-intervention (12 weeks), and post-intervention (24 weeks). Additionally, 20 participants from each group will undergo fMRI scans before and after the intervention to explore brain functional and structural changes relating to emotion, attention, cognition, motor skills, and sensory perception. Discussion This study aims to contribute valuable insights into the effectiveness of Qigong practice, specifically Baduanjin, in enhancing emotional regulation, attention, and cognitive functions in acupuncturists and to investigate the neuroimaging mechanisms behind these effects. Ethics and dissemination Approved by the Sichuan Regional Ethics Review Committee on Traditional Chinese Medicine (No. 2023KL − 118) and adhering to the Declaration of Helsinki. Results will be shared through policy briefs, workshops, peer-reviewed journals, and conferences. Clinical trial registration www.chictr.org.cn, ChiCTR2300076447.",16641078,PSYCHOLOGY
10.3390/cancers16071425,The Impact of Adjunct Medical Therapy on Survival after Spine Metastasis: A Systematic Review and Pooled Data Analysis,"Targeted therapy has greatly improved the outlook for patients with spinal metastatic cancers. Scoring systems like the Tokuhashi or Tomita scores are commonly used to predict prognosis and inform surgical decisions, but they are outdated and fail to consider recent advancements. We aimed to investigate the current state of the literature and treatment options pertaining to advancements in targeted therapy compared to other forms of medical management for metastatic spinal tumors. This study represents the first comprehensive systematic review that encompasses the most common primary cancers that metastasize to the spine and evaluates the median overall survival (mOS) across five different medical treatment modalities as well as surgical intervention. Additionally, our study analyzes the tumor receptor status in conjunction with these treatments. A PubMed search was conducted, and according to the PRISMA guidelines, 28 articles out of 1834 met the inclusion criteria. The pooled data analysis highlighted the superior efficacy of targeted therapy, evidenced by a significant improvement in the mOS and lower hazard ratios in patients with lung and breast cancers who received targeted therapy compared to those who did not. Our study provides valuable insights into the recent advancements in the medical management of metastatic spinal tumors. Future indications include incorporating this literature into personalized treatment approaches for metastatic spinal tumors.",20726694,ONCOLOGY
10.1007/s44196-024-00438-3,A Manta-Ray Hill Climbing Vision Transformer Model for Predicting Ischemic Stroke Outcome,"An ischemic stroke attack can cause permanent damage to healthy brain tissue, leading to a permanent loss of motor or sensory function. It can also result in disability or death if not diagnosed and treated promptly. Early prediction of the outcome of the first stroke, such as disability or death, can help many patients by administering appropriate medications to save their lives. Additionally, early prediction of a recurrent stroke within 14 days of the initial stroke can contribute to prevent its recurrence. This paper first proposes a modified Manta-Ray Foraging Optimizer (MMRFO) to enhance the characteristics of the MRFO technique. This approach is based on incorporating the Hill Climbing methodology into the original MRFO in order to improve the exploitation phase, which is responsible for locating the promising zone in the search area. The proposed approach is then utilized to determine the appropriate hyperparameters of the Vision Transformer(ViT) model to predict stroke outcomes prior to its occurrence. To transform categorical data to numerical values, an ASCII encoder module is included. In the feature selection step, the Harris Hawk Optimization approach (HHO) is used to identify the most important elements that may define the stroke. A comparative study has been performed to confirm the effectiveness of the proposed methodology. The results demonstrate that the proposed technique with a Vision Transformer achieves superior results compared to state-of-the-art algorithms. The accuracy of the proposed technique was improved to 87% for the first dataset and 83% for the second, which is clearly superior to that of the other models and earlier research.",18756883,AI
10.1007/s00432-024-05703-8,Safety and clinical efficacy of immune checkpoint inhibitors in advanced gastric cancer in the real world,"Background: To evaluate the clinical efficacy and safety of immune checkpoint inhibitors in patients with advanced gastric cancer in the real world. Methods: The retrospective analysis was conducted on the clinical records of 402 patients with advanced gastric cancer who were admitted to the Nanjing Drum Tower Hospital between December 2017 and April 2022 and who had received immunotherapy. Observation target: drug use, treatment, adverse reaction type and grade, objective response rate (ORR), disease control rate (DCR), progression free survival (PFS), and overall survival (OS). Results: By retrospectively analyzing the data of patients with advanced gastric cancer treated with ICIs previously admitted to our medical center, we found some clinical characteristic factors associated with the occurrence of irAEs as well as the efficacy and prognosis: the presence or absence of hypertension, whether or not to receive targeted therapies can predict the occurrence of immune-related adverse events (irAEs), and the more the presence of irAEs, the better the prognosis. These can help clinicians in clinical drug selection. Conclusions: The results of this paper show that the occurrence of irAEs is associated with patients’ OS. irAEs occurrence can prolong patients’ OS. irAEs occurrence may serve as a surrogate marker for ICIs.",14321335,ONCOLOGY
10.1007/s44196-024-00410-1,TrajectoFormer: Transformer-Based Trajectory Prediction of Autonomous Vehicles with Spatio-temporal Neighborhood Considerations,"Accurate trajectory prediction of autonomous vehicles is crucial for ensuring road safety. Predicting precise and accurate trajectories is still considered a challenging problem because of the intricate spatio-temporal dependencies among the vehicles. Our study primarily focuses on resolving this issue by introducing a comprehensive system called “TrajectoFormer”, which can effectively represent the spatio-temporal dependency between vehicles. In this system, we have conducted preprocessing on the NGSIM dataset by constructing an 8-neighborhood for each vehicle that represents the spatio-temporal dependency between vehicles effectively. Second, we have deployed a transformer network that captures dependencies between the target vehicle and its neighbor from the constructed neighborhood and predicts future trajectories for the target vehicle with notably reduced training times and significant accuracy compared to existing methods. Experiments on both NGSIM US-101 and US-I80 show that our proposed approach outperforms the other benchmarks in terms of showing low RMSE value for the 5-s prediction horizon of trajectory prediction. Our conducted ablation study also underscores the effectiveness of each component of our proposed TrajectoFormer model relative to traditional time-series prediction models.",18756883,AI
10.3390/ejihpe14040064,A Systematic Review with a Meta-Analysis of the Motivational Climate and Hedonic Well-Being Constructs: The Importance of the Athlete Level,"Motivational climate is known to relate to individual behaviors, emotions, and thoughts. Hedonic or subjective well-being includes self-assessed positive affect (i.e., pleasant affect, moods, and emotions), negative affect (i.e., unpleasant affect, moods, and emotions), and life or domain-specific satisfaction. The aim of this review was to quantify the relationships between task and ego motivational climate scales and measures representing hedonic well-being with sports participants. Potential moderators of the motivational climate and hedonic well-being were examined. This review followed the PRISMA guidelines (PROSPERO ID CRD42023470462, registered 28 October 2023). From five relevant databases, one relevant review, and hand searching, 82 articles totaling 26,378 participants (46.3% female) met the inclusion criteria. The articles spanned publication dates from 1993 to 2023, representing 18 countries, various team and individual sports, and athletes competing in elite (e.g., Olympic) to grassroot (e.g., club sport) competitions. To meta-analyze the motivational climate and hedonic well-being relationships, the random-effects model was used. For the moderation analyses, the mixed-effects model was used. The task or mastery climate relationships were medium in magnitude with positive affect and satisfaction and small with negative affect. The ego or performance climate relationships were small in magnitude for positive affect, negative affect, and satisfaction. Evidence of bias existed in the motivational climate and hedonic well-being relationships. For moderation analyses, athlete level (i.e., elite vs. non-elite) moderated (p < 0.05) the task (elite, r = 0.23; non-elite, r = 0.34) and ego motivational climate (elite, r = −0.02; non-elite, r = −0.13) and positive affect and satisfaction combined relationships. In conclusion, the motivational climate and hedonic well-being relationships were stronger for the task climate than for the ego climate. The finding that elite athlete correlations appeared dampened is important for future research. Even with the damped relationships, practitioners, from the Olympics to local clubs, should ensure the promotion of the task climate to maximize positive affect and satisfactions in and around the sport experience.",22549625,PSYCHOLOGY
10.3390/ejihpe14040065,The Positive and Negative Suicidal Ideation Inventory among Portuguese Adolescents: Factor Structure and Gender Invariance,"Suicide worldwide is an issue that needs to be addressed, and adolescents are an at-risk group. Assessing suicidal ideation is central to tackling the issue of suicide. The Positive and Negative Suicidal Ideation inventory is a widely validated measure of suicidal ideation, and yet, very little is known about its invariance across various groups. The present study aimed to adapt and test the PANSI’s structure in a Portuguese sample while testing its gender invariance. A total of 750 middle and high school students were recruited for the study, and data were collected on various suicide risk and protective factors, including the Portuguese-translated PANSI. Data were put through exploratory and confirmatory factor analysis. Kaiser’s criterion and scree plot both extracted two factors (64.10% variance explained). Confirmatory factor analysis also supported the PANSI’s structure (TLI = 0.943). The PANSI showed good reliability (α ≥ 0.83) and good construct and discriminative validity. The PANSI also exhibited scalar, but not strict, invariance. Overall, these results were similar to previous versions of this scale. The PANSI is a reliable measure of suicide risk among Portuguese adolescents. Future studies should further replicate these results in other cultures and expand on them by testing for invariance across other demographic variables.",22549625,PSYCHOLOGY
10.1007/s00432-024-05687-5,Prognostic and onco-immunological value of immune-related eRNAs-driven genes in lung adenocarcinoma,"Background We aimed to comprehensively analyze the clinical value of immune-related eRNAs-driven genes in lung adenocarcinoma (LUAD) and find the potential biomarkers for prognosis and therapeutic response to improve the survival of this malignant disease. Materials and methods Pearson’s correlation analysis was performed to identify the immune-related eRNAs-driven genes. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were used to construct this prognostic risk signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to investigate the underlying molecular mechanism. The single sample gene set enrichment analysis (ssGSEA) algorithm was conducted to evaluate the immune status based on the signature. The quantitative real-time PCR (qRT-PCR) analysis was performed to evaluate the expression value of the signature genes between LUAD tissues and adjacent lung tissues. Results Five immune-related eRNAs-driven genes (SHC1, GDF10, CCL14, FYN, and NOD1) were identified to construct a prognostic risk signature with favorable predictive capacity. The patients with high-risk scores based on the signature were significantly associated with the malignant clinical features compared with those with low-risk scores. Kaplan–Meier analysis demonstrated that the sample in the low-risk group had a prolonged survival compared with those in the high-risk group. This risk signature was validated to have a promising predictive capacity and reliability in diverse clinical situations and independent cohorts. The functional enrichment analysis demonstrated that humoral immune response and intestinal immune network for IgA production pathway might be the underlying molecular mechanism related to the signature. The proportion of the vast majority of immune infiltrating cells in the high-risk group was significantly lower than that in the low-risk group, and the immunotherapy response rate in the low-risk group was significantly higher than that in the high-risk group. Moreover, BI-2536, sepantronium bromide, and ULK1 were the potential drugs for the treatment of patients with higher risk scores. Finally, the experiment in vivo and database analysis indicated that CCL14, FYN, NOD1, and GDF10 are the potential LUAD suppressor and SHC1 is a potential treatment target for LUAD. Conclusion Above all, we constructed a prognostic risk signature with favorable predictive capacity in LUAD, which was significantly associated with malignant features, immunosuppressive tumor microenvironment, and immunotherapy response and may provide clinical benefit in clinical decisions.",14321335,ONCOLOGY
10.1007/s00432-024-05684-8,The role of histological subtype and chemotherapy on prognosis of ureteral cancer,"Objective: To date, there have been few studies examining the prognostic implications of histological subtypes in ureteral cancer. And chemotherapy plays a crucial role in the treatment of ureteral cancer, while many factors influence the efficacy of chemotherapy. This study aimed to utilize the Surveillance, Epidemiology and End Results database to assess the impact of histological type on ureteral cancer prognostic outcomes and discovered how histological type and T-stage influence the efficacy of chemotherapy. Methods: Based on Surveillance, Epidemiology, and End Results Program, we reviewed 8915 records of patients with primary ureteral cancer from 18 centers between 2000 and 2018. We focused on the overall survival and cancer-specific survival of the records and used Kaplan‒Meier method to calculate survival curves. Results: In the comparison of prognostic outcomes, atypical subtypes exhibited a less favorable prognosis compared to typical ureteral carcinoma. Notably, patients diagnosed with papillary urothelial carcinoma demonstrated the most favorable overall survival (p = 0.005). Statistically significant benefits were observed in the prognosis of patients with non-papillary urothelial carcinoma who received chemotherapy (HR = 0.860, 95% CI 0.764–0.966, p = 0.011), while chemotherapy did not yield a statistically significant effect on the prognosis of patients with papillary urothelial carcinoma (HR = 1.055, 95% CI 0.906–1.228, p = 0.493). Chemotherapy had an adverse impact on the prognosis of patients with T1 ureteral cancer (HR = 1.235, 95% CI 1.016–1.502, p = 0.034), whereas it exhibited a positive prognostic effect for T3/T4 cases (HR = 0.739, 95% CI 0.654–0.835, p < 0.001). Conclusions: Histological type affects the prognosis of ureteral cancer. And evaluation of cancer histological type and T stage in ureteral cancer patients prior to chemotherapy is mandatory.",14321335,ONCOLOGY
10.3390/cancers16081503,Measurable (Minimal) Residual Disease in Myelodysplastic Neoplasms (MDS): Current State and Perspectives,"Myelodysplastic Neoplasms (MDS) have been traditionally studied through the assessment of blood counts, cytogenetics, and morphology. In recent years, the introduction of molecular assays has improved our ability to diagnose MDS. The role of Measurable (minimal) Residual Disease (MRD) in MDS is evolving, and molecular and flow cytometry techniques have been used in several studies. In this review, we will highlight the evolving concept of MRD in MDS, outline the various techniques utilized, and provide an overview of the studies reporting MRD and the correlation with outcomes.",20726694,ONCOLOGY
10.1007/s00432-024-05719-0,Platinum-based adjuvant chemoradiotherapy versus adjuvant radiotherapy in patients with head and neck adenoid cystic carcinoma,"Purpose The objective of the study was to assess the effectiveness and toxicity of platinum-based adjuvant chemoradiotherapy (POCRT) in comparison to postoperative radiotherapy (PORT) in patients with head and neck adenoid cystic carcinoma (HNACC). Materials and methods This retrospective study analyzed patients diagnosed with HNACC at our center between January 2010 and April 2020. A 1:1 propensity score matching method was used to create a matched cohort. Results In this study, 206 patients were analyzed, with 147 patients (71.4%) receiving postoperative radiotherapy (PORT) and 59 patients (28.6%) receiving POCRT. Twenty-one patients experienced local–regional failure. The 3-, 5-, and 10-yr local–regional control (LRC) rate for the cohort were 92.0%, 90.6%, and 86.9%, respectively. In both the entire cohort and the matched cohort, the POCRT group exhibited superior LRC compared to the PORT group (Gray's test, all P < 0.05*). Multivariate analysis identified adjuvant concurrent chemotherapy as an independent prognostic factor for LRC (Competing risks regression, HR = 0.144, 95% CI 0.026–0.802, P = 0.027*). In addition, the POCRT group had higher incidences of upper gastrointestinal toxicity and hematologic toxicities, including leukopenia, neutropenia, and anemia (all P < 0.05*). Conclusion In terms of reducing locoregional failures in HNACC patients, POCRT may potentially offer a more effective therapeutic approach than using PORT alone, although it also entails an augmented burden of treatment-related toxicity.",14321335,ONCOLOGY
10.1007/s00432-024-05723-4,Identification and validation of a lactate metabolism-related six-gene prognostic signature in intrahepatic cholangiocarcinoma,"Purpose: Intrahepatic cholangiocarcinoma (iCCA) is a highly malignant and fatal liver tumor with increasing incidence worldwide. Lactate metabolism has been recently reported as a crucial contributor to tumor progression and immune regulation in the tumor microenvironment. However, it remains poorly identified about the biological functions of lactate metabolism in iCCA, which hinders the development of prognostic tools and therapeutic interventions. Methods: The univariate Cox regression analysis and Boruta algorithm were utilized to identify key lactate metabolism-related genes (LMRGs), and a prognostic signature was constructed based on LMRG scores. Genomic variations and immune cell infiltration were evaluated in the high and low LMRG score groups. Finally, the biological functions of key LMRGs were verified with in vitro and in vivo experiments. Results: Patients in the high LMRG score group exhibit a poor prognosis compared to those in the low LMRG score group, with a high frequency of TP53 and KRAS mutations. Moreover, the infiltration and function of NK cells were compromised in the high LMRG score group, consistent with the results from two independent single-cell RNA sequencing datasets and immunohistochemistry of tissue microarrays. Experimental data revealed that lactate dehydrogenase A (LDHA) knockdown inhibited proliferation and migration in iCCA cell lines and tumor growth in immunocompetent mice. Conclusion: Our study revealed the biological roles of LDHA in iCCA and developed a reliable lactate metabolism-related prognostic signature for iCCA, offering promising therapeutic targets for iCCA in the clinic.",14321335,ONCOLOGY
10.3390/ai5020027,ANNs Predicting Noisy Signals in Electronic Circuits: A Model Predicting the Signal Trend in Amplification Systems,"In the proposed paper, an artificial neural network (ANN) algorithm is applied to predict the electronic circuit outputs of voltage signals in Industry 4.0/5.0 scenarios. This approach is suitable to predict possible uncorrected behavior of control circuits affected by unknown noises, and to reproduce a testbed method simulating the noise effect influencing the amplification of an input sinusoidal voltage signal, which is a basic and fundamental signal for controlled manufacturing systems. The performed simulations take into account different noise signals changing their time-domain trend and frequency behavior to prove the possibility of predicting voltage outputs when complex signals are considered at the control circuit input, including additive disturbs and noises. The results highlight that it is possible to construct a good ANN training model by processing only the registered voltage output signals without considering the noise profile (which is typically unknown). The proposed model behaves as an electronic black box for Industry 5.0 manufacturing processes automating circuit and machine tuning procedures. By analyzing state-of-the-art ANNs, the study offers an innovative ANN-based versatile solution that is able to process various noise profiles without requiring prior knowledge of the noise characteristics.",26732688,AI
10.1007/s00432-024-05709-2,Imaging for local recurrence of breast cancer,"Purpose Isolated locoregional recurrence of breast cancer (ILRR) and contralateral breast cancer (CBC) affect up to 20% of all breast cancer (BC) patients in the first 20 years after primary diagnosis. Treatment options comprise surgical interventions and further systemic therapies depending on the histological subtype. Patients with hereditary breast or ovarian cancer (HBOC) undergo MRI, mammography, and ultrasound in the aftercare of BC, while non-HBOC (nHBOC) patients do not regularly receive MRI. Since early detection is crucial for morbidity and mortality, the evaluation and constant improvement of imaging methods of the breast is necessary. Methods We retrospectively analyzed the data of 1499 former BC patients that received imaging of the breast at a tertiary-care university hospital between 2015 and 2020. The analysis comprised various patient characteristics, such as breast density, age, tumor size and subtype, and their influence on BC detection rates by the different imaging methods. Results Within the patient sample, 176 individuals (11.7% of former BC patients) were diagnosed with either ILRR or CBC. CBC was observed in 32.4% of patients, while both ILRR and secondary breast cancer occurred in 20.5% and 23.9% of all patients. Sensitivity of MRI, mammography, and ultrasound for recurrent malignancy was 97.9%, 66.3%, and 67.8%, respectively. ILRR and CBC detection rates were similar for patients with and without HBOC history. Lower breast density and larger tumor size increased the detection rates of all imaging modalities. Conclusion In breast cancer survivors, MRI might improve the early detection of ILRR and CBC in both HBOC and nHBOC patients.",14321335,ONCOLOGY
10.3390/ejihpe14040072,"The Relationship between Attitudes toward Death and Emotional Intelligence, Personality, Resilience, and Justice Beliefs: A Cross-Sectional Study of Midwives in Greece","Midwifery practice inevitably includes miscarriages, stillbirths, and neonatal deaths. The aim of the present study was to investigate the relationship between attitudes toward death and emotional intelligence, personality, resilience, and justice beliefs among midwives in Greece. A descriptive cross-sectional study was conducted from 2020 to 2022 among 348 midwives employed in public hospitals, in regional health authorities, or as independent professionals. Research instruments included the Death Attitude Profile—Revised, the Connor–Davidson Resilience Scale, the Trait Emotional Intelligence Questionnaire—Short Form, the Eysenck Personality Questionnaire, and the Belief in a Just World scale. The results revealed that greater emotional intelligence was significantly associated with higher scores in the escape acceptance subscale. Midwives scored low on the neutral acceptance subscale (2.9 ± 0.8), with the highest score being recorded in the escape acceptance subscale (4.6 ± 1.0), which was significantly associated with greater emotional intelligence. Neuroticism was significantly associated with the death avoidance, approach acceptance, fear of death, and escape acceptance subscales. Finally, the subscale of distributive justice beliefs for self and others was significantly associated with the subscales of death avoidance and approach acceptance. These findings highlight the nuanced perspectives within the healthcare community. As we delve deeper into the complexities of end-of-life care, understanding these diverse attitudes is crucial for providing comprehensive and empathetic support to both patients and healthcare professionals.",22549625,PSYCHOLOGY
10.3390/cancers16081610,Imiquimod Is Effective in Reducing Cervical Intraepithelial Neoplasia: A Systematic Review and Meta-Analysis,"Introduction: Topical Imiquimod is an immune response modifier approved for the off-label use of vulvar intraepithelial neoplasia. We conducted this systematic review and meta-analysis to investigate the efficacy and safety of Imiquimod in treating cervical intraepithelial neoplasia (CIN) and human papillomavirus (HPV)-positive patients. Methods: The study was prospectively registered (CRD420222870) and involved a comprehensive systematic search of five medical databases on 10 October 2022. We included articles that assessed the use of Imiquimod in cervical dysplasia and HPV-positive patients. Pooled proportions, risk ratios (RRs), and corresponding 95% confidence intervals (CIs) were calculated using a random effects model to generate summary estimates. Statistical heterogeneity was assessed using I2 tested by the Cochran Q tests. Results: Eight articles reported on 398 patients who received Imiquimod out of 672 patients. Among CIN-2–3 patients, we observed a pooled regression rate of 61% (CI: 0.46–0.75; I2: 77%). When compared, Imiquimod was inferior to conization (RR: 0.62; CI: 0.42–0.92; I2: 64%). The HPV clearance rate in women who completed Imiquimod treatment was 60% (CI: 0.31–0.81; I2: 57%). The majority of side effects reported were mild to moderate in severity. Conclusions: Our findings indicate that topical Imiquimod is safe and effective in reducing cervical intraepithelial neoplasia and promoting HPV clearance. However, it was found to be inferior compared to conization. Imiquimod could be considered a potential medication for high-grade CIN patients and should be incorporated into guidelines for treating cervical dysplasia.",20726694,ONCOLOGY
10.3390/educsci14050439,Cultivating Professional Identity: The Vital Role of Practical Teaching Experience for Future Educators,"This article endeavors to investigate the impact of three years of teaching experience acquired during student teaching training on the professional identity of aspiring educators. The ensuing literature review expounds upon the concepts of identity and professional identity. To scrutinize this subject comprehensively, a quantitative study was conducted, the details of which are elucidated in the subsequent section devoted to research methodology. The findings of this study underscore the paramount significance of fostering a sense of belonging and mission as integral components that underpin the means of support, adaptability, and PI development, particularly pertinent to student teachers and, especially, those immersed in the practical experience phase, as discerned through their self-perceptions. The principal conclusions and insights drawn from the cumulative body of research evidence underscore that, despite the recent recognition accorded the pedagogical training processes and their multifaceted impact on various aspects of a student’s life as a future educator, the teaching profession still remains underappreciated. The finding that emerged during this study underscores the heightened significance of teaching practices as an essential element in the preparation of a prospective graduate who aspires to become a pioneering educator in shaping the future of generations to come. The investigation surveyed 216 students pursuing teaching degrees, analyzing their professional identity development throughout their academic journey. Results revealed a positive association between the students’ advancement in their training curriculum and the enhancement of their professional identity. Specifically, as students progressed further in their studies, there was a discernible growth in their identification with the teaching profession.",22277102,EDUCATION
10.1186/s40359-024-01725-6,Investigating learning burnout and academic performance among management students: a longitudinal study in English courses,"This study aims to move away from the cross-sectional approach related to burnout and conduct a longitudinal study to explore the factors influencing learning burnout among management students. The study primarily adopts a questionnaire survey, with students majoring in business management. Descriptive statistics and structural equation modeling (SEM) are used to analyze the data and validate the hypotheses. The findings are: (1) There is a significant negative relationship between English anxiety and self-efficacy and a significant positive relationship between past English learning performance and self-efficacy. (2) The changes in self-efficacy are negatively related to the changes in burnout, while the changes in workload are positively related to the changes in burnout. Additionally, there is a positive relationship between English anxiety and learning burnout. (3) There is a significant negative relationship between English learning performance and burnout. The direct impact of self-efficacy on English learning performance is not supported, but it has an indirect effect through the mediating role of burnout. The study proposes strategies to improve student outcomes and well-being: (1) making English courses more engaging to boost performance and confidence, reducing learning burnout; (2) encouraging and supporting students to enhance self-efficacy and motivation; (3) assigning tasks seen as useful and interesting to lessen perceived workload and emotional exhaustion; (4) and considering English anxiety in admissions to decrease learning burnout, especially as schools gain more autonomy in their policies.",20507283,PSYCHOLOGY
10.1007/s44196-024-00505-9,Correction to: Multi-objective Geometric Mean Optimizer (MOGMO): A Novel Metaphor-Free Population-Based Math-Inspired Multi-objective Algorithm,,18756883,AI
10.3390/ejihpe14050073,Attitudes of Polish Medical Students toward Organ Donation in Cases of Brain Death,"(1) The aim of our study was to determine the attitudes of medical students toward organ donation in the case of brain death. (2) The study was conducted among 1348 medical students from three medical universities in Poland. The research tool was the Polish version of the standardized questionnaire concerning attitudes toward organ donation and transplantation (ODT) [PCID-DTO RIOS: A questionnaire designed by the ‘International Collaborative Organ Donation project about organ transplantation and donation]. (3) Some sources of information on organ donation were found to have a significant impact on the recipients’ knowledge of brain death. These were books, friends, family, lectures in other centers, social media, and the Church. Medical students holding the opinion that recovery and leading a normal lifestyle after brain death is impossible were significantly more likely to donate their organs after death, not for religious reasons and not because they wanted to survive their own death. (4) The medical students in our study showed a high level of awareness and favorable attitudes toward ODT. However, the number of registered donors was low. It is important to educate students on these issues to raise the awareness of both future medical professionals and the public on organ transplantation procedures. The public should be made aware that transplantation procedures are of a high standard, and that the law protects both donors and recipients. These measures would reduce recipients’ waiting time, and certainly increase the statistics of the number of life-saving and health-saving procedures.",22549625,PSYCHOLOGY
10.3389/fpsyg.2024.1286579,Understanding and tackling meat reduction in different cultural contexts: a segmentation study of Swiss and Vietnamese consumers,"Objective: This study aims to disclose and compare meat consumer segments in Switzerland and Vietnam, which differ in terms of their socioeconomic and cultural settings (the former is a developed country, and the latter is an emerging one) to develop a set of segment-specific recommendations that might be applied to consumption in comparable contexts, that is, in other developed countries and other emerging economies.Methods: Data were collected through two online surveys: one for Swiss residents from randomly selected households and one for Vietnamese urban residents recruited via snowball sampling. The final sample size was N = 643 for Switzerland and N = 616 for Vietnam. Hierarchical cluster analyses followed by K-means cluster analyses revealed five distinct clusters in both countries.Results: Three clusters were common to both countries: meat lovers (21% in Switzerland and 19% in Vietnam), proactive consumers (22% in Switzerland and 14% in Vietnam) and suggestible consumers (19% in Switzerland and 25% in Vietnam). Two were specific to each country, namely traditional (19%) and basic (21%) consumers in Switzerland and confident (16%) and anxious (26%) consumers in Vietnam.Conclusion: Relying on voluntary actions, nudging techniques, private initiatives and consumers’ sense of responsibility will certainly be useful but will nevertheless be insufficient to achieve a planetary health diet within the given timeframe (the 2030 Agenda for Sustainable Development). Governments will have no choice but to activate all levers within their sphere of influence – including regulatory measures – and oblige private sector actors to commit to the measures imposed on them. A binding international agenda with common objectives and measures is a judicious approach. Unlike most previous studies, which focused on meat consumption intensity and frequency or diet type to segment consumers, our approach, based on psychographic profiles, allows the identification of segments that share common drivers and barriers and thus the development of better-targeted measures to reduce meat consumption.",16641078,PSYCHOLOGY
10.1186/s40359-024-01731-8,"Relationship between academic procrastination, self-esteem, and moral intelligence among medical sciences students: a cross-sectional study","Background: Academic procrastination is a widespread phenomenon among students. Therefore, evaluating the related factors has always been among the major concerns of educational system researchers. The present study aimed to determine the relationship of academic procrastination with self-esteem and moral intelligence in Shahroud University of Medical Sciences students.Methods: This cross-sectional descriptive-analytical study was conducted on 205 medical sciences students. Participants were selected based on inclusion and exclusion criteria using the convenience sampling technique. The data collection tools included a demographic information form, Solomon and Rothblum’s Procrastination Assessment Scale-Students, Rosenberg Self-Esteem Scale, and Lennick and Kiel’s Moral Intelligence Questionnaire, all of which were completed online. The data were analyzed using descriptive statistics and inferential tests (multivariate linear regression with backward method) in SPSS software.Results: 96.1% of participating students experienced moderate to severe levels of academic procrastination. Based on the results of the backward multivariate linear regression model, the variables in the model explained 27.7% of the variance of academic procrastination. Additionally, self-esteem (P < 0.001,β=-0.942), grade point average (P < 0.001,β=-2.383), and interest in the study field (P = 0.006,β=-1.139) were reported as factors related to students’ academic procrastination.Conclusion: According to the findings of this study, the majority of students suffer from high levels of academic procrastination. Furthermore, this problem was associated with low levels of self-esteem, grade point average, and interest in their field of study.",20507283,PSYCHOLOGY
10.1186/s40359-024-01737-2,Mental health during ecological crisis: translating and validating the Hogg Eco-anxiety Scale for Argentinian and Spanish populations,"Background: Eco-anxiety is increasingly recognized as a shared experience by many people internationally, encompassing fear of environmental catastrophe and anxiety about ecological crises. Despite its importance in the context of the changing climate, measures for this construct are still being developed in languages other than English. Methods: To contribute to global eco-anxiety research, we translated the Hogg Eco-Anxiety Scale (HEAS) into Spanish, creating the HEAS-SP. We validated this measure in samples from both Argentina (n = 990) and Spain (n = 548), performing measurement invariance and confirmatory factor analyses. Internal consistency of the scale and score stability over time were investigated through reliability analyses. Differences in eco-anxiety across sociodemographic variables were explored through Student’s t-tests and Pearson’s r tests. Results: The four-factor model of the HEAS-SP comprising affective and behavioural symptoms, rumination, and anxiety about personal impact demonstrated excellent model fit. We found good internal consistency for each subscale, and established measurement invariance between Spanish and Argentine samples, as well as across genders and participants’ age. Spanish participants reported higher scores on the affective symptoms and personal impact anxiety factors compared to the Argentinian sample. Also, men reported lower levels than women on the subscales of affective symptoms, rumination, and personal impact anxiety. It was found that the relationship between both age and personal impact anxiety and age and affective symptoms varies significantly depending on the gender of the individuals. Younger participants tended to report higher scores on most dimensions of eco-anxiety. Conclusions: These findings enhance the global initiative to investigate, explore and therefore comprehend eco-anxiety by introducing the first valid and reliable Spanish-language version of this psychometric instrument for its use within Spanish and Argentinian populations. This study augments the body of evidence supporting the robust psychometric properties of the HEAS, as demonstrated in prior validations for Australian, Turkish, Portuguese, German, French, and Italian populations.",20507283,PSYCHOLOGY
10.3390/cancers16091678,Proteins Involved in Focal Cell Adhesion and Podosome Formation Are Differentially Expressed during Colorectal Tumorigenesis in AOM-Treated Rats,"Colorectal tumorigenesis involves the development of aberrant crypt foci (ACF) or preneoplastic lesions, representing the earliest morphological lesion visible in colon cancer. The purpose of this study was to determine changes in protein expression in carcinogen-induced ACF as they mature and transform into adenomas. Protein expression profiles of azoxymethane (AOM)-induced F344 rat colon ACF and adenomas were compared at four time points, 4 (control), 8, 16, and 24 weeks post AOM administration (n = 9/group), with time points correlating with induction and transformation events. At each time point, micro-dissected ACF and/or adenoma tissues were analyzed across multiple quantitative two-dimensional (2D-DIGE) gels using a Cy-dye labeling technique and a pooled internal standard to quantify expression changes with statistical confidence. Western blot and subsequent network pathway mapping were used to confirm and elucidate differentially expressed (p ≤ 0.05) proteins, including changes in vinculin (Vcl; p = 0.007), scinderin (Scin; p = 0.02), and profilin (Pfn1; p = 0.01), By determining protein expression changes in ACF as they mature and transform into adenomas, a “baseline” of altered regulatory proteins associated with adenocarcinoma development in this model has been elucidated. These data will enable future studies aimed at biomarker identification and understanding the molecular biology of intestinal tumorigenesis and adenocarcinoma maturation under varying intestinal conditions.",20726694,ONCOLOGY
10.3390/educsci14050464,Redesigning and Evaluating a Science Activity to Foster Mathematical Problem Solving,"According to contemporary research, there exists an imbalance within the disciplines of Science, Technology, Engineering, and Mathematics (STEM), wherein certain subjects are lacking representation due to the neglect or omission of mathematical elements. The purpose of this study is to address this issue through the analysis of an established learning sequence that has been well-tested to promote mathematical skills. We adapted the selected biology-based learning sequence to foster mathematical problem solving and conducted it with a school class. The qualitative analysis of the recorded video footage of this adapted learning sequence revealed that the modified task effectively stimulated mathematical problem-solving skills. This successful adaptation demonstrates one approach through which mathematics can be strengthened and effectively utilized in STEM subjects.",22277102,EDUCATION
10.3389/fonc.2024.1404361,The impact of tumor budding and single-cell invasion on survival in patients with stage III/IV locally advanced oral squamous cell carcinoma- results from a prospective cohort study,"Introduction Tumor budding (TB) refers to the presence of small clusters of tumor cells at the invasive front of a malignant tumor. Single tumor cell invasion (SCI) is an extreme variant of TB, in which individual loose tumor cells are present at the invasive front. Both TB and SCI are important histomorphologic risk factors postulated to indicate loss of cellular cohesion. In this study, we investigated the influence of TB and SCI on different survival outcomes in patients with locally advanced oral squamous cell carcinoma (OSCC). Methods We included 129 patients with locally advanced OSCC (pT3-4) from a single-center, prospectively maintained cohort. We examined the association of TB and SCI with the presence of occult lymph node metastasis using a logistic regression model. Survival probabilities were estimated using the Kaplan-Meier method and cumulative incidence functions. The association of TB and SCI on overall survival (OS), oral cancer-specific survival (OCSS), and local recurrence-free survival (LRFS) was investigated using Cox’s proportional hazards regression models. Results TB was detected in 98 (76%) of the tumors, while SCI was observed in 66 (51%) patients. There was a significant association between TB and the occurrence of occult lymph node metastasis (OR=3.33, CI: 1.21-10.0). On multivariate analysis, TB had no detectable impact on survival outcomes. However, SCI showed a higher risk for local recurrence (Hazards ratio (HR): 3.33, CI: 1.19 – 9.27). Discussion This study demonstrates that TB and SCI in locally advanced OSCC function as an independent risk factor for occult lymph node metastases, as well as local recurrences. Both histomorphologic risk factors could serve as an additional parameter for stratifying therapy and escalating multimodal treatment approaches.",2234943X,ONCOLOGY
10.3389/fonc.2024.1309681,Dynamic changes in body composition during XELOX/SOX chemotherapy in patients with gastric cancer,"Objectives In this study, we compared the dynamic changes in body composition during XELOX/SOX chemotherapy in patients with gastric cancer. Furthermore, we investigated the potential impact of these changes on the occurrence of toxic side effects. Methods Patients with gastric cancer who received adjuvant or first-line XELOX/SOX chemotherapy between January 2020 and June 2023 were enrolled. The Brief Conghua Scale was used to assess energy intake, and nutritional management was carried out with reference to the Chinese Guidelines for Nutritional Therapy of Cancer 2020. The NRS 2002 Nutritional Risk Screening Scale, PG-SGA scale, bioelectrical impedance analysis, and dynamic changes in lumbar 3 vertebral skeletal muscle index were compared between baseline and post-chemotherapy in the study. The neutropenia was evaluated using the Common Terminology Criteria for Adverse Events V.5.0, developed by the National Institutes of Health. Results Dynamic follow-up was completed in 39 cases, with a mean follow-up time of 117.62 ± 43.38 days. The incidence of sarcopenia increased significantly after chemotherapy, escalating from 46.2% to 51.3%. After chemotherapy, the mean L3SMI decreased from 36.00 cm2/m2 to 34.99 cm2/m2. Furthermore, when compared to pre-chemotherapy values, the body composition indexes body mass index (BMI), SL3, fat mass free index (FFMI), lean body mass (LBM), and body surface area (BSA) were significantly reduced after chemotherapy. Regardless of baseline or post-chemotherapy status, the incidence of grade ≥ 3 neutropenia was significantly higher in the sarcopenia group than in the non-sarcopenia group. Furthermore, when the skeletal muscle index decreased during chemotherapy, the incidence of grade ≥ 3 neutropenia was significantly higher in both the sarcopenia and non-sarcopenia groups compared to baseline. When the incidence of grade ≥ 3 neutropenia in the post-chemotherapy sarcopenia group was compared to baseline status, the increase was significantly higher in the sarcopenia group than in the maintenance/increase group. Conclusions Skeletal muscle mass decreased progressively during XELOX/SOX chemotherapy in gastric cancer patients, followed by a higher incidence of grade ≥ 3 neutropenia.",2234943X,ONCOLOGY
10.1007/s00432-024-05707-4,Dynamic change in the peritoneal cancer index based on CT after chemotherapy in the overall survival prediction of gastric cancer patients with peritoneal metastasis,"Purpose: The purpose of this research was to investigate the efficacy of the CT-based peritoneal cancer index (PCI) to predict the overall survival of patients with peritoneal metastasis in gastric cancer (GCPM) after two cycles of chemotherapy. Methods: This retrospective study registered 112 individuals with peritoneal metastasis in gastric cancer in our hospital. Abdominal and pelvic enhanced CT before and after chemotherapy was independently analyzed by two radiologists. The PCI of peritoneal metastasis in gastric cancer was evaluated according to the Sugarbaker classification, considering the size and distribution of the lesions using CT. Then we evaluated the prognostic performance of PCI based on CT, clinical characteristics, and imaging findings for survival analysis using multivariate Cox proportional hazard regression. Results: The PCI change ratio based on CT after treatment (ΔPCI), therapy lines, and change in grade of ascites were independent factors that were associated with overall survival (OS). The area under the curve (AUC) value of ΔPCI for predicting OS with 0.773 was higher than that of RECIST 1.1 with 0.661 (P < 0.05). Patients with ΔPCI less than −15% had significantly longer OS. Conclusion: CT analysis after chemotherapy could predict OS in patients with GCPM. The CT-PCI change ratio could contribute to the determination of an appropriate strategy for gastric cancer patients with peritoneal metastasis.",14321335,ONCOLOGY
10.3390/educsci14050482,"Culture of Interculturality, Diversity, Equity, and Inclusion (IDEI) Assessment: Lessons from a Social Justice-Based Intercultural Learning Certificate Program for Preservice Teachers","Despite the pillars, rubrics, and standards provided by national education organizations and accrediting bodies, many educator preparation programs (EPPs) struggle to prepare teacher candidates to engage effectively with all children across differences in an intercultural context. The ability to engage across differences is especially important for teacher candidates as America’s public schools are more diverse than ever. To increase teacher candidates’ knowledge skills and dispositions, we propose a theory-based program focused on interculturality, diversity, equity, and inclusion (IDEI) that aligns with professional accreditation standards and weaves in effective assessment practices. By intentionally embedding assessment activities in program development, we hope to create a culture of IDEI assessment that not only meets accreditor standards but also results in program improvements and learners’ development.",22277102,EDUCATION
10.1186/s40594-024-00482-7,"Influence of career awareness on STEM career interests: examining the roles of self-efficacy, outcome expectations, and gender","Background: The studies of science, technology, engineering, and mathematics (STEM) career interests have progressed substantially over the recent years. However, the influence of career awareness on STEM career interests is an area that requires further discussion. Evidently, Chinese adolescents have limited awareness and interest in STEM careers in the context of the Chinese cultural milieu, which can potentially constrain their future career trajectories. This study explored the influence of career awareness on the STEM career interests of Chinese high school students, examining the mediating roles of self-efficacy and outcome expectations for STEM courses in this relationship. Additionally, it analyzes the impact of gender on the average levels and interrelations of these variables. A sample of high school students from both eastern and western regions of China (N = 2542) was selected, and data was analyzed using a structural equation modeling approach. Results: The findings indicate that while STEM career awareness impacts various types of STEM career interests, minor differences exist in these effects. Specifically, the influence of STEM career awareness on analytical STEM career interests is entirely mediated by self-efficacy and outcome expectations in STEM courses. However, for life-survival and life-healthy STEM career interests, this mediation is only partial, with respective effects accounting for 39% and 45%. Notably, significant mean-level differences exist between male and female students in STEM career interests and self-efficacy in STEM courses, yet the relationships among these variables remain consistent across genders. Conclusions: This study underscores the pivotal influence of career awareness in molding STEM career interests, shedding light on the mediating functions of self-efficacy and outcome expectations within STEM courses. Through a gender-based analysis, it offers valuable insights into the differing inclinations of male and female high school students in the STEM realm, while also revealing consistent patterns in the relationships among these variables across genders. These findings underscore the necessity for heightened efforts to bolster STEM career awareness and fortify self-efficacy and outcome expectations within STEM courses, particularly in domains characterized by notable gender disparities, aiming to foster equitable advancement within the STEM disciplines.",21967822,EDUCATION
10.3390/educsci14050494,Science Achievement of Multilingual Pupils: A Study on the Effectiveness of a Read-Aloud Assessment Accommodation,"To date, empirical investigations of the effects of test accommodations on the actual achievement of multilingual pupils have been inconclusive. In this present study, we investigated whether read-aloud accommodation contributes to better results in terms of science achievement for multilingual pupils. A computer-based science test, conducted with or without read-aloud accommodation, was administered to 1022 5th-grade pupils in 36 Flemish primary schools. We assessed the hypotheses that, first, pupils in a condition with accommodation perform better than their non-accommodated peers, and second, certain background characteristics are related to science achievement for different groups of pupils. The results indicate that read-aloud accommodation in language education does not significantly contribute to making assessments fairer. Overall, parental job status, grade retention, migration status, and self-reported oral proficiency significantly predicted pupils’ science achievement. For pupils taking an accommodated test, their age of arrival and the language they spoke at home did not significantly relate to their science achievement, but their self-rated literacy skills in the language of schooling did.",22277102,EDUCATION
10.3390/ejihpe14050083,Design and Evaluation of a Collective Preventive Program for Musical Performance Anxiety (ConfiDance),"Musical performance anxiety (MPA) is considered a subtype of social phobia and affects musicians who must face musical exposure in public, potentially severely affecting their emotional stability and significantly impairing the quality of their performance. This research has utilized previous scientific knowledge on the issue and a qualitative approach to musicians’ needs through focus groups in order to design a collective preventive program for MPA that could be implemented within the training curriculum of professional musicians. To evaluate the adequacy of the preventive program ‘ConfiDance’, a pilot test was conducted with a sample of 17 professional musicians in training, all post-graduate students in classical music performance. For the pilot test, a quasi-experimental model with a repeated measures methodology (pre-post and one-year follow-up after application) was carried out. The results indicate a significant decrease in MPA after the program implementation, with a notable improvement in effect one year post-application, demonstrating an even greater positive impact over time. These data should be interpreted cautiously due to sample limitations but represent an opportunity for the future implementation of a program that can prevent and treat MPA in music education centers.",22549625,PSYCHOLOGY
10.1007/s44196-024-00444-5,Chaotic-Based Mountain Gazelle Optimizer for Solving Optimization Problems,"The Mountain Gazelle Optimizer (MGO) algorithm has become one of the most prominent swarm-inspired meta-heuristic algorithms because of its outstanding rapid convergence and excellent accuracy. However, the MGO still faces premature convergence, making it challenging to leave the local optima if early-best solutions neglect the relevant search domain. Therefore, in this study, a newly developed Chaotic-based Mountain Gazelle Optimizer (CMGO) is proposed with numerous chaotic maps to overcome the above-mentioned flaws. Moreover, the ten distinct chaotic maps were simultaneously incorporated into MGO to determine the optimal values and enhance the exploitation of the most promising solutions. The performance of CMGO has been evaluated using CEC2005 and CEC2019 benchmark functions, along with four engineering problems. Statistical tests like the t-test and Wilcoxon rank-sum test provide further evidence that the proposed CMGO outperforms the existing eminent algorithms. Hence, the experimental outcomes demonstrate that the CMGO produces successful and auspicious results.",18756883,AI
10.3390/ai5020031,Ethical Considerations for Artificial Intelligence Applications for HIV,"Human Immunodeficiency Virus (HIV) is a stigmatizing disease that disproportionately affects African Americans and Latinos among people living with HIV (PLWH). Researchers are increasingly utilizing artificial intelligence (AI) to analyze large amounts of data such as social media data and electronic health records (EHR) for various HIV-related tasks, from prevention and surveillance to treatment and counseling. This paper explores the ethical considerations surrounding the use of AI for HIV with a focus on acceptability, trust, fairness, and transparency. To improve acceptability and trust towards AI systems for HIV, informed consent and a Federated Learning (FL) approach are suggested. In regard to unfairness, stakeholders should be wary of AI systems for HIV further stigmatizing or even being used as grounds to criminalize PLWH. To prevent criminalization, in particular, the application of differential privacy on HIV data generated by data linkage should be studied. Participatory design is crucial in designing the AI systems for HIV to be more transparent and inclusive. To this end, the formation of a data ethics committee and the construction of relevant frameworks and principles may need to be concurrently implemented. Lastly, the question of whether the amount of transparency beyond a certain threshold may overwhelm patients, thereby unexpectedly triggering negative consequences, is posed.",26732688,AI
10.3390/ejihpe14050086,Parental Responses to Online Sexual Grooming Events Experienced by Their Teenage Children,"Online sexual grooming (a manipulative process in which the perpetrator locates a young person and creates an abusive relationship with the child that involves sexual exploitation) poses significant challenges to parents. This study examined how parents of adolescent victims of online sexual grooming experienced guiding their children through the event. This qualitative study, conducted in Israel, was based on semi-structured in-depth interviews with 15 parents who guided their adolescents who had been subjected to online sexual grooming. Results indicate that the parents reported a spectrum of emotions, from insecurity and guilt to a sense of control and satisfaction in managing the situation. Also, the reluctance of some parents to engage with the education system indicates potential trust issues. The study demonstrates the urgent need for targeted interventions to equip parents and educational professionals with the necessary knowledge for prevention and effective response to online sexual grooming. Implications for future research, policy, and practice are discussed.",22549625,PSYCHOLOGY
10.1007/s00432-024-05747-w,KIF22 promotes multiple myeloma progression by regulating the CDC25C/CDK1/cyclinB1 pathway,"Purpose: Multiple myeloma (MM) is an incurable hematological malignancy characterized by clonal proliferation of malignant plasma B cells in bone marrow, and its pathogenesis remains unknown. The aim of this study was to determine the role of kinesin family member 22 (KIF22) in MM and elucidate its molecular mechanism. Methods: The expression of KIF22 was detected in MM patients based upon the public datasets and clinical samples. Then, in vitro assays were performed to investigate the biological function of KIF22 in MM cell lines, and subcutaneous xenograft models in nude mice were conducted in vivo. Chromatin immunoprecipitation (ChIP) and luciferase reporter assay were used to determine the mechanism of KIF22-mediated regulation. Results: The results demonstrated that the expression of KIF22 in MM patients was associated with several clinical features, including gender (P = 0.016), LDH (P < 0.001), β2-MG (P = 0.003), percentage of tumor cells (BM) (P = 0.002) and poor prognosis (P < 0.0001). Furthermore, changing the expression of KIF22 mainly influenced the cell proliferation in vitro and tumor growth in vivo, and caused G2/M phase cell cycle dysfunction. Mechanically, KIF22 directly transcriptionally regulated cell division cycle 25C (CDC25C) by binding its promoter and indirectly influenced CDC25C expression by regulating the ERK pathway. KIF22 also regulated CDC25C/CDK1/cyclinB1 pathway. Conclusion: KIF22 could promote cell proliferation and cell cycle progression by transcriptionally regulating CDC25C and its downstream CDC25C/CDK1/cyclinB1 pathway to facilitate MM progression, which might be a potential therapeutic target in MM.",14321335,ONCOLOGY
10.3389/fpsyg.2024.1394483,Navigating the “frontal lobe paradox”: integrating Real-Life Tasks (RLTs) approach into neuropsychological evaluations,,16641078,PSYCHOLOGY
10.1007/s00432-024-05755-w,Role played by MDSC in colitis-associated colorectal cancer and potential therapeutic strategies,"Colitis-associated colorectal cancer has been a hot topic in public health issues worldwide. Numerous studies have demonstrated the significance of myeloid-derived suppressor cells (MDSCs) in the progression of this ailment, but the specific mechanism of their role in the transformation of inflammation to cancer is unclear, and potential therapies targeting MDSC are also unclear. This paper outlines the possible involvement of MDSC to the development of colitis-associated colorectal cancer. It also explores the immune and other relevant roles played by MDSC, and collates relevant targeted therapies against MDSC. In addition, current targeted therapies for colorectal cancer are analyzed and summarized.",14321335,ONCOLOGY
10.3390/educsci14050512,Lesson Study as a Professional Development Model for Teaching Spatial Ability in Primary STEM,"This study explores the efficacy of a professional development (PD) model that employs lesson study to teach spatial ability skills in primary STEM education. The structure of the PD supported the ‘Insights’ mechanism by focusing on visualisation, mental rotation, construction and deconstruction, and spatial orientation, which are vital for nurturing students’ spatial abilities. The ‘Motivation’ mechanism was addressed through goal setting in lesson planning, motivating teachers to integrate spatial tasks into their curricula. Continuous feedback and practical support facilitated the ‘Technique’ mechanism, embedding learned skills into everyday teaching practices. Last, the ‘Embed in Practice’ mechanisms, including action planning and prompts, were effectively translated into classroom practices, evidencing the model’s operational efficacy.",22277102,EDUCATION
10.3390/educsci14050525,Facilitators of and Barriers to Inclusive Education in the Arab Community of Israel: The Parents’ Perspective,"A positive and collaborative partnership between parents and schools is required to improve the education of children with special educational needs. Therefore, the present study aimed to explore the educational context in the Arab community in Israel based on the perceptions and beliefs of parents of children with special educational needs about their children’s education in relation to schools. Twenty parents of children with different special educational needs were interviewed to understand their thoughts and beliefs about special education in the Arab community in Israel. Six core categories emerged from the analysis of the interviews [i.e., (a) parenting, (b) learning at home, (c) communicating, (d) volunteering, (e) inclusion of parents in decision-making related to their children, and (f) teachers’ attitudes towards children from the perspective of parents], which were perceived as axes with high potential to improve special education in this community and guarantee an optimal education for children with special needs. The role of the school as a tool to assist parents is highlighted, with the aim of empowering them and encouraging their active participation in school processes with a clear educational policy that clarifies the demands of the school system for parents and vice versa. Finally, we conclude by highlighting the importance of teachers in a child’s life, emphasizing the potential benefits of cooperation and collaboration between teachers, students, and parents.",22277102,EDUCATION
10.3389/fonc.2024.1373286,A retrospective study of 68Ga-FAPI PET/CT in differentiating the nature of pulmonary lesions,"Purpose This study aimed to investigate the characteristics of various pulmonary lesions as revealed by 68Ga-FAPI PET/CT and to determine the utility of 68Ga-FAPI PET/CT in distinguishing the nature of these pulmonary lesions. Methods A retrospective analysis was conducted on 99 patients with pulmonary lesions, who were categorized into three distinct groups: primary lung tumors (G1), metastatic lung tumors (G2), and benign lesions (G3). Each participant underwent a 68Ga-FAPI PET/CT scan. Among these groups, variables such as the Tumor/Background Ratio (TBR), Maximum Standardized Uptake Value (SUVmax), and the true positive rate of the lesions were compared. Furthermore, the FAPI uptake in nodular-like pulmonary lesions (d<3cm) and those with irregular borders was evaluated across the groups. A correlation analysis sought to understand the relationship between FAPI uptake in primary and pulmonary metastatic lesions. Results The study’s participants were composed of 52 males and 47 females, with an average age of 56.8 ± 13.2 years. A higher uptake and detection rate for pulmonary lesions were exhibited by Group G1 compared to the other groups (SUVmax [G1 vs. G2 vs. G3: 9.1 ± 4.1 vs. 6.1 ± 4.1 vs. 5.3 ± 5.8], P<0.05; TBR [G1 vs. G2 vs. G3: 6.2 ± 2.4 vs. 4.1 ± 2.2 vs. 3.2 ± 2.7], P<0.01; true positive rate 95.1% vs. 88% vs. 75.6%]. In nodular-like lung lesions smaller than 3 cm, G1 showed a significantly higher FAPI uptake compared to G2 and G3 (SUVmax [G1 vs. G2 vs. G3: 8.8 ± 4.3 vs. 5.2 ± 3.2 vs. 4.9 ± 6.1], P<0.01; TBR [G1 vs. G2 vs. G3: 5.7 ± 2.7 vs. 3.7 ± 2.1 vs. 3.3 ± 4.4], P<0.05). Both G1 and G2 demonstrated significantly elevated FAPI agent activity in irregular-bordered pulmonary lesions when compared to G3 (SUVmax [G1 vs. G2 vs. G3: 10.9 ± 3.3 vs. 8.5 ± 2.7 vs. 4.6 ± 2.7], P<0.01; TBR [G1 vs. G2 vs. G3: 7.2 ± 2.1 vs. 6.4 ± 1.3 vs. 3.2 ± 2.4], P<0.01). A positive correlation was identified between the level of 68Ga-FAPI uptake in primary lesions and the uptake in pulmonary metastatic lesions within G2 (r=0.856, P<0.05). Conclusion 68Ga-FAPI PET/CT imaging proves to be of significant value in the evaluation of pulmonary lesions, offering distinctive insights into their nature.",2234943X,ONCOLOGY
10.3390/ejihpe14050092,Analysis of Formative and Evaluative Activities on Statistical Graphs in Textbooks for Chilean Rural Multigrade Education,"The aim of this paper is to analyze the formative and evaluative activities involving statistical graphs in the new textbooks for Chilean rural multigrade education. The methodology is qualitative, at a descriptive level and uses the content analysis technique. The sample is made up of the six primary education textbooks distributed by the Ministry of Education for rural multigrade schools. The results show the predominance of the bar chart, semiotic level 3, the task of calculating and the personal context in both types of activities, although with respect to the reading level, it is evident that level 4 predominates in the formative activities and level 2 in the evaluative ones. According to the results, it is recommended to incorporate graphs proposed by the curricular guidelines of the Ministry of Education, which are absent in textbooks as well as to include evaluative activities that require reflection on the nature of the data, context, representation and conclusions obtained from them.",22549625,PSYCHOLOGY
10.3390/ejihpe14050094,Quality of Life and Clinical Impairment in Spanish Adolescent Anorexia Nervosa Patients,"Eating disorders have serious physical, mental and social consequences that can affect the quality of life of the sufferer. This study aimed to evaluate the relationship between the severity of ED-related psychopathology and clinical impairment in adolescents with anorexia nervosa (AN) as well as their perception of health-related quality of life. Eighty-six Spanish young women with AN completed a set of questionnaires assessing eating disorder pathology, clinical impairment, and quality of life. The set included the following instruments: the Eating Disorder Examination Questionnaire, Clinical Impairment Assessment, Short Form-12 Item Health Survey, and the Eating Disorder-Specific Heath-Related Quality of Life instrument. Descriptive and regression analyses were applied to identify associations between variables. Higher scores on clinical impairment domains were associated with greater impairment of mental and physical health. Moreover, clinical impairment domains and concerns due to ED were related to a lower quality of life. In conclusion, adolescents with AN have a poor quality of life. Moreover, the findings suggest that the clinical features of impairment may serve as severity indicators of quality of life.",22549625,PSYCHOLOGY
10.3390/ai5020038,The Eye in the Sky—A Method to Obtain On-Field Locations of Australian Rules Football Athletes,"The ability to overcome an opposition in team sports is reliant upon an understanding of the tactical behaviour of the opposing team members. Recent research is limited to a performance analysts’ own playing team members, as the required opposing team athletes’ geolocation (GPS) data are unavailable. However, in professional Australian rules Football (AF), animations of athlete GPS data from all teams are commercially available. The purpose of this technical study was to obtain the on-field location of AF athletes from animations of the 2019 Australian Football League season to enable the examination of the tactical behaviour of any team. The pre-trained object detection model YOLOv4 was fine-tuned to detect players, and a custom convolutional neural network was trained to track numbers in the animations. The object detection and the athlete tracking achieved an accuracy of 0.94 and 0.98, respectively. Subsequent scaling and translation coefficients were determined through solving an optimisation problem to transform the pixel coordinate positions of a tracked player number to field-relative Cartesian coordinates. The derived equations achieved an average Euclidean distance from the athletes’ raw GPS data of 2.63 m. The proposed athlete detection and tracking approach is a novel methodology to obtain the on-field positions of AF athletes in the absence of direct measures, which may be used for the analysis of opposition collective team behaviour and in the development of interactive play sketching AF tools.",26732688,AI
10.3389/fonc.2024.1361603,Patient-derived organoid elucidates the identical clonal origin of bilateral breast cancer with diverse molecular subtypes,"Bilateral breast cancer (BBC), an infrequent breast cancer subtype, has primarily been studied in terms of incidence, prognosis, and through comparative analysis of synchronous (SBBC) and metachronous (MBBC) manifestations. The advent and application of organoid technology hold profound implications for tumor research and clinical management. This study represents the pioneering use of organoid models in BBC research. We established organoid lines from two surgical tumor specimens of a BBC patient, with one line undergoing detailed pathological and genomic analysis. The BBC organoid from the right breast demonstrated a marker expression profile of ER (-), PR (-), HER-2 (0), and Ki67 index 10%, indicating that it may derived from the TNBC tissue. Whole Exome Sequencing (WES) displayed consistent set of Top10 cancer driver genes affected by missense mutations, frameshift mutation, or splice site mutations in three tumor tissues and the organoid samples. The organoids’ single nucleotide polymorphisms (SNPs) were more closely aligned with the TNBC tissue than other tumor tissues. Evolutionary analysis suggested that different tumor regions might evolve from a common ancestral layer. In this case, the development of BBC organoids indicated that simultaneous lesions with diverse molecular profiles shared a high degree of consistency in key tumor-driving mutations. These findings suggest the feasibility of generating BBC organoids representing various molecular types, accurately replicating significant markers and driver mutations of the originating tumor. Consequently, organoids serve as a valuable in vitro model for exploring treatment strategies and elucidating the underlying mechanisms of BBC.",2234943X,ONCOLOGY
10.3389/fonc.2024.1335533,From immune equilibrium to tumor ecodynamics,"Objectives There is no theory to quantitatively describe the complex tumor ecosystem. At the same time, cancer immunotherapy is considered a revolution in oncology, but the methods used to describe tumors and the criteria used to evaluate efficacy are not keeping pace. The purpose of this study is to establish a new theory for quantitatively describing the tumor ecosystem, innovating the methods of tumor characterization, and establishing new efficacy evaluation criteria for cancer immunotherapy. Methods Based on the mathematization of immune equilibrium theory and the establishment of immunodynamics in a previous study, the method of reverse immunodynamics was used, namely, the immune braking force was regarded as the tumor ecological force and the immune force was regarded as the tumor ecological braking force, and the concept of momentum in physics was applied to the tumor ecosystem to establish a series of tumor ecodynamic equations. These equations were used to solve the fundamental and applied problems of the complex tumor ecosystem. Results A series of tumor ecodynamic equations were established. The tumor ecological momentum equations and their component factors could be used to distinguish disease progression, pseudoprogression, and hyperprogression in cancer immunotherapy. On this basis, the adjusted tumor momentum equations were established to achieve the equivalence of tumor activity (including immunosuppressive activity and metabolic activity) and tumor volume, which could be used to calculate individual disease remission rate and establish new efficacy evaluation criteria (ieRECIST) for immunotherapy of solid tumor based on tumor ecodynamics. At the same time, the concept of moving cube-to-force square ratio and its expression were proposed to calculate the area under the curve of tumor ecological braking force of blood required to achieve an individual disease remission rate when the adjusted tumor ecological momentum was known. Conclusions A new theory termed tumor ecodynamics emphasizing both tumor activity and tumor volume is established to solve a series of basic and applied problems in the complex tumor ecosystem. It can be predicted that the future will be the era of cancer immune ecotherapy that targets the entire tumor ecosystem.",2234943X,ONCOLOGY
10.1007/s44196-024-00506-8,A Region-Selective Anti-compression Image Encryption Algorithm Based on Deep Networks,"In recent years, related research has focused on how to safely transfer and protect the privacy of images in social network services while providing easy access by authorized users. To safeguard privacy, we suggest an image encryption scheme that combines data hiding and image encryption. The proposed scheme successfully decrypts images after JPEG compression attacks and preserves the privacy of secret regions through the use of block scrambling encryption based on region selection. Simultaneously, the scheme can handle nonuniform secret regions and obtain more sensitive secret keys because of the incorporation of a chaotic system. The enhanced deep learning-based data-hiding technology reduces algorithm complexity by enabling the encryption position to be determined in the decryption phase without the need for any information or equipment. However, this approach also increases algorithm security, because only when the right secret data are extracted can they be decrypted successfully. According to the experimental findings, the proposed scheme can correctly decrypt images via JPEG compression while maintaining visually acceptable quality. The proposed scheme can achieve greater robustness against image processing algorithms and a wider secret key space than traditional schemes.",18756883,AI
10.3389/fpsyg.2024.1391258,The effects of mobile phone dependence on athletic performance and its mechanisms,"Mobile phone dependence (also known as internet dependence, MPD), defined as a problematic behavior characterized by excessive use or intermittent craving to use a mobile phone, results in various social, behavioral, and affective problems in daily life. In sports, MPD is directly related to the physical and mental health and sports performance of athletes. The individual and environmental factors, neurobiological mechanisms and theoretical models of MPD affecting athletic performance were analyzed by reviewing previous studies, aiming to construct effective training and development protocols to prevent and control the occurrence of MPD in athletes. At present, athletic performance can be affected by MPD through individual factors and environmental factors. The neurobiological mechanisms between the two are based on the brain reward system and microwave radiation from mobile phones, with athletic performance being restricted by alterations in the corresponding brain regions. Relevant theoretical models mainly include the social cognitive model of self-regulation and the integrative model of self-control, which explain the interrelationship between MPD and athletic performance from the perspectives of athletes’ self-regulation and self-control, respectively. As an emerging phenomenon, the influence pathways and mechanisms by which MPD affects athletic performance need to be further investigated. A longitudinal perspective should be adopted to trace the dynamic impact relationship between the two, and developing relevant theoretical frameworks from an interdisciplinary research perspective should be valuable for providing theoretical support for coaches and sports administrators to formulate scientific training protocols and thus improve the mental health of athletes.",16641078,PSYCHOLOGY
10.1007/s44196-024-00491-y,Attention-Focused Eye Gaze Analysis to Predict Autistic Traits Using Transfer Learning,"Autism spectrum disorder (ASD) is a complex developmental issue that affects the behavior and communication abilities of children. It is extremely needed to perceive it at an early age. The research article focuses on attentiveness by considering eye positioning as a key feature and its implementation is completed in two phases. In the first phase, various transfer learning algorithms are implemented and evaluated to predict ASD traits on available open-source image datasets Kaggle and Zenodo. To reinforce the result, fivefold cross-validation is used on the dataset. Progressive pre-trained algorithms named VGG 16, VGG 19, InceptionV3, ResNet152V2, DenseNet201, ConNextBase, EfficientNetB1, NasNetMobile, and InceptionResNEtV2 implemented to establish the correctness of the result. The result is being compiled and analyzed that ConvNextBase model has the best diagnosing ability on both datasets. This model achieved a prediction accuracy of 80.4% on Kaggle with a batch size of 16, a learning rate of 0.00002, 10 epochs and 6 units, and a prediction accuracy of 80.71% on the Zenodo dataset with a batch size of 4, a learning rate of 0.00002, 10 epochs and 4 units. The accuracy of the model ConvNextBase is found challenging in nature as compared to an existing model. Attentiveness is a parameter that will accurately diagnose the visual behavior of the participant which helps in the automatic prediction of autistic traits. In the second phase of the proposed model, attentiveness is engrossed in identifying autistic traits. The model uses a dlib library that uses HOG and Linear SVM-based face detectors to identify a particular facial parameter called EAR and it is used to measure participants' attentiveness based on the eye gaze analysis. If the EAR value is less than 0.20 for more than 100 consecutive frames, the model concludes the participant is un-attentive. The model generated a special graph for a time period by continuously plotting the value of EAR based on the attention level. The average EAR value will depict the attentiveness of the participant.",18756883,AI
10.1007/s00432-024-05790-7,Genome-wide investigation of lncRNAs revealed their tight association with gastric cancer,"Background: Gastric cancer (GC) is a significant health issue globally, ranking as the fifth most common cancer with over 10,000 new cases reported annually. Long non-coding RNA (lncRNA) has emerged as a critical player in cellular functions, influencing GC's development, growth, metastasis, and prognosis. However, our understanding of lncRNA's role in the pathogenesis of GC remains limited. Therefore, it is particularly important to explore the relationship between lncRNA and gastric cancer. Methods: we conducted a comprehensive analysis of RNA sequencing data from the GEO database and stomach adenocarcinoma (STAD) data from the TCGA database to identify lncRNAs that exhibit altered expression levels in GC and the mechanisms underlying lncRNA-mediated transcription and post-transcriptional regulation were explored. Results: This study uncovered 94 lncRNAs with differential expression and, through co-expression analysis, linked these to 1508 differentially expressed genes (DEGs). GO functional enrichment analysis highlighted that these DEGs are involved in critical pathways, such as cell adhesion and the positive regulation of cell migration. By establishing a lncRNA-miRNA-mRNA regulatory network, we found that the ceRNA mechanism, particularly involving RP11-357H14.17 and CTD-2377D24.4, could play a role in GC progression. Experimental validation of selected differentially expressed lncRNAs and mRNAs (including RP11-357H14.17-CLDN1, BBOX1, TRPM2-AS, CLDN1, PLAU, HOXB7) confirmed the RNA-seq results. Conclusions: Overall, our findings highlight the critical role of the lncRNA-mRNA regulatory network in the development and progression of GC, offering potential biomarkers for diagnosis and targets for innovative treatment strategies.",14321335,ONCOLOGY
10.3389/fpsyg.2024.1392629,A systematic literature review of the stereotype content model in the fields of psychology and marketing: main themes examined in the literature and an agenda for future research in marketing,"The stereotypes content model indicates that two traits (i.e., warmth and competence) govern individuals’ impression formation. The great variety of research that has used this theory since the early 2000s leads to a need for a structured overview of prior findings. The goal of this study is to provide a concise map of research streams and present a research agenda. We conducted a systematic literature review of 955 articles. A bibliographic coupling analysis showed four clusters, i.e., (1) the general theoretical foundations of the SCM, (2) the societal impact of key stereotypes (with emphasis on gender), (3) research in clinical psychology and child development, and (4) marketing. Taking a closer look at research in marketing (using co-occurrence analysis), six research streams were identified, including research on branding, country-of-origin, front-line service providers, prosocial consumer behavior, perception of endorsers, and, more recently, on artificial intelligence (AI). The review presents key findings and research gaps across these topics. Finally, we reviewed the few articles that, although not falling into these streams, opened important research veins. This process provided the essential information to present a promising and complete research agenda, to continue building knowledge with impactful implications in different contexts.",16641078,PSYCHOLOGY
10.1007/s44196-024-00523-7,A Hybrid CNN-TransXNet Approach for Advanced Glomerular Segmentation in Renal Histology Imaging,"In the specialized field of renal histology, precise segmentation of glomeruli in microscopic images is crucial for accurate clinical diagnosis and pathological analysis. Facing the challenge of discerning complex visual features, such as shape, texture, and size within these images, we introduce a novel segmentation model that innovatively combines convolutional neural networks (CNNs) with the advanced TransXNet block, specifically tailored for glomerular segmentation. This innovative model is designed to capture the intricate details and broader contextual features within the images, ensuring a comprehensive and precise segmentation process. The model's architecture unfolds in two primary phases: the down-sampling phase, which utilizes CNNs structures within the TransXNet block for meticulous extraction of detailed features, and the up-sampling phase, which employs CNNs deconvolution techniques to restore spatial resolution and enhance macroscopic feature representation. A critical innovation in our model is the implementation of residual connections between these two phases, which facilitate the seamless integration of features and minimize loss of precision during image reconstruction. Experimental results demonstrate a significant improvement in our model’s performance compared to existing medical image segmentation methods. We report enhancements in mean Pixel Accuracy (mPA) and mean Intersection over Union (mIoU), with increases of approximately 3–5% and 3–8%, respectively. Additionally, the segmented outputs exhibit higher subjective visual quality with fewer noise artifacts. These findings suggest that our model offers promising applications in the segmentation of medical microscopic images, marking a significant contribution to the domain.",18756883,AI
10.1186/s40359-024-01786-7,A family perspective for the mechanism of parent-child conflict on maternal anxiety in Chinese children with autism,"Mothers of children with autism reported higher levels of anxiety than mothers of typical children. This study revealed the relationship between parent-child conflict, children’s problem behavior, parenting stress, and maternal anxiety from the perspective of the relationship within the family. The State-Trait Anxiety Inventory (STAI) and Caregiver Strain Questionnaire (CGSQ) were used to measure maternal anxiety and parenting stress respectively from 102 mothers of children with autism. We also collected information on parent-child relationships and children’s problem behaviors by using the Child-Parent Relationship Scale (CPRS) and Conners Parent Symptom Questionnaire (PSQ). Parent-child conflict positively predicted state and trait anxiety in mothers of children with autism. The severity of children’s psychosomatic disorders fully mediated the positive association between parent-child conflict and state-trait anxiety in mothers of children with autism. Parenting stress significantly moderated the impact of parent-child conflict on maternal state anxiety and trait anxiety. In the case of children with autism spectrum disorders, parent-child conflict can directly affect maternal anxiety levels, especially when mothers have low levels of parenting stress. Parent-child conflict can also affect children’s problem behaviors and thus indirectly affect maternal anxiety. Therefore, this study is of great significance for the alleviation of anxiety of mothers of autistic children and the family intervention for the early rehabilitation of autistic children.",20507283,PSYCHOLOGY
10.3389/fpsyg.2024.1415054,The relationship between neonatal stress in preterm infants and developmental outcomes at the corrected age of 24–30 months,"Aim The aim of research was to study the relationship between the stress experienced by preterm infants in the neonatal intensive care unit (NICU) and developmental status in the follow up, and to establish factors, associated with their neurodevelopment. Methods The first stage of research involved measuring stress markers (cortisol, melatonin) in infants (n = 56) during their NICU stay; the second phase assessed the developmental status at the corrected age of 24–30 months. Results The total ASQ-3 score, communication, problem solving, and personal-social skills scores at the corrected age of 24–30 months were positively correlated with melatonin level determined in the neonatal period (r = 0.31, p = 0.026; r = 0.36, p = 0.009; r = 0.30, p = 0.033, and r = 0.32; p = 0.022 respectively). In the same time, ASQ-3 communication and personal-social scores were negatively correlated with cortisol level (r = −0.31, p = 0.043; r = −0.35, p = 0.022). The ROC-curve analysis revealed that a decrease of melatonin below 3.44 ng/mL and 3.71 ng/mL during the neonatal period could predict communication and problem-solving delay, respectively. An increase in cortisol above 0.64 mcg/dl is predictive in personal-social delay. Negative correlation was identified between the NICU and total hospital stay duration and ASQ-3 communication scores in the follow-up (r = −0.27; p = 0.049 and r = −0.41; p = 0.002, respectively). The duration of mechanical ventilation was negatively correlated with gross motor scores (r = −0.46; p = 0.043). Apgar score was positively correlated with ASQ-3 communication (r = 0.29; p = 0.032) and personal-social scores (r = 0.28; p = 0.034); maternal age—with ASQ-3 total (r = 0.29; p = 0.034), communication (r = 0.37; p = 0.006), and personal-social scores (r = 0.29; p = 0.041). Positive correlations were observed between gestational age and communication scores (r = 0.28; p = 0.033). Infants who suffered neonatal sepsis had significantly often delay of communication (p = 0.014) and gross motor skills (p = 0.016). Children who required mechanical ventilation were more likely to have communication delay (p = 0.034). Conclusion Developmental outcomes in preterm infants at the corrected age of 24–30 months were associated with neonatal stress. Correlations between the communication, problem-solving and personal-social development in the follow up and cortisol and melatonin levels determined in the neonatal period supported this evidence. Factors as low gestational age, duration of hospital and NICU stay, mechanical ventilation, and sepsis were associated with more frequent delays in communication, gross motor and problems-solving skills.",16641078,PSYCHOLOGY
10.1007/s44196-024-00571-z,A Multiple Environment Available Path Planning Based on an Improved A* Algorithm,"The objective of the path planning for a mobile robot is to generate a collision-free path from a starting position to a target position, aiming to realize a higher quality of path planning, an improved A* algorithm and a hybrid approach incorporating the dynamic window algorithm have been proposed for robot path planning in various environments in this paper. In global path planning, first, a bidirectional search strategy was introduced into to improve the searching efficiency, and an adaptive heuristic function was designed to reduce redundant search nodes. In the meantime, a filtering function for key path nodes and an enhanced jump point optimization method help to remove redundant nodes in the path, reduce turning angles, greatly shorten the path length, and smooth the path using cubic B-spline curves. Furthermore, in local path planning, the combination of key path nodes and the dynamic window approach (DWA) algorithm is utilized to achieve obstacle avoidance in dynamic environments and adjust the heading angle of the section enables seamless locomotion of the robot. Finally, the simulation experiments and physical experiments on the robot were conducted to validate that the proposed improved algorithm significantly improves the speed of path planning while also reducing the length of the planned path and improve the reliability of the algorithm when compared with other algorithms.",18756883,AI
10.1186/s40359-024-01866-8,"Correction: Structural modeling of Chinese students’ academic achievement identity and basic psychological needs: do academic self-efficacy, and mindfulness play a mediating role?",,20507283,PSYCHOLOGY
10.3389/feduc.2024.1358620,The CABANA model 2017–2022: research and training synergy to facilitate bioinformatics applications in Latin America,"The CABANA project (Capacity Building for Bioinformatics in Latin America) was funded by the UK’s Global Challenges Research Fund in 2017 with the aim to strengthen the bioinformatics capacity and extend its applications in Latin America focused on three challenge areas – communicable diseases, sustainable food production and protection of biodiversity. For 5 years, the project executed activities including data analysis workshops, train-the-trainer workshops, secondments, eLearning development, knowledge exchange meetings, and research projects in 10 countries. The project was successful in accomplishing all its goals with a major impact on the region. It became a model by which the research needs determined the training that was delivered. Multiple publications and over 800 trainees are part of the legacy of the project.",2504284X,EDUCATION
10.3390/ejihpe14070130,VISCERAL SENSITIVITY INDEX (VSI-IT): Italian Adaptation and Validation,"The Visceral Sensitivity Index (VSI) represents a significant advancement in the assessment of gastrointestinal-specific anxiety among patients with irritable bowel syndrome (IBS) and chronic inflammatory bowel diseases (IBD)—such as ulcerative colitis and Crohn’s disease. However, an Italian version of the instrument is not yet available for the Italian-speaking population. This study utilized a national sample of 500 individuals divided into four groups: (a) patients with Crohn’s disease, (b) patients with ulcerative colitis, (c) patients with IBS, and (d) healthy controls (individuals without any diagnoses) to test the validity and reliability of the Italian VSI. Using back-translation methodology to ensure translation fidelity, this research applied a questionnaire and the VSI through an online format to 500 participants. Confirmatory Factor Analysis (CFA) revealed that the Italian VSI had excellent psychometric properties, demonstrating high internal consistency (Cronbach’s α = 0.949) and construct validity. The scale proved sensitive in detecting significant differences in visceral sensitivity among groups, highlighting its utility as a clinical and research assessment tool. Specifically, the Italian VSI exhibited a unidimensional factorial structure and maintained a strong correlation with interoceptive awareness, type of disease, and gastrointestinal symptom severity, confirming its role in enhancing the understanding and management of IBD and IBS in Italy.",22549625,PSYCHOLOGY
10.1007/s00432-024-05873-5,Nasopharyngeal amyloidoma: report of three cases and review of the literature,"Background: Nasopharyngeal amyloidoma is a rare, locally aggressive tumor that has been reported in the English literature in only 38 cases to date, most of which were in the form of case reports. The present study was aimed to summarize the characteristics of this rare tumor, with the goal of providing new insights for diagnosis and treatment. Materials and methods: We report three cases of nasopharyngeal amyloidoma diagnosed in our hospital following comprehensive medical examination and review the current literature on all cases of nasopharyngeal amyloidoma from PubMed. The journey of nasopharyngeal amyloidoma, including presentation, diagnostics, surgeries, and follow-up was outlined. Results: None of the three patients had systemic amyloidosis. CT and nasal endoscopy showed irregular masses obstructing the nasopharyngeal cavity. Congo red staining confirmed the deposition of amyloid, and immunohistochemical analysis showed that the amyloid deposition was the AL light chain type. Through literature review, we found that nasopharyngeal amyloidoma most commonly occurred in individuals over the age of 40, patients usually had a good prognosis after complete tumor resection; however, there were still cases of recurrence, and unresected patients were at risk of progression to systemic amyloidosis. The efficacy of radiotherapy and chemotherapy was currently uncertain. Conclusion: Early clinical and pathological diagnosis is crucial, and surgical intervention is the primary treatment option for this disease. Although patients usually have a favorable prognosis, long-term monitoring is necessary to detect potential relapses and initiate timely intervention.",14321335,ONCOLOGY
10.3390/cancers16132488,A Probabilistic Approach to Estimate the Temporal Order of Pathway Mutations Accounting for Intra-Tumor Heterogeneity,"The development of cancer involves the accumulation of somatic mutations in several essential biological pathways. Delineating the temporal order of pathway mutations during tumorigenesis is crucial for comprehending the biological mechanisms underlying cancer development and identifying potential targets for therapeutic intervention. Several computational and statistical methods have been introduced for estimating the order of somatic mutations based on mutation profile data from a cohort of patients. However, one major issue of current methods is that they do not take into account intra-tumor heterogeneity (ITH), which limits their ability to accurately discern the order of pathway mutations. To address this problem, we propose PATOPAI, a probabilistic approach to estimate the temporal order of mutations at the pathway level by incorporating ITH information as well as pathway and functional annotation information of mutations. PATOPAI uses a maximum likelihood approach to estimate the probability of pathway mutational events occurring in a specific sequence, wherein it focuses on the orders that are consistent with the phylogenetic structure of the tumors. Applications to whole exome sequencing data from The Cancer Genome Atlas (TCGA) illustrate our method’s ability to recover the temporal order of pathway mutations in several cancer types.",20726694,ONCOLOGY
10.3390/educsci11030094,Increasing Requests for Information by Preschoolers with and without Language-Based Disabilities,"We report two experiments on the emission of questions to request the names of unfamiliar stimuli by preschoolers. In the first experiment, 19 preschoolers with and without disabilities served as participants. Experiment 1 was a descriptive analysis of whether or not the 19 participants asked questions about unfamiliar pictures and objects in one-to-one and group settings. These were dependent variables in the second experiment as well. Four participants, who did not ask any questions in the first experiment, served as participants in the second experiment. During the intervention, the participants observed the peer confederates (1) ask questions (e.g., “What is that?”), (2) receive information from the experimenter, and (3) receive praise and tokens contingent on asking a question. A multiple probe design across participants was used. The data showed that the participants increased the number of questions when we returned to baseline conditions. Results are discussed in terms of where the reinforcement exists for asking questions about unfamiliar things in one’s environment, and whether this truly measures the “need to know”.",22277102,EDUCATION
10.1186/s40359-024-01870-y,"Chinese version of the Tendency to Avoid Physical Activity and Sport (TAPAS) scale: testing unidimensionality, measurement invariance, concurrent validity, and known-group validity among Taiwanese youths","Background and objectives: Psychosocial factors affect individuals’ desire for physical activity. A newly developed instrument (Tendency to Avoid Physical Activity and Sport; TAPAS) has been designed to assess the avoidance of physical activity. Considering cultural differences could be decisive factors, the present study aimed to translate and validate the TAPAS into Chinese (Mandarin) for Taiwanese youths, and further cultural comparisons are expected. Methods: Standard translation procedure (i.e., forward translation, back translation, and reconciliation) was used to translate the English TAPAS into the Chinese TAPAS. Following translation, 608 youths (mean [SD] age 29.10 [6.36] years; 333 [54.8%] women) participated in the study via a snowballing sampling method with an online survey. All participants completed the Chinese TAPAS and additional instruments assessing weight stigma and psychological distress. Confirmatory factor analysis (CFA) was used to examine the factor structure of the Chinese TAPAS and multigroup CFA to examine measurement invariance across gender (men vs. women) and weight status (overweight vs. non-overweight). Pearson correlations were used to examine the concurrent validity; independent t-tests between gender groups and weight status groups were used to examine the known-group validity. Results: Consistent with the English version, the Chinese TAPAS was found to have a one-factor structure evidenced by CFA results. The structure was invariant across gender and weight status groups evidenced by multigroup CFA results. Concurrent validity was supported by significant associations with the related constructs assessed (r = 0.326 to 0.676; p < 0.001). Known-group validity was supported by the significant differences in TAPAS total scores between gender and weight status groups (p = 0.004 and < 0.001; Cohen’s d = 0.24 and 0.48). Conclusion: The Chinese version of the TAPAS is a valid and reliable instrument assessing individuals’ avoidance of physical activity and sports due to underlying psychosocial issues among Taiwanese youths. It is anticipated to be applied within a large Asian population, as well as cross-cultural comparisons, for further explorations in health, behavioral and epidemiological research and practice.",20507283,PSYCHOLOGY
10.3389/fpsyg.2024.1425359,A study on the relationship between yoga exercise intervention and the comprehensive well-being of female college students,"Background: Due to the influence of theories, tools, and methodologies in studying well-being, sports science has predominantly focused on subjective well-being, with less attention given to psychological well-being and even less to the integrated study of comprehensive well-being. This study aims to analyze the relationship between yoga exercise intervention and the comprehensive well-being of college students and to explore the mechanism of a yoga exercise intervention to improve the comprehensive well-being of female college students.Methods: With 92 female college students as subjects, the “Comprehensive Well-being Scale” was used, and research methods such as yoga exercise intervention, questionnaire surveys, qualitative analysis, expert interviews, and statistical analysis were employed to investigate the role of a yoga exercise intervention on the comprehensive well-being of female college students.Results: Among the nine dimensions of comprehensive well-being, the three dimensions of subjective well-being and the two dimensions of psychological well-being (health concern and personality growth) of female college students were significantly improved. Additionally, four other dimensions of psychological well-being also showed significant improvement. Furthermore, the improvement in the life satisfaction of female college students’ subjective well-being was mainly achieved through yoga meditation, while partner yoga posture practice could help individuals gradually form a stable pattern of altruistic behavior.Conclusion: Yoga exercise intervention can improve the comprehensive well-being of female college students and can be an effective counseling method for college students’ mental health education.",16641078,PSYCHOLOGY
10.3389/fpsyg.2024.1426450,The impact of negative urgency on implicit mobile phone addiction tendency among college freshmen in the context of social exclusion,"Purpose: The purpose of this study is to investigate the impact of negative urgency on implicit mobile phone addiction tendency among college freshmen, and to observe whether social exclusion situations affect the relationship between negative urgency and implicit mobile phone addiction tendency.Methods: The UPPS-P Impulsive Behavior Scale was used to screen 575 freshmen from a certain university. The experiment utilized a GO/NO-GO paradigm. Experiment 1 employed a 2 (negative urgency group: high negative urgency group, low negative urgency group) × 2 (word type: phone related words, phone non-related words) two-factor mixed experimental design. Experiment 2 employed a 2 (negative urgency group: high negative urgency group, low negative urgency group) × 2 (social exclusion type: priming group, non-priming group) × 2 (word type: phone related words, phone non-related words) three-factor mixed experimental design.Results: Experiment 1 results showed a significant main effect of negative urgency group and a significant interaction effect between negative urgency group and word type. Experiment 2 results demonstrated a significant main effect of negative urgency group and a significant main effect of social exclusion type. There was a significant interaction effect between word type and social exclusion type, as well as between word type and negative urgency group. The three-way interaction effect among negative urgency group, word type, and social exclusion type was significant.Conclusion: College freshmen with high negative urgency exhibit a higher tendency toward implicit mobile phone addiction. In social exclusion situations, college freshmen show a higher tendency toward implicit smartphone addiction. Social exclusion situations and negative urgency jointly influence the implicit mobile phone addiction tendency of college freshmen.",16641078,PSYCHOLOGY
10.1007/s00432-024-05866-4,Association of body composition indicators with colorectal cancer: a hospital-based case-control study,"Purpose: Colorectal cancer (CRC) is a common malignancy that affects adults worldwide, causing a high disease burden. Few studies have examined the relationship between body composition (BC) measures and the prevalence of CRC. Our purpose was to investigate the relationship between pertinent BC indicators and CRC. Methods: Bioelectrical impedance analysis, laboratory test results, face-to-face questionnaire investigation, and nutritional risk assessment (Nutritional Risk Screening 2002 and Patient-Generated Subjective Global Assessment) were used in this case-control study. Bioelectrical impedance analysis in the case group was performed prior to antitumor therapy/surgery. Results: From June 2018 to January 2019, a total of 303 cases and 286 controls were included. The results showed that low body fat percentage (BFP) and high visceral adiposity index (VAI) groups had a higher risk of developing CRC in comparison to the normal BFP and normal VAI groups. The risk of CRC decreased with the increase of BFP. The group with a normal BC had a lower risk of developing CRC compared to those with a greater VAI and a lower BFP, as indicated by the results of the pairwise and total combinations of VAI, fat-free mass index (FFMI), and BFP. Additionally, FFMI and VAI had positive correlations with prealbumin, serum albumin, and nutritional risk scores. Conclusion: Low BFP and high VAI are associated with higher CRC risk. FFMI and VAI are positively correlated with prealbumin, serum albumin, and nutritional risk scores in CRC patients.",14321335,ONCOLOGY
10.1007/s44196-024-00544-2,Bipolar Neutrosophic Dombi-Based Heronian Mean Operators and Their Application in Multi-criteria Decision-Making Problems,"Dombi operations based on the Dombi t-norm (TN) and t-conorm (TCN) have the advantage in terms of operational parameter flexibility in dealing with varying degrees of uncertainty and aggregation requirements. Meanwhile, Heronian mean (HM) operator is an effective technique for capturing the interrelationship between any number of inputs. Bipolar neutrosophic set (BNS) offers the ability to represent both positive and negative information as well as indeterminate information. It is beneficial in cases where there is uncertainty or insufficient information. However, the existing Dombi operator under BNS do not take into account the interrelationship between input arguments. To overcome this limitation, this study incorporates Dombi operator into HM and propose the bipolar neutrosophic Dombi Heronian mean aggregation operator. This paper introduces two type of aggregation operators namely bipolar neutrosophic Dombi-based generalized weighted Heronian mean (BND-GWHM), and bipolar neutrosophic Dombi-based improved generalized weighted Heronian mean (BND-IGWHM). The proposed operators are integrated into MCDM procedure. The influence of different parameter values on decision-making results is discussed. Finally, a comparison analysis with existing methods is also provided.",18756883,AI
10.1186/s40359-024-01875-7,Validation of a German version of the caregiver strain questionnaire-short form 11 (CGSQ-SF11),"Objective: Caring for a child, particularly one with special healthcare needs, is a demanding task that can lead to the experience of caregiver strain. This in turn has an effect on the caregiver’s mental health, as well as on the child and his or her treatment. To enable the identification of afflicted parents, this study aims to provide a German version of the Caregiver Strain Questionnaire–Short Form 11 (CGSQ-SF11) and to examine its factor structure and psychometric properties. Methods: Data from 698 caregivers were included in the analyses. Caregivers completed the CGSQ-SF11 along with measures of parenting stress (PSI-SF), stress (PSS-10), anxiety (GAD-7), depression (PHQ-8), family-related quality of life (FLQ), and social desirability (SES-17) as additional instruments for validation. A two-week follow-up questionnaire included only the CGSQ-SF11. Exploratory factor analysis followed by a confirmatory factor analysis was conducted for parents of children with and without special healthcare needs, separately. Further analyses examined the validity and reliability of the instrument. Results: For parents of children with special healthcare needs, a three-factor structure (objective, internalized subjective, externalized subjective strain) with a second-order factor (caregiver strain) was supported. For parents of children without special healthcare needs, a similar three-factor structure was found, although the second-order factor was not supported. Measurement invariance between the two groups was not confirmed. Internal consistency, test-retest reliability, and validity were largely supported in both groups. Conclusions: The results indicate that the German version of the CGSQ SF-11 is a valid and reliable questionnaire for measuring caregiver strain.",20507283,PSYCHOLOGY
10.3389/feduc.2024.1252222,A latent class analysis on students' beliefs about teachers' practices enhancing their well-being,"Student well-being and student voice are two interrelated concepts that can play a critical role in education. While Student well-being refers to the overall state of students' physical, mental, and emotional health, student voice represents the active involvement and participation of students in shaping their own educational experiences. Notwithstanding the intimate association, there is a limited body of research that explores how students' distinct perceptions of teachers' practices that promote their well-being influence students' actual well-being levels. To address this research gap, a study was conducted involving 486 students. The participants, with an average age of 13.5 years, completed a questionnaire. Among the participants, 51.1% identified as female, and 13.6% had experienced academic retention. The latent class results classified the 7–9 grade student's beliefs about teacher's practices into “few times,” sometimes' and “often.” The model fitting results were as follows: Akaike Information Criterion (AIC) was 2,555.904, Bayesian Information Criterion (BIC) was 2,610.244, Adjusted Bayesian Information Criterion (aBIC) was 2,568.983, and Entropy was 0.802. Compared with the “few times” and “sometimes” class, the “often” class was more prevalent in 8th grade (p = 0.05) and among male students (p = 0.04). Findings show that class membership is a predictor of student well-being (interpersonal, life satisfaction and perceived competence). Students who feel that their teachers are attentive, supportive, and address their needs more frequently are more likely to experience enhanced well-being.",2504284X,EDUCATION
10.3389/feduc.2024.1418398,Research approaches in master-based teacher education preparing student teachers for professional work,"Student teachers have been found to be critical toward the research approaches they learned from their master's-based teacher education programmes. Our aim is to discuss how certain research approaches learnt during a 5-year academic master's level teacher education, may bring student teachers close to practice and provide them with conceptual and practical tools for a thorough understanding of the practice of teaching. The argumentation is based on an elaboration of master's-based teacher education programs in Finland and Norway and the essential characteristics of teachers' work. We elaborate on student teachers' need to understand constative, critical and constructive research approaches. This includes critical approaches such as observations and interviews for understanding and interpretation, and constructive approaches such as action research and lesson studies. Finally, we argue that, through these approaches, student teachers make use of research knowledge in teachers' work with an inquiring orientation as well as develop and change their practice.",2504284X,EDUCATION
10.3390/ejihpe14070135,"Determinants of Inequalities in the Exposure to and Adoption of Multiple Health Risk Behaviors among Brazilian Adolescents, 2009–2019","The occurrence of multiple risk behaviors among adolescents imposes challenges in the context of public policies of health, particularly in low- and middle-income countries. Evidence on the conditions leading to the exposure to and adoption of multiple risk behaviors allows the identification of vulnerable groups of adolescents, and may support the proposition of targeted strategies directed to individuals at risk. Therefore, the aim of this study was to perform a quantitative analysis to identify recent trends in the exposure to and adoption of multiple health risk behaviors among Brazilian adolescents, highlighting individual-, household-, and school-level characteristics linked to inequalities among social groups. The analysis was based on cross-sectional data from the National Student Health Survey (PeNSE), conducted by the Brazilian Institute for Geography and Statistics in 2009, 2012, 2015, and 2019. The trends in the occurrence of multiple risk behaviors among adolescents were estimated according to social strata, allowing the calculation of concentration indexes and their disaggregation into major determinants of inequalities in the exposure and adoption of risk behaviors. The analyses were conducted using a complex survey design to allow representativeness at the population level. The results showed a rise in the incidence of multiple risk behaviors among youngsters in Brazil from 2009 to 2019. Factors influencing inequalities in the exposure to multiple risk behaviors were socioeconomic status and the characteristics of the household and school environments, whilst the adoption of multiple risk behaviors was also influenced by early exposure to multiple risk behaviors. Furthermore, trends in inequalities in the exposure to and adoption of multiple risk behaviors showed an intensification from 2009 to 2019, being initially concentrated among wealthier adolescents, followed by a transition to higher incidence in the lower socioeconomic strata in 2012 and 2015, respectively. The findings underscore the role of support systems for adolescents at risk within the familial and school contexts, whereas strategies of public policies of health based on the strengthening of community ties may require improvements to tackle socioeconomic inequalities in the occurrence of risk behaviors among youngsters.",22549625,PSYCHOLOGY
10.1186/s40594-024-00490-7,Employing technology-enhanced feedback and scaffolding to support the development of deep science understanding using computer simulations,"Constructivist learning theories consider deep understanding of the content to be the result of engagement in relevant learning activities with appropriate scaffolding that provides the learner with timely and substantive feedback. However, any group of students has a variety of levels of knowledge and cognitive development, which makes providing appropriate individual-level scaffolding and feedback challenging in the classroom. Computer simulations can help meet this challenge by providing technology-enhanced embedded scaffolding and feedback via specific simulation design. The use of computer simulations does not, however, guarantee development of deep science understanding. Careful research-driven design of the simulation and the accompanying teaching structure both play critical roles in achieving the desired learning outcomes. In this paper, we discuss the capabilities of computer simulations and the issues that can impact the learning outcomes when combining technology-enhanced scaffolding and feedback with external teaching structures. We conclude with suggestions of promising research avenues on simulation design and their use in the classroom to help students achieve deep science understanding.",21967822,EDUCATION
10.3389/fonc.2024.1403522,Predicting Ki-67 expression levels in breast cancer using radiomics-based approaches on digital breast tomosynthesis and ultrasound,"Purpose: To construct and validate radiomics models that utilize ultrasound (US) and digital breast tomosynthesis (DBT) images independently and in combination to non-invasively predict the Ki-67 status in breast cancer.Materials and methods: 149 breast cancer women who underwent DBT and US scans were retrospectively enrolled from June 2018 to August 2023 in total. Radiomics features were acquired from both the DBT and US images, then selected and reduced in dimensionality using several screening approaches. Establish radiomics models based on DBT, and US separately and combined. The area under the receiver operating characteristic curve (AUC), accuracy, specificity, and sensitivity were utilized to validate the predictive ability of the models. The decision curve analysis (DCA) was used to evaluate the clinical applicability of the models. The output of the classifier with the best AUC performance was converted into Rad-score and was regarded as Rad-Score model. A nomogram was constructed using the logistic regression method, integrating the Rad-Score and clinical factors. The model’s stability was assessed through AUC, calibration curves, and DCA.Results: Support vector machine (SVM), logistic regression (LR), and random forest (RF) were trained to establish radiomics models with the selected features, with SVM showing optimal results. The AUC values for three models (US_SVM, DBT_SVM, and merge_SVM) were 0.668, 0.704, and 0.800 respectively. The DeLong test indicated a notable disparity in the area under the curve (AUC) between merge_SVM and US_SVM (p = 0.048), while there was no substantial variability between merge_SVM and DBT_SVM (p = 0.149). The DCA curve indicates that merge_SVM is superior to unimodal models in predicting high Ki-67 level, showing more clinical values. The nomogram integrating Rad-Score with tumor size obtained the better performance in test set (AUC: 0.818) and had more clinical net.Conclusion: The fusion radiomics model performed better in predicting the Ki-67 expression level of breast carcinoma, but the gain effect is limited; thus, DBT is preferred as a preoperative diagnosis mode when resources are limited. Nomogram offers predictive advantages over other methods and can be a valuable tool for predicting Ki-67 levels in BC.",2234943X,ONCOLOGY
10.3389/fpsyg.2024.1389581,The geo domain: a review on the conceptualization of geographical and geopolitical entities,"Investigating how people represent the natural environment and abstract it into geographical (e.g., mountain) and geopolitical (e.g., city) categories is pivotal to comprehending how they move and interact with the places they inhabit. Yet, the conceptualization of geographical and geopolitical domains has received scant attention so far. To deal with that, we reviewed 50 articles tackling this topic. Most studies have focused on assessing the universality of these concepts—especially geographical ones—mainly using free-listing and ethnophysiographic methods. Current perspectives tend to favor a non-universalistic characterization of these kinds of concepts, emphasizing their high cross-linguistic and cross-cultural variability, especially when compared to other semantic domains. Since geographical and geopolitical features are not pre-segmented by nature, the role of categories imposed by humans is crucial for these concepts. Significantly, their variability does not only depend on “cross” differences: evidence suggests that the cognitive demand requested by the task, idiosyncratic characteristics of individuals such as expertise level, and the typology of inhabited environments are further factors impacting the conceptual flexibility of these domains. Exploring the factors influencing our understanding of geographical and geopolitical categories can provide valuable insights for instructing effective communication policies to enhance sustainable development and address ecological emergencies, taking into consideration diverse cultural backgrounds within different populations.",16641078,PSYCHOLOGY
10.1186/s40359-024-01886-4,Emotional intelligence impact on academic achievement and psychological well-being among university students: the mediating role of positive psychological characteristics,"The main objective of this study is to examine the relationship of emotional intelligence with psychological well-being and academic achievement through positive psychological characteristics among university students in China. The study was conducted with postgraduate and undergraduate students. The integration of emotional intelligence theory and positive psychological theory was used in this study. The introduced framework included emotional intelligence as the main independent variable, self-efficacy, motivation, and resilience as three mediators, and psychological well-being and academic achievement as two dependent variables. A survey was conducted among 518 students, and structural equation modelling was used to analyse the data. The study found that emotional intelligence was positively related to positive psychological characteristics, psychological well-being, and academic achievement, and the effects were stronger among postgraduate students. Also, positive psychological characteristics, which include self-efficacy, motivation, and resilience, mediate the relationship between emotional intelligence and psychological well-being and academic achievement, and the relationship was stronger among postgraduate students. Proper coping strategies and mechanisms can be helpful to improve both psychological well-being and academic achievement at the same time among university students.",20507283,PSYCHOLOGY
10.1186/s40594-024-00491-6,The development of mathematics expectancy-value profiles during the secondary–tertiary transition into STEM fields,"Background: To master the secondary–tertiary transition into fields of science, technology, engineering, and mathematics (STEM), academic self-beliefs play a pivotal role, especially those related to learning mathematics. The framework of expectancy-value theory has been used widely in primary and secondary education and partly in tertiary education to assess the self-beliefs of students in terms of expectancy of success and perceived value of mathematics. Based on this framework, we measured how the intrinsic value, the attainment value, the utility value, and the cost of learning mathematics as well as the expectancy of success when learning mathematics developed during the secondary–tertiary transition of students into STEM fields. Data were collected in a quantitative repeated-measures questionnaire study with two measurement points (measurement point 1: n = 710, measurement point 2: n = 487, listwise: n = 409). We conducted a latent profile analysis to identify the prevalent patterns of mathematics self-beliefs, called profiles, at each of the two measurement points. We studied the relation of these profiles to prior education, achievement at school, and achievement at university. By performing a latent transition analysis, we determined the probabilities of transitioning from the initial profiles to the posterior profiles. Results: Our analysis revealed four distinct prevalent profiles at each measurement point, ranging from highly favorable (i.e., high expectancy, high value, low cost) to highly unfavorable with respect to learning mathematics. The profiles with favorable manifestations remained stable over time, while those with undesirable manifestations deteriorated further. We observed a sharp increase in cost across all profiles. Prior achievement correlated strongly with profile membership. Conclusions: The expenditure of time and energy increased sharply during the secondary–tertiary transition, independently of the students’ initial motivational patterns. The perceived utility of mathematics for potential future careers was shown to be a significant source of motivation. The role of mathematics in future careers should thus be made visible in university teaching. Keeping the detrimental development of initially undesirable motivational profiles in mind, university teachers should create ample opportunities for students to gain a sense of accomplishment.",21967822,EDUCATION
10.3389/fpsyg.2024.1436216,Music performance anxiety: development and validation of the Portuguese music performance anxiety scale,"Several studies have developed and validated specific scales to understand, identify and confirm research hypotheses associated with music performance anxiety (MPA). These scales mostly assess behavioral, cognitive, and physiological factors. There is currently no original MPA assessment tool for higher music education in Continental Portuguese, which suggests a research gap. The aim of this study was to determine if the Portuguese Music Performance Anxiety Scale (PoMPAS), developed for this research, is a valid and reliable measure of MPA for the context of higher education in Portugal. The total sample was N = 414 (166 male, 245 female, and three without gender identification). The development of this scale was based on a three-dimensional model (behavioral, cognitive, and physiological), following the theoretical models of Salmon (1990) and Osborne and Kenny (2005). Confirmatory factor analysis of the PoMPAS suggested a good fit in a three-dimensional model with 27 items. The internal consistency values proved appropriate, showing good Cronbach’s alphas (between α = 0.81 and α = 0.90). The McDonald’s Omega also demonstrated good consistency (between ω = 0.81 and ω = 0.90). The PoMPAS is a reliable tool to measure the impact of MPA, with good psychometric qualities, specifically for the Portuguese higher music education context.",16641078,PSYCHOLOGY
10.1007/s00432-024-05869-1,Targeting CD73 limits tumor progression and enhances anti-tumor activity of anti-PD-1 therapy in intrahepatic cholangiocarcinoma,"Background & aims: Patients with intrahepatic cholangiocarcinoma (iCCA) respond poorly to immune checkpoint blockades (ICBs). In this study, we aimed to dissect the potential mechanisms underlying poor response to ICBs and explore a rational ICB-based combination therapy in iCCA. Methods: scRNA-seq dataset GSE151530 was analyzed to investigate the differentially expressed genes in malignant cells following ICBs therapy. RNA-seq analysis and western blot assays were performed to examine the upstream and downstream signaling pathways of CD73. Subcutaneous tumor xenograft models were utilized to investigate the impact of CD73 on iCCA growth. Plasmid AKT/NICD-induced spontaneous murine iCCAs were used to explore the therapeutic efficacy of CD73 enzymatic inhibitor AB680 combined with PD-1 blockade. Time-of-flight mass cytometry (CyTOF) was conducted to identify the tumor-infiltrating immune cell populations and their functional changes in murine iCCAs treated with AB680 in combination with PD-1 antibody. Results: scRNA-seq analysis identified elevated CD73 expression in malignant cells in response to ICBs therapy. Mechanistically, ICBs therapy upregulated CD73 expression in malignant cells via TNF-α/NF-κB signaling pathway. In vivo studies revealed that CD73 inhibition suppressed the growth of subcutaneous tumors, and achieved synergistic depression effects with gemcitabine and cisplatin (GC). Adenosine produced by CD73 activates AKT/GSK3β/β-catenin signaling axis in iCCA cells. CD73 inhibitor AB680 potentiates anti-tumor efficacy of PD-1 antibody in murine iCCAs. CyTOF analysis showed that AB680 combined with anti-PD-1 therapy promoted the infiltration of CD8+ T, CD4+ T cells, and NK cells in murine iCCAs, while simultaneously decreased the proportions of macrophages and neutrophils. Moreover, AB680 combined with anti-PD-1 significantly upregulated the expression of Granzyme B, Tbet and co-stimulatory molecule ICOS in infiltrating CD8+ T cells. Conclusions: CD73 inhibitor AB680 limits tumor progression and potentiates therapeutic efficacy of GC chemotherapy or anti-PD-1 treatment in iCCA. AB680 combined with anti-PD-1 therapy effectively elicits anti-tumor immune response.",14321335,ONCOLOGY
10.1186/s40594-024-00492-5,Exploring the role of disciplinary knowledge in students’ covariational reasoning during graphical interpretation,"Background: This study investigates undergraduate STEM students’ interpretation of quantities and quantitative relationships on graphical representations in biology (population growth) and chemistry (titration) contexts. Interviews (n = 15) were conducted to explore the interplay between students’ covariational reasoning skills and their use of disciplinary knowledge to form mental images during graphical interpretation. Results: Our findings suggest that disciplinary knowledge plays an important role in students’ ability to interpret scientific graphs. Interviews revealed that using disciplinary knowledge to form mental images of represented quantities may enhance students’ covariational reasoning abilities, while lacking it may hinder more sophisticated covariational reasoning. Detailed descriptions of four students representing contrasting cases are analyzed, showing how mental imagery supports richer graphic sense-making. Conclusions: In the cases examined here, students who have a deep understanding of the disciplinary concepts behind the graphs are better able to make accurate interpretations and predictions. These findings have implications for science education, as they suggest instructors should focus on helping students to develop a deep understanding of disciplinary knowledge in order to improve their ability to interpret scientific graphs.",21967822,EDUCATION
10.3389/feduc.2024.1224720,Disparities in prevalence of screening/monitoring in children with intellectual and developmental disabilities: culturally sensitive provider can mitigate effects,"Introduction: About one in six children in the US, about 17% of the population, have one or more intellectual or developmental disabilities. Increases in disability due to neurodevelopmental or mental health conditions have increased by 21% in the last decade. Early intervention based on developmental screening and provider-initiated monitoring can significantly improve long-term health and cognitive outcomes. This paper assesses whether differences in receipt of developmental screening or monitoring are associated with access to a high-quality primary care medical home and having a provider who shows sensitivity to a family’s customs and values among neurotypical children and children with intellectual and developmental disabilities (IDD).Methods: We used cross-sectional data from the National Survey of Children’s Health (NSCH) from 2017 to 2019. The NSCH is a nationally representative, parent-completed annual survey of children under 18. Children between 9 months and 5 years with IDD (n = 2,385) and neurotypical children (n = 20,200) were included in the analysis.Results: Uptake of developmental screening/monitoring in neurotypical children and children with IDD conditions was associated with belonging to minority race/ethnic backgrounds, specifically Black, Asian, and AIAN/NHPI, and single-parent households with lower incomes, being publicly insured or uninsured and not having access to a high-quality medical home. Weighted regression models showed that the odds of neurotypical children receiving developmental monitoring/screening were 53% higher when their healthcare provider always or usually demonstrated cultural sensitivity to the family’s values and customs (OR 1.53, 95% CI, 1.08–2.18, p < 0.05). For children with IDD, the odds of receipt of monitoring/screening increased by 2.1 times when the provider always/usually demonstrated an understanding of the family’s cultural norms (95% CI, 0.99–4.43, p = 0.053). Being female was significantly associated with a lack of screening/surveillance (OR 0.73, 95% CI, 0.58–0.91, p < 0.05).Discussion: With the rising prevalence of children with IDD conditions, early identification of developmental delays and subsequent access to interventions are crucial steps in supporting children and children with IDD to receive preventive care, services, and reduce disparities in accessing quality care. Implementing culturally sensitive approaches can be a low-cost and effective intervention in improving rates of provider-initiated monitoring and parent-completed screening.",2504284X,EDUCATION
10.3390/cancers16142553,Imaging and Metabolic Diagnostic Methods in the Stage Assessment of Rectal Cancer,"Rectal cancer (RC) is a prevalent malignancy with significant morbidity and mortality rates. The accurate staging of RC is crucial for optimal treatment planning and patient outcomes. This review aims to summarize the current literature on imaging and metabolic diagnostic methods used in the stage assessment of RC. Various imaging modalities play a pivotal role in the initial evaluation and staging of RC. These include magnetic resonance imaging (MRI), computed tomography (CT), and endorectal ultrasound (ERUS). MRI has emerged as the gold standard for local staging due to its superior soft tissue resolution and ability to assess tumor invasion depth, lymph node involvement, and the presence of extramural vascular invasion. CT imaging provides valuable information about distant metastases and helps determine the feasibility of surgical resection. ERUS aids in assessing tumor depth, perirectal lymph nodes, and sphincter involvement. Understanding the strengths and limitations of each diagnostic modality is essential for accurate staging and treatment decisions in RC. Furthermore, the integration of multiple imaging and metabolic methods, such as PET/CT or PET/MRI, can enhance diagnostic accuracy and provide valuable prognostic information. Thus, a literature review was conducted to investigate and assess the effectiveness and accuracy of diagnostic methods, both imaging and metabolic, in the stage assessment of RC.",20726694,ONCOLOGY
10.1007/s44196-024-00591-9,Enhancing the Performance of Vocational Education in the Digital Economy with the Application of Fuzzy Logic Algorithm,"Vocational education improves the skill and efficiency of students/learners in addition to their regular courses. Within a short period of such courses, the performance has to be improved for providing professional development. In this article, the fuzzy-based performance improvement validation method (FPIVM) is introduced. This method excels in analyzing the performance of instructor-centered vocational education improvements for varied learners. In this process, the differential performance between various training and learning sessions is identified for identifying the gap in skill improvement. The fuzzy process operates using continuous intervals for performance measures based on instructor and learner scores. This is synchronized based on the existing learner’s skill and the instructor’s efficiency in meeting the vocational course study level. In particular, the fuzzification over the independent (learner and trainer) skill score is updated for new intervals. Such skill scores are classified as high or low compared to the previous outcomes. This improves the change in instructor or mode of education for successive sessions. Thus, the quality and performance of the sessions are retained unanimously for providing better outcomes. The outcomes are revised after each session for sustaining a high learning score regardless of student density.",18756883,AI
10.3390/ejihpe14070138,"Military Values, Military Virtues, and Vulnerable Narcissism among Cadets of the Swiss Armed Forces—Results of a Cross-Sectional Study","Background: For military leaders, military values and virtues are important psychological prerequisites for successful leadership and for ethical and moral military behavior. However, research on predictors of military values and virtues is scarce. Given this background, we investigated whether Organizational Citizenship Behavior (OCB), resilience, and vulnerable narcissism might be favorably or unfavorably associated with military values and virtues, and whether vulnerable narcissism could moderate the association between the OCB-by-resilience-interaction, and military virtues. Methods: A total of 214 officer cadets (mean age: 20.75 years; 96.8% males) of the Swiss Armed Forces (SAF) volunteered to take part in this cross-sectional study. They completed a booklet of self-rating scales covering dimensions of military values and military virtues, OCB, resilience, and vulnerable narcissism. Results: Higher scores for military virtues were associated with higher scores for military values, OCB, and resilience, and with lower scores for vulnerable narcissism. Multiple regression models showed that higher scores for OCB and resilience were associated with military values and virtues. Vulnerable narcissism moderated the association between military virtues, and the OCB-by-resilience-interaction: the higher the vulnerable narcissism, the more the OCB-by-resilience-interaction was associated with lower scores for military virtues. Conclusions: Among cadets of the SAF, the associations between military values, military virtues, OCB, and resilience were highly intertwined, while vulnerable narcissism appeared to attenuate the association between military virtues, OCB, and resilience.",22549625,PSYCHOLOGY
10.1007/s44196-024-00599-1,Skin Lesion Prediction and Classification Using Innovative Modified Long Short-Term Memory-Based Hybrid Optimization Algorithm,"Identification of pigmented skin lesions is necessary for the detection of severe diseases associated with the skin organ, notably malignancy. Accurate skin cancer diagnosis can be improved with the use of image detection approaches and computer classification skills. Therefore, this research work plans to perform skin lesion prediction and classification using a novel deep learning methodology. Initially, the data related to the skin lesion are gathered from the ISIC dataset. After collecting the images, the pre-processing is performed using hair removal and filtering hair removed images via median filtering. These pre-processed images undergo segmentation process accomplished using the U-Net method. Next, the features are extracted from these segmented images with the help of color features, and texture features by GLCM and RGB histogram features. These extracted features undergo the prediction phase that is accomplished using the MLSTM model, in which the parameter optimization is done by the nature inspired novel hybrid metaheuristic algorithm referred as SC-STBO algorithm with the consideration of accuracy maximization and RMSE minimization as the major fitness for the objective function. If the predicted output is returned as the presence of skin lesion, the same novel MLSTM model classifies the final skin lesion output into seven types, such as Vascular Lesions, Melanocytic Nevi, Melanoma, Dermatofibroma, Benign Keratosis-like Lesions, BCC, and Actinic Keratoses, respectively. Seven groups of skin diseases can be identified early thanks to the suggested effort, which can then be tested and properly handled by medical professionals. With an accuracy of 0.9931, the recommended methodology clearly outperforms traditional techniques. Similarly, the suggested methodology clearly beats the conventional methods, with a recall of 0.9825.",18756883,AI
10.1186/s40594-024-00489-0,Attending to STEM education in servingness at Hispanic-serving institutions: a systematic review of more than a decade of scholarship,"Background, context, and purpose of the study: Enrolling over 60% of all Latinx undergraduate students, Hispanic-serving institutions (HSIs) are poised to play a critical role in diversifying and strengthening Science, Technology, Engineering, and Mathematics (STEM) education and the STEM workforce. However, how HSIs serve STEM students is not well understood. Accordingly, guided by Garcia et al. (Review of Educational Research 89:5–745, 2019) multidimensional servingness framework, we conducted a systematic review of the research on STEM education within the HSI context. By attending to STEM education in conversations around how HSIs may serve Latinx students and their campus communities, our ultimate aim is to improve STEM education particularly at HSIs and advance STEM servingness more broadly. Results, main findings: Through our systematic review of STEM education research at HSIs, we identified (under)studied components of servingness and gaps within this literature base. Specifically, among the 128 qualifying articles, nearly two-thirds focused on student outcomes but overlooked institutions’ organizational context, raising questions about the effect(iveness) of the studied interventions. Additionally, we identified three thematic gaps in this literature: ghosting the HSI context (i.e., relying on HSIs as research sites without considering the unique HSI context); ghosting Latinx culture (i.e., decentering Latinx students and the Latinx community’s sociocultural aspects and assets), and ghosting people and places (i.e., under-examining certain student populations like Latino men in STEM and places like Hispanic-serving community colleges). Ultimately, our study extends the field’s understanding of servingness by attending to STEM education within the context of HSI institutions. Conclusions, brief summary, and potential implications: By systematically reviewing studies on STEM education at HSIs, we identified (under)studied components of servingness and patterned gaps within this literature. In doing so, we highlight opportunities to advance STEM servingness at HSIs through future research, policy, and practice. Collectively, these avenues hold the promise of improving STEM education and diversifying the STEM workforce.",21967822,EDUCATION
10.3390/ai5030058,Computer Vision for Safety Management in the Steel Industry,"The complex nature of the steel manufacturing environment, characterized by different types of hazards from materials and large machinery, makes the need for objective and automated monitoring very critical to replace the traditional methods, which are manual and subjective. This study explores the feasibility of implementing computer vision for safety management in steel manufacturing, with a case study implementation for automated hard hat detection. The research combines hazard characterization, technology assessment, and a pilot case study. First, a comprehensive review of steel manufacturing hazards was conducted, followed by the application of TOPSIS, a multi-criteria decision analysis method, to select a candidate computer vision system from eight commercially available systems. This pilot study evaluated YOLOv5m, YOLOv8m, and YOLOv9c models on 703 grayscale images from a steel mini-mill, assessing performance through precision, recall, F1-score, mAP, specificity, and AUC metrics. Results showed high overall accuracy in hard hat detection, with YOLOv9c slightly outperforming others, particularly in detecting safety violations. Challenges emerged in handling class imbalance and accurately identifying absent hard hats, especially given grayscale imagery limitations. Despite these challenges, this study affirms the feasibility of computer vision-based safety management in steel manufacturing, providing a foundation for future automated safety monitoring systems. Findings underscore the need for larger, diverse datasets and advanced techniques to address industry-specific complexities, paving the way for enhanced workplace safety in challenging industrial environments.",26732688,AI
10.3389/feduc.2024.1374641,Distance education challenges: insight from a nationwide teacher-centric study post- COVID-19 for informed advancements,"Scholars persistently explore the enormous effects of the COVID-19 epidemic on schooling, striving to comprehend its intricacies and derive significant perspectives for forthcoming endeavors. The research-based conclusions and suggestions are deemed potentially effective in closing the gap between theory and practice in literature. This is one of the few studies that connects problems with remedies as proposed by teachers. This national teacher-centric study uses a mixed-method methodology with a random sample of teachers from public and private schools in the State of Qatar to look extensively into the problems faced during the pandemic. In the sample, there were 45 instructors who participated in semi-structured online interviews and 1,553 teachers who answered an online questionnaire. The study points out a number of issues, such as teachers’ deficiency in pedagogical competencies, sophisticated technological proficiency in the classroom, curriculum density, inadequate teaching strategies, challenges with determining students’ needs and obtaining an honest and realistic assessment that accurately represents the students’ level of learning, and the lack of extracurricular activities. According to the findings, the challenges were influenced by a number of factors, including year of experience, gender, age, specialization, education level, and extracurricular activities. We need to leverage the lessons learned to shape the future course that distance education takes to move forward, guided by our observations and insights.",2504284X,EDUCATION
10.3389/frai.2024.1330258,One or two things we know about concept drift—a survey on monitoring in evolving environments. Part B: locating and explaining concept drift,"In an increasing number of industrial and technical processes, machine learning-based systems are being entrusted with supervision tasks. While they have been successfully utilized in many application areas, they frequently are not able to generalize to changes in the observed data, which environmental changes or degrading sensors might cause. These changes, commonly referred to as concept drift can trigger malfunctions in the used solutions which are safety-critical in many cases. Thus, detecting and analyzing concept drift is a crucial step when building reliable and robust machine learning-driven solutions. In this work, we consider the setting of unsupervised data streams which is highly relevant for different monitoring and anomaly detection scenarios. In particular, we focus on the tasks of localizing and explaining concept drift which are crucial to enable human operators to take appropriate action. Next to providing precise mathematical definitions of the problem of concept drift localization, we survey the body of literature on this topic. By performing standardized experiments on parametric artificial datasets we provide a direct comparison of different strategies. Thereby, we can systematically analyze the properties of different schemes and suggest first guidelines for practical applications. Finally, we explore the emerging topic of explaining concept drift.",26248212,AI
10.1186/s40359-024-01887-3,"Understanding the public stigma of mental illness: a mixed-methods, multi-level, exploratory triangulation study","Background: This study examines the role of themata in understanding mental health-related stigma. It is motivated by the need for alternative theoretical-methodological approaches beyond the dominant frameworks in education and contact-based anti-stigma public health efforts, which have shown mixed effects. Specifically, it addresses the need for a more nuanced framework in stigma research, one that is sensitive to the dialogues through which people relate themselves to mental health and stigma in context. Methods: The research employs an exploratory mixed-methods approach, including the analysis of 529 news reports, 20 focus group discussions, and 19 one-to-one interviews, all concerning representations of shared living arrangements with someone perceived to have experiences of mental illness. Thematic analysis and natural language processing are used within a convergent triangulation design to analyze the data. Results: We found that mental health and illness were communicated through an overarching Self/Other thema and five subordinate themata: normal/abnormal, harm/non-harm, bounded/non-bounded, and moral/immoral. Despite familiarity with psychological distress and ‘modern’ explanations of mental illness, concerns about social identity motivated representations of mental illness as a predominantly permanent, negative form of personhood marked by abnormality, harm, distance, and immorality. Additionally, concerns about personal vulnerability, including historically rooted fears of contagion, motivated distancing representations of mental illness, rather than neutral portrayals. Conclusions: Themata have under-developed theoretical and methodological potential for addressing mental health-related stigma, particularly in their ability to describe the dynamic ways in which culture motivates people to both resist and reproduce stigma, partly through ambivalences, absences, tensions, and ambiguities in representation. A critical discussion is provided on how themata may support ecological strategies in mental health campaigns over generic models, emphasizing the need to understand group knowledge and contact dynamics to mitigate adverse effects. Themata Public Health Unintended Consequences Mixed Methods Behaviour Change Natural Language Processing.",20507283,PSYCHOLOGY
10.3390/educsci14070797,Enhancing Technology-Focused Entrepreneurship in Higher Education Institutions Ecosystem: Implementing Innovation Models in International Projects,"Innovation models are key to fostering technology-focused entrepreneurship in higher education institutions (HEIs). These models create dynamic environments that encourage collaboration, creativity, and problem-solving skills among students and faculty. HEIs face several challenges in fostering entrepreneurship, including allocating sufficient financial and human resources, integrating entrepreneurship education across disciplines, and managing intellectual property. Overcoming these challenges requires HEIs to cultivate an entrepreneurial culture and establish strong partnerships with industry stakeholders. To achieve these goals, HEIs must adopt successful innovation models proven to work. This article presents an international case study highlighting such models and the factors contributing to their success. This study explores the implementation and impact of innovation models, specifically IDEATION and DEETECHTIVE, within HEIs to foster technology-focused entrepreneurship. By implementing numerous actions focusing on online education integration and the Quintuple Helix Innovation Model, these models support shifting engineering students’ mindsets toward entrepreneurship. This research highlights the importance of academia–industry collaboration, international partnerships, and the integration of entrepreneurship education in technology-focused disciplines. This study presents two models. The first, IDEATION, focuses on open innovation and sharing economy aspects. This model underwent rigorous testing and refinement, evolving into the second model, DEETECHTIVE, which is more comprehensive and deep tech-focused. These models have been validated as effective frameworks for fostering entrepreneurship and innovation within HEIs. This study’s findings underscore the potential of these models to enhance innovation capacity, foster an entrepreneurial culture, and create ecosystems rich in creativity and advancement. Practical implications include the establishment of open innovation-oriented structures and mechanisms, the development of specialized curriculum components, and the creation of enhanced collaboration platforms.",22277102,EDUCATION
10.3390/ejihpe14070140,Well-Being and Dispositional Hope in a Sample of Portuguese Citizens: The Mediating Role of Mental Health,"In our pursuit of a fulfilling and contented life, the study of well-being has emerged as a fundamental field of research. Higher levels of well-being are associated with better mental health outcomes. Individuals with better mental health might possess the personal resources necessary to set and pursue meaningful goals, maintain positive expectations, and overcome adversities. We aim to explore the positive relationship between well-being (hedonic, psychological, and social) and dispositional hope. We suggest that mental health acts as a mediator in this relationship, since improved mental health can create a conducive environment for the development and maintenance of dispositional hope. Data were collected using an e-survey through social media during the last quarter of 2022. The hypothesis of this study was tested using mediation analysis. The sample was composed of 471 participants (85.4% female) with a mean age of 47.72 ± 11.86 years. Participants were mainly workers (88.6%), followed by pensioners (6.8%), university students (2.5%), and unemployed (2.1%). Results revealed that well-being was positively and significantly associated with dispositional hope. Additionally, well-being presented a significant and positive relationship with mental health, which, in turn, also presented a significant and positive relationship with dispositional hope. Finally, using the Hayes process macro for SPSS, we found that mental health mediates the relationship between well-being and dispositional hope. Our findings reinforce the conceptual frameworks that consider well-being and mental health as key contributors to a resilient and optimistic mindset. Interventions that aim to cultivate positive affect, facilitate personal growth, and foster supportive social environments might help improve mental health outcomes.",22549625,PSYCHOLOGY
10.3390/ai5030059,Dynamic Programming-Based White Box Adversarial Attack for Deep Neural Networks,"Recent studies have exposed the vulnerabilities of deep neural networks to some carefully perturbed input data. We propose a novel untargeted white box adversarial attack, the dynamic programming-based sub-pixel score method (SPSM) attack (DPSPSM), which is a variation of the traditional gradient-based white box adversarial approach that is limited by a fixed hamming distance using a dynamic programming-based structure. It is stimulated using a pixel score metric technique, the SPSM, which is introduced in this paper. In contrast to the conventional gradient-based adversarial attacks, which alter entire images almost imperceptibly, the DPSPSM is swift and offers the robustness of manipulating only a small number of input pixels. The presented algorithm quantizes the gradient update with a score generated for each pixel, incorporating contributions from each channel. The results show that the DPSPSM deceives the model with a success rate of 30.45% in the CIFAR-10 test set and 29.30% in the CIFAR-100 test set.",26732688,AI
10.1007/s44196-024-00601-w,A Novel Hierarchical High-Dimensional Unsupervised Active Learning Method,"This paper processes a novel hierarchical high-dimensional clustering algorithm based on the Active Learning Method (ALM), which is a fuzzy-learning algorithm. The hierarchical part of the algorithm is composed of two phases: divisible and agglomerative. The divisible phase, a zooming-in-process, searches for sub-clusters in already-found clusters hierarchically. At each level of the hierarchy, the clusters are found by an ensemble clustering method based on the density of data. This part of the algorithm blurs each data point as multiple one-dimensional fuzzy membership functions called ink-drop patterns; then, it accumulates the ink-drop patterns of all data points on every dimension separately. Next, it performs one-dimensional density partitioning to produce an ensemble of clustering solutions; after that, combining the results is done based on a novel consensus method with the aid of prime numbers. An agglomerative phase is a bottom-up approach that merges clusters based on a novel distance metric, named $${K}^{2}$$",18756883,AI
10.3389/feduc.2024.1376805,Unveiling mode effects in grade 1 vocabulary assessment: the intriguing influence of test mode,"Background: Vocabulary knowledge plays a pivotal role in academic development, particularly among Grade 1 students. To support students in their academic development, effective assessment instruments in educational settings are crucial. The GraWo (Graz Vocabulary Test) is introduced as a tool designed to evaluate receptive vocabulary in German-speaking countries in print and in digital mode.Objectives: This study aims to investigate mode effects in the GraWo among Grade 1 students, comparing vocabulary gains in digital and print versions. Additionally, it explores the influence of student characteristics, such as gender and language status, and examines item-level differences between the two modes in order to gain a more comprehensive understanding of test performance.Design: The research design entails a longitudinal approach, following children (n = 421) from the beginning to the end of Grade 1, varying the test modes (digital or print) only at second measurement (40% receiving the print version), while at first measurement all children worked with the digital version.Results: Baseline comparisons of test mode groups indicated almost no significant differences. In terms of growth in vocabulary during Grade 1, an ANOVA with repeated measures revealed a main effect for time, indicating increased performance in both groups at second measurement. Moreover, an interaction effect between time and test mode group showed that the print group exhibited higher gains in the vocabulary test compared to the digital group. Further analysis using MNLFA confirmed that the print mode group outperformed the digital group overall and that four items were also individually affected by differences between the digital and print versions.Conclusion: The study emphasizes the need for nuanced investigations into the impact of test mode on student performance and suggests incorporating observational methods to comprehensively understand student interactions with digital and print modes. In acknowledging potential variations in performance, educators and policymakers need to tailor practices to accommodate the demands of hybrid test procedures and to consider the role of digital competence in shaping testing experiences.",2504284X,EDUCATION
10.3389/fpsyg.2024.1356999,"Exercise motivation, physical exercise, and mental health among college students: examining the predictive power of five different types of exercise motivation","Introduction: The mental health (MH) of college students has long been a crucial concern for families, educational institutions, and society. Extensive research has demonstrated the influential role of exercise motivation in shaping MH. However, further investigation is warranted to ascertain which types of exercise motivation may have more influence on the MH of college students. The present study examined the direct effects of five distinct types of exercise motivation, namely health motivation (HM), appearance motivation (APM), fun motivation (FM), ability motivation (ABM), and social motivation (SM) on MH. Additionally, the study explored the potential mediating role of physical exercise (PE) in these relationships.Methods: An cross-sectional study design was employed. A total of 433 Chinese college students participated in the study and completed our questionnaires, which included the Exercise motivation scale (EM scale), the Physical exercise scale (PE scale), and the Mental health scale (MH scale).Results: The findings revealed a significant and positive relationship between all five categories of exercise motivation and the MH of college students. Specifically, FM was found to have the most pronounced impact on MH, followed by HM, ABM, SM, and APM, in descending order of influence. Furthermore, the impacts of HM, FM, ABM, and SM on MH were found to be partially mediated by PE. However, the association between APM and MH was entirely mediated by PE.Discussion: The present study contributes to enhancing the comprehension of the underlying mechanisms behind different exercise motivations in relation to PE and MH. Additionally, it offers practical implications for developing intervention strategies for improving the MH of college students.",16641078,PSYCHOLOGY
10.3390/ai5030061,Recent Advances in 3D Object Detection for Self-Driving Vehicles: A Survey,"The development of self-driving or autonomous vehicles has led to significant advancements in 3D object detection technologies, which are critical for the safety and efficiency of autonomous driving. Despite recent advances, several challenges remain in sensor integration, handling sparse and noisy data, and ensuring reliable performance across diverse environmental conditions. This paper comprehensively surveys state-of-the-art 3D object detection techniques for autonomous vehicles, emphasizing the importance of multi-sensor fusion techniques and advanced deep learning models. Furthermore, we present key areas for future research, including enhancing sensor fusion algorithms, improving computational efficiency, and addressing ethical, security, and privacy concerns. The integration of these technologies into real-world applications for autonomous driving is presented by highlighting potential benefits and limitations. We also present a side-by-side comparison of different techniques in a tabular form. Through a comprehensive review, this paper aims to provide insights into the future directions of 3D object detection and its impact on the evolution of autonomous driving.",26732688,AI
10.3389/fpsyg.2024.1382614,Evaluating the before operational stress program: comparing in-person and virtual delivery,"Introduction: Public safety personnel (PSP) are at increased risk for posttraumatic stress injuries (PTSI). Before Operational Stress (BOS) is a mental health program for PSP with preliminary support mitigating PTSI. The current study compared the effectiveness of delivering BOS in-person by a registered clinician (i.e., Intensive) to virtually delivery by a trained clinician (i.e., Classroom).Methods: Canadian PSP completed the Intensive (n = 118; 61.9% male) or Classroom (n = 149; 50.3% male) program, with self-report surveys at pre-, post-, 1 month, and 4 months follow-ups.Results: Multilevel modelling evidenced comparable reductions in anxiety (p < 0.05, ES = 0.21) and emotional regulation difficulties (ps < 0.05, ESs = 0.20, 0.25) over time with no significant difference between modalities. Participants discussed benefits of the delivery modality they received.Discussion: The results support virtual delivery of the BOS program (Classroom) as an accessible mental health training option for PSP, producing effects comparable to in-person delivery by clinicians.",16641078,PSYCHOLOGY
10.3390/educsci14080818,The Design and Impact of Interactive Online Modules for Dental Faculty Calibration,"The diverse backgrounds of health professions faculty often result in inconsistent teaching, clinical techniques, and feedback for students. Faculty calibration is essential for uniform, high-quality instruction. However, scheduling training sessions is challenging due to faculty availability. This study introduces a self-paced, interactive online approach to dental faculty calibration. Four self-paced online modules were developed using an interactive cloud-based platform. A variety of learning activities were interspersed throughout the module to promote active learning. A survey captured faculty’s perception of the online format. ANOVA analyses examined differences in perceived effectiveness of the online format between full-time, part-time, and adjunct faculty. The platform analytics offered insights into the faculty’s module performance. Anecdotal feedback from faculty provided evidence of behavioral changes. 94% of the faculty expressed high satisfaction with the online format. The majority of faculty agreed or strongly agreed that the online format was effective (89%), engaging (88%), and easy to navigate (84%). They highlighted the modules’ user-friendliness, flexibility, and engaging content. ANOVA analyses revealed no significant differences in perceived effectiveness of the online format between full-time, part-time, and adjunct faculty. Anecdotal feedback demonstrated that faculty were incorporating the knowledge gained from the modules into their teaching practices. This positive online experience also motivated several faculty to integrate similar online approaches into their own courses. This online approach provides a more flexible, sustainable, and interactive approach to faculty development that could be beneficial to other institutions.",22277102,EDUCATION
10.3389/frai.2024.1408843,Multimodal data integration for oncology in the era of deep neural networks: a review,"Cancer research encompasses data across various scales, modalities, and resolutions, from screening and diagnostic imaging to digitized histopathology slides to various types of molecular data and clinical records. The integration of these diverse data types for personalized cancer care and predictive modeling holds the promise of enhancing the accuracy and reliability of cancer screening, diagnosis, and treatment. Traditional analytical methods, which often focus on isolated or unimodal information, fall short of capturing the complex and heterogeneous nature of cancer data. The advent of deep neural networks has spurred the development of sophisticated multimodal data fusion techniques capable of extracting and synthesizing information from disparate sources. Among these, Graph Neural Networks (GNNs) and Transformers have emerged as powerful tools for multimodal learning, demonstrating significant success. This review presents the foundational principles of multimodal learning including oncology data modalities, taxonomy of multimodal learning, and fusion strategies. We delve into the recent advancements in GNNs and Transformers for the fusion of multimodal data in oncology, spotlighting key studies and their pivotal findings. We discuss the unique challenges of multimodal learning, such as data heterogeneity and integration complexities, alongside the opportunities it presents for a more nuanced and comprehensive understanding of cancer. Finally, we present some of the latest comprehensive multimodal pan-cancer data sources. By surveying the landscape of multimodal data integration in oncology, our goal is to underline the transformative potential of multimodal GNNs and Transformers. Through technological advancements and the methodological innovations presented in this review, we aim to chart a course for future research in this promising field. This review may be the first that highlights the current state of multimodal modeling applications in cancer using GNNs and transformers, presents comprehensive multimodal oncology data sources, and sets the stage for multimodal evolution, encouraging further exploration and development in personalized cancer care.",26248212,AI
10.3389/fonc.2024.1407003,Tumor-informed ctDNA assessment as a valuable prognostic and predictive biomarker in diffuse large B-cell lymphoma,"Background: A novel approach for molecular residual disease (MRD) detection and treatment monitoring is needed in diffuse large B-cell lymphoma (DLBCL) to identify patients with a poor prognosis. We performed a retrospective evaluation of commercial ctDNA testing in patients with stage I-IV DLBCL to evaluate the prognostic and predictive role of tumor-informed ctDNA assessment.Methods: A personalized and tumor-informed multiplex PCR assay (Signatera™ bespoke mPCR NGS assay) was used for ctDNA detection and quantification.Results: In total, 50 patients (median age: 59 years; median follow-up: 12.68 months) were analyzed, of which 41 had pretreatment time points with ctDNA detected in 95% (39/41). Baseline ctDNA levels correlated with R-IPI scores and stage. ctDNA clearance during first-line therapy was predictive of improved therapy responses and outcomes (EFS, HR: 6.5, 95% CI: 1.9-22, p=0.003 and OS, HR: 22, 95% CI: 2.5-191, p=0.005). Furthermore, 48% (13/27) of patients cleared their ctDNA following the first cycle of treatment. Patients who cleared their ctDNA, irrespective of their R-IPI score, had superior outcomes compared to ctDNA-positive patients. ctDNA clearance outperformed other factors associated with EFS in multivariate analysis (HR: 49.76, 95% CI:1.1-2225.6, p=0.044). Finally, ctDNA clearance predicted complete response (CR)/no evidence of disease (NED) on average 97 days (range: 0-14.7 months) ahead of imaging/biopsy.Conclusion: ctDNA testing in patients with DLBCL is predictive of patient outcomes and may enable personalized surveillance, intervention, and/or trial options.",2234943X,ONCOLOGY
10.1186/s40594-024-00494-3,Scaffolded team-based computational modeling and simulation projects for promoting representational competence and regulatory skills,"Background: This study posits that scaffolded team-based computational modeling and simulation projects can support model-based learning that can result in evidence of representational competence and regulatory skills. The study involved 116 students from a second-year thermodynamics undergraduate course organized into 24 teams, who worked on three two-week-long team-based computational modeling and simulation projects and reflected upon their experience.Results: Results characterized different levels of engagement with computational model-based learning in the form of problem formulation and model planning, implementation and use of the computational model, evaluation, and interpretation of the outputs of the model, as well as reflection on the process. Results report on students’ levels of representational competence as related to the computational model, meaning-making of the underlying code of the computational model, graphical representations generated by the model, and explanations and interpretations of the output representations. Results also described regulatory skills as challenges and strategies related to programming skills, challenges and strategies related to meaning-making skills for understanding and connecting the science to the code and the results, and challenges and strategies related to process management mainly focused on project management skills.Conclusion: Characterizing dimensions of computational model-based reasoning provides insights that showcase students’ learning, benefits, and challenges when engaging in team-based computational modeling and simulation projects. This study also contributes to evidence-based scaffolding strategies that can support undergraduate students' engagement in the context of computational modeling and simulation.",21967822,EDUCATION
10.3390/educsci14080834,Foresight Methodologies in Responsible GenAI Education: Insights from the Intermedia-Lab at Complutense University Madrid,"This study, conducted at Complutense Intermedia-Lab, employs a dual approach to explore university students’ use of Generative AI (GenAI), combining a survey with foresight methodologies (Sci-fi prototyping). The initial survey gathers baseline data on students’ experiences, attitudes, and concerns regarding GenAI, providing a comprehensive understanding of current practices among university students in Spain. This empirical foundation informs subsequent Sci-fi prototyping sessions, where students creatively envision future scenarios, fostering futurist thinking and deeper engagement. By integrating principles of Responsible Research and Innovation (RRI), this approach facilitates a nuanced exploration of GenAI’s potential impacts on education. The incorporation of both quantitative data collection and qualitative foresight methods in this study serves to navigate challenges and level opportunities of promoting the ethical and inclusive incorporation of GenAI in Higher Education, ensuring that future innovations align with societal values and needs.",22277102,EDUCATION
10.1007/s44196-024-00606-5,A Dynamic Scheduling Method for Logistics Supply Chain Based on Adaptive Ant Colony Algorithm,"To reduce the dynamic scheduling cost of logistics supply chain and improve customer satisfaction, this paper proposes a dynamic scheduling method for logistics supply chain based on adaptive ant colony algorithm. First, determine the goal of dynamic scheduling in the logistics supply chain. Second, considering supplier satisfaction, transportation costs, and maximum delivery distance constraints, a dynamic scheduling model for logistics supply chain is constructed. Then by smoothing the pheromones and designing a transition function, adjusting factors are introduced to update the pheromone rules. Finally, based on the adaptive ant colony algorithm, the solution of the dynamic scheduling function of the logistics supply chain is solved to achieve the dynamic scheduling of the current logistics supply chain. The experimental results show that after 19 iterations, the method can search for the optimal route A1 group with a length of 33.85 km, with fewer iterations and shorter paths. The total cost is 114,290 yuan, and the degree of cargo loss is low, with a maximum of only 0.14%. The task completion time is short, customer satisfaction is above 0.85, and the scheduling accuracy is 99.9%. It can effectively control costs, improve customer satisfaction, and accurately arrange logistics supply chains.",18756883,AI
10.3390/ejihpe14080147,"Social Media Use and Consumption of Prescription-Free Medications for Anxiety, Sleep, and Pain among Norwegian University Students","A relationship has been recognized between social media use and health issues. However, no studies have explored the potential link between social media use and consumption of over-the-counter (OTC) medications. We examined social media use, self-reported anxiety, depression, sleep problems, pain, and OTC medications use among Norwegian university students. The goal was to gain insights that would guide preventive health strategies for this target group. A quantitative, cross-sectional study was conducted with an online questionnaire distributed to university student Facebook groups in Norway. A total of 132 completed surveys were analyzed. Among the respondents, 28% experienced anxiety, 35% depression, 64% sleep problems, 71% headaches, and 78% musculoskeletal pain. Moreover, 56% reported using OTC analgesics or sleep aids, mostly purchased from community pharmacies. No statistically significant correlation was found between social media use and headache, musculoskeletal pain, sleep disturbances, or consumption of OTC medications among university students in Norway. The findings, however, demonstrated a positive trend, highlighting the need for further research with larger, more diverse samples, and potentially employing a qualitative or longitudinal design. We propose increased awareness of the potential negative effects of social media among university students, the inclusion of social media and health topics in study curricula, and the more proactive engagement of community pharmacists with young clients concerning the consumption of OTC medications.",22549625,PSYCHOLOGY
10.1186/s40359-024-01912-5,"Correction: Chinese version of the tendency to avoid physical activity and Sport (TAPAS) scale: testing unidimensionality, measurement invariance, concurrent validity, and known-group validity among Taiwanese youths",,20507283,PSYCHOLOGY
10.3390/ejihpe14080148,"Mother–Child Attachment Relationship in Pregnancy, Postpartum, and Early Childhood: Current Status and New Research Perspectives","The mother–child attachment relationship is a cornerstone of human development, with profound implications for the well-being of both the mother and child",22549625,PSYCHOLOGY
10.3389/feduc.2024.1414081,Computational thinking in primary mathematics classroom activities,"The integration of computational thinking (CT) into primary education is often facilitated using one or more CT tools, such as block-based programming environments and educational robotics. A major concern is that these CT tools often are used to design mathematics classroom activities that focus on CT at the expense of mathematics. Hence, there is a need to investigate more closely how CT tools can be used in primary mathematics classroom activities in ways that enable a stronger focus on the learning of mathematics. Using information ecology as a theoretical lens, this study aims to understand how and why CT tools are integrated into primary mathematics classrooms, and how teachers value the possible contributions of such tools. We draw on multiple interviews with two primary teachers, recordings of planning sessions where classroom activities that include CT were designed, the classroom implementations themselves, and reflective conversations with the teachers after the CT tools were integrated in their mathematics classrooms. A deductive analytical approach to our data revealed that (1) CT tools, to varying degrees, facilitate the learning of mathematics; (2) some CT tools were valued by teachers as a better ‘fit’ than others; and (3) CT tools are primarily used to support the learning of geometry, excluding other mathematical domains. Based on these findings, we suggest that there is a need for more research on the use of different CT tools and their role in the learning of primary mathematics. Moreover, more research is needed to understand how CT tools can be used in topics other than geometry.",2504284X,EDUCATION
10.3389/fpsyg.2024.1445549,Exploring social media determinants in fostering pro-environmental behavior: insights from social impact theory and the theory of planned behavior,"Introduction: This study investigates the impact of social media on pro-environmental behavior (PEB) through the lenses of the Theory of Planned Behavior (TPB) and Social Impact Theory. The research aims to elucidate how social media influences Environmental Attitude (EA) and Subjective Norms (SN), and how these factors contribute to Behavioral Intentions (BI) that ultimately affect PEB. Additionally, it examines the moderating effect of Perceived Behavioral Control (PBC) on the relationship between BI and PEB.Methods: To explore these relationships, the study employs a dual methodological approach using Variance-Based Structural Equation Modeling (VBSEM) and Artificial Neural Networks (ANN). Data were collected from two distinct samples: 1200 participants from Taiwan for the SEM analysis and 602 respondents for the ANN study. SEM was utilized to explore causal relationships, while ANN was employed to enhance predictive accuracy.Results: The SEM analysis reveals that social media significantly affects both EA and SN, except for Social Networking Site Involvement (SNSI), which does not significantly impact EA. Additionally, the findings indicate that BI mediates the relationship between EA and PEB. However, BI does not mediate the SN-PEB relationship, and the link between SN and BI is found to be non-significant. Empirical evidence also suggests that PBC moderates the BI-PEB relationship, with a stronger influence observed under higher levels of PBC and a weaker influence under lower levels.Discussion: These results underscore the complex dynamics between social media factors and pro-environmental behavior. The study concludes that while social media plays a significant role in shaping EA and SN, its impact on EA is not mediated by SNSI. Furthermore, PBC significantly moderates the BI-PEB relationship, highlighting its critical role in PEB. The discussion addresses the implications of these findings, acknowledges the limitations encountered, and suggests potential avenues for future research.",16641078,PSYCHOLOGY
10.1007/s44196-024-00604-7,Multi-objective Approach for Dynamic Economic Emission Dispatch Problem Considering Power System Reliability and Transmission Loss Prediction Using Cascaded Forward Neural Network,"This study addresses the significant problem of Dynamic Economic Emission Dispatch (DEED), a critical consideration in power systems from both economic and environmental protection viewpoints. Reliability stands as another vital facet, impacting maintenance and operation perspectives. The integration of Artificial Neural Network (ANN)-based transmission loss prediction into the DEED model is also essential to address specific limitations and enhance the overall performance of the dispatch process. Traditionally, the DEED model relies on a single B-loss coefficient to estimate transmission losses. While this approach simplifies calculations, it fails to account for the significant variations in demand that occur throughout the dispatch period and it leads to inaccuracies in loss prediction, especially in dynamic environments. Using a single coefficient, the model cannot adequately capture the complex, non-linear relationships between power generation, load, and transmission losses under different operating conditions. To overcome this limitation, this study introduces an ANN-based loss prediction method integrated into the DEED model and uses trained ANN to replace the process of finding B-loss coefficients during each dispatch period. This paper also introduces a strategy leveraging the multi-objective northern goshawk optimizer algorithm, characterized by a non-dominated sorting and crowding distance mechanism, to enhance DEED considerations incorporating reliability (DEEDR). This novel algorithm improves the solution space effectively, maintains high population diversity and enables an even distribution of individuals sharing the same rank in the objective space. The fundamental objective of this study is to balance fuel cost, emission, and system reliability in power system operations. Compared with a few existing multi-objective optimization algorithms, this study demonstrates superior performance in generating a series of non-dominated solutions. The experimental results highlight its competitive and potential as an efficient tool in the DEED and DEEDR problems, promising a synergistic coordination of economy, environmental protection, and system reliability benefits in power system management.",18756883,AI
10.1007/s00432-024-05907-y,Impact of response to neoadjuvant chemotherapy on surgical modality in patients with T1-2N0-1M0 triple-negative breast cancer,"Purpose: Many T1-2N0-1M0 triple-negative breast cancer (TNBC) patients who undergo neoadjuvant chemotherapy (NAC) do not receive breast-conserving therapy (BCT) due to concerns about non-pCR or lymph node metastasis presence. Methods: T1-2N0-1M0 TNBC patients who underwent NAC between 2010 and 2017 were collected from the SEER database. Factors affecting surgical modalities were analyzed by multinomial logistic regression. The overall survival (OS) and breast cancer-specific survival (BCSS) were evaluated by Kaplan-Meier curves and Cox proportional hazards models. Further stratified subgroup analyses were performed based on the response to NAC and N-stage. Adjusted-hazard ratios were also calculated to exclude potential bias. Results: A total of 1112 patients were enrolled (median follow-up: 81 months), 58.5% received BCT, 23.6% received reconstruction and 17.9% received mastectomy. Response to NAC and N-stage not only influenced the choice of surgical modality but also were independent predictors for OS and BCSS. The surgery-induced survival differences mainly affect OS. Survival analyses demonstrated that the 10-year OS of BCT was superior or equal to that of mastectomy even in patients with partial response (PR) (77.4% vs. 64.1%, P = 0.013), no response (NR) (44.9% vs. 64.2%, P = 0.33), or N1 stage (75.7% vs. 57.4%, P = 0.0021). In the N1-PR cohort, mastectomy may lead to worse OS (P = 0.0012). Besides, between reconstruction and BCT, there was no statistical difference in OS or BCSS (P > 0.05). Conclusion: Our study reveals the necessity of breast surgical de-escalation. Besides, physicians should actively recommend reconstruction for individuals who strongly desire mastectomy.",14321335,ONCOLOGY
10.3390/ejihpe14080149,"Teachers’ Heart Rate Variability and Behavioral Reactions in Aggressive Interactions: Teachers Can Downregulate Their Physiological Arousal, and Progesterone Favors Social Integrative Teacher Responses","Aggressive student behavior is considered one of the main risk factors for teacher stress. The present study investigated teachers’ physiological and behavioral reactions when facing aggressive student behavior and examined which resources favor adaptive teacher reactions. The sample included 42 teachers. We assessed (a) teacher self-reports (i.e., resources, risk factors, and vital exhaustion) (b) classroom observations, (c) ambulatory assessments of teachers’ heart rate and heart rate variability, and (d) teachers’ progesterone concentrations in the hair. The present study focused on a subsample of ten teachers (9 females, Mage = 34.70, SD = 11.32) managing classes which were potentially very stressful as they had a high density of aggressive behavior. High levels of work satisfaction, hair progesterone, and a low level of work overload fostered social integrative teacher responses. Moreover, in 75% of the cases, teachers succeeded in downregulating their physiological reaction. Our results support the notion that teachers evaluate stressors in light of their resources. When they perceive their resources as insufficient for coping with a challenging situation, stress arises, and subsequently, they react inefficiently to aggressive behavior. Thus, teacher education could benefit from strengthening teacher resources and strategies for coping with aggressive student behavior.",22549625,PSYCHOLOGY
10.1186/s40594-024-00493-4,Unpacking the role of AI ethics online education for science and engineering students,"Background: As artificial intelligence (AI) technology rapidly advances, it becomes imperative to equip students with tools to navigate through the many intricate ethical considerations surrounding its development and use. Despite growing recognition of this necessity, the integration of AI ethics into higher education curricula remains limited. This paucity highlights an urgent need for comprehensive ethics education initiatives in AI, particularly for science and engineering students who are at the forefront of these innovations. Hence, this research investigates the role of an online explicit-reflective learning module in fostering science and engineering graduate students' ethical knowledge, awareness, and problem-solving skills. The study’s participants included 90 graduate students specializing in diverse science and engineering research tracks. Employing the embedded mixed-methods approach, data were collected from pre- and post-intervention questionnaires with closed-ended and open-ended questions. Results: The study's results indicate that the online explicit-reflective learning module significantly enhanced students' knowledge of AI ethics. Initially, students exhibited a medium–high level of perceived ethical awareness, which saw a modest but statistically significant enhancement following the participation. Notably, a more distinct increase was observed in students' actual awareness of ethical issues in AI, before and after the intervention. Content analysis of students’ responses to the open-ended questions revealed an increase in their ability to identify and articulate concerns relating to privacy breaches, the utilization of flawed datasets, and issues of biased social representation. Moreover, while students initially displayed limited problem-solving abilities in AI ethics, a considerable enhancement in these competencies was evident post-intervention. Conclusions: The study results highlight the important role of explicit-reflective learning in preparing future professionals in science and engineering with the skills necessary for ethical decision-making. The study highlights the need for placing more emphasis not only on students’ ability to identify AI-related ethical issues but also on their capacity to resolve and perhaps mitigate the impact of such ethical dilemmas.",21967822,EDUCATION
10.3390/ai5030065,Teaming Up with an AI: Exploring Human–AI Collaboration in a Writing Scenario with ChatGPT,"Recent advancements in artificial intelligence (AI) technologies, particularly in generative pre-trained transformer large language models, have significantly enhanced the capabilities of text-generative AI tools—a development that opens new avenues for human–AI collaboration across various domains. However, the dynamics of human interaction with AI-based chatbots, such as ChatGPT, remain largely unexplored. We observed and analyzed how people interact with ChatGPT in a collaborative writing setting to address this research gap. A total of 135 participants took part in this exploratory lab study, which consisted of engaging with ChatGPT to compose a text discussing the prohibition of alcohol in public in relation to a given statement on risky alcohol consumption. During the writing task, all screen activity was logged. In addition to the writing task, further insights on user behavior and experience were gained by applying questionnaires and conducting an additional short interview with a randomly selected subset of 18 participants. Our results reveal high satisfaction with ChatGPT regarding quality aspects, mainly cognitive rather than affect-based trust in ChatGPT’s responses, and higher ratings on perceived competence than on warmth. Compared to other types of prompts, mostly content-related prompts for data, facts, and information were sent to ChatGPT. Mixed-method analysis showed that affinity for technology integration and current use of ChatGPT were positively associated with the frequency of complete text requests. Moreover, prompts for complete texts were associated with more copy–paste behavior. These first insights into co-writing with ChatGPT can inform future research on how successful human–AI collaborative writing can be designed.",26732688,AI
10.1186/s40594-024-00495-2,Enhancing programming learning performance through a Jigsaw collaborative learning method in a metaverse virtual space,"Computational thinking (CT) is crucial to fostering critical thinking and problem-solving skills. Many elementary schools have been cultivating students’ CT through block-based programming languages such as Scratch using traditional teacher-centered teaching methods. However, the approach excessively relies on teacher lectures, so the teacher’s teaching load is hefty, and most students cannot receive timely assistance from teachers, thus reducing students’ programming learning performance, interest, and confidence. Therefore, this study designs a Jigsaw collaborative learning method implemented in a metaverse virtual space (JCLM-MVS) for peer-to-peer Scratch programming learning to promote learners’ programming learning performance, CT, and learning attitudes. This study used a quasi-experimental research method, with 48 fifth-grade students from two classes in Taiwan’s elementary school as the research participants. One class of 24 students was randomly assigned to the experimental group using JCLM-MVS to conduct Scratch programming learning, whereas the other class of 24 students was assigned to the control group using the traditional teacher-centered teaching method. The study found that the experimental group of learners showed significantly better Scratch programming learning performance and attitude than the control group, and there was no statistically significant difference in CT between both groups, but both learning approaches effectively promoted CT. Additionally, the interview results showed that most interviewees stated that using JCLM-MVS for Scratch programming learning could receive timely assistance from peers, make collaborative learning more efficient and learning more enjoyable, and more intend to use JCLM-MVS for Scratch programming learning than using traditional teacher-centered teaching method due to the effective collaborative interaction mechanisms and realistic learning space provided in the metaverse virtual space. This study presents a novel and engaging learning approach by integrating a metaverse virtual space with the Jigsaw collaborative learning method, referred to as JCLM-MVS, which enhances the effectiveness of the Jigsaw collaborative learning method in promoting Scratch programming learning performance, CT, and attitudes.",21967822,EDUCATION
10.1007/s44196-024-00611-8,Online Portfolio Selection of Fuzzy Mean Regression Strategy Considering Investor Sentiment Based on Text Data,"Investors are often affected by emotion, cognition, and other psychological factors in stock trading when making decisions. At present, people can use machine learning and other technologies to obtain a massive amount of text data from the Internet to mine information related to investor behavior and sentiment. Building intelligent online portfolio trading strategies that consider investor sentiment has become an important topic and key challenge in the financial field. Therefore, this paper explores how to use text data to depict investor sentiment, fuzzifies historical stock price data, designs a new weight transfer equation, and finally obtains a novel fuzzy mean regression strategy that considers investor sentiment based on text data. We conduct empirical tests on this strategy by using the stock price data selected from CSI300 constituent stocks, as well as the text data of investors’ opinions on the internet. The results show that the strategy proposed in this study has a higher Calmar ratio than other mean regression strategies previously studied.",18756883,AI
10.1007/s44196-024-00602-9,A Fairness Group Recommendation Algorithm Based On User Activity,"In the process of group recommendation, due to the different preferences of group members, the recommendation results cannot meet the needs of all users. How to maximize the fairness of group recommendation is still a challenge. Therefore, this paper proposes a group recommendation algorithm based on user activity. Firstly, a group discovery algorithm based on item cluster preference was used to mine potential groups. Secondly, considering the dynamic change of activity, a sliding time window is designed to investigate the recent activity of each member in the group at the time of subgroup division, and the group is divided into active subgroup and inactive subgroup. Finally, the group recommendation list was generated by aggregating the subgroup preferences by average consensus. Experimental results on the public dataset show that compared with the AGREE algorithm, the recommendation accuracy and coverage of the proposed algorithm are improved by 2.1% and 2.9%, respectively. By focusing on the preference needs of inactive users, the proposed algorithm effectively improves the recommendation satisfaction and group fairness.",18756883,AI
10.1007/s44196-024-00618-1,EFection: Effectiveness Detection Technique for Clustering Cloud Workload Traces,"Clustering is widely used in cloud computing studies to extract vital information. These studies have ignored investigating the potential improvements in clustering quality from better selection of its dimensions and methods. Consequently, developing an automated technique to perform such a selection was not addressed thoroughly. Most of the recent attempts either relied on feature reduction or general non-automated techniques, which were deemed unreliable for sufficient selection. Therefore, we first conducted a comprehensive investigation to study the impact of selecting better clustering dimensions and methods. Our results indicate achieving significant improvement by 15–70% points through better selection. Then, we developed a novel technique (EFection) to detect the best selection in advance using a combination of internal validation metrics (Davies–Bouldin) and the Pearson correlation coefficient. We evaluate our technique’s accuracy by comparing the clustering quality of its suggestions with that of the optimal selection. We then compare EFection’s performance with recent attempts to measure its superiority. Finally, we validate its applicability when adopted in cloud clustering-based studies. The results show that EFection offers high accuracy, around 83%, and surpasses prior art by 11%.",18756883,AI
10.3389/frai.2024.1433494,Enhanced fingerprint classification through modified PCA with SVD and invariant moments,"This research introduces a novel MOMENTS-SVD vector for fingerprint identification, combining invariant moments and SVD (Singular Value Decomposition), enhanced by a modified PCA (Principal Component Analysis). Our method extracts unique fingerprint features using SVD and invariant moments, followed by classification with Euclidean distance and neural networks. The MOMENTS-SVD vector reduces computational complexity by outperforming current models. Using the Equal Error Rate (EER) and ROC curve, a comparative study across databases (CASIA V5, FVC 2002, 2004, 2006) assesses our method against ResNet, VGG19, Neuro Fuzzy, DCT Features, and Invariant Moments, proving enhanced accuracy and robustness.",26248212,AI
10.1007/s00432-024-05903-2,"Advancements in triple-negative breast cancer sub-typing, diagnosis and treatment with assistance of artificial intelligence : a focused review","Triple negative breast cancer (TNBC) is most aggressive type of breast cancer with multiple invasive sub-types and leading cause of women’s death worldwide. Lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) causes it to spread rapidly making its treatment challenging due to unresponsiveness towards anti-HER and endocrine therapy. Hence, needing advanced therapeutic treatments and strategies in order to get better recovery from TNBC. Artificial intelligence (AI) has been emerged by giving its high inputs in the automated diagnosis as well as treatment of several diseases, particularly TNBC. AI based TNBC molecular sub-typing, diagnosis as well as therapeutic treatment has become successful now days. Therefore, present review has reviewed recent advancements in the role and assistance of AI particularly focusing on molecular sub-typing, diagnosis as well as treatment of TNBC. Meanwhile, advantages, certain limitations and future implications of AI assistance in the TNBC diagnosis and treatment are also discussed in order to fully understand readers regarding this issue. Graphical Abstract",14321335,ONCOLOGY
10.3389/fpsyg.2024.1438581,Stochastic heuristics for decisions under risk and uncertainty,"Models of heuristics are often predicated on the desideratum that they should possess no free parameters. As a result, heuristic implementations are usually deterministic and do not allow for any choice errors, as the latter would require a parameter to regulate the magnitude of errors. We discuss the implications of this in light of research that highlights the evidence supporting stochastic choice and its dependence on preferential strength. We argue that, in principle, the existing models of deterministic heuristics should, and can, be quite easily modified to stochastic counterparts through the addition of an error mechanism. This requires a single free parameter in the error mechanism, whilst otherwise retaining the parameter-free cognitive processes in the deterministic component of existing heuristics. We present various types of error mechanisms applicable to heuristics and discuss their comparative virtues and drawbacks, paying particular attention to their impact on model comparisons between heuristics and parameter-rich models.",16641078,PSYCHOLOGY
10.1186/s40359-024-01921-4,"Rates of, and factors associated with, common mental disorders in homeworking UK Government response employees’ during COVID-19: a cross-sectional survey and secondary data analysis","Introduction: Working on the frontline during the COVID-19 pandemic has been associated with increased risk to mental health and wellbeing in multiple occupations and contexts. The current study aimed to provide an insight into the rate of probable mental health problems amongst United Kingdom (UK) Government employees who contributed to the COVID-19 response whilst working from home, and to ascertain what factors and constructs, if any, influence mental health and wellbeing in the sample population.Method: This paper reports on the findings from two studies completed by UK Government employees. Study 1: A cross-sectional online survey, containing standardised and validated measures of common mental health disorders of staff who actively contributed to the COVID-19 response from their own homes. Binary logistic regression was used to assess factors associated with mental health outcomes. Study 2: A secondary data analysis of cross-sectional survey data collected across three timepoints (May, June, and August) in 2020 focusing on the wellbeing of employees who worked from home during the COVID-19 pandemic.Results: Study 1: 17.9% of participants met the threshold criteria for a probable moderate anxiety disorder, moderate depression, or post-traumatic stress disorder. Younger, less resilient, less productive individuals, with lower personal wellbeing and less enjoyment of working from home, were more likely to present with poorer mental health. Study 2: Found lower wellbeing was consistently associated with having less opportunities to look after one’s physical and mental health, and having unsupportive line managers and colleagues.Conclusion: It is important to ensure UK Government employees’ psychological needs are met whilst working from home and responding to enhanced incidents. It is recommended that workplaces should be seeking to continually build and improve employee resilience (e.g., through opportunities to increase social ties and support networks), essentially ensuring employees have necessary resources and skills to support themselves and others.",20507283,PSYCHOLOGY
10.1007/s00432-024-05910-3,"ATG10-dependent autophagy is required for DDX10 to regulate cell proliferation, apoptosis and stemness in colorectal cancer","Colorectal cancer (CRC) remains a highly prevalent gastrointestinal neoplasm, presenting significant prevalence and lethality rate. DEAD/H box RNA helicase 10 (DDX10) has been proposed as a potential oncogene in CRC, the specific action mechanism by which DDX10 modulates the aggressive biological cellular events in CRC remains implicitly elucidated, however. During this study, DDX10 expression was detected via RT-qPCR and Western blotting. Cell proliferation was estimated via EDU staining. TUNEL staining and Western blotting appraised cell apoptosis. Cell stemness was evaluated by sphere formation assay, RT-qPCR, Western blotting as well as immunofluorescence staining. Relevant assay kit examined aldehyde dehydrogenase (ALDH) activity. Western blotting and immunofluorescence staining also detected autophagy. DDX10 was hyper-expressed in CRC cells. Down-regulation of DDX10 hampered cell proliferation, aggravated the apoptosis while eliminated the ability to form spheroid cells in CRC. In addition, DDX10 deletion improved ATG10 expression and therefore activated autophagy in CRC cells. Consequently, ATG10 depletion or treatment with autophagy inhibitor 3-Methyladenine (3-MA) partially compensated the influences of DDX10 silencing on the proliferation, apoptosis and stemness of CRC cells. Accordingly, DDX10 deficiency may aggravate autophagy mediated by ATG10 to impede cell proliferation, stemness and facilitate cell apoptosis, hence blocking the progression of CRC.",14321335,ONCOLOGY
10.3390/ejihpe14080156,Exploring Teacher Awareness of Artificial Intelligence in Education: A Case Study from Northern Cyprus,"This study investigates the level of awareness among teachers regarding the use of artificial intelligence (AI) in education, focusing on whether this awareness varies according to socio-demographic characteristics, access to technology, and specific knowledge and beliefs about AI. Conducted in Northern Cyprus during the 2023–2024 academic year, this study employed a survey model with purposive and snowball sampling methods, involving 164 teachers. Teachers at different levels, namely, primary school, secondary school, high school, and university, were included in this study. The “Artificial Intelligence Awareness Scale”, developed by Ferikoğlu and Akgün (2022), was used to measure AI awareness. Data normality was verified through skewness and kurtosis values, allowing for parametric statistical tests such as t-tests, one-way ANOVA, logistic regression, and chi-square analysis. This study explored the distribution of AI use across different school types and educational levels and assessed the impact of sub-dimensions of AI awareness on its application in teaching. Findings revealed no significant influence of teacher demographics (age, gender, education level, type of school, institution level, and monthly income) on AI awareness. However, usage patterns indicated that university lecturers were more likely to incorporate AI in their teaching, followed by primary and high school teachers, with secondary school teachers using it the least. A Multilayer Neural Network Analysis identified practical knowledge as the most critical factor influencing the use of AI in teaching (importance weight of 0.450), followed by beliefs and attitudes (0.298), relatability (0.148), and theoretical knowledge (0.104). These results highlight the importance of practical knowledge for fostering AI integration in educational practices, underscoring significant implications for teacher training and professional development programs.",22549625,PSYCHOLOGY
10.3390/educsci14080886,Improving Teaching and Learning in Higher Education through Machine Learning: Proof of Concept’ of AI’s Ability to Assess the Use of Key Microskills,"Advances in artificial intelligence (AI), including intelligent machines, are opening new possibilities to support teaching and learning in higher education. This research has found a ‘proof of concept’ in the application of machine learning in the assessment of educators’ use of four key microskills, drawn from an internationally established framework. The analysis of teaching videos where these microskills were demonstrated multiple times in front of a green screen or in a space formed the data set. Multiple videos of this nature were recorded to allow for increased analysis and deconstruction of the video components to enable the application of machine learning. The results showed how AI can be used to support the collaborative and reflective practice of educators in a time when online teaching has become the norm. Having achieved a ‘proof of concept’, this research has laid the groundwork to allow for the whole framework of ten microskills to be applied in this way thus adding a new dimension to its use. Providing such critical information that is not currently available in such a systematic and personalised way to educators in the higher education sector can also support the validity of formative assessment practices.",22277102,EDUCATION
10.3390/cancers16162845,Deep Neural Network Integrated into Network-Based Stratification (D3NS): A Method to Uncover Cancer Subtypes from Somatic Mutations,"(1) Background: The identification of tumor subtypes is fundamental in precision medicine for accurate diagnoses and personalized therapies. Cancer development is often driven by the accumulation of somatic mutations that can cause alterations in tissue functions and morphologies. In this work, a method based on a deep neural network integrated into a network-based stratification framework (D3NS) is proposed to stratify tumors according to somatic mutations. (2) Methods: This approach leverages the power of deep neural networks to detect hidden information in the data by combining the knowledge contained in a network of gene interactions, as typical of network-based stratification methods. D3NS was applied using real-world data from The Cancer Genome Atlas for bladder, ovarian, and kidney cancers. (3) Results: This technique allows for the identification of tumor subtypes characterized by different survival rates and significant associations with several clinical outcomes (tumor stage, grade or response to therapy). (4) Conclusion: D3NS can provide a base model in cancer research and could be considered as a useful tool for tumor stratification, offering potential support in clinical settings.",20726694,ONCOLOGY
10.1186/s40359-024-01782-x,Psychometric properties of the newly developed self-report environmental determinants of health questionnaire (EDH-Q): development and validation,"The environmental determinants of health (EDH) have a significant impact on people’s physical, mental, and social wellbeing. Everyone needs access to environmental resources of all types, including food, materials, and energy, to survive. Currently, no valid and reliable instrument exists for evaluating individuals’ perceived levels of EDH. Hence, the purpose of this study was to develop and validate the environmental determinants of health questionnaire (EDH-Q) among undergraduate students in Nigeria. We conducted a cross-sectional survey among undergraduate students in Nigeria to assess the psychometric properties of the newly developed Environmental Determinants of Health Questionnaire (EDH-Q). Respondents were selected using a convenience sampling approach to evaluate their perceptions of environmental determinants of health. The Content Validity Index (CVI) and Face Validity Index (FVI) were calculated to ascertain the scale’s content validity and response process validity, respectively. Additionally, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), composite reliability (CR), average variance extracted (AVE), Cronbach’s alpha, and intraclass correlation coefficient (ICC) were computed to assess the scale’s construct validity. The study involved 300 respondents in the EFA (males 55.7%, females 44.3%) and 430 respondents in the CFA (males 54.0%, females 46.0%). In the EFA, two constructs were identified (the natural environment and the built environment). The EFA model was able to explain 63.57% of the total cumulative variance, and the factor correlation was 0.671. The whole scale Cronbach’s alpha value was 0.947, while the two constructs’ Cronbach’s alpha values were 0.918 (natural environment) and 0.935 (built environment). In the CFA, six pairs of error covariances were included between items within the same construct to improve the fit indices of the initial proposed measurement model. The final re-specified measurement model showed that the EDH-Q, which has two constructs and 18 items, has adequate construct validity (CFI = 0.948, TLI = 0.938, SRMR = 0.046, RMSEA = 0.052, and RMSEA p-value = 0.344). The CRs were 0.845 (natural environment) and 0.854 (built environment). The ICCs were 0.976 (natural environment) and 0.970 (built environment). The results show that the newly created EDH-Q has sufficient construct validity and may be utilized to assess participants’ perceptions of their level of EDH. Researchers should examine this instrument in populations with different age ranges and other demographic characteristics, as the present study only applied it to undergraduate students who may share similar characteristics.",20507283,PSYCHOLOGY
10.1007/s44196-024-00623-4,The Application of Big Data and Fuzzy Decision Support Systems in the Innovation of Personalized Music Teaching in Universities,Personalized music teaching in universities improves students’ learning and efficiency through adaptive guidance. This adaptability requires large study data and intelligent decisions based on the learner’s ability. This article introduces a Definitive Teaching Support System (DTSS) exclusive to music learning to augment this concept. This system is designed to increase the adaptability of music learning based on student interest and ability. The system is powered by a fuzzy decision system for identifying maximum teaching adaptability to personalized processes. Low-to-high-sorted personalization provides new endorsements for further music sessions in the fuzzy derivative process. Maximum adaptability is the target for new personalized sessions in the universities. This differs for various students from which a common adaptability level for monotonous recommendations is identified. The identified adaptability is set as a global maximum solution towards music learning personalization. The defuzzification reduces the chances of low adaptability by expelling the stationary adaptability outcomes.,18756883,AI
10.3389/fonc.2024.1422776,Applying enhanced recovery after surgery protocols in a patient with a giant spleen: a case report,"Although splenomegaly is a common finding in several diseases, massive splenomegaly is rare. Patients with massive splenomegaly often present with a complex clinical picture. This case report describes a 72-year-old female with a complex medical history. Fifteen years ago, she was diagnosed with primary myelofibrosis, which subsequently led to progressive abdominal enlargement and bloating over the past 5 years. Recently, she developed edema in her limbs, accompanied by dizziness, shortness of breath, and fatigue. A massive splenomegaly was discovered during her hospitalization. Additionally, the patient has a history of Crohn’s disease, gout, renal insufficiency, and hypertension. Laboratory results reveal severe anemia and thrombocytopenia. Abdominal CT scans confirm the enlarged spleen and show ascites. She was treated by a multidisciplinary team comprising several departments. Even after a period of comprehensive treatment, the symptoms of massive splenomegaly did not significantly improve. Thus, the patient underwent an open surgical excision of the giant spleen. The weight of the giant spleen was 5.0 kg. During the perioperative period, Enhanced Recovery After Surgery (ERAS) protocols were applied to facilitate recovery. Her recovery was uneventful, and she was able to resume her regular daily routine shortly after the procedure. This report presented a complex and rare case of massive splenomegaly, and underscored that a proper medical and nursing care is the key to better recovery.",2234943X,ONCOLOGY
10.3389/fonc.2024.1425545,Mechanisms of crosstalk between the oropharyngeal microbiome and human papillomavirus in oropharyngeal carcinogenesis: a mini review,"Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer globally. Notably, human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPSCC) is on the rise, accounting for 70% of all OPSCC cases. Persistent high-risk HPV infection is linked to various cancers, but HPV infection alone is not sufficient to cause cancer. Advances in next-generation sequencing have improved our understanding of changes in the human microbiome of cancerous environments. Yet, there remains a dearth of knowledge on the impact of HPV-microbiome crosstalk in HPV-positive OPSCC. In this review, we examine what is known about the oropharyngeal microbiome and the compositional shifts in this microbiome in HPV-positive OPSCC. We also review potential mechanisms of crosstalk between HPV and specific microorganisms. Additional research is needed to understand these interactions and their roles on cancer development and progression.",2234943X,ONCOLOGY
10.3390/cancers16162864,Real-Life Management of FLT3-Mutated AML: Single-Centre Experience over 24 Years,"We analyzed 140 patients with a median age of 51 years; 21% had WBC ≥ 100 × 109/L, and 52% had an NPM1 co-mutation. Until 2018, 101 patients received chemotherapy; thereafter, 39 received 3+7+midostaurin. The overall CR rate was 64%, higher in NPM1 mutant patients (73%). Univariate analysis showed that NPM1 mutation (p = 0.032) and WBC < 100 × 109/L (p = 0.013) positively influenced the response, with a trend for FLT3i administration (p = 0.052). Multivariate analysis confirmed WBC count as an independent prognostic factor (p = 0.017). In CR1, 41/90 patients underwent allogeneic and 18 autologous transplantation. The median EFS was 1.1 vs. 1.6 years in autografted and allografted patients, respectively (p = 0.9). The one-year non-relapse mortality was 0.00% for autologous and 28% for allogeneic transplants (p = 0.007); CIR at 1 and 3 years was higher in autologous transplants (39% vs. 15% and 57% vs. 21%, p = 0.004). The median survival was not reached in the FLT3i group. Overall, 69 patients received stem cell transplantation (18 autologous, 51 allogeneic). Post-transplant FLT3i was resumed in eight patients, all alive after a median of 65 months. Allogeneic transplantation is crucial in FLT3-mutated AML, but the next challenge will be to identify which patients can benefit from transplants in CR1 and in which to intensify post-transplant therapy.",20726694,ONCOLOGY
10.3390/educsci14080898,Investigating the Impact of the Stratified Cognitive Apprenticeship Model on High School Students’ Math Performance,"This study assessed the impact of a cognitive apprenticeship model (CAM)-based stratified teaching module on the mathematical proficiency of high school students. The stratified cognitive apprenticeship model teaching module (SCTM) first involves grouping students based on their mathematical abilities. Students with higher performance are placed in one class, while those with lower scores are placed in another. Instruction for each group is then conducted using the cognitive apprenticeship model, tailoring the teaching approach to align with the specific needs and abilities of each group. A quasi-experimental design was adopted and 150 students were recruited. This study compared the outcomes of a control group, which was instructed using conventional teaching methods (CI), with those of two experimental groups—one instructed using a stratified cognitive teaching method (SCTM)-based on the CAM—and another instructed using the CAM alone. Students’ performance was evaluated based on a mathematics test including the following dimensions: knowing and understanding, investigating, communication, and application (of mathematical knowledge to real-life problems). The data were analyzed using an analysis of covariance (ANCOVA). The results indicated that students instructed using the SCTM outperformed their peers in mathematical achievement, thereby validating SCTM’s effectiveness as a comprehensive educational strategy for mathematics education at the senior high school level.",22277102,EDUCATION
10.3390/ejihpe14080157,Affective Regulation and Trait Anger Personalities: The Buffering Effect of the Companion Animal Bond,"Emotional dysregulation involving anger can have severe consequences on the individual’s psychosocial and emotional functioning. This study aimed to investigate the role that the companion animal bond and the personality dimension of trait anger play in explaining affective dysregulation. A cross-sectional online survey was administered to 365 participants. Using the PROCESS macro for SPSS, a moderated model was tested to analyze the hypothesis that affective dysregulation depends on trait anger and that the companion animal bond moderates the relationship between trait anger and affective dysregulation. The results showed that the effect of trait anger on affective dysregulation increases especially when the degree of bonding to an animal companion is low, suggesting that a strong bond to a companion animal may protect individuals with trait anger from the likelihood of experiencing affective regulation problems. The psychological, health-related, and educational implications of the current anthrozoological study include the potential of the human–animal bond in acting as a facilitator of adaptive affective regulation processes, which can reduce the levels of uncontrolled anger-related emotions and the subsequent risk of out-of-control behaviors.",22549625,PSYCHOLOGY
10.3390/ejihpe14080159,Development of Internalizing Mental Health Symptoms from Early Childhood to Late Adolescence,"Children’s mental health symptoms’ development can be characterized by both continuity and discontinuity. However, existing studies ignore the potential discontinuity in children’s internalizing symptoms’ development. Hence, the current study examines continuous and discontinuous developmental trajectories using representative data from a sample of 2792 children (49.10% females) from the Growing Up in Australia cohort assessed seven times (ages 4, 6, 8, 10, 12, 14, 16). Longitudinal measurement invariance analyses revealed that internalizing symptoms were comparable over time. Linear, quadratic, and piecewise latent growth curve models were deployed to estimate the trajectory of internalizing symptoms from early childhood to late adolescence. The analyses showed that internalizing symptoms were characterized by a quadratic-quadratic piecewise growth curve comprising two distinct phases of upward concave growth. Internalizing scores reduced steadily between ages 4 and 8 years but exhibited a slight upward curvature between ages 8 and 10 years. By age 14 years, the trajectory remained relatively stable but spiked between age 14 and 16 years. The two phases of internalizing symptoms’ development were largely unrelated. Overall, the study adds to the knowledge about the development of internalizing mental health from early childhood to late adolescence and highlights the need for additional support in late adolescence.",22549625,PSYCHOLOGY
10.3390/ai5030070,H-QNN: A Hybrid Quantum–Classical Neural Network for Improved Binary Image Classification,"Image classification is an important application for deep learning. With the advent of quantum technology, quantum neural networks (QNNs) have become the focus of research. Traditional deep learning-based image classification involves using a convolutional neural network (CNN) to extract features from the image and a multi-layer perceptron (MLP) network to create the decision boundaries. However, quantum circuits with parameters can extract rich features from images and also create complex decision boundaries. This paper proposes a hybrid QNN (H-QNN) model designed for binary image classification that capitalizes on the strengths of quantum computing and classical neural networks. Our H-QNN model uses a compact, two-qubit quantum circuit integrated with a classical convolutional architecture, making it highly efficient for computation on noisy intermediate-scale quantum (NISQ) devices that are currently leading the way in practical quantum computing applications. Our H-QNN model significantly enhances classification accuracy, achieving a 90.1% accuracy rate on binary image datasets. In addition, we have extensively evaluated baseline CNN and our proposed H-QNN models for image retrieval tasks. The obtained quantitative results exhibit the generalization of our H-QNN for downstream image retrieval tasks. Furthermore, our model addresses the issue of overfitting for small datasets, making it a valuable tool for practical applications.",26732688,AI
10.3389/frai.2024.1398205,Diagnostic performance of AI-based models versus physicians among patients with hepatocellular carcinoma: a systematic review and meta-analysis,"Background: Hepatocellular carcinoma (HCC) is a common primary liver cancer that requires early diagnosis due to its poor prognosis. Recent advances in artificial intelligence (AI) have facilitated hepatocellular carcinoma detection using multiple AI models; however, their performance is still uncertain.Aim: This meta-analysis aimed to compare the diagnostic performance of different AI models with that of clinicians in the detection of hepatocellular carcinoma.Methods: We searched the PubMed, Scopus, Cochrane Library, and Web of Science databases for eligible studies. The R package was used to synthesize the results. The outcomes of various studies were aggregated using fixed-effect and random-effects models. Statistical heterogeneity was evaluated using I-squared (I2) and chi-square statistics.Results: We included seven studies in our meta-analysis;. Both physicians and AI-based models scored an average sensitivity of 93%. Great variation in sensitivity, accuracy, and specificity was observed depending on the model and diagnostic technique used. The region-based convolutional neural network (RCNN) model showed high sensitivity (96%). Physicians had the highest specificity in diagnosing hepatocellular carcinoma(100%); furthermore, models-based convolutional neural networks achieved high sensitivity. Models based on AI-assisted Contrast-enhanced ultrasound (CEUS) showed poor accuracy (69.9%) compared to physicians and other models. The leave-one-out sensitivity revealed high heterogeneity among studies, which represented true differences among the studies.Conclusion: Models based on Faster R-CNN excel in image classification and data extraction, while both CNN-based models and models combining contrast-enhanced ultrasound (CEUS) with artificial intelligence (AI) had good sensitivity. Although AI models outperform physicians in diagnosing HCC, they should be utilized as supportive tools to help make more accurate and timely decisions.",26248212,AI
10.3389/frai.2024.1408029,Refinement of machine learning arterial waveform models for predicting blood loss in canines,"Introduction: Hemorrhage remains a leading cause of death in civilian and military trauma. Hemorrhages also extend to military working dogs, who can experience injuries similar to those of the humans they work alongside. Unfortunately, current physiological monitoring is often inadequate for early detection of hemorrhage. Here, we evaluate if features extracted from the arterial waveform can allow for early hemorrhage prediction and improved intervention in canines.Methods: In this effort, we extracted more than 1,900 features from an arterial waveform in canine hemorrhage datasets prior to hemorrhage, during hemorrhage, and during a shock hold period. Different features were used as input to decision tree machine learning (ML) model architectures to track three model predictors—total blood loss volume, estimated percent blood loss, and area under the time versus hemorrhaged blood volume curve.Results: ML models were successfully developed for total and estimated percent blood loss, with the total blood loss having a higher correlation coefficient. The area predictors were unsuccessful at being directly predicted by decision tree ML models but could be calculated indirectly from the ML prediction models for blood loss. Overall, the area under the hemorrhage curve had the highest sensitivity for detecting hemorrhage at approximately 4 min after hemorrhage onset, compared to more than 45 min before detection based on mean arterial pressure.Conclusion: ML methods successfully tracked hemorrhage and provided earlier prediction in canines, potentially improving hemorrhage detection and objectifying triage for veterinary medicine. Further, its use can potentially be extended to human use with proper training datasets.",26248212,AI
10.3389/feduc.2024.1442318,An inclusive Research and Education Community (iREC) model to facilitate undergraduate science education reform,"Over the last two decades, there have been numerous initiatives to improve undergraduate student outcomes in STEM. One model for scalable reform is the inclusive Research Education Community (iREC). In an iREC, STEM faculty from colleges and universities across the nation are supported to adopt and sustainably implement course-based research – a form of science pedagogy that enhances student learning and persistence in science. In this study, we used pathway modeling to develop a qualitative description that explicates the HHMI Science Education Alliance (SEA) iREC as a model for facilitating the successful adoption and continued advancement of new curricular content and pedagogy. In particular, outcomes that faculty realize through their participation in the SEA iREC were identified, organized by time, and functionally linked. The resulting pathway model was then revised and refined based on several rounds of feedback from over 100 faculty members in the SEA iREC who participated in the study. Our results show that in an iREC, STEM faculty organized as a long-standing community of practice leverage one another, outside expertise, and data to adopt, implement, and iteratively advance their pedagogy. The opportunity to collaborate in this manner and, additionally, to be recognized for pedagogical contributions sustainably engages STEM faculty in the advancement of their pedagogy. Here, we present a detailed pathway model of SEA that, together with underpinning features of an iREC identified in this study, offers a framework to facilitate transformations in undergraduate science education.",2504284X,EDUCATION
10.3389/feduc.2024.1333697,How can multiculturalism be celebrated through teacher training in Israel?,"Can we celebrate multiculturalism through teachers’ training in a heterogeneous and diverse setting such as Israeli society? The current study examines teachers’ processes through an online teachers’ professional development program and an interactive activity, where 68 Israeli teachers shared their cultural stories with teachers from other cultures. Findings indicate that the teachers who met with teachers from other cultures, whom they usually do not meet, wanted to learn about each other’s culture, including their religious values, practices, and traditions while looking for commonalities. Furthermore, such intercultural meetings can occur online if the activities are designed to foster meaningful meetings and discussions between different cultures despite the social rifts and the separation within the education system.",2504284X,EDUCATION
10.3390/educsci14090930,Mobile Smartphones as Tools for ICT Integration in Geography Teaching,"This article seeks to reflect on the opportunities that mobile smartphones (MSPs) present as ICT integration tools in teaching geography. The more extensive study, underpinned by the Professional Development Framework for Digital Learning (PDFDL) in ICT integration, employed a qualitative research approach. Lensed by the Professional Development Framework for Digital Learning (PDFDL), the article used the qualitative approach to garner insights from the participants regarding using MSPs as tools to integrate ICT in geography teaching. Data collection tools included interviews, observations, and document reviews. Researchers sampled (n = 4) schools, interviewed and observed (n = 13) teachers, and interviewed (n = 10) learners and (n = 8) parents in the province of KwaZulu-Natal. Furthermore, they used a purposive sampling technique to access the participants, basing the research on the premise that MSPs promote virtual reality for an array of learners. As the findings revealed, although some participants viewed the use of MSPs as a distractor in the learning space, teachers felt compelled to heed the call to modify their teaching pedagogies, such that they integrated mobile phones fruitfully in their teaching. The findings further revealed that such a paradigm shift would benefit homeschooling and facilitate a dual teaching mode at learning institutions. Curriculum planners are responsible for helping teachers accept that uncertainty is the only certainty about the future, considering the volatility, uncertainty, complexity, and augmentation (VUCA) challenges brought on by the COVID-19 pandemic. Extended lockdown periods accelerated the use of MSPs in teaching, requiring every stakeholder in the educational space to become a life-long learner by using a range of technologies and platforms.",22277102,EDUCATION
10.1186/s40594-024-00499-y,Unlocking STEM pathways: A person-centred approach exploring a teacher recruitment intervention,"This research employed a person-centred approach to evaluate the effectiveness of a recruitment intervention aimed at attracting STEM undergraduate students to the teaching profession. The study aimed to identify participant profiles based on changes of interest in teaching, examine the demographic factors associated with these profiles, and explore the outcomes associated with the identified profiles. A total of 267 participants from 18 universities in England were recruited for the study. The intervention involved presenting 12 vignettes that depicted different motivations for choosing teaching as a career. Participants rated their change of interest in teaching after reading each vignette. The latent profile analysis revealed four distinct profiles: dissuaded participants, unpersuaded participants, moderately persuaded participants, and highly persuaded participants. The highly persuaded profile reported the highest levels of self-efficacy, interest, perceived fit, and enjoyment in teaching. Participants from higher socioeconomic backgrounds were more likely to be persuaded by the recruitment intervention, but gender, ethnicity, or program levels did not significantly affect profile membership. The findings demonstrate the potential of recruitment interventions to influence the interest of STEM undergraduate students in teaching and underscore the importance of considering individual characteristics and motivations when attracting prospective teachers to the profession.",21967822,EDUCATION
10.3390/educsci14090938,Application of Student-Centered Learning in Improving Teaching English as a Foreign Language Students’ 21st-Century Skills Performance,"A student-centered learning (SCL) method has been applied to improve Teaching English as a Foreign Language (TEFL) students’ 21st-century skills at the English department of a university. Therefore, this study aimed to investigate the effect of SCL application on TEFL students’ 21st-century skills performance. To achieve this objective, a total of 220 questionnaires were distributed to TEFL students, and ten course designs were obtained from the department. Content analysis on course designs showed that hard skills were more prioritized than soft skills, while character slightly ebbed in learning design. Furthermore, SCL application through Group, Independent, and Online learning methods significantly increased TEFL students’ 21st-century skills. Hard and soft skills were most and slightly associated with cumulative grade point average (CGPA), respectively. These results showed that SCL should be properly applied to deliver course content and improve 21st-century skills performance.",22277102,EDUCATION
10.3389/frai.2024.1402098,Bayesian model of tilling wheat confronting climatic and sustainability challenges,"Conventional farming poses threats to sustainable agriculture in growing food demands and increasing flooding risks. This research introduces a Bayesian Belief Network (BBN) to address these concerns. The model explores tillage adaptation for flood management in soils with varying organic carbon (OC) contents for winter wheat production. Three real soils, emphasizing texture and soil water properties, were sourced from the NETMAP soilscape of the Pang catchment area in Berkshire, United Kingdom. Modified with OC content at four levels (1, 3, 5, 7%), they were modeled alongside relevant variables in a BBN. The Decision Support System for Agrotechnology Transfer (DSSAT) simulated datasets across 48 cropping seasons to parameterize the BBN. The study compared tillage effects on wheat yield, surface runoff, and GHG-CO2 emissions, categorizing model parameters (from lower to higher bands) based on statistical data distribution. Results revealed that NT outperformed CT in the highest parametric category, comparing probabilistic estimates with reduced GHG-CO2 emissions from “7.34 to 7.31%” and cumulative runoff from “8.52 to 8.50%,” while yield increased from “7.46 to 7.56%.” Conversely, CT exhibited increased emissions from “7.34 to 7.36%” and cumulative runoff from “8.52 to 8.55%,” along with reduced yield from “7.46 to 7.35%.” The BBN model effectively captured uncertainties, offering posterior probability distributions reflecting conditional relationships across variables and offered decision choice for NT favoring soil carbon stocks in winter wheat (highest among soils “NT.OC-7%PDPG8,” e.g., 286,634 kg/ha) over CT (lowest in “CT.OC-3.9%PDPG8,” e.g., 5,894 kg/ha). On average, NT released minimum GHG- CO2 emissions to “3,985 kgCO2eqv/ha,” while CT emitted “7,415 kgCO2eqv/ha.” Conversely, NT emitted “8,747 kgCO2eqv/ha” for maximum emissions, while CT emitted “15,356 kgCO2eqv/ha.” NT resulted in lower surface runoff against CT in all soils and limits runoff generations naturally for flood alleviation with the potential for customized improvement. The study recommends the model for extensive assessments of various spatiotemporal conditions. The research findings align with sustainable development goals, e.g., SDG12 and SDG13 for responsible production and climate actions, respectively, as defined by the Agriculture and Food Organization of the United Nations.",26248212,AI
10.3390/educsci14090953,Transforming Education Leadership through Multiple Approaches to Develop and Support School Leadership,"This article elaborates on the multiple approaches to develop and support school leadership. In a 5-year quasi-experimental longitudinal mixed-methods study based on a sample of 122 schools in three regions in a German state, 75 school leaders and their teams participated in a 3-year program using multiple approaches; the rest served as the control group. The multiple approaches covered the school leaders’ (a) professional development, comprising (i) a professional development program, (ii) individual coaching series, and (b) support for them, including (iii) school consultancy and (iv) additional financial resources. The quality of the interventions (regarding both the process and didactic qualities, as well as outcome qualities) and how the quality of both the school leadership and the schools changes over time as a consequence of these interventions are analyzed. The study’s results show a highly positive assessment of the quality and advantages of the multiple approaches and their benefits for the quality of school leadership and further aspects of the school. The regression analyses demonstrate that positively perceived outcome qualities of the interventions are associated with improvements in numerous dimensions of school quality.",22277102,EDUCATION
10.1186/s40594-024-00502-6,One size doesn’t fit all: how different types of learning motivations influence engineering undergraduate students’ success outcomes,"Motivation is the inherent belief to guide students learning goals and behaviors to make continuous efforts and strengthen learning outcomes. Previous research reported the positive impacts of learning motivation on student success, but there have been limited efforts in systematically and structurally studying different types of motivations and their impacts on students’ success in engineering education. The current study contributes to the literature by systematically examining two important types of motivations and their influences on undergraduate engineering students in a theoretically grounded manner while using an advanced analytical approach. The current study conducted a cross-sectional survey with undergraduate engineering students (n = 514) from 18 different schools across nine U.S. states. The survey assessed students’ self-report scores on six types of motivations to study developed based on formative research and the current literature and then collected students’ self-reported learning outcomes, current GPA, university satisfaction, engineering program satisfaction, and individual demographic factors. The data were then analyzed using structural equation modeling. The results showed that motivations related to family, personality, and academic expectations were consistently positively associated with all measured students’ success outcomes; motivations related to educators were associated with all four outcomes but student GPA; motivations related to course contents were associated with learning outcomes and student GPA; and motivations related to peers did not predict any of the four measured students’ success outcomes. We explain some of the unexpected results with further literature that examines engineering culture and ecology. We also make recommendations related to cognitive training, tailored engineering education, peer culture interventions, and family orientation programs.",21967822,EDUCATION
10.3389/frai.2024.1425713,Fall risk prediction using temporal gait features and machine learning approaches,"Introduction: Falls have been acknowledged as a major public health issue around the world. Early detection of fall risk is pivotal for preventive measures. Traditional clinical assessments, although reliable, are resource-intensive and may not always be feasible.Methods: This study explores the efficacy of artificial intelligence (AI) in predicting fall risk, leveraging gait analysis through computer vision and machine learning techniques. Data was collected using the Timed Up and Go (TUG) test and JHFRAT assessment from MMU collaborators and augmented with a public dataset from Mendeley involving older adults. The study introduces a robust approach for extracting and analyzing gait features, such as stride time, step time, cadence, and stance time, to distinguish between fallers and non-fallers.Results: Two experimental setups were investigated: one considering separate gait features for each foot and another analyzing averaged features for both feet. Ultimately, the proposed solutions produce promising outcomes, greatly enhancing the model’s ability to achieve high levels of accuracy. In particular, the LightGBM demonstrates a superior accuracy of 96% in the prediction task.Discussion: The findings demonstrate that simple machine learning models can successfully identify individuals at higher fall risk based on gait characteristics, with promising results that could potentially streamline fall risk assessment processes. However, several limitations were discovered throughout the experiment, including an insufficient dataset and data variation, limiting the model’s generalizability. These issues are raised for future work consideration. Overall, this research contributes to the growing body of knowledge on fall risk prediction and underscores the potential of AI in enhancing public health strategies through the early identification of at-risk individuals.",26248212,AI
10.3390/educsci14090957,Where Are the Costs? Using an Economic Analysis of Educational Interventions Approach to Improve the Evaluation of a Regional School Improvement Programme,"Education systems are moving to a more evidence-informed paradigm to improve outcomes for learners. To help this journey to evidence, robust qualitative and quantitative research can help decisionmakers identify more promising approaches that provide value for money. In the context of the utilisation of scarce resources, an important source of evidence commonly used in health and social care research is an understanding of the economic impact of intervention choices. However, there are currently very few examples where these methodologies have been used to improve the evaluation of education interventions. In this paper we describe the novel use of an economic analysis of educational interventions (EAEI) approach to understand both the impact and the cost of activities in the evaluation of a formative assessment implementation project (FAIP) designed to improve teachers’ understanding and use of formative assessment strategies. In addition to utilising a mixed method quasi-experimental design to explore the impact on learner wellbeing, health utility and attainment, we describe the use of cost-consequence analysis (CCA) to help decisionmakers understand the outcomes in the context of the resource costs that are a crucial element of robust evaluations. We also discuss the challenges of evaluating large-scale, universal educational interventions, including consideration of the economic tools needed to improve the quality and robustness of these evaluations. Finally, we discuss the importance of triangulating economic findings alongside other quantitative and qualitative information to help decisionmakers identify more promising approaches based on a wider range of useful information. We conclude with recommendations for more routinely including economic costs in education research, including the need for further work to improve the utility of economic methods.",22277102,EDUCATION
10.3390/ai5030075,Effective Hybrid Structure Health Monitoring through Parametric Study of GoogLeNet,"This paper presents an innovative approach that utilizes infused images from vibration signals and visual inspections to enhance the efficiency and accuracy of structure health monitoring through GoogLeNet. Scrutiny of the structure of GoogLeNet identified four key parameters, and thus, the optimization of GoogLeNet was completed through manipulation of the four key parameters. First, the impact of the number of inception modules on the performance of GoogLeNet revealed that employing eight inception layers achieves remarkable 100% accuracy while requiring less computational time compared to nine layers. Second, the choice of activation function was studied, with the Rectified Linear Unit (ReLU) emerging as the most effective option. Types of optimizers were then researched, which identified Stochastic Gradient Descent with Momentum (SGDM) as the most efficient optimizer. Finally, the influence of learning rate was compared, which found that a rate of 0.001 produces the best outcomes. By amalgamating these findings, a comprehensive optimized GoogLeNet model was found to identify damage cases effectively and accurately through infused images from vibrations and visual inspections.",26732688,AI
10.3390/cancers16173032,Predictors of Clinical Hematological Toxicities under Radiotherapy in Patients with Cervical Cancer—A Risk Analysis,"Background: Cervical cancer ranks third in frequency among female cancers globally and causes high mortality worldwide. Concurrent chemoradiotherapy improves the overall survival in cervical cancer patients by 6% but it can cause significant acute and late toxicities affecting patient quality of life. Whole pelvis radiotherapy doses of 10–20 Gy can lead to myelosuppression and to subsequent hematological toxicities since pelvic bones contain half of bone marrow tissue. Methods: A total of 69 patients with IB-IVB-staged cervical cancer have been included in this retrospective cohort study. We analyzed clinical adverse events and changes in blood cell counts (hemoglobin, neutrophils, leukocytes, and platelets) during radiation or chemoradiotherapy received at the Oncological Institute of Bucharest from 2018 to 2021. Results: Decreases in hemoglobin levels of over 2.30 g/dL during treatment were associated with BMI > 23.2 kg/m2 (OR = 8.68, 95%CI = [1.01, 75.01]), age over 53 years (OR = 4.60 95%CI = [1.10, 19.22]), with conformational 3D irradiation (OR = 4.78, 95%CI = [1.31, 17.40]) and with total EQD2 of over 66.1 Gy (OR = 3.67, 95%CI = [1.02, 13.14]). The hemoglobin decrease rate of 0.07 g/dL/day was related to 95% isodose volume (OR = 18.00). Neutropenia is associated frequently with gastrointestinal side effects and with the bowel and rectal V45 isodoses (OR = 16.5 and OR = 18.0, respectively). Associations of total external and internal radiation dose with the time durations calculated from the initiation of treatment to the onset of hematological adverse reactions were also obtained. The maximum drop in leukocytes was observed before day 35 from the RT initiation in patients who underwent treatment with 3D conformal radiotherapy (OR = 4.44, 95%CI = [1.25, 15.82]). Neutrophil levels under 2.2 × 103/μL and thrombocyte levels under 131 × 103/μL during the follow-up period were associated with a total planned dose of 54 Gy to the pelvic region volume (OR = 6.82 and OR = 6.67, respectively). Conclusions: This study shows the existence of clinical and blood predictors of hematological adverse reactions in cervical cancer patients. Thus, patients who are in a precarious clinical situation, with low hematological values (but not yet abnormal), should be monitored during days 29–35 after the initiation of RT, especially if they are obese or over 53 years of age.",20726694,ONCOLOGY
10.1186/s40594-024-00501-7,Academic social comparison: a promising new target to reduce fear of negative evaluation in large-enrollment college science courses,"Fear of negative evaluation, defined as a sense of dread associated with being unfavorably evaluated in a social situation, is the primary factor underlying student anxiety in college science courses and is disproportionately experienced by students who are underserved in science. Yet, it is unknown why fear of negative evaluation disproportionately affects these students and what can be done to reduce student fear of negative evaluation. Academic social comparison describes how students perceive themselves compared to their peers with regard to desirability as a groupmate, the extent they fit in among others in their major, and academic talent. We hypothesize that academic social comparison mediates the relationship between student identities and fear of negative evaluation, where individuals with underserved identities in science may perceive themselves as “less than” their peers, contributing to their fear of negative evaluation. We surveyed 909 undergraduate science majors across 15 research-intensive institutions in the United States (U.S.) to assess: (1) To what extent do student identities predict fear of negative evaluation among science undergraduates? and (2) For identities that significantly predict fear of negative evaluation, to what extent does academic social comparison mediate the relationship? We used regression, single-mediator models, and multi-mediator models to address our research questions. Women/non-binary and LGBTQ + science majors reported disproportionately high fear of negative evaluation compared to men and non-LGBTQ + science majors. Women/non-binary and LGBTQ + students also expressed lower academic social comparison relative to their respective counterparts, meaning they perceive themselves as less than their peers with regard to their desirability as a groupmate, the extent to which they fit in among others in their major, and their academic talent. Academic social comparison partially mediated the relationship between fear of negative evaluation and both gender and LGBTQ + status. Major fit, defined as the extent to which students perceive they fit in among others in their major, was found to be the primary mediating subconstruct of academic social comparison for both gender and LGBTQ + identities. Women/non-binary and LGBTQ + science majors perceive themselves as less than their peers to a greater extent than men and non-LGBTQ + science majors, contributing to their higher fear of negative evaluation in college science course. Major fit, defined as the extent to which students feel they fit in with others in their major, is the subconstruct of academic social comparison that had the strongest influence on fear of negative evaluation in our sample. Academic social comparison is a promising target for future efforts aimed at decreasing fear of negative evaluation in active learning college science courses.",21967822,EDUCATION
10.3389/feduc.2024.1392104,MAICC model: development of complex thinking through citizen science project evaluation,"As traditional education systems struggle to keep up with technological advances, incorporating open science into Education 5.0 is critical to addressing student skills gaps. In this study, the MAICC model is introduced, a tool designed to foster complex thinking in higher education students through the evaluation of citizen science projects. It integrates research-based learning and service learning, and helps develop critical and reflective skills by applying them to real-life settings. To assess student engagement and skills development, a mixed methods approach combining qualitative and quantitative analysis was used. Findings indicate that the MAICC model promotes complex thinking, enhances critical thinking through citizen science project evaluation, and features an emphasis on citizen science and educational technology. Discussion highlights citizen science’s important role in education and suggests future research exploring its wider application across disciplines and contexts to enhance 21st century skills.",2504284X,EDUCATION
10.3390/educsci14090962,A Justice-Oriented Conceptual and Analytical Framework for Decolonising and Desecularising the Field of Educational Technology,"Education systems globally are increasingly being shaped by the logics, assumptions and pedagogical underpinnings of educational technology (EdTech) products, services, programmes, policies, and systems. These often promote rationalistic, secular, universal, objectivist, (post)modernist, written, behaviourist, and individualistic ways of being, marginalising religious, spiritual, oral, subjective, critical, and communitarian ways of being. Given that technological ways of being have been propagated globally, these logics are no longer predominantly promoted by those in the Global North, but by techno-solutionists globally, although the core-to-periphery flows of ideology and funding are still prominent. This article develops a conceptual and analytical framework for decolonising and desecularising the field of EdTech. Concepts are drawn from various discourses: the desecularisation of knowledge to set the ontological framing; embodied cognition to set the epistemological framing; and social justice and decolonial discourses to set the axiological framing. From this, the article develops the Dimensions of Human Injustice Analytical Framework—covering material, ontological and epistemic, and (geo)political injustices—to assist policymakers, educators, EdTech developers, and international development practitioners in identifying and confronting coloniality in their EdTech. Acknowledging the complexity and contentions within decolonial thought, this article does not claim a unified stance on achieving justice but aims to offer a tool for deconstructing and questioning injustices.",22277102,EDUCATION
10.3389/fonc.2024.1438179,"New insights into acinic cell carcinoma of the breast: clinicopathology, origin of histology, molecular features, prognosis, and treatment","Acinic cell carcinoma (AciCC) of the breast is a rare malignant epithelial neoplasm, with approximately 60 cases reported in the literature. It predominantly affects women and exhibits significant histological heterogeneity. The diagnosis of breast AciCC is primarily based on the presence of eosinophilic and/or basophilic granular cytoplasm and markers of serous acinar differentiation. Despite being considered a low-grade variant of conventional triple-negative breast cancer (TNBC), over 25% of patients with breast AciCC have adverse clinical outcomes. Additionally, in early research, microglandular adenosis (MGA) and atypical MGA were considered potential precursors for various breast cancers, including intraductal carcinoma, invasive ductal carcinoma, adenoid cystic carcinoma, metaplastic carcinoma, and AciCC. Similarly, some studies have proposed that breast AciCC should be considered a type of carcinoma developing in MGA with acinic cell differentiation rather than a distinct entity. Therefore, the pathogenesis of breast AciCC has not yet been clarified. Moreover, to the best of our knowledge, the literature has not summarized the latest prognosis and treatment of breast AciCC. In this review, we synthesized the current literature and the latest developments, aiming at exploring the clinicopathology, histological origin, molecular features, prognosis, and treatment of breast AciCC from a novel perspective.",2234943X,ONCOLOGY
10.1007/s44196-024-00635-0,An Improved Adaptive Neuro-fuzzy Inference Framework for Lung Cancer Detection and Prediction on Internet of Medical Things Platform,"It has become increasingly difficult for medical practitioners to recognize illness in recent years due to the emergence of new diseases from their myriad causes on a daily basis. Due in large part to inadequate diagnostic and monitoring infrastructure, a substantial amount of illness and death are associated with lung cancer (LC). The aim of the paper is to find lung cancer early and help patients receive curative treatment. Quitting smoking or never starting is the best way to mitigate the potential for disease-related death. As a result, cutting-edge detection and monitoring technologies must be developed to enable rapid, accurate, and timely diagnosis. Fuzzy logic (FL) is one of the best approaches to modeling complex and uncertain systems; therefore, it helps us deal with these challenges. Fuzzy expert system for lung cancer [FES-LC] detection and prediction on Internet of medical things (IoMT) is employed to overcome the challenges. Hence, an enhanced adaptive neuro-fuzzy inference framework [ANF-IF] is proposed in the current research. The cloud-based application of an adaptive neuro-fuzzy inference system yields four risk categories: not at risk, slightly at risk, moderately at risk, and severely at risk. New methods and theoretical frameworks have made it possible to diagnose LC in its earliest stages with the help of magnetic nanoparticles (MNPs), which allow researchers to overcome the limitations of conventionally slow diagnostic efficiency. The proposed system exhibits a precision of 93.4%, accuracy of 95.1%, specificity of 90.6%, sensitivity of 92.8%, false positive rate of 0.22%, false negative ratio of 0.18%, and classification accuracy of 98.2%. The proposed method outperforms all methods and provides better lung cancer detection accuracy than others.",18756883,AI
10.3389/frai.2024.1457586,AI integration in nephrology: evaluating ChatGPT for accurate ICD-10 documentation and coding,"Background: Accurate ICD-10 coding is crucial for healthcare reimbursement, patient care, and research. AI implementation, like ChatGPT, could improve coding accuracy and reduce physician burden. This study assessed ChatGPT’s performance in identifying ICD-10 codes for nephrology conditions through case scenarios for pre-visit testing.Methods: Two nephrologists created 100 simulated nephrology cases. ChatGPT versions 3.5 and 4.0 were evaluated by comparing AI-generated ICD-10 codes against predetermined correct codes. Assessments were conducted in two rounds, 2 weeks apart, in April 2024.Results: In the first round, the accuracy of ChatGPT for assigning correct diagnosis codes was 91 and 99% for version 3.5 and 4.0, respectively. In the second round, the accuracy of ChatGPT for assigning the correct diagnosis code was 87% for version 3.5 and 99% for version 4.0. ChatGPT 4.0 had higher accuracy than ChatGPT 3.5 (p = 0.02 and 0.002 for the first and second round respectively). The accuracy did not significantly differ between the two rounds (p > 0.05).Conclusion: ChatGPT 4.0 can significantly improve ICD-10 coding accuracy in nephrology through case scenarios for pre-visit testing, potentially reducing healthcare professionals’ workload. However, the small error percentage underscores the need for ongoing review and improvement of AI systems to ensure accurate reimbursement, optimal patient care, and reliable research data.",26248212,AI
10.1007/s44196-024-00639-w,Prediction of Remaining Useful Life of Aero-engines Based on CNN-LSTM-Attention,"Accurately predicting the remaining useful life (RUL) of aircraft engines is crucial for maintaining financial stability and aviation safety. To further enhance the prediction accuracy of aircraft engine RUL, a deep learning-based RUL prediction method is proposed. This method possesses the potential to strengthen the recognition of data features, thereby improving the prediction accuracy of the model. First, the input features are normalized and the CMAPSS (Commercial Modular Aero-Propulsion System Simulation) dataset is utilized to calculate the RUL for aircraft engines. After extracting attributes from the input data using a convolutional neural network (CNN), the extracted data are input into a long short-term memory (LSTM) network model, with the addition of attention mechanisms to predict the RUL of aircraft engines. Finally, the proposed aircraft engine model is evaluated and compared through ablation studies and comparative model experiments. The results indicate that the CNN-LSTM-Attention model exhibits superior prediction performance for datasets FD001, FD002, FD003, and FD004, with RMSEs of 15.977, 14.452, 13.907, and 16.637, respectively. Compared with CNN, LSTM, and CNN-LSTM models, the CNN-LSTM model demonstrates better prediction performance across datasets. In comparison with other models, this model achieves the highest prediction accuracy on the CMAPSS dataset, showcasing strong reliability and accuracy.",18756883,AI
10.3390/ai5030078,Generative Models Utilizing Padding Can Efficiently Integrate and Generate Multi-Omics Data,"Technological advances in information-processing capacity have enabled integrated analyses (multi-omics) of different omics data types, improving target discovery and clinical diagnosis. This study proposes novel artificial intelligence (AI) learning strategies for incomplete datasets, common in omics research. The model comprises (1) a multi-omics generative model based on a variational auto-encoder that learns tumor genetic patterns based on different omics data types and (2) an expanded classification model that predicts cancer phenotypes. Padding was applied to replace missing data with virtual data. The embedding data generated by the model accurately classified cancer phenotypes, addressing the class imbalance issue (weighted F1 score: cancer type > 0.95, primary site > 0.92, sample type > 0.97). The classification performance was maintained in the absence of omics data, and the virtual data resembled actual omics data (cosine similarity mRNA gene expression > 0.96, mRNA isoform expression > 0.95, DNA methylation > 0.96). Meanwhile, in the presence of omics data, high-quality, non-existent omics data were generated (cosine similarity mRNA gene expression: 0.9702, mRNA isoform expression: 0.9546, DNA methylation: 0.9687). This model can effectively classify cancer phenotypes based on incomplete omics data with data sparsity robustness, generating omics data through deep learning and enabling precision medicine.",26732688,AI
10.3389/fpsyg.2024.1335886,Effect of social support on Muslim women’s sporting activities: mediating effect of psychological adjustment,"Objective: This study explores the relationship between social support and sporting activities of Muslim women and constructs a mediation model through role of psychological adjustment.Methods: Using stratified cluster sampling, 301 Muslim women were measured in group psychology using the Social Support Scale and the Sports Activities and Psychological Adjustment Scale. The statistical software SPSS 24.0 and SPSS PROCESS 3.3 were used for statistical processing. The common-method variation test was carried out using the Harman single-factor control test. Finally, the Bootstrap sampling test method and process plug-in were used to test the significance of the intermediary effect.Results: (1) Social support has a significant predictive effect on sports activities (β = 0.32, p < 0.001); (2) psychological adjustment (β = 0.552, p < 0.001) mediates the relationship between social support and sporting activities [social support → psychological adjustment → sporting activities (95% Cl, 0.093, 0.323)].Conclusion: Social support positively influences sporting participation among Muslim women, and psychological adjustment mediates this relationship. Strengthening social support for Muslim women can enhance their psychological adjustment, thereby improving their participation in sporting activities and offering valuable theoretical and practical guidance.",16641078,PSYCHOLOGY
10.3390/ai5030079,Facial Recognition Using Hidden Markov Model and Convolutional Neural Network,"Face recognition (FR) uses a passive approach to person authentication that avoids face-to-face contact. Among different FR techniques, most FR approaches place little emphasis on reducing powerful cryptography and instead concentrate on increasing recognition rates. In this paper, we have proposed the Hidden Markov Model (HMM) and convolutional Neural Network (CNN) models for FR by using ORL and Yale datasets. Facial images from the given data sets are divided into 3 portions, 4 portions, 5 portions, and 6 portions corresponding to their respective HMM hidden states being used in the HMM model. Quantized levels of eigenvalues and eigenvector coefficients of overlapping blocks of facial images define the observation states of the HMM model. For image selection and rejection, a threshold is calculated using singular value decomposition (SVD). After training HMM on 3 states HMM, 4 states HMM, 5 states HMM, and 6 states HMM, the recognition accuracies are 96.5%, 98.5%, 98.5%, and 99.5%, respectively, on the ORL database and 90.6667%, 94.6667%, 94.6667%, and 94.6667% on the Yale database. The CNN model uses convolutional layers, a max-pooling layer, a flattening layer, a dense layer, and a dropout layer. Relu is used as the activation function in all layers except in the last layer, where softmax is used as the activation function. Cross entropy is used as a loss function, and we have used the Adam optimizer in our proposed algorithm. The proposed CNN model has given 100% training and testing accuracy on the ORL data set. While using the Yale data set, the CNN model has a training accuracy of 100% and a testing accuracy of 85.71%. In this paper, our proposed model showed that the HMM model is cost-effective with lesser accuracy, while the CNN model is more accurate as compared to HMM but has a higher computational cost.",26732688,AI
10.3389/frai.2024.1410790,Transparency and precision in the age of AI: evaluation of explainability-enhanced recommendation systems,"In today’s information age, recommender systems have become an essential tool to filter and personalize the massive data flow to users. However, these systems’ increasing complexity and opaque nature have raised concerns about transparency and user trust. Lack of explainability in recommendations can lead to ill-informed decisions and decreased confidence in these advanced systems. Our study addresses this problem by integrating explainability techniques into recommendation systems to improve both the precision of the recommendations and their transparency. We implemented and evaluated recommendation models on the MovieLens and Amazon datasets, applying explainability methods like LIME and SHAP to disentangle the model decisions. The results indicated significant improvements in the precision of the recommendations, with a notable increase in the user’s ability to understand and trust the suggestions provided by the system. For example, we saw a 3% increase in recommendation precision when incorporating these explainability techniques, demonstrating their added value in performance and improving the user experience.",26248212,AI
10.3389/frai.2024.1419638,Noise-induced modality-specific pretext learning for pediatric chest X-ray image classification,"Introduction: Deep learning (DL) has significantly advanced medical image classification. However, it often relies on transfer learning (TL) from models pretrained on large, generic non-medical image datasets like ImageNet. Conversely, medical images possess unique visual characteristics that such general models may not adequately capture.Methods: This study examines the effectiveness of modality-specific pretext learning strengthened by image denoising and deblurring in enhancing the classification of pediatric chest X-ray (CXR) images into those exhibiting no findings, i.e., normal lungs, or with cardiopulmonary disease manifestations. Specifically, we use a VGG-16-Sharp-U-Net architecture and leverage its encoder in conjunction with a classification head to distinguish normal from abnormal pediatric CXR findings. We benchmark this performance against the traditional TL approach, viz., the VGG-16 model pretrained only on ImageNet. Measures used for performance evaluation are balanced accuracy, sensitivity, specificity, F-score, Matthew’s Correlation Coefficient (MCC), Kappa statistic, and Youden’s index.Results: Our findings reveal that models developed from CXR modality-specific pretext encoders substantially outperform the ImageNet-only pretrained model, viz., Baseline, and achieve significantly higher sensitivity (p < 0.05) with marked improvements in balanced accuracy, F-score, MCC, Kappa statistic, and Youden’s index. A novel attention-based fuzzy ensemble of the pretext-learned models further improves performance across these metrics (Balanced accuracy: 0.6376; Sensitivity: 0.4991; F-score: 0.5102; MCC: 0.2783; Kappa: 0.2782, and Youden’s index:0.2751), compared to Baseline (Balanced accuracy: 0.5654; Sensitivity: 0.1983; F-score: 0.2977; MCC: 0.1998; Kappa: 0.1599, and Youden’s index:0.1327).Discussion: The superior results of CXR modality-specific pretext learning and their ensemble underscore its potential as a viable alternative to conventional ImageNet pretraining for medical image classification. Results from this study promote further exploration of medical modality-specific TL techniques in the development of DL models for various medical imaging applications.",26248212,AI
10.3389/feduc.2024.1398477,Piloting puberty content books and a teacher training guide in Sierra Leone: a qualitative assessment,"Introduction: Ensuring young people receive adequate information and guidance about puberty is essential for healthy adolescent transitions. Although many countries are moving toward including comprehensive sexuality education in national curricula, content on puberty during early adolescence, including peer pressure and stigma related to physical and emotional changes, are rarely included. Limited evidence exists about the inclusion of puberty education in schools, and the role of teachers in delivering such content in low-and middle-income countries, including Sierra Leone.Methods: We conducted a qualitative assessment using multiple methodologies (in-depth interviews with teachers; focus group discussions with girls and boys; key informant interviews with teacher training lecturers and government) to explore the feasibility and acceptability of a puberty education package (a teacher training guide and boys’ and girls’ puberty books) for primary school teachers to introduce puberty content in Sierra Leone.Results: Three key themes were identified, including the importance of teacher comfort in discussing puberty, the value of the teacher’s guide for delivering puberty content, and system and resource constraints that impact the implementation of puberty education. Additional insights included how integrating puberty education into existing curriculum courses may be more effective than stand-alone puberty classes; education systems can enable in-service and pre-service teacher training, along with culturally appropriate puberty resources, to increase effective puberty education delivery in schools; and governments serve a key role in providing puberty education teacher training, ensuring sustainable funding to retain trained teachers, and offering guidance on national curriculum requirements on puberty education.Discussion: There is a strong need to integrate puberty education into formal educational systems, with well trained teachers serving a valuable role in its delivery. Research is needed on how best to scale sustainable teacher training interventions to support the delivery of puberty education to adolescents in low- and middle-income contexts.",2504284X,EDUCATION
10.1007/s00432-024-05930-z,Integrative radiopathomics model for predicting progression-free survival in patients with nonmetastatic nasopharyngeal carcinoma,"Purpose To construct an integrative radiopathomics model for predicting progression-free survival (PFS) in nonmetastatic nasopharyngeal carcinoma (NPC) patients. Methods 357 NPC patients who underwent pretreatment MRI and pathological whole-slide imaging (WSI) were included in this study and randomly divided into two groups: a training set (n = 250) and validation set (n = 107). Radiomic features extracted from MRI were selected using the minimum redundancy maximum relevance and least absolute shrinkage and selection operator methods. The pathomics signature based on WSI was constructed using a deep learning architecture, the Swin Transformer. The radiopathomics model was constructed by incorporating three feature sets: the radiomics signature, pathomics signature, and independent clinical factors. The prognostic efficacy of the model was assessed using the concordance index (C-index). Kaplan-Meier curves for the stratified risk groups were tested by the log-rank test. Results The radiopathomics model exhibited superior predictive performance with C-indexes of 0.791 (95% confidence interval [CI]: 0.724–0.871) in the training set and 0.785 (95% CI: 0.716–0.875) in the validation set compared to any single-modality model (radiomics: 0.619, 95% CI: 0.553–0.706; pathomics: 0.732, 95% CI: 0.662–0.802; clinical model: 0.655, 95% CI: 0.581–0.728) (all, P < 0.05). The radiopathomics model effectively stratified patients into high- and low-risk groups in both the training and validation sets (P < 0.001). Conclusion The developed radiopathomics model demonstrated its reliability in predicting PFS for NPC patients. It effectively stratified individual patients into distinct risk groups, providing valuable insights for prognostic assessment.",14321335,ONCOLOGY
10.1007/s00432-024-05923-y,Paclitaxel hyperthermia suppresses gastric cancer migration through MiR-183-5p/PPP2CA/AKT/GSK3β/β-catenin axis,"Background Gastric cancer (GC), a prevalent malignant tumor which is a leading cause of death from malignancy around the world. Peritoneal metastasis accounts for the major cause of mortality in patients with GC. Despite hyperthermia intraperitoneal chemotherapy (HIPEC) improves the therapeutic effect of GC, it’s equivocal about the mechanism under HIPEC. Methods MiR-183-5p expression was sifted from miRNA chip and detected in both GC patients and cell lines by qRT-PCR. Gene interference and rescue experiments were performed to identified biological function in vitro and vivo. Next, we affirmed PPP2CA as targeted of miR-183-5p by dual luciferase reporter assay. Finally, the potential relationship between HIPEC and miR-183-5p was explored. Results MiR-183-5p is up-regulated in GC and associated with advanced stage and poor prognosis. MiR-183-5p accelerate GC migration in vitro which is influenced by miR-183-5p/PPP2CA/AKT/GSK3β/β-catenin Axis. HIPEC exerts migration inhibition via attenuating miR-183-5p expression. Conclusion MiR-183-5p can be used as a potential HIPEC biomarker in patients with CC.",14321335,ONCOLOGY
10.3390/ai5030081,Enhancing Literature Review Efficiency: A Case Study on Using Fine-Tuned BERT for Classifying Focused Ultrasound-Related Articles,"Over the past decade, focused ultrasound (FUS) has emerged as a promising therapeutic modality for various medical conditions. However, the exponential growth in the published literature on FUS therapies has made the literature review process increasingly time-consuming, inefficient, and error-prone. Machine learning approaches offer a promising solution to address these challenges. Therefore, the purpose of our study is to (1) explore and compare machine learning techniques for the text classification of scientific abstracts, and (2) integrate these machine learning techniques into the conventional literature review process. A classified dataset of 3588 scientific abstracts related and unrelated to FUS therapies sourced from the PubMed database was used to train various traditional machine learning and deep learning models. The fine-tuned Bio-ClinicalBERT (Bidirectional Encoder Representations from Transformers) model, which we named FusBERT, had comparatively optimal performance metrics with an accuracy of 0.91, a precision of 0.85, a recall of 0.99, and an F1 of 0.91. FusBERT was then successfully integrated into the literature review process. Ultimately, the integration of this model into the literature review pipeline will reduce the number of irrelevant manuscripts that the clinical team must screen, facilitating efficient access to emerging findings in the field.",26732688,AI
10.1186/s40359-024-01956-7,Prediction of accident-proneness among a sample of Iranian workers: usefulness of an adjusted version of the Health Belief Model with spiritual health,"Workforce health is one of the primary and challenging issues, especially in industrialized countries. The purpose of the present study was to evaluate the ability to predict accident-proneness among Saveh Industry workers in Iran, based on an extended Health Belief Model, that included the construct of spiritual health. This descriptive-analytical study was conducted in 2022 on 384 workers in Saveh, Iran. The study aimed to explore relationships between accident proneness behavior, spiritual health, and health beliefs. The accident-proneness questionnaire consisted of two parts: the first part included demographic questions, and the second part comprised 9 sections covering personality traits, workplace harmful factors, miscellaneous factors, musculoskeletal disorders, safety culture, safety attitudes, job stress, organization interest, and degree of risk-taking. The Health Belief Model included 31 questions, while spiritual health was measured with the 20-question Paloutzian and Ellison questionnaire. The collected data were analyzed using SPSS version 26 software. In terms of accident proneness, 229 (59.6%), exhibited high levels, 148 (38.5%) had medium levels, and 7 (1.8%) showed low levels of accident-proneness. Hierarchical multiple regression analysis showed that in the first model, variables of perceived self-efficacy, vulnerability, and severity independently predicted workers accident proneness, explaining a total of 43% of variance in accident proneness behavior. In the second step, perceived self-efficacy (β = 34%), perceived sensitivity (β = 27%), spiritual health (β = 16%), and perceived severity (β = 12%) were included, respectively, which explained a total of 46% of the variance of accident-prone behavior of workers. Given the high rate of accident proneness observed in this study, there is a critical need for policymakers and health planners to design policies aimed at mitigating the risks associated with occupational accidents. Furthermore, the findings highlight the potential of integrating spiritual health into the Health Belief Model, as a conceptual framework for planning effective intervention programs to enhance workplace safety.",20507283,PSYCHOLOGY
10.3389/fpsyg.2024.1440013,Slovenian validation of the Capacity to Love Inventory: associations with clinical measures and mindfulness,"Aim: The main purpose of the present study was to validate the Slovenian version of the 41- item Capacity to Love Inventory (CTL-I). Based on psychoanalytic theory, limitations to capacity to love are expected to be associated with personality dysfunction and disintegration as well as fundamental mental capacities such as self-reflection and self-awareness.Method: To examine these assumptions, a sample of 552 Slovenian non-clinical individuals were recruited through academic networks. The construct validity of the CTL-I was assessed using a confirmatory factor analysis and convergent validity of the CTL-I and its subscales was established against IPO-16, PID-5 BF, MAAS.Results: Our findings show that the Slovenian version of the CTL-I replicated the six-factor structure, exhibiting good model fit as well as satisfactory internal consistency of all subscales. In line with expectations, capacity to love was found to be inversely associated with dysfunctional personality traits and structural personality disturbances. Accordingly, higher dispositional mindfulness was coherently associated with all domains of CTL-I.Conclusion: The results add to the growing evidence for the cross-cultural validity and sound psychometric properties of CTL-I, presented here in the Slovenian version. Our findings also point to the significance of dispositional mindfulness both in relation to capacity to love as well as mental health.",16641078,PSYCHOLOGY
10.1186/s40594-024-00498-z,The transfer effect of computational thinking (CT)-STEM: a systematic literature review and meta-analysis,"Background: Integrating computational thinking (CT) into STEM education has recently drawn significant attention, strengthened by the premise that CT and STEM are mutually reinforcing. Previous CT-STEM studies have examined theoretical interpretations, instructional strategies, and assessment targets. However, few have endeavored to delineate the transfer effects of CT-STEM on the development of cognitive and noncognitive benefits. Given this research gap, we conducted a systematic literature review and meta-analysis to provide deeper insights. Results: We analyzed results from 37 studies involving 7,832 students with 96 effect sizes. Our key findings include: (i) identification of 36 benefits; (ii) a moderate overall transfer effect, with moderate effects also observed for both near and far transfers; (iii) a stronger effect on cognitive benefits compared to noncognitive benefits, regardless of the transfer type; (iv) significant moderation by educational level, sample size, instructional strategies, and intervention duration on overall and near-transfer effects, with only educational level and sample size being significant moderators for far-transfer effects. Conclusions: This study analyzes the cognitive and noncognitive benefits arising from CT-STEM’s transfer effects, providing new insights to foster more effective STEM classroom teaching.",21967822,EDUCATION
10.1007/s44196-024-00641-2,Creating Personalized Higher Education Teaching System Using Fuzzy Association Rule Mining,"Universities and colleges aim to provide students with a solid academic foundation. Quality instruction is one strategy for achieving the highest possible standard in the higher education system. Personalized teaching caters to each student by adapting the learning pace and method to their specific requirements. However, the present state of customized education in higher education resources prevents proper resources from being extracted due to a lack of multi-dimensional association analysis between students, circumstances, and materials. A hybrid personalized teaching system utilizing fuzzy association rules mining is the goal of this research to improve learning in higher education. Effective multi-dimensional association analysis among students, settings, and instructional materials is facilitated by the fuzzy association rules mining-based hybrid personalized teaching system (FARM-HPT). The proposed study conforms to AI standards, is based on fuzzy logic theories, and guarantees precise university-level resource discovery. The study builds on earlier work in data mining by presenting a new, learner-specific recommendation model for personalized teaching that uses FARM to ensure accurate resource recognition and efficient mining of instructional assets at the higher education level. This new approach generates fewer set comparisons and does them faster than the current standard. Focusing on experimental validation, the study shows that the FARM-HPT system can generate individualized lessons while overcoming the constraints of traditional information mining methods. These findings align with AI standards, which shows how important it is to validate new AI approaches using robust empirical evidence. The system ensures effective accuracy on various datasets: LFW (89.76%), JAOLAD (94.43%), OECD (95.43%) and OULAD (97.45%).",18756883,AI
10.3389/feduc.2024.1466128,Multi-version interactive assessment through the integration of GeoGebra with Moodle,"AI systems are now capable of providing accurate solutions to questions presented in text format, causing a major problem in assessment integrity. To address this issue, interactive material can be integrated with the questions, preventing current AI systems from processing the requirements. This study proposes a novel approach that combines two important tools: GeoGebra and Moodle. GeoGebra is a widely used tool in schools and universities for creating dynamic and interactive material in the STEM field. On the other hand, Moodle is a popular learning management system with integrated tools capable of generating multiple versions of the same question to enhance academic integrity. We combine these two tools to automatically create unique interactive questions for each student in a computer-based assessment. Detailed implementation steps that do not require prior coding experience or the installation of additional plugins are presented, making the technique accessible to a wider range of instructors. The proposed approach was tested on a group of students and showed enhanced performance in animation-based questions compared to traditional question formats. Moreover, a survey exploring the students’ opinions on the proposed approach reported strong student endorsement of animated questions.",2504284X,EDUCATION
10.3389/feduc.2024.1447731,Relationship between cultural diversity awareness and achievement motivation of medical students at the undergraduate level in Pakistan,"This study investigates the relationship between cultural diversity awareness and achievement-oriented goals among undergraduate medical students at the university level. Utilizing the Achievement Motivation Model by McInerney et al. (2003) and the General Fulfillment Aims Orientation Scale (GAGOS), it examines mastery, performance, and social goals. Additionally, it incorporates Ennejar's (2021) cultural diversity awareness model to assess students' attitudes toward cultural diversity. Data were collected from 80 final-year MBBS students through a survey and analyzed using SPSS for descriptive and inferential statistics. Results show that students have a high level of cultural diversity awareness and recognize biases, supporting diverse voices and cultural differences. A significant positive correlation (r = 0.948, p < 0.05) between cultural diversity awareness and achievement motivation was found, although no significant differences were observed based on gender or age. These findings suggest that enhancing personal development, altruism, and social recognition may boost motivation and that diversity and inclusion programs are crucial for fostering environments that promote achievement motivation.",2504284X,EDUCATION
10.3389/frai.2024.1401126,OLTW-TEC: online learning with sliding windows for text classifier ensembles,"In the digital age, rapid dissemination of information has elevated the challenge of distinguishing between authentic news and disinformation. This challenge is particularly acute in regions experiencing geopolitical tensions, where information plays a pivotal role in shaping public perception and policy. The prevalence of disinformation in the Ukrainian-language information space, intensified by the hybrid war with russia, necessitates the development of sophisticated tools for its detection and mitigation. Our study introduces the “Online Learning with Sliding Windows for Text Classifier Ensembles” (OLTW-TEC) method, designed to address this urgent need. This research aims to develop and validate an advanced machine learning method capable of dynamically adapting to evolving disinformation tactics. The focus is on creating a highly accurate, flexible, and efficient system for detecting disinformation in Ukrainian-language texts. The OLTW-TEC method leverages an ensemble of classifiers combined with a sliding window technique to continuously update the model with the most recent data, enhancing its adaptability and accuracy over time. A unique dataset comprising both authentic and fake news items was used to evaluate the method’s performance. Advanced metrics, including precision, recall, and F1-score, facilitated a comprehensive analysis of its effectiveness. The OLTW-TEC method demonstrated exceptional performance, achieving a classification accuracy of 93%. The integration of the sliding window technique with a classifier ensemble significantly contributed to the system’s ability to accurately identify disinformation, making it a robust tool in the ongoing battle against fake news in the Ukrainian context. The application of the OLTW-TEC method highlights its potential as a versatile and effective solution for disinformation detection. Its adaptability to the specifics of the Ukrainian language and the dynamic nature of information warfare offers valuable insights into the development of similar tools for other languages and regions. OLTW-TEC represents a significant advancement in the detection of disinformation within the Ukrainian-language information space. Its development and successful implementation underscore the importance of innovative machine learning techniques in combating fake news, paving the way for further research and application in the field of digital information integrity.",26248212,AI
10.3389/fpsyg.2024.1435691,Navigating virtual selves: validation of the German version of the presentation of online self scale,"The Presentation of Online Self Scale for Adults (POSSA), originally developed by Strimbu et al. is a well-regarded instrument for assessing online self-presentation. This study evaluated the factorial structure, reliability, and validity of the German adaptation of POSSA. A CFA analysis confirmed a satisfactory fit for the proposed three-factor model, as evidenced by a CFI of 0.919, a TLI of 0.902 and a RSMEA of 0.075. The subscales of the German POSSA demonstrated high internal consistency. Additionally, convergent validity was established through significant correlations with the Impostor-Profile 30 (IPP), affirming the interpretive accuracy of the subscale scores. Specifically, the Adaptable Self and Freedom of Self Online subscales positively correlated with IPP measures of Alienation and Other-Self-Divergence, whereas the Authentic Self subscale inversely correlated with these measures. Moreover, the German POSSA scores accounted for variance in the number of Instagram followers, surpassing the predictive power of self-esteem alone. Notably, the Adaptable Self factor was positively associated with the follower count, while the Freedom of Self Online factor displayed a negative association. Collectively, these findings underscore the DE-POSSA as a robust tool for assessing self-presentation behaviors in German-speaking populations and highlight its potential for cross-cultural research in online interpersonal interactions.",16641078,PSYCHOLOGY
10.1186/s40359-024-01973-6,Development of Chinese college students’ perception teacher differential behavior scale and its reliability and validity test,"To compile a scale of Chinese college students’ perception of teachers’ differential behavior and to provide a reference for college students to establish correct life values, promote college students’ physical and mental health, and reduce teachers’ differential treatment. Open-ended questionnaires and expert interviews were used to conduct interviews and correspondence with 58 college students, ten psychologists, and six psychologists to form an initial questionnaire. Then, the scale’s exploratory factor analysis, confirmatory factor analysis, and reliability and validity test were conducted on 7053 college students from 18 universities in 6 provinces (municipalities directly under the Central Government). The Chinese college students’ perception of teachers’ differential behavior scale has two dimensions: teacher prejudice and preference. Each dimension includes three aspects: emotional feedback, behavior orientation, and opportunity privilege, and each aspect have a total of 4 items. The consistency test coefficients of each dimension and each factor of the prepared scale are all above 0.7, and the split-half reliability is above 0.6. Confirmatory factor analysis shows that the six-factor structural model fits well (χ2/df = 4.287, RMSEA = 0.066, CFI = 0.950, TLI = 0.919). Using the generalized anxiety disorder scale and the patient health questionaire-9items as empirical criteria, each factor in the scale demonstrated significant correlations with both the GAD scale and the patient health questionaire-9items. The Chinese college students’ perception of teachers’ differential behavior scale has a two-dimensional six-factor structure and has good reliability and validity. It can be used as an effective tool to measure Chinese college students’ perceived teacher differential behavior.",20507283,PSYCHOLOGY
10.1186/s40359-024-01968-3,No significant difference in salivary cortisol response on the Trier Social Stress Test-Online based on coffee consumption habits,"Background: Coffee is widely consumed around the world. In Japan, it is a type of “Shikohin” (consumed for flavor, not nutrition). Several medical studies have reported the beneficial effects of coffee consumption, whereas others suggest that these beneficial effects on psychological aspects are marginal. The habit of consuming large amounts of caffeine through coffee may improve short-term resilience in stressful situations and may exhaust individuals in the long term. We hypothesized that people who habitually drink high amounts of coffee would have lower resilience scores and higher acute stress responses. Methods: Adult Japanese men completed a questionnaire that included a resilience scale and Shikohin consumption habits. Experimental participants were recruited from the survey respondents and classified into three groups based on their coffee consumption per day: No Coffee, Low Coffee, and High Coffee. All participants were asked to join the Trier Social Stress Test-Online (TSST-OL). Subjective stress and salivary cortisol concentrations was measured at eight time points during the experiment. There were 16 participants in each group for the analysis (mean age = 46.10 years, SD = 12.58). Results: Statistical analysis showed that both subjective stress and salivary cortisol concentrations significantly increased following TSST-OL exposure. However, there were no significant differences among the groups, and the hypotheses were not supported. Conclusions: This study demonstrated the effectiveness and stability of the TSST-OL. Additionally, coffee consumption habits were not significantly related to resilience scale scores or acute stress responses.",20507283,PSYCHOLOGY
10.3389/feduc.2024.1447270,A systematic review of student learning outcomes in CLIL in LOTE,"Introduction: This paper aims to provide a first systematic research overview of student learning outcomes in programs teaching school subjects through languages other than English (LOTE) which are not the mother tongue of the students, according to school- or researcher-administered assessments and stakeholder perspectives, following the PRISMA statement. For brevity, we shall refer to these types of programs as CLIL in LOTE, though we have also included programs which use other labels, such as bilingual education or immersion, due to their similarities with those labeled “content and language integrated learning” (CLIL).Methods: The selected studies, published between November 1994 and December 2023, were identified through the search of SCOPUS and EBSCO. In determining which studies to include in the review, we employed the following selection criteria: (1) articles focusing on children and youth (ages 5–17 years), (2) articles focusing on CLIL programs in LOTE, (3) articles focusing on student achievement, (4) articles focusing on studies that have collected primary data, and (5) studies that used school−/researcher-administered assessments (objective) or self/ hetero-reported measures (subjective). The screening of titles, abstracts and keywords left a final sample of n = 29 scientific papers, which were then read exhaustively and assessed for methodological quality.Results: Most studies (26 of 29) addressed academic and/or linguistic outcomes, with some studies additionally addressing social/cultural outcomes, behavioral/affective outcomes, and/or (meta) cognitive outcomes. Of the learning outcomes reported, 25 (53%) were positive, five (11%) were negative, four (9%) were neutral, eight (17%) were mixed and four (9%) identified factors influencing outcomes.Discussion: Theoretically, the study contributes to establishing more general theories about the specific role of CLIL in LOTE in students’ learning. Empirically, the study outlines pathways for future research on CLIL in LOTE. In practice, the study presents challenges identified by stakeholders to suggest pathways forward in CLIL teaching/learning.Systematic review registration: Open Science Framework (OSF):",2504284X,EDUCATION
10.1186/s40359-024-01989-y,Associations between motivational factors and burnout syndrome among elite skiers,"The present research investigated the association between a series of motivational factors and burnout syndrome among elite skiers at the contextual level within the Hierarchical Model of Intrinsic and Extrinsic Motivation (HMIEM). There are 352 subjects (258 males, 94 females, aged 18 to 25 years) across five skiing events from three sport universities in this study. Four psychological scales related to motivational factors and burnout syndrome were completed by subjects. Overall, the result showed that a task-involving climate had a positive relationship with basic psychological needs, eliciting a positive pathway to autonomous motivation, and thus negatively affecting burnout syndromes. On the other hand, an ego-involving climate had a negative relationship with basic psychological needs, eliciting a negative pathway to amotivation, and then positively affecting burnout syndromes. The results underscore the intricate associations between a variety of motivational factors and athletes’ burnout syndrome, supporting the need to incorporate burnout syndrome elements into the outcomes of HMIEM sequence.",20507283,PSYCHOLOGY
10.1186/s40359-024-01975-4,Collaborative AI-enhanced digital mind-mapping as a tool for stimulating creative thinking in inclusive education for students with neurodevelopmental disorders,"Nowadays, inclusive education is becoming an increasingly important method in the education of people with various types of disabilities. This study is aimed at investigating the effectiveness of utilizing collaborative digital mind-mapping techniques in the practical work of students in inclusive educational groups, as well as examining how the use of AI-provided prompts influences the development of creative skills. The study involved 163 participants, among whom 28 had neurodevelopmental disorders. The application of the proposed methodology resulted in an improvement in the indicators of creative thinking as measured by the Torrance Figural Creativity Test, specifically in terms of Fluency, Originality, Elaboration, and overall creativity score; the observed increase was statistically significant according to the Wilcoxon signed-rank test (p = 0.05). This increase in indicators was observed both in students with neurodevelopmental disorders and in students without developmental disorders, with a notably stronger impact observed on students with neurodevelopmental disorders. Furthermore, a slightly higher effectiveness of the applied methodology was recorded when AI prompts were used for both categories of students. Students with neurodevelopmental disorders largely perceived the usefulness of the prompts they received subjectively. The present research may contribute to further study of various creativity development methodologies in inclusive education, as well as regarding the influence of AI utilization on creative skills. The obtained results can be utilized in the development of educational programs for students in higher education institutions that support inclusive forms of learning.",20507283,PSYCHOLOGY
10.3390/educsci14091020,The Effects of Invented Spelling Instruction on Literacy Achievement and Writing Motivation,"Early writing performance strongly predicts long-term literacy performance. It follows that early underachievement in writing is highly correlated with early underachievement in reading. One strategy teachers and students can use to approach writing in the kindergarten classroom is invented spelling. Invented spelling is children’s spontaneous or self-directed attempts to represent words in print by matching sounds to known letters or phonics patterns. A quasi-experimental study was used to evaluate the impact of invented spelling on foundational literacy skills and writing motivation in 63 kindergarten students at a rural school in the Mid-South. The research questions focused on the impact of invented spelling instruction on a variety of literacy outcomes, including foundational skills, spelling, and motivation. The results indicate the significant main effects of invented spelling instruction on students’ invented spelling (p < 0.001), conventional spelling (p < 0.001), complex vocabulary use (p < 0.001, writing motivation (p = 0.040), and writing achievement (p < 0.001). Other outcomes as well as implications and future directions are reported. The invented spelling intervention encouraged low-stake risk taking when writing and removed barriers to writing entry. Allowing time and space for invented spellings means students can focus on communicating their ideas in print without being hindered by the expectation to conform to conventional spellings.",22277102,EDUCATION
10.3390/ai5030082,Probabilistic Ensemble Framework for Injury Narrative Classification,"In this research, we analyzed narratives from the National Electronic Injury Surveillance System (NEISS) dataset to predict the top two injury codes using a comparative study of ensemble machine learning (ML) models. Four ensemble models were evaluated: Random Forest (RF) combined with Logistic Regression (LR), K-Nearest Neighbor (KNN) paired with RF, LR combined with KNN, and a model integrating LR, RF, and KNN, all utilizing a probabilistic likelihood-based approach to improve decision-making across different classifiers. The combined KNN + LR ensemble achieved an accuracy of 90.47% for the top one prediction, while the KNN + RF + LR model excelled in predicting the top two injury codes with a very high accuracy of 99.50%. These results demonstrate the significant potential of ensemble models to enhance unstructured narrative classification accuracy, particularly in addressing underrepresented cases, and the potential of the proposed probabilistic ensemble framework ML models in improving decision-making in public health and safety, providing a foundation for future research in automated clinical narrative classification and predictive modeling, especially in scenarios with imbalanced data.",26732688,AI
10.1007/s00432-024-05949-2,Transarterial chemoembolization combined with sintilimab and lenvatinib for the treatment of unresectable hepatocellular carcinoma: a retrospective study,"Background The treatment of unresectable hepatocellular carcinoma (uHCC) challenging due to unfulfilled clinical requirements. Objective To evaluate the safety and efficacy of combining transarterial chemoembolization (TACE) with sintilimab and lenvatinib in the treatment of uHCC. Methods We retrospectively analyzed the data of patients with uHCC who were treated with a combination of TACE, sintilimab, and lenvatinib between May 2019 and December 2021 at the Chinese PLA General Hospital. Systemic treatment was started 1 week after TACE was performed. Sintilimab was administered intravenously at a dosage of 200 mg every three weeks, and lenvatinib was given orally at dosages of 8 mg or 12 mg daily, contingent upon the weight of the patients. The primary endpoint was the objective response rate (ORR) as per the mRECIST. Secondary endpoints were disease control rate (DCR), progression-free survival (PFS), overall survival (OS) and treatment-related adverse events (tr-AEs). Results A total of 32 patients were enrolled in the study. Among them, 9 patients were classified as Barcelona Clinic Liver Cancer-B (BCLC-B), 23 patients were classified as BCLC-C, 14 patients diagnosed with portal vein tumors, and 12 patients were diagnosed with extra hepatic metastases. The ORR and DCR were 75% and 90.6% respectively, with 4 patients exhibiting (12.5%) complete response, 20 patients exhibiting (62.5%) partial response, 5 patients exhibiting (15.6%) stable disease, and 3 patients exhibiting (9.4%) progressive disease. With a median follow-up time of 19.6 months, the median PFS was 9.9 months, and the median OS was 33.3 months. A total of 31 patients experienced different degrees of tr-AEs, of which 2 were grade 3 tr-AEs. Conclusion The combination therapy of TACE, sintilimab, and lenvatinib demonstrates satisfactory efficacy in the treatment of uHCC with manageable tr-AEs.",14321335,ONCOLOGY
10.3390/ejihpe14090170,Implementing a Social Presence-Based Teaching Strategy in Online Lecture Learning,"Previous studies have focused on the design of video lectures to improve students’ social presence by enhancing instructor presence for learners in lecture-based online courses; however, there has been limited emphasis on the peer presence in which learning from video lectures takes place. This study’s first objective is to develop a social presence (SP)-based teaching strategy to design online learning activities aimed at improving students’ social presence by providing social clues about peer presence and encouraging peer communication. The second objective is to compare students’ social presence, social interaction, and academic performance from lecture-based online learning supported by either a conventional teaching strategy or an SP-based teaching strategy. Using a quasi-experiment, we selected 81 Chinese university students to participate in a ten-week online course. The participants were randomly assigned to either an experimental group (EG) (N = 43) or a control group (CG) (N = 38). This study revealed that the SP-based strategy enhanced EG members’ social presence in online learning and that EG members achieved better academic performance than CG members. A significant correlation was found between the EG members’ academic performance and their social presence. The researchers also identified more concentrated social network sociograms with more cohesive subgroups in the EG members’ online interactions. The results indicate the necessity of applying an SP-based teaching strategy in lecture-based online courses to promote students’ social presence, social interaction, and academic performance.",22549625,PSYCHOLOGY
10.3390/ai5030084,Improving Distantly Supervised Relation Extraction with Multi-Level Noise Reduction,"Background: Distantly supervised relation extraction (DSRE) aims to identify semantic relations in large-scale texts automatically labeled via knowledge base alignment. It has garnered significant attention due to its high efficiency, but existing methods are plagued by noise at both the word and sentence level and fail to address these issues adequately. The former level of noise arises from the large proportion of irrelevant words within sentences, while noise at the latter level is caused by inaccurate relation labels for various sentences. Method: We propose a novel multi-level noise reduction neural network (MLNRNN) to tackle both issues by mitigating the impact of multi-level noise. We first build an iterative keyword semantic aggregator (IKSA) to remove noisy words, and capture distinctive features of sentences by aggregating the information of keywords. Next, we implement multi-objective multi-instance learning (MOMIL) to reduce the impact of incorrect labels in sentences by identifying the cluster of correctly labeled instances. Meanwhile, we leverage mislabeled sentences with cross-level contrastive learning (CCL) to further enhance the classification capability of the extractor. Results: Comprehensive experimental results on two DSRE benchmark datasets demonstrated that the MLNRNN outperformed state-of-the-art methods for distantly supervised relation extraction in almost all cases. Conclusions: The proposed MLNRNN effectively addresses both word- and sentence-level noise, providing a significant improvement in relation extraction performance under distant supervision.",26732688,AI
10.3389/frai.2024.1411838,Governing AI in Southeast Asia: ASEAN’s way forward,"Despite the rapid development of AI, ASEAN has not been able to devise a regional governance framework to address relevant existing and future challenges. This is concerning, considering the potential of AI to accelerate GDP among ASEAN member states in the coming years. This qualitative inquiry discusses AI governance in Southeast Asia in the past 5 years and what regulatory policies ASEAN can explore to better modulate its use among its member states. It considers the unique political landscape of the region, defined by the adoption of unique norms such as non-interference and priority over dialog, commonly termed the ASEAN Way. The following measures are concluded as potential regional governance frameworks: (1) Elevation of the topic’s importance in ASEAN’s intra and inter-regional forums to formulate collective regional agreements on AI, (2) adoption of AI governance measures in the field of education, specifically, reskilling and upskilling strategies to respond to future transformation of the working landscape, and (3) establishment of an ASEAN working group to bridge knowledge gaps among member states, caused by the disparity of AI-readiness in the region.",26248212,AI
10.1186/s40594-024-00504-4,The S in STEM: gender differences in science anxiety and its relations with science test performance-related variables,"STEM education has experienced significant growth due to its pivotal role in innovation and economic development. While cognitive factors like prior knowledge are known predictors of STEM success, non-cognitive factors, including attitudes and demographics, also play vital roles. However, there is a notable scarcity of research focusing on the ""S"" in STEM—science—compared to extensive studies in fields like mathematics. This study aims to address this gap by exploring gender differences in science test performance and related attitudes, providing insights into this under-researched aspect of STEM education. The effective sample comprised 1839 Estonian 12th-grade students who took a computer-assisted science test. The test consisted of tasks combining chemistry, physics, biology, and geography, and a post-test survey was also administered. Across the total sample, the results showed that test performance positively correlated with test-taking duration, effort, and test importance. Test performance was negatively correlated with perceived test difficulty. Interestingly, while general science anxiety was not associated with test performance, subject-specific anxiety, especially chemistry anxiety had a negative association with test performance. While there were no gender differences in test performance, female students scored consistently higher on all science anxiety measures, compared to male students. Furthermore, female students assessed the science test to be more difficult, and they also took more time to complete the test. The correlations in gender subsamples mirrored those observed in the total sample. The association between science test performance and test-related variables is nuanced: students might not necessarily have a “general” STEM anxiety but it may be associated with a specific subject. Moreover, the findings imply that although there are no gender differences in test performance, girls have a greater anxiety when it comes to natural sciences subjects. These findings indicate the need for investigating the origin of such anxieties, which do not seem to stem from aptitude.",21967822,EDUCATION
10.3389/feduc.2024.1389462,Enhancing public dialogue about inclusion in school education: a citizens’ panel pilot,"Introduction: This paper reports on a small-scale Citizens’ Panel pilot project using deliberative democratic methods to produce policy ideas about inclusion in school education of young people with special educational needs and disabilities (SEN/D) in England. The project had two aims: (i) to obtain information about modifying a Citizens’ Panel process to enhance the effective participation of young people with SEN/D; and (ii) to generate more nuanced, grounded and integrated policy ideas about inclusion than can be found in recent English school education policy.Methods: The Citizens’ Panel was a two phase deliberative process. Phase 1 involved working with six young people with SEN/D and their parents/carers to shape the Citizens’ Panel agenda, and to obtain information about how they could participate and communicate their perspectives during the events. Phase 2 involved the delivery of the Citizens’ Panel itself, which comprised 28 people: the six young people from phase 1, plus four young people without SEN/D, 13 parents/carers, and five education professionals.Results: The process evaluation revealed the need for and impact of meticulous planning using a differentiated and strengths-based approach to design. While participants reported that taking part in the Citizens’ Panel was overall, a positive and worthwhile experience, the differentiated approach involved trade-offs that affected the experiences of some participants without SEN/D, though not detrimentally. The panel produced distinctive ideas about more inclusive schools, where almost all of the themes were about general school changes for everyone. Most general themes involved some specific SEN/D aspects, with only one theme being SEN/D specific. This paper illustrates how these ideas are more nuanced, grounded and integrated than those in current national policy.Discussion: This paper provides evidence of how deliberative approaches can be used within and between schools, groups of schools (e.g., multi academy trusts), local networks (including local authorities), as well as at the national level. Lessons drawn show how deliberative methods used by advocacy groups, protest movements and non-governmental organisations in support of more transformational change can be developed in ways that enable young people with SEN/D to participate and have their voices heard.",2504284X,EDUCATION
10.3389/fonc.2024.1419310,Associations of HALP score with serum prostate-specific antigen and mortality in middle-aged and elderly individuals without prostate cancer,"Background: The association between the Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) score and serum prostate-specific antigen (PSA) and all-cause mortality remains underexplored. We aimed to investigate the relationship between HALP score and these outcomes among middle-aged and elderly individuals without prostate cancer (PCa).Methods: This cross-sectional study included participants aged 40 years and older from National Health and Nutrition Examination Survey (NHANES) 2001–2010. HALP score was calculated using the formula: HALP score = (Hemoglobin × Albumin × Lymphocytes)/Platelets. High PSA level was defined as a percentage free PSA (%fPSA) less than or equal to 25% and a total PSA (tPSA) level equal to or higher than 4.0 ng/mL. Mortality data were obtained through December 30, 2019 by linking to the National Death Index.Results: Among 7,334 participants, 6,826 were classified as having low PSA level, while 508 were categorized as having high PSA level. Logistic regression revealed lower odds of high PSA level with higher HALP quartiles (Ptrend<0.001). Among 508 participants with high PSA level, over a median follow-up period of 10.13 years (IQR: 5.42-13.17 years), a total of 268 all-cause deaths were recorded. Cox regression analysis showed that participants in the highest HALP quartile had the lowest risk of all-cause mortality (HR = 0.527, 95% CI: 0.368-0.754) in participants with high PSA level. Restricted cubic spline analysis indicated a non-linear and negative correlation between HALP score and all-cause mortality, with an inflection point at 43.98 (P for non-linearity = 0.009). Random survival forest analysis ranked HALP score as the most significant predictor for all-cause mortality.Conclusion: Our study highlights that the HALP score the HALP score is associated with high PSA level and all-cause mortality among middle-aged and elderly individuals without PCa. Further research is warranted to validate these findings and elucidate underlying mechanisms.",2234943X,ONCOLOGY
10.3389/fpsyg.2024.1415448,The relationship between physical activity and mental health of middle school students: the chain mediating role of negative emotions and self-efficacy,"Objective: To explore the relationship between mental health and physical activity (PA) in middle school students, and examining the roles of negative emotions and self-efficacy in the relationship.Methods: Data from 1,134 Chinese middle school students (50.2% females, 49.8% males; Mage = 15.18, SDage = 2.00) were collected using the Physical Activity Rating Scale (PARS-3), Positive and Negative Affect Scale (PANAS), General Self-Efficacy Scale (GSES), and Middle School Student Mental Health Scale (MSSMHS).Results: (1) There is a significant positive correlation between PA and mental health (r = 0.16, p < 0.01), and the direct path of PA on mental health is significant (t = 2.101, p < 0.01). (2) PA negatively predicts negative emotions (r = −0.12, p < 0.01), and is significantly positively correlated with self-efficacy (r = 0.24, p < 0.01). Negative emotions negatively predict self-efficacy (r = −0.23, p < 0.01) and mental health (r = −0.67, p < 0.01). Self-efficacy positively predicts mental health (r = 0.30, p < 0.01). (3) Negative emotions and self-efficacy play a significant mediating role between PA and mental health. The mediating effect includes three paths: PA → negative emotion → mental health (effect value: 0.130); PA → self-efficacy → mental health (effect size: 0.052); PA → negative emotions → self-efficacy → mental health (effect size: 0.006).Conclusion: PA among middle school students can indirectly affect mental health through negative emotions and self-efficacy. Middle school students should be encouraged to participate in PA to reduce their negative emotions and increase their self-efficacy, thus improving their mental health.",16641078,PSYCHOLOGY
10.3389/frai.2024.1460217,Towards enhanced creativity in fashion: integrating generative models with hybrid intelligence,"Introduction: This study explores the role and potential of large language models (LLMs) and generative intelligence in the fashion industry. These technologies are reshaping traditional methods of design, production, and retail, leading to innovation, product personalization, and enhanced customer interaction.Methods: Our research analyzes the current applications and limitations of LLMs in fashion, identifying challenges such as the need for better spatial understanding and design detail processing. We propose a hybrid intelligence approach to address these issues.Results: We find that while LLMs offer significant potential, their integration into fashion workflows requires improvements in understanding spatial parameters and creating tools for iterative design.Discussion: Future research should focus on overcoming these limitations and developing hybrid intelligence solutions to maximize the potential of LLMs in the fashion industry.",26248212,AI
10.3389/frai.2024.1353873,Image restoration in frequency space using complex-valued CNNs,"Real-valued convolutional neural networks (RV-CNNs) in the spatial domain have outperformed classical approaches in many image restoration tasks such as image denoising and super-resolution. Fourier analysis of the results produced by these spatial domain models reveals the limitations of these models in properly processing the full frequency spectrum. This lack of complete spectral information can result in missing textural and structural elements. To address this limitation, we explore the potential of complex-valued convolutional neural networks (CV-CNNs) for image restoration tasks. CV-CNNs have shown remarkable performance in tasks such as image classification and segmentation. However, CV-CNNs for image restoration problems in the frequency domain have not been fully investigated to address the aforementioned issues. Here, we propose several novel CV-CNN-based models equipped with complex-valued attention gates for image denoising and super-resolution in the frequency domains. We also show that our CV-CNN-based models outperform their real-valued counterparts for denoising super-resolution structured illumination microscopy (SR-SIM) and conventional image datasets. Furthermore, the experimental results show that our proposed CV-CNN-based models preserve the frequency spectrum better than their real-valued counterparts in the denoising task. Based on these findings, we conclude that CV-CNN-based methods provide a plausible and beneficial deep learning approach for image restoration in the frequency domain.",26248212,AI
10.3389/frai.2024.1441205,Anomaly detection via Gumbel Noise Score Matching,"We propose Gumbel Noise Score Matching (GNSM), a novel unsupervised method to detect anomalies in categorical data. GNSM accomplishes this by estimating the scores, i.e., the gradients of log likelihoods w.r.t. inputs, of continuously relaxed categorical distributions. We test our method on a suite of anomaly detection tabular datasets. GNSM achieves a consistently high performance across all experiments. We further demonstrate the flexibility of GNSM by applying it to image data where the model is tasked to detect poor segmentation predictions. Images ranked anomalous by GNSM show clear segmentation failures, with the anomaly scores strongly correlating with segmentation metrics computed on ground-truth. We outline the score matching training objective utilized by GNSM and provide an open-source implementation of our work.",26248212,AI
10.3390/cancers16193271,Genetic Analysis of Biopsy Tissues from Colorectal Tumors in Patients with Ulcerative Colitis,"Background/Objectives: Colorectal neoplasia developing from ulcerative colitis mucosa (CRNUC) can be divided into ulcerative colitis-associated neoplasia (UCAN) and non-UCAN; however, it is often difficult to distinguish UCAN from non-UCAN during a biopsy diagnosis. We investigated whether a genomic analysis could improve the diagnostic accuracy of UCAN using biopsy specimens. Methods: In step 1, 14 CRNUCs were used to examine whether the genomic landscape of biopsy and resection specimens matched. In step 2, we investigated the relationship between the genomic landscapes and the pathological diagnosis of 26 CRNUCs. The cancer genome was analyzed by deep sequencing using a custom panel of 27 genes found to be mutated in our previous CRNUC analysis. Results: In step 1, of the 27 candidate genes, 14 were mutated. The concordance rate of the pathogenic mutations in these 14 genes between the biopsy and resection specimens was 29% (4/14), while that of the pathogenic mutations in TP53 and KRAS was 79% (11/14). In step 2, the pathological diagnosis of biopsy specimens using only hematoxylin and eosin (HE) staining had a sensitivity of 33% and an accuracy of 38% for UCAN diagnosis. On the other hand, the combination of the HE pathology and p53 immunohistochemical staining had a sensitivity of 73% and an accuracy of 85% for UCAN diagnosis, while the combination of HE staining and a TP53 mutation had a sensitivity of 87% and an accuracy of 88% for UCAN diagnosis. Conclusions: An evaluation of TP53 mutations in biopsy specimens may be useful for diagnosing UCAN. However, further studies with larger sample sizes are required before this can be applied in clinical practice.",20726694,ONCOLOGY
10.3390/cancers16193307,First-Line Use of Daratumumab in Patients with Multiple Myeloma Shows Delayed Neutrophil and Platelet Engraftment after Autologous Stem Cell Transplantation: Results from a Real-Life Single-Center Study,"Background: This real-life study aimed to investigate the possible impact of D-VTd induction therapy on hematopoietic engraftment after autologous stem cell transplantation (auto-SCT). Methods: Sixty consecutive NDMM patients received four cycles of induction therapy with D-VTd. The conditioning regimen consisted of melphalan 200 mg/m2. These patients were compared with a historical control group of 80 patients who received four cycles of VTd as induction therapy. Results: The median days to reach neutrophil and platelet engraftment significantly differed between patients treated with D-VTd (11 and 13 days, respectively) and VTd (10 and 12 days). Univariate Cox analyses show that patients treated with D-VTd had a hazard ratio of neutrophil engraftment that was 42% significantly lower than those in the VTd arm (HR: 0.58, p = 0.002), and a multivariate model confirmed this result. Patients treated with D-VTd developed FN more frequently. Univariate and multivariate logistic regressions revealed an association between D-VTd and FN. Delayed engraftment did not correlate with more extended hospitalization. No patients died in the first six months after transplantation. Conclusions: Our real-life study showed that a four-drug induction therapy containing DARA does not impact transplant safety outcomes.",20726694,ONCOLOGY
10.3390/educsci14101063,Integration of AI Training in the Field of Higher Education in the Republic of Bulgaria: An Overview,"The presented work provides a comprehensive evaluation of the current availability of education programs and courses related to of AI the field of Information Technologies and Computer Science in higher education institutions (HIEs) in the Republic of Bulgaria. More specifically, this study examines 163 bachelor’s and 239 master’s degree programs from 28 HEIs available during the 2023/24 academic year in four professional fields: (1) Electrical Engineering, Electronics, and Automation; (2) Communication and Computer Technologies; (3) Informatics and Computer Science; and (4) Mathematics. The conducted evaluation shows that 41.1% of evaluated BSc programs and 26.4% of MSc programs include at least one AI-dedicated course. Results indicate a significant presence of AI-focused education, particularly in degrees related to Informatics and Computer Science, where 47.8% of AI courses are concentrated. However, a notable disparity exists in the inclusion of AI subjects across other technical fields, particularly in Electrical Engineering and related degrees, which contain only 8% of the identified AI courses for BSc degree programs. The findings highlight the need for a broader and more accelerated integration of AI education to meet the evolving demands of both students and the labor market. This work underscores the importance of strategic curriculum adaptation to enhance the readiness of Bulgarian HEIs to support the development and application of AI technologies, addressing the skills gap and fostering a workforce capable of navigating the AI-driven future.",22277102,EDUCATION
10.3390/ai5040088,Advancing Persistent Character Generation: Comparative Analysis of Fine-Tuning Techniques for Diffusion Models,"In the evolving field of artificial intelligence, fine-tuning diffusion models is crucial for generating contextually coherent digital characters across various media. This paper examines four advanced fine-tuning techniques: Low-Rank Adaptation (LoRA), DreamBooth, Hypernetworks, and Textual Inversion. Each technique enhances the specificity and consistency of character generation, expanding the applications of diffusion models in digital content creation. LoRA efficiently adapts models to new tasks with minimal adjustments, making it ideal for environments with limited computational resources. It excels in low VRAM contexts due to its targeted fine-tuning of low-rank matrices within cross-attention layers, enabling faster training and efficient parameter tweaking. DreamBooth generates highly detailed, subject-specific images but is computationally intensive and suited for robust hardware environments. Hypernetworks introduce auxiliary networks that dynamically adjust the model’s behavior, allowing for flexibility during inference and on-the-fly model switching. This adaptability, however, can result in slightly lower image quality. Textual Inversion embeds new concepts directly into the model’s embedding space, allowing for rapid adaptation to novel styles or concepts, but is less effective for precise character generation. This analysis shows that LoRA is the most efficient for producing high-quality outputs with minimal computational overhead. In contrast, DreamBooth excels in high-fidelity images at the cost of longer training. Hypernetworks provide adaptability with some tradeoffs in quality, while Textual Inversion serves as a lightweight option for style integration. These techniques collectively enhance the creative capabilities of diffusion models, delivering high-quality, contextually relevant outputs.",26732688,AI
10.3390/ai5040089,Aircraft Skin Damage Visual Testing System Using Lightweight Devices with YOLO: An Automated Real-Time Material Evaluation System,"Inspection and material evaluation are some of the critical factors to ensure the structural integrity and safety of an aircraft in the aviation industry. These inspections are carried out by trained personnel, and while effective, they are prone to human error, where even a minute error could result in a large-scale negative impact. Automated detection devices designed to improve the reliability of inspections could help the industry reduce the potential effects caused by human error. This study aims to develop a system that can automatically detect and identify defects on aircraft skin using relatively lightweight devices, including mobile phones and unmanned aerial vehicles (UAVs). The study combines an internet of things (IoT) network, allowing the results to be reviewed in real time, regardless of distance. The experimental results confirmed the effective recognition of defects with the mean average precision (mAP@0.5) at 0.853 for YOLOv9c for all classes. However, despite the effective detection, the test device (mobile phone) was prone to overheating, significantly reducing its performance. While there is still room for further enhancements, this study demonstrates the potential of introducing automated image detection technology to assist the inspection process in the aviation industry.",26732688,AI
10.1007/s00432-024-05958-1,Sequential therapy for extramedullary plasmacytoma of the palate: a rare case report with seven years of follow-up and literature review,"Background Extramedullary plasmacytoma (EMP) is a rare solitary malignancy that accounts for 3% of plasma cell neoplasms, and EMP with a primary occurrence in the palate is extremely uncommon. Owing to the long course of EMP and the limited available data on treatment outcomes, there are no definitive guidelines for its management, especially for high-risk patients who are more susceptible to early progression to multiple myeloma. Case presentation In this study, we review nine relevant studies and describe a 54-year-old woman who presented with an asymptomatic nonulcerative mass localized in the palate. After initial radical surgical resection of the lesion, the patient was definitively diagnosed with EMP with minimal plasmacytosis in the bone marrow, and adjuvant intensity-modulated radiation therapy with a minimum dose of 39.6 Gy was administrated in the surgical area. There was no evidence of local recurrence, nodal metastasis or progression to multiple myeloma (MM) during the seven-year follow-up period. Conclusion Given the atypical clinical features of palate EMP reported in the literature and the encouraging results of our patient, sequential therapy involving surgery and adjuvant radiotherapy for primary palatal lesions in high-risk EMP patients without nodal involvement could be an effective treatment modality.",14321335,ONCOLOGY
10.3390/ejihpe14100176,A Bio-Psycho-Social Approach to Understanding Optimism and Pessimism in Response to Stress,"Stress is widely known to have debilitating effects on physical health and mental wellbeing, particularly on one’s coping styles, personality traits, and outlook on life. Cumulative and chronic stress, which can serve as a triggering or aggravating factor for many pathological disorders if left unaddressed, has been linked to many life-threatening diseases. While many studies have looked at how optimism and pessimism are used as a form of coping mechanism, few have examined how different bio-psycho-social reactions to stress shape the level of optimism and pessimism. Using a sample of adult individuals aged 18 and older in the United States (n = 3361), this study addressed the following research questions: (1) What types of stress are predictive of optimism and pessimism? (2) Which responses to stress and coping mechanisms are most predictive of optimism and pessimism? (3) Do optimism and pessimism share the same stress-related risk and protective factors? Overall, this study found that while optimism and pessimism share conceptual similarities, they are not necessarily influenced by the same stress mechanisms. Stress, whether personal or financial, was associated with a negative outlook on life. This study showed that having good sleep quality and a lower number of psychological stress symptoms was linked to increasing optimism and reducing pessimism, while overeating or eating unhealthily was connected to both optimism and pessimism. Additionally, this study found that exercise/walking and emotional support mediated the effects of the responses to stress on the respondents’ level of optimism and pessimism.",22549625,PSYCHOLOGY
10.3390/educsci14101073,The Role of Growth Mindset on the Relationships between Students’ Perceptions of English Language Teachers’ Feedback and Their ESL Learning Performance,"The importance of growth mindset and teachers’ feedback has been widely recognised to improve the English language performance of students; however, the impact of growth mindset as a mediator is least explored. Therefore, the study aimed to empirically analyse the interrelationships between growth mindset and teachers’ feedback levels on secondary school students’ English as a Second Language (ESL) performance and to study the mediation effects of growth mindset in the relationships. The research model examined growth mindset along with four types of feedback. The levels of feedback include task, process, self-regulation and self-based feedback that teachers provide to improve the ESL performance of students. Survey questionnaires were administered to 301 secondary school students in Class 9 from two private schools in India. The data were analysed using PLS-SEM 4.0 software. The results indicated that the direct effect of feedback that emphasised process and self-regulation fosters a growth mindset in ESL students. Feedback levels focused on task, process, self-regulation, and growth mindset significantly impact ESL performance. Moreover, growth mindset mediated the relationships between process and self-regulation-focused feedback and ESL performance. However, no evidence supports the relationship between self-focused feedback, growth mindset, and ESL performance. The study concludes with implications and directions for future research.",22277102,EDUCATION
10.1186/s40359-024-02016-w,Pursuing beauty: socio-cultural and labor-economic determinants of cosmetic surgery consideration among female college students in China,"Cosmetic surgery has a profound impact on health and other aspects. As a means of enhancing physical attractiveness, it is increasingly being considered by female college students in China. However, current knowledge about the determinants of cosmetic surgery consideration among Chinese female college students still needs to be improved due to the lack of systematic perspectives and large-scale representative data sets. This study aimed to contribute to the literature in these two aspects. We framed cosmetic surgery consideration as a function of two broad sets of determinants: socio-cultural and labor-economic. We used data from a large, nationally representative sample of female college students in China (N = 6658, mean age = 20.3 years). In terms of socio-cultural oriented factors, we found that family socioeconomic status, peers' cosmetic surgery practices, and media exposure were positively associated with the likelihood of considering cosmetic surgery. In terms of labor-economic oriented factors, we found that self-rated physical appearance, higher grades, and expected income after graduation were positively associated with a higher likelihood of considering cosmetic surgery. These findings suggest that the decision-making process for cosmetic surgery among Chinese female college students goes beyond personal factors and is significantly influenced by structural factors.",20507283,PSYCHOLOGY
10.3389/frai.2024.1393903,Comparing emotions in ChatGPT answers and human answers to the coding questions on Stack Overflow,"Introduction: Recent advances in generative Artificial Intelligence (AI) and Natural Language Processing (NLP) have led to the development of Large Language Models (LLMs) and AI-powered chatbots like ChatGPT, which have numerous practical applications. Notably, these models assist programmers with coding queries, debugging, solution suggestions, and providing guidance on software development tasks. Despite known issues with the accuracy of ChatGPT’s responses, its comprehensive and articulate language continues to attract frequent use. This indicates potential for ChatGPT to support educators and serve as a virtual tutor for students.Methods: To explore this potential, we conducted a comprehensive analysis comparing the emotional content in responses from ChatGPT and human answers to 2000 questions sourced from Stack Overflow (SO). The emotional aspects of the answers were examined to understand how the emotional tone of AI responses compares to that of human responses.Results: Our analysis revealed that ChatGPT’s answers are generally more positive compared to human responses. In contrast, human answers often exhibit emotions such as anger and disgust. Significant differences were observed in emotional expressions between ChatGPT and human responses, particularly in the emotions of anger, disgust, and joy. Human responses displayed a broader emotional spectrum compared to ChatGPT, suggesting greater emotional variability among humans.Discussion: The findings highlight a distinct emotional divergence between ChatGPT and human responses, with ChatGPT exhibiting a more uniformly positive tone and humans displaying a wider range of emotions. This variance underscores the need for further research into the role of emotional content in AI and human interactions, particularly in educational contexts where emotional nuances can impact learning and communication.",26248212,AI
10.3389/fpsyg.2024.1427514,How depression and ADHD relate to exercise addiction: a cross-sectional study among frequent exercisers,"Background: To date, there are no official diagnostic criteria for the frequently reported phenomenon of exercise addiction. Therefore, the aim of the present study was to investigate how mental disorders, specifically depression and attention-deficit hyperactivity disorder (ADHD), are related to exercise addiction (EA).Methods: A total of 173 participants aged between 18 and 70 years, who reported exercising more than 10 h a week and continued to exercise despite injury or illness, answered questionnaires including the Exercise Dependence Scale, the Beck Depression Inventory, and the Homburger ADHD scale for adults. Multiple linear regression analyses were performed adjusting for relevant confounders (age, gender) and stepwise regression was used to identify which of the two mental disorders is the more influential predictor of EA.Results: Pearson correlation analysis showed that depressive symptoms [r (171) = 0.422, p < 0.00] and ADHD symptoms [r (171) = 0.308, p < 0.001] were positively correlated with EA symptoms. The relation between depressive symptoms and EA remained after adjusting for confounders in the regression model (B = 20.531; t(170) = 5.950; 95% CI [13.719, 27.343]; p < 0.001). Similarly, the positive link between ADHD symptoms and EA persisted after controlling for confounders (B = 15.507; t(170) = 3.771; 95% CI [7.389, 23.625]; p < 0.001). Additionally, a stepwise regression model identified that depressive symptoms are a stronger predictor for EA than ADHD symptoms.Conclusion: Depressive symptoms seem to be a stronger predictor for EA compared to ADHD symptoms in frequent exercisers. Although individuals with ADHD May exercise extensively, they might be less at risk for EA than individuals with depression. These results contribute to the complex characterization of the psychiatric profile of individuals with exercise addiction, and underline the need for further research elucidating the interplay between mental disorders and EA.",16641078,PSYCHOLOGY
10.3389/feduc.2024.1354621,I’m not half and half: navigating being a “both” in discipline-based education research,"Introduction and methods: Through years of conversations, three discipline-based education researchers used a duoethnographic process to interrogate their own discipline-based education research (DBER) identities. We present a description of how these individuals navigate being a “both,” gathered through reflections, discussions, and deeper research to explore perspectives of our professional identities and what we perceive those identities look like to our peers, supervisors, and trainees.Results: Our own definitions and eventually realized identities as a “both” emerged through this research process. We envision that science faculty have multiple roles, demands, and identities; at the most basic level, they are “both” an educator and a researcher. In the unique case of discipline-based education research (i.e., scholars studying the teaching and learning of science often in science departments), some faculty find an overlap between complementary yet sometimes competing research agendas (i.e., biology research (BR) and discipline-based education research (DBER)), of which they do “both.”Discussion: This article has two key contributions. First, it articulates this side-glancing process of our navigation of being a DBER “both,” leveraging each of our unique perspectives and the literature. Second, it represents how such an exploration may be useful to other interdisciplinary researchers in understanding and embracing all parts of their identities.",2504284X,EDUCATION
10.3389/frai.2024.1381290,Efficient incremental training using a novel NMT-SMT hybrid framework for translation of low-resource languages,"The data-hungry statistical machine translation (SMT) and neural machine translation (NMT) models offer state-of-the-art results for languages with abundant data resources. However, extensive research is imperative to make these models perform equally well for low-resource languages. This paper proposes a novel approach to integrate the best features of the NMT and SMT systems for improved translation performance of low-resource English–Tamil language pair. The suboptimal NMT model trained with the small parallel corpus translates the monolingual corpus and selects only the best translations, to retrain itself in the next iteration. The proposed method employs the SMT phrase-pair table to determine the best translations, based on the maximum match between the words of the phrase-pair dictionary and each of the individual translations. This repeating cycle of translation and retraining generates a large quasi-parallel corpus, thus making the NMT model more powerful. SMT-integrated incremental training demonstrates a substantial difference in translation performance as compared to the existing approaches for incremental training. The model is strengthened further by adopting a beam search decoding strategy to produce k best possible translations for each input sentence. Empirical findings prove that the proposed model with BLEU scores of 19.56 and 23.49 outperforms the baseline NMT with scores 11.06 and 17.06 for Eng-to-Tam and Tam-to-Eng translations, respectively. METEOR score evaluation further corroborates these results, proving the supremacy of the proposed model.",26248212,AI
10.3389/fonc.2024.1448502,Long non-coding RNA FAM87A is associated with overall survival and promotes cell migration and invasion in gastric cancer,"Background: The role of long non-coding RNAs (lncRNAs) in the invasion and metastasis of gastric cancer remains largely unclear.Methods: Integrating transcriptome data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, differentially expressed genes were identified in gastric cancer. Using the Catalogue of Somatic Mutations in Cancer (COSMIC) database-curated gene set, lncRNAs associated with invasion and metastasis were identified. The Cox analyses were performed to identify prognostic lncRNAs. The competing endogenous RNA (ceRNA) regulation network was constructed to identify hub lncRNAs in gastric cancer. Functional and pathway analyses were used to investigate the function of identified lncRNAs. RT-qPCR and Transwell assays were used to investigate the expression in gastric cancer tissues and functions in gastric cancer cell lines.Results: Based on GEO and TCGA databases, 111 differentially expressed lncRNAs were identified between gastric cancer and normal samples. A total of 43 lncRNAs were significantly correlated with hallmark genes of cancer invasion and metastasis. Among them, as a hub lncRNA in the invasion-related ceRNA regulation network, FAM87A showed potential regulation on MAPK signaling and transforming growth factor (TGF) signaling cascade, such as TGFB2, TGFBR1, and TGFBR2. Furthermore, FAM87A also showed a significant correlation with cell adhesion molecules, such as Integrin alpha 6 (ITGA6) and Contactin-1 (CNTN1). RT-qPCR experiments showed that FAM87A expression was upregulated in gastric cancer tissues compared to normal samples (n = 30). Transwell assays showed that FAM87A knockdown inhibited the migration and invasion abilities of gastric cancer cells in vitro. Notably, clinical data analysis showed that lncRNA FAM87A could be an independent factor for the overall survival of patients with gastric cancer.Conclusion: LncRNA FAM87A may play a pivotal role in regulating migration and invasion of gastric cancer cells. FAM87A could be a potential biomarker for the overall survival of patients with gastric cancer.",2234943X,ONCOLOGY
10.3389/fonc.2024.1477610,The role of extracellular vesicles in the pathogenesis of gynecological cancer,"Gynecological cancer, the most common form of cancers in women worldwide, initiates in the reproductive organs of females. More often, the common treatment measures, i.e. surgery, radiation, and medical oncology are found to be unsuccessful in the treatment of gynecological tumors. Emerging evidence indicates that extracellular vesicles (EVs) play a significant role in the pathogenesis of gynecological cancers by distinct mechanisms. The present review highlights how EVs contribute to the progression of different types of gynecological cancers such as cervical cancer, endometrial cancer, ovarian cancer, vaginal cancer, uterine sarcoma, gestational trophoblastic disease (GTD), and vulvar cancer. The primary focus is to understand how EVs’ cargo alters the phenotypic response of the recipient cells, thereby contributing to the progression of the disease, thus can be considered as a prognostic and diagnostic biomarker. A brief discussion on the role of EVs in the diagnosis and prognosis of different gynecological cancer types is also highlighted. Targeting the biogenesis of the EVs, their inside cargo, and EVs uptake by the recipient cells could be a potential therapeutic approach in the treatment of gynecological cancer beside conventional therapeutic means.",2234943X,ONCOLOGY
10.3389/fonc.2024.1414900,PD-1 expression in tumor infiltrating lymphocytes as a prognostic marker in early-stage non-small cell lung cancer,"Introduction: Programmed death ligand – 1 (PD-L1) expression is a well-established predictive biomarker for immunotherapy in non-small cell lung cancer (NSCLC). Programmed death – 1 (PD-1) serves as the target protein to PD-L1 and their interaction serves as a crucial pathway for immune evasion. This study aimed to investigate the expression pattern of PD-1 on Tumor-infiltrating lymphocytes (TILs) in early-stage NSCLC, and its potential role as prognostic biomarker.Materials & methods: PD-1 was evaluated in 474 surgical resected early-stage NSCLC specimens, using Tissue microarray and immunohistochemical staining. Expression was scored as negative (<1%) or positive. Positive PD-1 expression was further divided into low (<10%) and high (≥10%). None of the patients had received treatment with PD-1/PD-L1 inhibitors.Results: PD-1 expression ≥1% in TILs was observed in 83.5% of cases and was associated with pT stage (p=0.02), grade 3 (p=0.004), and adenocarcinoma subtype (p=0.05). Individuals with high PD-1 expression (≥10%) experienced reduced 10-year overall survival (Log-Rank test = 0.005). In addition, high PD-1 expression emerged as an independent factor associated with reduced survival on multivariate analysis (HR: 1.328 (95% CI: 1.074-1.641).Conclusions: Patients with early-stage NSCLC who exhibited PD-1 expression of ≥10% on TILs had an unfavorable 10-year OS rate. These findings indicate that elevated PD-1 expression on TILs can be associated with immune evasion during the early stages of malignancy evolution in the NSCLC setting and further research is required to further delineate the role of PD-1/PD-L1 pathway on tumor immune senescence. These results underline the potential role of PD-1/PD-L1 inhibitors in the treatment of early-stage NSCLC.",2234943X,ONCOLOGY
10.1186/s40594-024-00507-1,Enhancing mathematical problem posing competence: a meta-analysis of intervention studies,"Mathematical problem posing, generally defined as the process of interpreting given situations and formulating meaningful mathematical problems, is academically important, and thus several interventions have been used to enhance this competence among students and teachers. Yet little is known about the interventions’ various components and their relative or combined effectiveness. In this meta-analysis of 26 intervention studies in mathematics, we identified nine intervention components and found that the interventions had a medium, positive, and significant mean weighted effect size. A stepwise meta-regression analysis revealed that intervention efficacy varied by moderators relevant to the research design, sample characteristics, and intervention characteristics. The findings obtained from this meta-analysis are expected to serve as a foundation for future efforts to design and implement (more) effective interventions to improve mathematical problem posing competence.",21967822,EDUCATION
10.1186/s40594-024-00508-0,“Not a cookie cutter situation”: how neurodivergent students experience group work in their STEM courses,"Although group work is increasingly used in STEM courses and may lead to improved academic outcomes, there is evidence that some implementations of group work may lead to unintended barriers for certain students’ learning. Despite the growing number of neurodivergent undergraduate students, there is limited research on neurodivergent students’ experiences with group work in STEM courses. To address this knowledge gap, the current research investigated the experiences of 22 neurodivergent undergraduate students with group work in STEM courses at a range of institution types and in a variety of STEM disciplines. Participants shared experiences with in-class and out-of-class group work assignments for lecture and laboratory courses. Through inductive thematic coding of semi-structured interview transcripts, we identified seven themes impacting participants’ experiences. Three themes were individual level: personal characteristics that participants associated with their neurodivergence; strategies for academic success (with subthemes of organization/time management, adaptive communication, and self-advocacy); and beliefs on group work’s value. Four themes were group level/classroom level: group dynamics; role in group (including leadership roles); the competitive culture within STEM; and recommendations for instructors. Through a social-relational perspective on disability, we proposed a model showcasing how group and classroom factors serve as supports or barriers to neurodivergent students’ full participation in group work, as well as to their sense of belonging. Using the seven themes we articulated, we outlined a set of practices for designing group work assignments. In addition, we propose how pairing inclusive assignment design with instructor reflection and articulating anti-ableist values can support neurodivergent student belonging by disrupting discourses of normalcy in STEM. As one of the first studies exploring the impact that group work in STEM courses has on neurodivergent undergraduates, this work may inform reimaginations of group work practices to better address the needs of neurodivergent STEM students and support a more inclusive culture in STEM classrooms. In addition, our conceptual model may serve as the basis for future research regarding interactions between individual-level and group-level factors associated with neurodivergent students’ learning through group work and other active learning practices.",21967822,EDUCATION
10.3389/feduc.2024.1455669,The mediating role of meaning in work in promoting teachers’ technology integration,"Teachers’ integration of technology has been a critical focus for both teachers and researchers over the past three decades. This emphasis has intensified due to the COVID-19 pandemic, where technology integration has become a key factor in the success of classroom teaching and learning processes. Despite this attention, previous studies have shown limited exploration of the relationship between teachers’ technology integration and meaning in work as an internal variable. Therefore, using AMOS-structural equation modeling (SEM) analysis, this study aimed to develop a conceptual model examining the mediating role of meaning in work in the relationship between digital leadership, self-efficacy, and teachers’ technology integration. The study involved 200 junior high school teachers from Balikpapan City, East Kalimantan Province, a region in eastern Indonesia projected to become the new capital. A total of four variables were analyzed in this study: meaning in work, digital leadership, self-efficacy, and teachers’ technology integration (Z, X, and Y, respectively). The results showed that (1) digital leadership affected meaning in work and teachers’ technology integration, (2) self-efficacy affected meaning in work and teachers’ technology integration, (3) meaning in work affected teachers’ technology integration, and (4) meaning in work could mediate the relationship between digital leadership and self-efficacy in teachers’ technology integration. These findings contribute to a deeper understanding of the relationships among digital leadership, self-efficacy, and meaning in work, and their collective impact on teachers’ technology integration. Furthermore, the study highlights the significant role of meaning in work as a mediator in these relationships, providing a foundation for the development of digital leadership strategies and training programs aimed at improving technology integration in education.",2504284X,EDUCATION
10.1007/s44196-024-00646-x,Bayesian Optimization with Additive Kernels for a Stepwise Calibration of Simulation Models for Cost-Effectiveness Analysis,"A critical aspect of simulation models used in cost-effectiveness analysis lies in accurately representing the natural history of diseases, requiring parameters such as probabilities and disease burden rates. While most of these parameters can be sourced from scientific literature, they often require calibration to align with the model’s expected outcomes. Traditional optimization methods can be time-consuming and computationally expensive, as they often rely on simplistic heuristics that may not ensure feasible solutions. In this study, we explore using Bayesian optimization to enhance the calibration process by leveraging domain-specific knowledge and exploiting structural properties within the solution space. Specifically, we investigate the impact of additive kernel decomposition and a stepwise approach, which capitalizes on the sequential block structure inherent in simulation models. This approach breaks down large optimization problems into smaller ones without compromising solution quality. In some instances, parameters obtained using this methodology may exhibit less error than those derived from naive calibration techniques. We compare this approach with two state-of-the-art high-dimensional Bayesian Optimization techniques: SAASBO and BAxUS. Our findings demonstrate that Bayesian optimization significantly enhances the calibration process, resulting in faster convergence and improved solutions, particularly for larger simulation models. This improvement is most pronounced when combined with a stepwise calibration methodology.",18756883,AI
10.3389/fonc.2024.1428802,Metabolic modulation of melanoma enhances the therapeutic potential of immune checkpoint inhibitors,"Introduction: Lactate is a pivotal molecule with diverse functions in the metabolic reprogramming of cancer cells. Beyond its role in metabolism, lactate exerts a modulatory effect within the tumor microenvironment; it is utilized by stromal cells and has been implicated in the suppression of the immune response against the tumor.Methods: Using in vitro assays (including flow cytometry, live-cell imaging and metabolic analyses), the impact of lactate dehydrogenase inhibitors (LDHIs) on melanoma cells were assessed. The therapeutic potential of LDHIs with immune checkpoint inhibitors (ICIs) were tested in vivo in murine models of melanoma tumors.Results: A potent anti-proliferative effect (via both cell cycle alterations and enhanced apoptosis) of LDHIs, Oxamate (Oxa) and methyl 1-hydroxy-6-phenyl-4-(trifluoromethyl)-1H-indole-2-carboxylate (NHI-2), was found upon treatment of melanoma cell lines. Using a combination of Oxa and NHI-2, a synergistic effect to inhibit proliferation, glycolysis, and ATP production was observed. Metabolic analysis revealed significant alteration in glycolysis and oxidative phosphorylation, while metabolite profiling emphasized consequential effects on lactate metabolism and induced energy depletion by LDHIs. Detection of increased RANTES and MCP-1, with Oxa and NHI-2 treatment, prompted the consideration of combining LDHIs with ICIs. In vivo studies using a murine B78 melanoma tumor model revealed a significant improvement in treatment efficacy when LDHIs were combined with ICIs.Conclusions: These findings propose the potential of targeting lactate metabolism to enhance the efficacy of ICI treatments in patients with melanoma.",2234943X,ONCOLOGY
10.3389/fpsyg.2024.1466905,Validation and psychometric evaluation of the French version of the recovery experience questionnaire: internal consistency and validity assessment,"Background: Entrepreneurs often experience high levels of stress, anxiety, and burnout due to the demanding nature of their professional activities. Therefore, recovery from work-related stress is a relevant activity for entrepreneurs. The Recovery Experience Questionnaire (REQ) is a widely used 16-item self-reported measure covering four recovery factors: psychological detachment from work, relaxation, mastery, and control. The present study addresses the validation of a French version of the REQ.Methods: A total of 1,043 French entrepreneurs from various sectors participated in this study. Internal consistency and correlations were examined to assess the psychometric properties of the French version of the REQ. Confirmatory factor analysis (CFA) was used to validate the four-factor structure of the REQ, with seven error covariances added to improve model fit.Results: The French version of the REQ demonstrated good internal consistency (psychological detachment: α = 0.88, relaxation: α = 0.91, mastery: α = 0.90, control: α = 0.91). CFA supported that the four-factor structure was confirmed based on the following data: RMSEA = 0.071 (95% CI [0.066, 0.077]), CFI/TLI = 0.955/0.950, SRMR = 0.050, and χ2 (108) = 593.861, p < 0.001. Significant correlations were found between REQ scores and health indicators such as stress, loneliness, physical health, mental health, and sleep quality. The results confirm that the REQ is a valid and reliable measure for assessing recovery experiences among French entrepreneurs.Conclusion: We conclude that the REQ is a valid measure and a useful tool for research on entrepreneurs’ general health. Additionally, the validated French version of the REQ can be applied to other working populations, making it a versatile instrument for evaluating health and recovery in diverse occupational settings. To support this claim, we conducted the same validation analysis on a sample of 1,231 French agricultural employees, again showing that REQ is a valid and reliable measure for assessing recovery experiences.",16641078,PSYCHOLOGY
10.3389/fonc.2024.1462997,The value of adjusted PSAD in prostate cancer detection in the Chinese population,"Objective: To investigate the value of adjusted prostate-specific antigen density (PSADadj) in the diagnosis of prostate cancer (PCa).Methods: Data from 410 patients who underwent transrectal ultrasound-guided prostate biopsy were retrospectively analyzed in Beijing Tsinghua Changgung Hospital between November 2014 and March 2024. All patients were divided into PCa and benign prostatic hyperplasia (BPH) groups according to pathological results. Multivariate logistic regression analyses were performed to evaluate the odd ratios (ORs) of predictors for PCa occurrence. Receiver operating characteristic curves were plotted, and the area under the curve (AUC) values were used to assess and compare the diagnostic accuracies of total PSA (tPSA), free-to-total (f/t) PSA, free PSA (fPSA), PSAD, and PSADadj (PSAD×weight).Results: There were 166 patients in the PCa group and 244 in the BPH group. Multivariate analyses demonstrated that PSAD was positively correlated with the presence of PCa, with the highest OR value among all PSA-related parameters (OR = 19.075, p<0.001). tPSA, fPSAD, PSAD, and PSADadj had high accuracy in predicting PCa, with AUC values of 0.633, 0.730, 0.778, and 0.780. Of note, PSADadj had the highest AUC with a sensitivity of 63.3% and specificity of 81.6%. Similarly, in patients with a PSA level in the gray zone, the diagnostic accuracy of PSADadj in predicting PCa (AUC, 0.709; 95% CI, 0.616–0.802) remained better than other PSA-related markers.Conclusion: PSADadj has an advantage over other PSA-related markers in detecting PCa and could be used for making biopsy decisions.",2234943X,ONCOLOGY
10.3389/feduc.2024.1393070,Evaluating technology breaks on cell phone use in a college classroom,"Cell phones in the college classroom can be used to increase interaction between students and the professor; they can also distract from academic tasks and decrease academic performance. To decrease task-switching in the classroom, researchers have suggested the use of “technology breaks” (TB), in which students are provided periodic breaks to use cell phones throughout class. The purpose of the present study was to evaluate the use of technology breaks in a college classroom (N = 21). Cell phone use was evaluated over 22 class periods. Observers recorded how many students were using cell phones every 10 s. Three experiment conditions were alternated with yoked controls in a multi-element design: (A) 1 min technology breaks, (B) 2 min technology break, and (C) 4 min technology break. The control condition [question breaks, (QB)] provided breaks for students to ask the professor questions regarding class materials. No penalties or punishers were delivered for cell phone use under any conditions. The average rate of cellphone use in QB was 0.53 responses per min (range = 0.06–1.02), while the average rate for TB was 0.35 responses per min (range = 0.20–0.74). Overall, the study found that technology breaks were a promising way to utilize reinforcement-based strategies to reduce classroom cell phone use, though variability in the data weakened conclusions regarding the utility of technology breaks.",2504284X,EDUCATION
10.3389/frai.2024.1374162,Modeling disagreement in automatic data labeling for semi-supervised learning in Clinical Natural Language Processing,"Introduction: Computational models providing accurate estimates of their uncertainty are crucial for risk management associated with decision-making in healthcare contexts. This is especially true since many state-of-the-art systems are trained using the data which have been labeled automatically (self-supervised mode) and tend to overfit.Methods: In this study, we investigate the quality of uncertainty estimates from a range of current state-of-the-art predictive models applied to the problem of observation detection in radiology reports. This problem remains understudied for Natural Language Processing in the healthcare domain.Results: We demonstrate that Gaussian Processes (GPs) provide superior performance in quantifying the risks of three uncertainty labels based on the negative log predictive probability (NLPP) evaluation metric and mean maximum predicted confidence levels (MMPCL), whilst retaining strong predictive performance.Discussion: Our conclusions highlight the utility of probabilistic models applied to “noisy” labels and that similar methods could provide utility for Natural Language Processing (NLP) based automated labeling tasks.",26248212,AI
10.1186/s40359-024-02019-7,"The associations between self-rated autistic traits, social camouflaging, and mental health outcomes in Taiwanese anime, comics and games (ACG) doujin creators: an exploratory study","Doujin (どうじん) is a Japanese term referring to a circle where people share the same interests, usually something that belongs to the Anime, Comics, and Games (ACG) subculture. Individuals who belong to it and create related works, known as ACG doujin creators, are usually described as socially awkward and at potential risk of isolation. In such a context, they may theoretically exhibit higher autistic traits and manifest camouflaging tendencies, which may consequently be associated with their mental health. Nonetheless, the impact of autistic traits and camouflaging on mental health in this subculture remains significantly underexplored. We recruited 183 Taiwanese ACG doujin creators (age ranges from 18 to 41, 146 female and 37 male) via social networking platforms. Participants completed Chinese online surveys assessing socio-demographic information, doujin activities, past psychiatric history, the 35-item Version of Autism-Spectrum Quotient (AQ-35), Chinese version Camouflaging Autistic Traits Questionnaire (CAT-Q-Ch), the General Anxiety Disorder-7 (GAD-7), and the Patient Health Questionnaire-9 (PHQ-9). Linear regression analysis was employed to examine the associations between the aforementioned scales. Our findings revealed that among ACG doujin creators, descriptively higher level of AQ-35 and CAT-Q-Ch than previous studies were found. Moreover, we observed a positive association between camouflaging behaviours and most AQ-35 subscales, with the exception of the mindreading subscale. Additionally, we identified that both camouflaging and autistic traits were significantly linked to higher PHQ-9 and GAD-7 scores. Through this study, we gained insight into the distinctive characteristics of autistic traits, camouflaging behaviours, and mental health among Taiwanese ACG doujin creators, as the associations between the factors mentioned above are divergent compared to previous research. This topic demonstrated that camouflaging is also associated with adverse mental health in a subculture group.",20507283,PSYCHOLOGY
10.1186/s40594-024-00509-z,"Synergistic effects of students’ mathematics and science motivational beliefs on achievement, and their determinants","Background: Students’ mathematics and science motivational beliefs are crucial determinants of their school academic achievement in math and science. The current study aimed to identify the group memberships of students’ motivational beliefs in math and science, which are closely related. Furthermore, this study probed the predictive effects of individual students’ experiences at school on forming group membership. We also tested the mean differences of the identified latent groups in math and science achievement. Results: Using latent profile analysis modeling, we examined data from 3857 Korean eighth-grade students participating in the 2019 Trends in International Mathematics and Science Study. The theoretical rationale and supplementary statistical indices showed a five-group membership as the optimal solution. The five groups are high motivation, medium motivation, low math/high science motivation, low motivation, and very low motivation. Students’ sense of school belonging was the most crucial predictor in forming group membership, whereas perceived student bullying did not predict group membership. Finally, students in distinct motivational belief groups exhibited differences in their math and science achievements. Conclusions: This study identified five subgroups of students based on their distinct motivational beliefs in math and science, and variations in their association with achievements. In terms of policy development and intervention, it is important to nurture students’ sense of school belonging. This study advances motivational theories in science, technology, engineering, and mathematics education, and provides practical suggestions for improving educational practices to enhance student math and science motivational beliefs.",21967822,EDUCATION
10.1186/s40359-024-02025-9,Psychosocial impacts of post-disaster compensation processes: narrative systematic review,"After disasters, many people seek compensation for physical, psychological or economic damages. However, compensation processes can be perceived as arduous and unfair and potentially create stress for both individuals and communities. This systematic review explored the psychosocial impacts of post-disaster compensation processes, including compensation sought through both litigation and government assistance programmes. We searched seven databases, hand-searched reference lists of included studies, and used thematic analysis to synthesise results of included studies. We screened 6,532 papers, ultimately including 66 in the review. While we found mixed evidence regarding the relationship between individual mental health and the compensation process, many studies suggested the process placed demands on emotional resources and could cause stress. Numerous challenges of the compensation process were described, including complicated paperwork, lengthy processes, inadequate information, confusing eligibility criteria, lack of inter-agency cooperation, poor understanding of communities’ unique needs, insufficient pay-outs, and politicisation of the process. Inequities in compensation distribution introduced additional stress to already traumatised communities, who often experienced resentment, envy and conflict. The mixed nature of the relationship between mental health and the compensation process was evident in research trends where a small number of studies reported positive findings related to relating to gratitude, helpfulness of compensation and strengthened community relationships, while a substantial number of others reported negative impacts including higher mental health problems. Positive and negative impacts were reported for both litigation and non-litigation compensation-seeking. The nuanced dynamics of these findings are described in greater detail within the paper. It is important that compensation regulators consider the potential impacts on individuals and communities and take steps to address compensation inequities. This enhanced understanding of how those affected by disasters can rebuild their lives and furthering understanding of how to support them will enable evidence-based approaches to building resilience and planning for long-term recovery. Significant compensation process improvements could be realised by ensuring clear communication and transparent decision-making. Overall, this review underscores the importance of ensuring that compensation processes are fair and straightforward so they can repair material losses without deteriorating the social norms and relationships of affected communities.",20507283,PSYCHOLOGY
10.3389/feduc.2024.1438322,"Predictor of low academic achievement among Dilla university students, southern Ethiopia, 2024","Introduction: In Ethiopia, despite its growing higher education sector, student achievement rates remain concerningly low. Understanding the multifaceted factors influencing academic performance is crucial for improving educational equity and quality. This study delves into potential predictors of academic achievement among Ethiopian higher education students, examining individual characteristics, institutional elements, and broader socioeconomic influences.Methodology: This survey enrolled 362 respondents and was conducted from December 7, 2023 till January 22, 2024. Simple random sampling, validated assessment tools and online data collection methods were employed to select and collect information from respondents. Data entry and analysis was done using Epi-info 7.0 and SPSS 25, respectively. Logistic regression analysis method was used to determine the association between the outcome and independent variable.Result: The current results show that 166 (45/9%) of participants have GPAs below 3.18. Gender, social sciences/humanities or business/economics majors, suboptimal class environments, inadequate laboratory facilities, chronic illness, class sizes, low emotional coping skills, poor academic self-perception, and high social media use emerged as significant predictors of low academic achievement.Conclusion: This study identified factors associated with academic achievement. Female students, optimal learning environments, and smaller class sizes were linked to better performance, while social sciences/humanities or business/economics, inadequate facilities, and high social media use increased the risk of low achievement. Personal characteristics like emotional coping, self-perception, and chronic illness also played a role. These findings suggest interventions targeting individual and environmental factors could improve student outcomes.",2504284X,EDUCATION
10.3390/educsci14101094,"Influence and Relationship of Physical Activity before, during and after the School Day on Bullying and Cyberbullying in Young People: A Systematic Review","The aim of this systematic review was to analyze the influence of the practice of Physical Activity (PA) before, during and after school hours on bullying and cyberbullying in children and adolescents. Studies were identified in four databases (PubMed, SCOPUS, Web of Science, ERIC) from January 2013 to March 2024. A total of 29 studies met the inclusion criteria. Seventeen studies used a cross-sectional design to explore the association between these variables, and 12 articles had a longitudinal design with PA interventions. The review found that PA is associated with significant improvements in bullying and cyberbullying, reduced depressive symptoms, and strengthened social relationships, responsibility, and self-esteem. PA before the school day may be effective in reducing bullying victimization. During the school day, it promotes affective behaviors related to bullying, such as empathy and respect for others, and optimizes psychological factors such as self-concept and self-esteem. After-school PA reduces bullying and disruptive behaviors in non-educational contexts. It is recommended to implement PA programs that address social, emotional and behavioral aspects throughout the day, with Educational Centers and Physical Education as the central axis. Didactic recommendations for implementing PA programs against bullying/cyberbullying in school and extracurricular contexts are included.",22277102,EDUCATION
10.3390/ai5040091,A Bag-of-Words Approach for Information Extraction from Electricity Invoices,"In the context of digitization and automation, extracting relevant information from business documents remains a significant challenge. It is typical to rely on machine-learning techniques to automate the process, reduce manual labor, and minimize errors. This work introduces a new model for extracting key values from electricity invoices, including customer data, bill breakdown, electricity consumption, or marketer data. We evaluate several machine learning techniques, such as Naive Bayes, Logistic Regression, Random Forests, or Support Vector Machines. Our approach relies on a bag-of-words strategy and custom-designed features tailored for electricity data. We validate our method on the IDSEM dataset, which includes 75,000 electricity invoices with eighty-six fields. The model converts PDF invoices into text and processes each word separately using a context of eleven words. The results of our experiments indicate that Support Vector Machines and Random Forests perform exceptionally well in capturing numerous values with high precision. The study also explores the advantages of our custom features and evaluates the performance of unseen documents. The precision obtained with Support Vector Machines is 91.86% on average, peaking at 98.47% for one document template. These results demonstrate the effectiveness of our method in accurately extracting key values from invoices.",26732688,AI
10.1186/s40359-024-02056-2,The effect of workplace bullying on knowledge sharing of the employees in scientific and technological enterprises: a moderated mediation model,"This study aims to understand how workplace bullying affects knowledge sharing among employees in Chinese scientific and technological enterprises. A convenience sampling method was employed to survey 275 employees from scientific and technological enterprises of Yangtze River Delta, China. The survey utilized a general information questionnaire, a workplace bullying scale, an organizational belonging scale, a knowledge sharing scale, and a forbearance scale. A moderated mediation model was set up, and the hierarchical regression and the bootstrapping method were applied. The empirical results indicated that workplace bullying has a negative effect on the knowledge sharing, and organization belonging has played mediating effect. Furthermore, Forbearance not only moderated the effect of workplace bullying on organizational belonging, but also moderated the mediated effect of organization belonging, and the effect will be stronger when employees are at a lower level of forbearance. This study offers important implications for scientific and technological enterprises. The findings imply that enterprises should discourage person-related workplace bullying to increase employees’ intention to engage in knowledge-sharing behavior. Moreover, the manager of these firms should develop a culture of family so that they can care for the organization belonging.",20507283,PSYCHOLOGY
10.3389/feduc.2024.1411503,Multifaceted perception of school climate: association between students’ and teachers’ perceptions and other teacher factors,"Introduction: This study aimed to investigate whether there is a significant association between teachers’ and students’ perceptions of school climate, and if not, whether teacher factors are associated with the respective perceptions.Methods: The participants included 1,831 students and 59 homeroom teachers from 11 public elementary and junior high schools in Japan. Multilevel models were used to examine the association between students’ and teachers’ perceptions of school climate.Results: Of the three teacher-rated school climate scales, only teacher-perceived disciplinary climate was associated with students’ perceptions of school climate. Teachers’ working conditions, such as self-efficacy and stress, were associated with teachers’ perceptions but not students’ perceptions of school climate. Disciplinary climate was associated with students’ perceptions of school climate, even after accounting for the teachers’ working conditions.Discussion: Items questioning specific student behaviors, such as those included in the disciplinary climate scale, may be effective in avoiding incongruence with student evaluations. Moreover, maintaining disciplinary climate itself is important for students’ positive perceptions of the school climate. A disciplinary climate in which teachers and students share responsibility for learning and classroom organization, and strategies that support positive student behavior are preferable to exclusionary discipline strategies. Incorporating feedback data gathered through classroom observations or student perceptions is also important in resolving the incongruence between teachers’ and students’ perceptions of the school climate.",2504284X,EDUCATION
10.3389/fpsyg.2024.1387698,Parental conflict and adolescents’ socially adverse emotions: the mediating role of family functioning,"Objective: To examine the process of how parental conflict and family functioning influence adolescents’ socially adverse emotions (shyness and loneliness).Methods: Stratified cluster sampling was used to conduct a questionnaire survey among 1,100 junior high school students from three junior high schools in Beijing, Chongqing, and Shijiazhuang, China.Results: (1) The overall experience of adolescents’ socially adverse emotions was at the moderate level; boys’ experience of shyness and loneliness was significantly higher than that of girls; the experience of shyness and loneliness in the second grade was significantly higher than that in the first grade; (2) Parental conflict was significantly negatively correlated with family functioning and significantly positively correlated with adolescents’ socially adverse emotions, while family functioning was significantly negatively correlated with adolescents’ socially adverse emotions; (3) Family functioning partially mediates the relationship between parental conflict and adolescents’ shyness and completely mediates the relationship between parental conflict and adolescents’ loneliness.Conclusion: Compared to adolescents’ shyness, family functioning plays a more important mediating role in the relationship between parental conflict and adolescents’ loneliness.",16641078,PSYCHOLOGY
10.3389/fonc.2024.1466912,Electrolyte prognosis scoring system can predict overall survival in patients with osteosarcoma,"Osteosarcoma stands as the most prevalent bone tumor, characterized by a heightened tendency for local recurrence and distant metastasis, resulting in a bleak prognosis. Presently, there exists a shortage of novel markers to effectively determine the prognosis of osteosarcoma patients. Recent research indicates that hematological markers partially mirror an individual’s microenvironment, offering potential insights into predicting patient prognosis. However, prior studies predominantly focused on the prognostic significance of singular hematological indices, failing to comprehensively represent the tumor microenvironment of patients. In our investigation, we meticulously gathered data on 22 hematological and electrolyte markers, utilizing LASSO Cox regression analysis to devise an Electrolyte Prognostic Scoring System (EPSS). The EPSS encompasses various indicators, including immunity, inflammation, coagulation, and electrolyte levels. Our findings indicate that the EPSS stands as an independent prognostic factor for overall survival among osteosarcoma patients. It serves as a valuable addition to clinical characteristics, adept at discerning high-risk patients from those deemed clinically low-risk. Furthermore, EPSS-based nomograms demonstrate commendable predictive capabilities.",2234943X,ONCOLOGY
10.3389/feduc.2024.1473353,Who gets to be an ELT course book author? Native speakerism in English for specific purposes and business English course books,"Introduction: Native speakerism has a profound influence on many aspects of ELT, for example negatively affecting job opportunities of those perceived as ‘non-native speakers’. Nevertheless, little is known about the effect of native speakerism on the recruitment of course book authors (CBAs).Methods: Therefore, this study analysed the linguistic and ethnic representation of 161 CBAs of 77 business English business English and English for specific purposes English for Specific Purposes course books (CBs) published globally by Pearson, OUP, CUP, Macmillan and NGL.Results: The data clearly show that publishers tend to hire white ‘native speakers’ from the UK as CBAs. More specifically, 90% of all CBA slots were taken by ‘native speakers’, 95% by white CBAs, and 78% by CBAs from the UK.Discussion: This indicates a profound native speakerist bias among publishers against not only ‘non-native speakers’, but also those ‘native speakers’ who are not white or do not come from the UK. It is thus suggested that business English and English for Specific Purposes publishers pay greater attention to the diversity of the author teams they hire.",2504284X,EDUCATION
10.3390/ai5040094,Causal Economic Machine Learning (CEML): “Human AI”,"This paper proposes causal economic machine learning (CEML) as a research agenda that utilizes causal machine learning (CML), built on causal economics (CE) decision theory. Causal economics is better suited for use in machine learning optimization than expected utility theory (EUT) and behavioral economics (BE) based on its central feature of causal coupling (CC), which models decisions as requiring upfront costs, some certain and some uncertain, in anticipation of future uncertain benefits that are linked by causation. This multi-period causal process, incorporating certainty and uncertainty, replaces the single-period lottery outcomes augmented with intertemporal discounting used in EUT and BE, providing a more realistic framework for AI machine learning modeling and real-world application. It is mathematically demonstrated that EUT and BE are constrained versions of CE. With the growing interest in natural experiments in statistics and causal machine learning (CML) across many fields, such as healthcare, economics, and business, there is a large potential opportunity to run AI models on CE foundations and compare results to models based on traditional decision-making models that focus only on rationality, bounded to various degrees. To be most effective, machine learning must mirror human reasoning as closely as possible, an alignment established through CEML, which represents an evolution to truly “human AI”. This paper maps out how the non-linear optimization required for the CEML structural response functions can be accomplished through Sequential Least Squares Programming (SLSQP) and applied to data sets through the S-Learner CML meta-algorithm. Upon this foundation, the next phase of research is to apply CEML to appropriate data sets in various areas of practice where causality and accurate modeling of human behavior are vital, such as precision healthcare, economic policy, and marketing.",26732688,AI
10.1186/s40594-024-00511-5,STEM career expectations across four diverse countries: motivation to learn mathematics mediates the effects of gender and math classroom environments,"We tested the broad generality of a model for predicting 9th–10th grade students’ STEM career expectations by age 30, focusing on hard science, mathematics and engineering professions only, known for driving innovation, research and development. The model’s predictors included motivation to learn mathematics, gender, and math classroom environments (disciplinary climate, teacher support and instructional strategies fostering conceptual understanding). We used data from the Programme for International Student Assessment (PISA) 2022. Four countries were selected based on the percentage of students expecting STEM careers, representing high vs. low groups (Qatar and Morocco vs. Czech Republic and Lithuania, respectively). Analysis began with computing correlations between the variables, followed by path analyses for each country to determine both direct and indirect effects of the predictors on students’ STEM career expectations. We found that motivation to learn mathematics not only directly predicted STEM career expectations but also mediated the influence of the remaining variables: gender (boys show higher motivation to learn math), and math classroom environments (students in well-disciplined math classes with supportive teachers who employ instructional strategies fostering math reasoning also demonstrate higher motivation to learn math). Remarkably, our model consistently demonstrated robustness across all four countries, despite their significant economic, ethnic, and religious diversity. Theoretically, the model reveals that 9th–10th grade students’ transitory long-term STEM career expectations are shaped by their interest in mathematics, their perceived importance of the subject, confidence in their self-efficacy to succeed in math tasks, perceptions of classroom disciplinary climate, teacher support, and their exposure to instructional strategies aimed at enhancing math reasoning. Practically, it suggests widespread potential for informing interventions aimed at increasing student motivation to pursue STEM careers through improved mathematics education practices.",21967822,EDUCATION
10.3390/educsci14101107,Evaluation of the Implementation of Project-Based-Learning in Engineering Programs: A Review of the Literature,"Project-Based Learning (PBL), as an experiential methodology, improves learning outcomes and competencies (technical and non-technical) in engineering students. The Conceive–Design–Implement–Operate (CDIO) approach, adopted globally in engineering education, is based on PBL but expands the curriculum framework. Developed by MIT and the Royal Institute of Technology (KTH) in Sweden, CDIO focuses on the entire life cycle of engineering projects to train engineers so that they are capable of applying knowledge in real-life situations. Integrating CDIO and PBL into engineering curricula requires changes in teaching methodologies, teacher training and workspaces. The literature has explored their combination, highlighting shared values and mutual reinforcements. An assessment model is crucial for implementing PBL and evidencing improvement in student and course skills. Only through assessment and the cycle of continuous improvement will the adoption of PBL in engineering programs be advanced. A systematic review of the literature is proposed to identify effective methods in the evaluation of educational programs based on PBL, analyzing related research areas and evaluations according to the CDIO approach.",22277102,EDUCATION
10.3389/fonc.2024.1437347,Comparison of the diagnostic efficacy between imaging features and iodine density values for predicting microvascular invasion in hepatocellular carcinoma,"Background: In recent years, studies have confirmed the predictive capability of spectral computer tomography (CT) in determining microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). Discrepancies in the predicted MVI values between conventional CT imaging features and spectral CT parameters necessitate additional validation.Methods: In this retrospective study, 105 cases of small HCC were reviewed, and participants were divided into MVI-negative (n=53, Male:48 (90.57%); mean age, 59.40 ± 11.79 years) and MVI-positive (n=52, Male:50(96.15%); mean age, 58.74 ± 9.21 years) groups using pathological results. Imaging features and iodine density (ID) obtained from three-phase enhancement spectral CT scans were gathered from all participants. The study evaluated differences in imaging features and ID values of HCC between two groups, assessing their diagnostic accuracy in predicting MVI occurrence in HCC patients. Furthermore, the diagnostic efficacy of imaging features and ID in predicting MVI was compared.Results: Significant differences were noted in the presence of mosaic architecture, nodule-in-nodule architecture, and corona enhancement between the groups, all with p-values < 0.001. There were also notable disparities in IDs between the two groups across the arterial phase, portal phase, and delayed phases, all with p-values < 0.001. The imaging features of nodule-in-nodule architecture, corona enhancement, and nonsmooth tumor margin demonstrate significant diagnostic efficacy, with area under the curve (AUC) of 0.761, 0.742, and 0.752, respectively. In spectral CT analysis, the arterial, portal, and delayed phase IDs exhibit remarkable diagnostic accuracy in detecting MVI, with AUCs of 0.821, 0.832, and 0.802, respectively. Furthermore, the combined models of imaging features, ID, and imaging features with ID reveal substantial predictive capabilities, with AUCs of 0.846, 0.872, and 0.904, respectively. DeLong test results indicated no statistically significant differences between imaging features and IDs.Conclusions: Substantial differences were noted in imaging features and ID between the MVI-negative and MVI-positive groups in this study. The ID and imaging features exhibited a robust diagnostic precision in predicting MVI. Additionally, our results suggest that both imaging features and ID showed similar predictive efficacy for MVI.",2234943X,ONCOLOGY
10.1007/s44196-024-00656-9,AI-FEED: Prototyping an AI-Powered Platform for the Food Charity Ecosystem,"This paper presents the development and functionalities of the AI-FEED web-based platform (ai-feed.ai), designed to address food and nutrition insecurity challenges within the food charity ecosystem. AI-FEED leverages advancements in artificial intelligence (AI) and blockchain technology to facilitate improved access to nutritious food and efficient resource allocation, aiming to reduce food waste and bolster community health. The initial phase involved comprehensive interviews with various stakeholders to gather insights into the ecosystem’s unique challenges and requirements. This informed the design of four distinct modules in the AI-FEED platform, each targeting the needs of one of four stakeholder groups (food charities, donors, clients, and community leaders). Prototyping and iterative feedback processes were integral to refining these modules. The food charity module assists charities in generating educational content and predicting client needs through AI-driven tools. Based on blockchain technology, the food donor module streamlines donation processes, enhances donor engagement, and provides donor recognition. The client module provides real-time information on food charity services and offers a centralized repository for nutritional information. The platform includes a comprehensive mapping and proposal system for community leaders to strategically address local food insecurity issues. AI-FEED’s integrated platform approach allows data sharing across modules, enhancing overall functionality and impact. The paper also discusses ethical considerations, potential biases in AI systems, and the transformation of AI-FEED from a research project to a sustainable entity. The AI-FEED platform exemplifies the potential of interdisciplinary collaboration and technological innovation in addressing societal challenges, particularly in improving food security and community health.",18756883,AI
10.3390/ai5040096,Feasibility of GPT-3.5 versus Machine Learning for Automated Surgical Decision-Making Determination: A Multicenter Study on Suspected Appendicitis,"Background: Nonsurgical treatment of uncomplicated appendicitis is a reasonable option in many cases despite the sparsity of robust, easy access, externally validated, and multimodally informed clinical decision support systems (CDSSs). Developed by OpenAI, the Generative Pre-trained Transformer 3.5 model (GPT-3) may provide enhanced decision support for surgeons in less certain appendicitis cases or those posing a higher risk for (relative) operative contra-indications. Our objective was to determine whether GPT-3.5, when provided high-throughput clinical, laboratory, and radiological text-based information, will come to clinical decisions similar to those of a machine learning model and a board-certified surgeon (reference standard) in decision-making for appendectomy versus conservative treatment. Methods: In this cohort study, we randomly collected patients presenting at the emergency department (ED) of two German hospitals (GFO, Troisdorf, and University Hospital Cologne) with right abdominal pain between October 2022 and October 2023. Statistical analysis was performed using R, version 3.6.2, on RStudio, version 2023.03.0 + 386. Overall agreement between the GPT-3.5 output and the reference standard was assessed by means of inter-observer kappa values as well as accuracy, sensitivity, specificity, and positive and negative predictive values with the “Caret” and “irr” packages. Statistical significance was defined as p < 0.05. Results: There was agreement between the surgeon’s decision and GPT-3.5 in 102 of 113 cases, and all cases where the surgeon decided upon conservative treatment were correctly classified by GPT-3.5. The estimated model training accuracy was 83.3% (95% CI: 74.0, 90.4), while the validation accuracy for the model was 87.0% (95% CI: 66.4, 97.2). This is in comparison to the GPT-3.5 accuracy of 90.3% (95% CI: 83.2, 95.0), which did not perform significantly better in comparison to the machine learning model (p = 0.21). Conclusions: This study, the first study of the “intended use” of GPT-3.5 for surgical treatment to our knowledge, comparing surgical decision-making versus an algorithm found a high degree of agreement between board-certified surgeons and GPT-3.5 for surgical decision-making in patients presenting to the emergency department with lower abdominal pain.",26732688,AI
10.3390/ejihpe14100184,FOBism Unveiled: Quantifying Assimilative Racism within Asians in the United States,"FOB (fresh-off-the-boat) is a term used to refer to unassimilated immigrants or sojourners, which has created a divide within the Asian community. In this study, we coined the term FOBism, a form of internalized racism (or appropriated racial oppression) that intersects with assimilation, and we developed a measure of FOBism. We created a 14-item, 3-factor FOBism Scale and evaluated its psychometric properties among a sample of 296 Asians in the United States. Exploratory structural equation modeling (ESEM) was utilized to select items and evaluate the factorial validity. Results yielded a strong factor structure, internal consistency reliability, and construct validity. Construct validity was demonstrated through FOBism scores’ positive correlations with measures of within-group discrimination and internalized racism, and negative associations with an Asian cultural orientation. The FOBism Scale is a promising measure that could be used as an assessment tool and to raise awareness of the phenomenon.",22549625,PSYCHOLOGY
10.3389/frai.2024.1460364,Large language models for whole-learner support: opportunities and challenges,"In recent years, large language models (LLMs) have seen rapid advancement and adoption, and are increasingly being used in educational contexts. In this perspective article, we explore the open challenge of leveraging LLMs to create personalized learning environments that support the “whole learner” by modeling and adapting to both cognitive and non-cognitive characteristics. We identify three key challenges toward this vision: (1) improving the interpretability of LLMs' representations of whole learners, (2) implementing adaptive technologies that can leverage such representations to provide tailored pedagogical support, and (3) authoring and evaluating LLM-based educational agents. For interpretability, we discuss approaches for explaining LLM behaviors in terms of their internal representations of learners; for adaptation, we examine how LLMs can be used to provide context-aware feedback and scaffold non-cognitive skills through natural language interactions; and for authoring, we highlight the opportunities and challenges involved in using natural language instructions to specify behaviors of educational agents. Addressing these challenges will enable personalized AI tutors that can enhance learning by accounting for each student's unique background, abilities, motivations, and socioemotional needs.",26248212,AI
10.3390/cancers16203510,Targeting the Leloir Pathway with Galactose-Based Antimetabolites in Glioblastoma,"Background: Glioblastoma (GBM) uses Glut3 and/or Glut14 and the Leloir pathway to catabolize D-Galactose (Gal). UDP-4-deoxy-4-fluorogalactose (UDP-4DFG) is a potent inhibitor of the two key enzymes, UDP-galactose-4-epimerase (GALE) and UDP-Glucose 6-dehydrogenase (UGDH), involved in Gal metabolism and in glycan synthesis. The Gal antimetabolite 4-deoxy-4-fluorogalactose (4DFG) is a good substrate for Glut3/Glut14 and acts as a potent glioma chemotherapeutic. Methods: Primary GBM cell cultures were used to examine toxicity and alterations in glycan composition via lectin binding in fixed cells and by Western blots. Toxicity/efficacy in vivo data was performed in mouse flank and intracranial models. The effect of 4DFG on D-glucose (Glc) metabolism in GBM cells was assessed by using 13C NMR-based tracer studies. Results: 4DFG is moderately potent against GBM cells (IC50: 125–300 µM). GBM glycosylation is disrupted by 4DFG. Survival analysis in an intracranial mouse model showed that treatment with 4DFG (6 × 25 mg/kg of 4DFG, intravenously) improved outcomes by three-fold (p < 0.01). Metabolic flux analysis revealed that both glycolytic and mitochondrial metabolic fluxes of [U-13C]Glc were significantly decreased in the presence of 4DFG in GBM cells. Conclusion: A functional Gal-scavenging pathway in GBM allows Gal-based antimetabolites to act as chemotherapeutics. 4DFG is metabolized by GBM in vitro and in vivo, is lethal to GBM tumors, and is well tolerated in mice.",20726694,ONCOLOGY
10.3390/educsci14101128,The Integration of Mixed Reality Simulation into Reading Literacy Modules,"The reading literacy crisis, among learners, in countries throughout the world and in South Africa seems to be reaching pandemic levels. Hence, the quality of teaching and the preparation that pre-service teachers receive at initial teacher education institutions is under the spotlight. A proactive action research design is used to integrate mixed reality simulation into reading literacy modules. Our data collection methods included professional conversations, WhatsApp voice notes and video calls, reflective journal entries and reflections on observing video recordings of lesson segments in the MRS environment. The data was analyzed using content analysis. The main themes emanating from the data included: lack of focus on high leverage teaching practices, limited use of pedagogies of enactment, add-on to existing content, experimentation, perceptions, planning and preparation, content-method integration, pedagogies of enactment, assessment, resources and feedback. Grounded in a Community of Practice framework, we narrate our experiences of re-imagining mixed reality simulation as a core component of initial teacher education programs. The authors conclude by sharing insights and recommendations for policymakers, faculty leaders, and curriculum designers, contributing to informed decisions regarding integrating and potentially upscaling mixed reality simulation within reading literacy modules in initial teacher education programs.",22277102,EDUCATION
10.3389/frai.2024.1435895,A review on the efficacy of artificial intelligence for managing anxiety disorders,"Anxiety disorders are psychiatric conditions characterized by prolonged and generalized anxiety experienced by individuals in response to various events or situations. At present, anxiety disorders are regarded as the most widespread psychiatric disorders globally. Medication and different types of psychotherapies are employed as the primary therapeutic modalities in clinical practice for the treatment of anxiety disorders. However, combining these two approaches is known to yield more significant benefits than medication alone. Nevertheless, there is a lack of resources and a limited availability of psychotherapy options in underdeveloped areas. Psychotherapy methods encompass relaxation techniques, controlled breathing exercises, visualization exercises, controlled exposure exercises, and cognitive interventions such as challenging negative thoughts. These methods are vital in the treatment of anxiety disorders, but executing them proficiently can be demanding. Moreover, individuals with distinct anxiety disorders are prescribed medications that may cause withdrawal symptoms in some instances. Additionally, there is inadequate availability of face-to-face psychotherapy and a restricted capacity to predict and monitor the health, behavioral, and environmental aspects of individuals with anxiety disorders during the initial phases. In recent years, there has been notable progress in developing and utilizing artificial intelligence (AI) based applications and environments to improve the precision and sensitivity of diagnosing and treating various categories of anxiety disorders. As a result, this study aims to establish the efficacy of AI-enabled environments in addressing the existing challenges in managing anxiety disorders, reducing reliance on medication, and investigating the potential advantages, issues, and opportunities of integrating AI-assisted healthcare for anxiety disorders and enabling personalized therapy.",26248212,AI
10.3389/feduc.2024.1449363,"Synchronous online learning and career readiness in higher education: student perceptions, challenges, and solutions","Synchronous Online Learning (SOL) environments have rapidly transformed the educational landscape. However, there is limited research on their efficacy in equipping students with the necessary skills to succeed in the workforce, particularly in developing essential professional skills like digital literacy, interpersonal communication, and practical experience. This study explores how SOL impacts students’ readiness for the workforce and the development of these critical skills. The research employed a qualitative methodology involving in-depth interviews with 27 third- and fourth-year students from a South African university. Purposive sampling was used to capture diverse experiences regarding SOL and its influence on professional skill development. Thematic analysis was performed to identify critical patterns and insights from the interviews. Findings reveal that SOL environments effectively enhance students’ technical skills and digital adaptability, essential for navigating a digital workforce. However, SOL is inadequate in developing interpersonal skills and providing practical, hands-on experiences. Students reported a lack of networking opportunities and expressed concerns about their preparedness for the demands of real-world employment, particularly in fields requiring strong interpersonal skills and practical experience. The study highlights the need for educational innovations that combine the benefits of digital learning with comprehensive skill development strategies, particularly in soft skills and experiential learning.",2504284X,EDUCATION
10.1007/s00432-024-05946-5,"Feasibility of a complex psychosocial intervention for families with parental cancer: acceptability, suitability, implementability, and perceived support","Purpose: This study aimed to assess the feasibility of a comprehensive psychosocial intervention for families coping with parental cancer. Methods: A quasi-experimental trial with intervention and control group, employing a mixed-methods approach, was conducted. A total of 472 families affected by parental cancer participated. The feasibility of the intervention was evaluated based on study monitoring measures (on-site visits, team supervision meeting observations, case conference observations, best practice workshops, coordinating information exchange between intervention sites, and reviewing intervention documentation), process evaluation (semi-structured interviews, focus group discussion) and survey data. Data analysis involved thematic coding and descriptive statistics. Results: The intervention was well-received by the participating families, with a high degree of acceptance observed. The feasibility of the intervention was found to be associated with specific dynamics within each family system and the motivation of the family members. The success of the intervention was described as dependent on the family-centered arrangement of the encounters, including factors such as frequency, duration, and mode, which greatly influenced its overall acceptability. Conclusion: The family-scout intervention demonstrates its feasibility as an effective intervention to reduce the burden experienced by families coping with parental cancer. Psychosocial oncology services should continue to develop and implement family-centered interventions to offer support to families during their cancer journey. Trial registration: ClinicalTrials.gov, NCT04186923. Retrospectively registered on 4 December 2019.",14321335,ONCOLOGY
10.3389/frai.2024.1497705,The impact of pedagogical beliefs on the adoption of generative AI in higher education: predictive model from UTAUT2,"Artificial Intelligence in Education (AIEd) offers advanced tools that can personalize learning experiences and enhance teachers’ research capabilities. This paper explores the beliefs of 425 university teachers regarding the integration of generative AI in educational settings, utilizing the UTAUT2 model to predict their acceptance and usage patterns through the Partial Least Squares (PLS) method. The findings indicate that performance expectations, effort expectancy, social influence, facilitating conditions, and hedonic motivation all positively impact the intention and behavior related to the use of AIEd. Notably, the study reveals that teachers with constructivist pedagogical beliefs are more inclined to adopt AIEd, underscoring the significance of considering teachers’ attitudes and motivations for the effective integration of technology in education. This research provides valuable insights into the factors influencing teachers’ decisions to embrace AIEd, thereby contributing to a deeper understanding of technology integration in educational contexts. Moreover, the study’s results emphasize the critical role of teachers’ pedagogical orientations in their acceptance and utilization of AI technologies. Constructivist educators, who emphasize student-centered learning and active engagement, are shown to be more receptive to incorporating AIEd tools compared to their transmissive counterparts, who focus on direct instruction and information dissemination. This distinction highlights the need for tailored professional development programs that address the specific beliefs and needs of different teaching philosophies. Furthermore, the study’s comprehensive approach, considering various dimensions of the UTAUT2 model, offers a robust framework for analyzing technology acceptance in education.",26248212,AI
10.1186/s40359-024-02065-1,Improving cognitive function in Chinese children with ADHD and/or RD through computerized working memory training,"Prior research has found that children with attention-deficit hyperactivity disorder (ADHD) and reading difficulties (RD) are at an elevated risk of developing further cognitive deficits and developmental challenges [1]. ADHD and RD are characterized by a deficit in working memory, which negatively affects learning and behavior. The main aims of this study were to design a working memory training app and examine its effectiveness through a 5-week training program in Chinese children with ADHD and/or RD. There were three experimental groups, with 26 participants in the ADHD group, 38 participants in the RD group, and 24 participants in the ADHD + RD group. The typically developing (TD) control group had 32 participants. All participants completed the pretest and posttest assessments on executive function and reading performance. The findings indicate that the experimental groups improved performance in verbal and visual-spatial working memory as well as Chinese word reading. There was an overall reduction in functional impairment following the training, in contrast to the TD group. This study showed that working memory can be improved through computerized training in children with ADHD and/or RD. The implications of future research in working memory are discussed. Clinical Trials Identifier: NCT06567444 (retrospectively registered) on 20 August 2024.",20507283,PSYCHOLOGY
10.3389/frai.2024.1414122,Heuristic machine learning approaches for identifying phishing threats across web and email platforms,"Life has become more comfortable in the era of advanced technology in this cutthroat competitive world. However, there are also emerging harmful technologies that pose a threat. Without a doubt, phishing is one of the rising concerns that leads to stealing vital information such as passwords, security codes, and personal data from any target node through communication hijacking techniques. In addition, phishing attacks include delivering false messages that originate from a trusted source. Moreover, a phishing attack aims to get the victim to run malicious programs and reveal confidential data, such as bank credentials, one-time passwords, and user login credentials. The sole intention is to collect personal information through malicious program-based attempts embedded in URLs, emails, and website-based attempts. Notably, this proposed technique detects URL, email, and website-based phishing attacks, which will be beneficial and secure us from scam attempts. Subsequently, the data are pre-processed to identify phishing attacks using data cleaning, attribute selection, and attacks detected using machine learning techniques. Furthermore, the proposed techniques use heuristic-based machine learning to identify phishing attacks. Admittedly, 56 features are used to analyze URL phishing findings, and experimental results show that the proposed technique has a better accuracy of 97.2%. Above all, the proposed techniques for email phishing detection obtain a higher accuracy of 97.4%. In addition, the proposed technique for website phishing detection has a better accuracy of 98.1%, and 48 features are used for analysis.",26248212,AI
10.3389/fpsyg.2024.1365180,The limits of personal experience,"This article examines how three types of experience—personal, related others, and unrelated others—influence decision-making. We present the complexities and nuances in using these experiential sources to suggest that personal experience is preferred to the other two sources. We discuss the implications of this preference for decision-making processes, especially in contexts involving transformative outcomes. To conclude, we discuss how people rely on other experiential sources when their preferred source is limited.",16641078,PSYCHOLOGY
10.3390/ai5040097,Machine Learning Models Informed by Connected Mixture Components for Short- and Medium-Term Time Series Forecasting,"This paper presents a new approach in the field of probability-informed machine learning (ML). It implies improving the results of ML algorithms and neural networks (NNs) by using probability models as a source of additional features in situations where it is impossible to increase the training datasets for various reasons. We introduce connected mixture components as a source of additional information that can be extracted from a mathematical model. These components are formed using probability mixture models and a special algorithm for merging parameters in the sliding window mode. This approach has been proven effective when applied to real-world time series data for short- and medium-term forecasting. In all cases, the models informed by the connected mixture components showed better results than those that did not use them, although different informed models may be effective for various datasets. The fundamental novelty of the research lies both in a new mathematical approach to informing ML models and in the demonstrated increase in forecasting accuracy in various applications. For geophysical spatiotemporal data, the decrease in Root Mean Square Error (RMSE) was up to 27.7%, and the reduction in Mean Absolute Percentage Error (MAPE) was up to 45.7% compared with ML models without probability informing. The best metrics values were obtained by an informed ensemble architecture that fuses the results of a Long Short-Term Memory (LSTM) network and a transformer. The Mean Squared Error (MSE) for the electricity transformer oil temperature from the ETDataset had improved by up to 10.0% compared with vanilla methods. The best MSE value was obtained by informed random forest. The introduced probability-informed approach allows us to outperform the results of both transformer NN architectures and classical statistical and machine learning methods.",26732688,AI
10.1007/s00432-024-06001-z,RETRACTED ARTICLE: Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients,"Background Breast cancer remains the leading malignant neoplasm among women globally, posing significant challenges in terms of treatment and prognostic evaluation. The metabolic pathway of polyamines is crucial in breast cancer progression, with a strong association to the increased capabilities of tumor cells for proliferation, invasion, and metastasis. Methods We used a multi-omics approach combining bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) to study polyamine metabolism. Data from The Cancer Genome Atlas, Gene Expression Omnibus, and Genotype-Tissue Expression identified 286 differentially expressed genes linked to polyamine pathways in breast cancer. These genes were analyzed using univariate COX and machine learning algorithms to develop a prognostic scoring algorithm. Single-cell RNA sequencing validated the model by examining gene expression heterogeneity at the cellular level. Results Our single-cell analyses revealed distinct subpopulations with different expressions of genes related to polyamine metabolism, highlighting the heterogeneity of the tumor microenvironment. The SuperPC model (a constructed risk score) demonstrated high accuracy when predicting patient outcomes. The immune profiling and functional enrichment analyses revealed that the genes identified play a crucial role in cell cycle control and immune modulation. Single-cell validation confirmed that polyamine metabolism genes were present in specific cell clusters. This highlights their potential as therapeutic targets. Conclusions This study integrates single cell omics with machine-learning to develop a robust scoring model for breast cancer based on polyamine metabolic pathways. Our findings offer new insights into tumor heterogeneity, and a novel framework to personalize prognosis. Single-cell technologies are being used in this context to enhance our understanding of the complex molecular terrain of breast cancer and support more effective clinical management.",14321335,ONCOLOGY
10.3389/fpsyg.2024.1449629,Mindfulness and mental health: the importance of a clinical intervention to prevent the effects of a traumatic event. A pilot study,"Numerous research studies show that mindfulness can mitigate the negative impact of trauma on mental health by reducing symptoms of anxiety, mediating the relationship between trauma exposure and mental health, and treating symptoms resulting from traumatic events. During the COVID-19 pandemic, which was considered a traumatic event, the wellbeing of adults and children was severely compromised. Although children seem less vulnerable to the physical effects of the virus, this does not seem to be true for the psychological effects. Indeed, a prolonged period of loss of family activities and routines can have a negative impact on the mental health of children and adolescents. To investigate how mindfulness can help preschool children cope with the effects of COVID-19, a study was conducted on 46 children aged 4–5 years. The programme, based on the work of Jon Kabat-Zinn and adapted to the age of the participants, consisted of eight weekly 45-min sessions. Qualitative and quantitative results showed positive feedback, indicating that mindfulness helps children make sense of their experiences and achieve functional post-traumatic growth. This approach is seen as a challenge to guide children toward the restoration of psychological wellbeing, which is essential for good psychological balance.",16641078,PSYCHOLOGY
10.1186/s40359-024-02074-0,A scoping review of well-being measures: conceptualisation and scales for overall well-being,"This study aims to identify the conceptualisation of overall well-being used for well-being assessment through a review of the characteristics and key components and/or dimensions of well-being scales as presented in current literature. Scopus and Web of Science were searched, and thematic analysis was conducted inductively to analyse the identified components within scales, as well as the types of well-being these scales measure. 107 peer-reviewed articles from 2003 to 2022 were included, and 69 well-being scales were identified covering nine areas of well-being. Four final themes were identified as the foundational dimensions of overall well-being: hedonic; eudaimonic; physical health; and generic happiness. Notably, these 69 scales are mainly validated and adopted in the Western context. ‘4 + N’ frameworks of overall well-being are recommended for assessing overall well-being. This review provides researchers with a synthesis of what types of well-being have been measured and which measures have been used to assess these types of well-being for which research participants. Non-Western-based well-being research is called for that incorporates a broader range of research participants and cultural contexts in contributing to a more inclusive understanding of well-being.",20507283,PSYCHOLOGY
10.3389/frai.2024.1446640,Impact of hypertension on coronary artery plaques and FFR-CT in type 2 diabetes mellitus patients: evaluation utilizing artificial intelligence processed coronary computed tomography angiography,"Objective: This study utilized artificial intelligence (AI) to quantify coronary computed tomography angiography (CCTA) images, aiming to compare plaque characteristics and CT-derived fractional flow reserve (FFR-CT) in type 2 diabetes mellitus (T2DM) patients with or without hypertension (HTN).Methods: A retrospective analysis was conducted on 1,151 patients with suspected coronary artery disease who underwent CCTA at a single center. Patients were grouped into T2DM (n = 133), HTN (n = 442), T2DM (HTN+) (n = 256), and control (n = 320). AI assessed various CCTA parameters, including plaque components, high-risk plaques (HRPs), FFR-CT, severity of coronary stenosis using Coronary Artery Disease Reporting and Data System 2.0 (CAD-RADS 2.0), segment involvement score (SIS), and segment stenosis score (SSS). Statistical analysis compared these parameters among groups.Results: The T2DM (HTN+) group had the highest plaque volume and length, SIS, SSS, and CAD-RADS 2.0 classification. In the T2DM group, 54.0% of the plaque volume was noncalcified and 46.0% was calcified, while in the HTN group, these values were 24.0 and 76.0%, respectively. The T2DM (HTN+) group had more calcified plaques (35.7% noncalcified, 64.3% calcified) than the T2DM group. The average necrotic core volume was 4.25 mm3 in the T2DM group and 5.23 mm3 in the T2DM (HTN+) group, with no significant difference (p > 0.05). HRPs were more prevalent in both T2DM and T2DM (HTN+) compared to HTN and control groups (p < 0.05). The T2DM (HTN+) group had a higher likelihood (26.1%) of FFR-CT ≤0.75 compared to the T2DM group (13.8%). FFR-CT ≤0.75 correlated with CAD-RADS 2.0 (OR = 7.986, 95% CI = 5.466–11.667, cutoff = 3, p < 0.001) and noncalcified plaque volume (OR = 1.006, 95% CI = 1.003–1.009, cutoff = 29.65 mm3, p < 0.001). HRPs were associated with HbA1c levels (OR = 1.631, 95% CI = 1.387–1.918).Conclusion: AI analysis of CCTA identifies patterns in quantitative plaque characteristics and FFR-CT values. Comorbid HTN exacerbates partially calcified plaques, leading to more severe coronary artery stenosis in patients with T2DM. T2DM is associated with partially noncalcified plaques, whereas HTN is linked to partially calcified plaques.",26248212,AI
10.3390/educsci14111161,The Role of Cognitive Learner Prerequisites for Cognitive Load and Learning Outcomes in AR-Supported Lab Work,"Augmented Reality (AR) can enhance student-centered lab work by bridging the spatial and temporal split between virtual information and observed real-world phenomena. While the Cognitive Theory of Multimedia Learning and the Cognitive Load Theory suggest that AR can reduce extraneous cognitive load (ECL) and foster learning, the empirical results remain inconsistent. This re-analysis of three related studies with different target groups and AR devices explores whether learners’ spatial abilities and verbal working memory capacity moderate the effect of AR support in lab work settings on ECL and conceptual knowledge gains. Although these moderators could not be confirmed consistently, the results indicate that tablet-based AR holds the potential to support learners with low spatial abilities. Moreover, low verbal working memory learners were demonstrated to be particularly vulnerable to the spatial contiguity failure that can be caused by smartglasses AR. Moderation effects were only observed for ECL but not for conceptual knowledge gains. The findings highlight that the benefit of AR support can depend on learners’ cognitive prerequisites and additional contextual factors, such as the AR device used and the age of the target group. The design and implementation of AR-supported lab work environments should account for these factors to optimize the learning outcomes.",22277102,EDUCATION
10.3389/feduc.2024.1253671,Tax credit for support of university-community partnerships in low-income urban school districts,"Tying public school funding to property taxes has prevented low-income school districts in the United States from garnering adequate financial and social resources. As a result of this regressive funding system, millions of children find themselves trapped in underfunded schools and neighborhoods that perpetuate intergenerational trauma, tenuous employment, poor health, and poverty. However, in many underserved neighborhoods, including in cities like Philadelphia and Chicago, where poverty rates have been as high as 25 and 40%, respectively, many of the most under-resourced schools border or are adjacent to wealthy universities. Given this proximity of many universities and their wealth of resources spanning medical centers, community organizations, faculty, and students, the potential for mutual benefit, long-term structural change, and the ability to fulfill shared missions is significant, and partnerships that breakdown historical siloes must be encouraged. Therefore, this policy brief advocates for a tax credit at the federal level to incentivize and catalyze scaling of successful university-community partnership models that have been transformative in their respective communities.",2504284X,EDUCATION
10.3390/educsci14111165,Developing Doctoral Theses in Education: The Role of Systematic Reviews in the Spanish Context,"The production and development of doctoral theses have grown exponentially with the advent of the Internet and the democratization of access to information and education. In the field of education, this production is no stranger to this trend, so it is interesting to analyze the implications, causes and scientific–academic contributions of this increase. To this end, a systematic literature review (SLR) was carried out using the PRISMA 2020 protocol, with the Dialnet database as the documentary source, based on a previous study that justified its use and the availability of documents. Thus, a set of pre-established criteria are defined to identify doctoral theses carried out in Spanish universities and related to the education area that have been published in the last 17 years, finding a total of (n = 120) publications whose analysis answered the researchers’ questions focused on identifying patterns and strategies in the publication and methodological design of this type of document and what is the role of systematic reviews of the literature in them. In this sense, this research process aimed to analyze this kind of production and facilitate the process of designing new theses and research projects in the field of education. In this sense, this research process aimed to analyze this sort of output and facilitate the process of designing new theses and research projects in the field of education. The results make it possible to identify the increased importance of SLR in the development of doctoral theses and reveal the predominant models related to this type of production. Additionally, other aspects, such as the most common universities or research fields, the quantity and nature of subsequent studies, etc., concerning doctoral theses that incorporate an SLR were determined. Thus, conducting an SLR represents a solid and structured approach to initiate and build up the research process of doctoral theses, being essential to address students’ potential training needs in these regards.",22277102,EDUCATION
10.3390/cancers16213626,A Systematic Review of the Use of Surgical Checklists in Transurethral Resection of Bladder Tumour,"Context: Surgical checklists have previously been shown to improve surgical quality and patient outcomes. However, their use in transurethral resection of bladder tumour (TURBT), one of the most commonly performed urological procedures, has yet to be explored in depth. Objective: To evaluate the effect of surgical checklist implementation in TURBT on documentation quality, specimen quality, and oncological outcomes according to the existing literature. We then hope to develop an optimised TURBT checklist by identifying the most pertinent parameters for inclusion. Evidence acquisition: A literature search using PubMed was performed to identify literature pertaining to the use of surgical checklists in the context of TURBT. A systematic review was then performed on the 41 identified studies, of which six were included in the final analysis. Evidence synthesis: We explored three primary outcomes that arose from the literature, namely: (1) comprehensiveness of documentation; (2) resection quality; and (3) recurrence rates and recurrence-free survival (RFS). We found agreement in the literature that surgical checklist implementation does lead to an overall improvement in documentation. The effect of surgical checklists on resection quality and recurrence rates, however, was mixed in the literature, with some studies showing statistically significant improvements and others showing no significant change. Conclusions: There are multiple benefits to surgical checklist implementation in TURBT procedures. We propose an optimised 14-item surgical checklist that should be implemented in every TURBT report to ensure sufficient information documentation for risk stratification and post-operative management.",20726694,ONCOLOGY
10.3390/ai5040100,Leveraging Explainable Artificial Intelligence (XAI) for Expert Interpretability in Predicting Rapid Kidney Enlargement Risks in Autosomal Dominant Polycystic Kidney Disease (ADPKD),"Autosomal dominant polycystic kidney disease (ADPKD) is the predominant hereditary factor leading to end-stage renal disease (ESRD) worldwide, affecting individuals across all races with a prevalence of 1 in 400 to 1 in 1000. The disease presents significant challenges in management, particularly with limited options for slowing cyst progression, as well as the use of tolvaptan being restricted to high-risk patients due to potential liver injury. However, determining high-risk status typically requires magnetic resonance imaging (MRI) to calculate total kidney volume (TKV), a time-consuming process demanding specialized expertise. Motivated by these challenges, this study proposes alternative methods for high-risk categorization that do not rely on TKV data. Utilizing historical patient data, we aim to predict rapid kidney enlargement in ADPKD patients to support clinical decision-making. We applied seven machine learning algorithms—Random Forest, Logistic Regression, Support Vector Machine (SVM), Light Gradient Boosting Machine (LightGBM), Gradient Boosting Tree, XGBoost, and Deep Neural Network (DNN)—to data from the Polycystic Kidney Disease Outcomes Consortium (PKDOC) database. The XGBoost model, combined with the Synthetic Minority Oversampling Technique (SMOTE), yielded the best performance. We also leveraged explainable artificial intelligence (XAI) techniques, specifically Local Interpretable Model-Agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP), to visualize and clarify the model’s predictions. Furthermore, we generated text summaries to enhance interpretability. To evaluate the effectiveness of our approach, we proposed new metrics to assess explainability and conducted a survey with 27 doctors to compare models with and without XAI techniques. The results indicated that incorporating XAI and textual summaries significantly improved expert explainability and increased confidence in the model’s ability to support treatment decisions for ADPKD patients.",26732688,AI
10.3390/ai5040101,Deep Learning in Finance: A Survey of Applications and Techniques,"Machine learning (ML) has transformed the financial industry by enabling advanced applications such as credit scoring, fraud detection, and market forecasting. At the core of this transformation is deep learning (DL), a subset of ML that is robust in processing and analyzing complex and large datasets. This paper provides a comprehensive overview of key deep learning models, including Convolutional Neural Networks (CNNs), Long Short-Term Memory networks (LSTMs), Deep Belief Networks (DBNs), Transformers, Generative Adversarial Networks (GANs), and Deep Reinforcement Learning (Deep RL). Beyond summarizing their mathematical foundations and learning processes, this study offers new insights into how these models are applied in real-world financial contexts, highlighting their specific advantages and limitations in tasks such as algorithmic trading, risk management, and portfolio optimization. It also examines recent advances and emerging trends in the financial industry alongside critical challenges such as data quality, model interpretability, and computational complexity. These insights can guide future research directions toward developing more efficient, robust, and explainable financial models that address the evolving needs of the financial sector.",26732688,AI
10.3390/ai5040102,Airfoil Shape Generation and Feature Extraction Using the Conditional VAE-WGAN-gp,"A machine learning method was applied to solve an inverse airfoil design problem. A conditional VAE-WGAN-gp model, which couples the conditional variational autoencoder (VAE) and Wasserstein generative adversarial network with gradient penalty (WGAN-gp), is proposed for an airfoil generation method, and then, it is compared with the WGAN-gp and VAE models. The VAEGAN model couples the VAE and GAN models, which enables feature extraction in the GAN models. In airfoil generation tasks, to generate airfoil shapes that satisfy lift coefficient requirements, it is known that VAE outperforms WGAN-gp with respect to the accuracy of the reproduction of the lift coefficient, whereas GAN outperforms VAE with respect to the smoothness and variations of generated shapes. In this study, VAE-WGAN-gp demonstrated a good performance in all three aspects. Latent distribution was also studied to compare the feature extraction ability of the proposed method.",26732688,AI
10.3390/educsci14111181,A Systematic Review of Digital Competence Evaluation in Higher Education,"University students’ digital skills depend significantly on educators’ proficiency, necessitating regular assessments. Tools like DigComp and the TPACK model are provided in this technological context. A systematic review, following PRISMA criteria, aims to evaluate digital competencies through globally used tools. DigCompEdu is prominent, with Spain leading the research, while unvalidated instruments from Asia highlight global disparities. This review will identify key tools and expose geographical and validation gaps, stressing the need for standardized assessments. Understanding the predominance of DigCompEdu and seeing the variation that is generated in Asia highlights the poor ability to transmit self-perceived competencies to learners.",22277102,EDUCATION
10.1007/s00432-024-06005-9,Dysregulation of SIGLEC1 in non-small cell lung cancer: prognostic implications and immunomodulatory role-a multicenter cohort study,"Purpose To investigate the clinical significance and functional role of SIGLEC1-positive cells in non-small cell lungcancer (NSCLC) patients, focusing on their prognostic impact and therapeutic response. Methods A multicenter retrospective cohort analysis was conducted, integrating data from multiple sources. Weanalyzed SIGLEC1 expression in NSCLC tissues, clinicopathological features, overall survival outcomes,chemotherapy responsiveness, and sensitivity to targeted therapies. We also developed a prognostic model basedon SIGLEC1 expression and clinical variables. Results SIGLEC1 expression was significantly downregulated in NSCLC tissues, and the density of SIGLEC1-positivecells was inversely correlated with various clinicopathological features. Notably, patients with high infiltration ofSIGLEC1-positive cells exhibited significantly better overall survival outcomes. Furthermore, elevated SIGLEC1expression was associated with improved responsiveness to chemotherapy and demonstrated distinct patterns ofsensitivity to targeted therapies. A robust prognostic model was developed by integrating SIGLEC1 expression andclinical variables. Conclusions This study highlighted the downregulation of SIGLEC1 in NSCLC tissues and its significant associationwith patient prognosis and therapeutic response. The findings suggested that SIGLEC1 played a critical role inmodulating the tumor immune microenvironment and has potential as both a prognostic biomarker and therapeutictarget in NSCLC.",14321335,ONCOLOGY
10.1007/s44196-024-00676-5,Fuzzy Association Rule Mining for Personalized Chinese Language and Literature Teaching from Higher Education,"Due to rapid information technology growth, teaching Chinese in higher education has changed, and Chinese literary majors have vigorously evolved. The key teaching difficulties are scalability, individualized teaching, and a lack of resources and methodologies. Research shows individualized education improves topic comprehension, cultural engagement, and learner interest. Fuzzy association rule mining uses fuzzy linguistic values and membership functions to provide more realistic results. Hence, an algorithm, EF-PCL2T, has been proposed to improve personalized Chinese language and literature teaching (PCL2T) using enhanced fuzzy (EF) Apriori association rule mining integrated with the genetic algorithm. Fuzzy Apriori association rule mining identified frequent itemsets with relevant learning patterns and produced applicable association rules from datasets with fuzzy or unclear information, capturing fluctuating itemset importance and providing a flexible representation of relationships to determine student preferences. From fuzzy-related data, a genetic algorithm optimizes skill sets and creates individualized lesson plans considering each student’s competency and preferences for adjusting to personalized teaching tactics. Testing shows that fuzzy enhancement association rule mining for the PCL2T model improves student retention, PET (personalized teaching efficiency), minimal support and confidence update with fuzzy rules, and student involvement compared to other state-of-the-art methods. Students agree that tailored Chinese language and literary instruction is possible. The improvement results show fuzzy rules with minimum confidence levels of 50% to 100%, highly correlated in this model, student retention ratio of 96%, improved assessment grade of various language skills by 40 marks, PTE analysis of 93%, and student involvement ratio of 97%.",18756883,AI
10.1007/s44196-024-00680-9,Federated Learning Enhanced MLP–LSTM Modeling in an Integrated Deep Learning Pipeline for Stock Market Prediction,"In this study, the research presents the Federated Learning Enhanced Multi-Layer Perceptron (Fed-MLP) Long Short-Term Memory that is suggested by the research. The research intends to use the LSTM networks extensively that are proficient in spatial dependence capturing and integrate them with the collaborative learning framework of Federated Learning in an endeavor to augment the predictive competency. In the first step, we gather stock market indices from various financial organizations, using CAC40 stocks as the index for the French stock market. To guarantee data consistency and quality, pre-processing methods including linear interpolation and Z-score normalization are used. There are two types of models for each of the three basic elements within the Fed-MLP–LSTM, namely, MLP for feature extraction and LSTM for sequence modeling. Institutionally, each refining institution trains a local MLP–LSTM on the corpus specific to their institution, with only the model parameters being transferred to a central server through Federated Learning. A global model is created and updated through repeated training and totaling of parameters while preserving privacy of the data going to each node. In the performance evaluation, quantitative measures like Root-Mean-Square Error (RMSE), and accuracy are seven used. Hypothesis testing shows that we have good evidence to support that the proposed Fed-MLP–LSTM outperforms the other methods with the lowest RMSE of 0. 0108 and 98.3% of accuracy with reference to their respective cocaine molecule target. The proposed method is implemented in python. This suggests that using Federated Learning along with MLP and LSTM as the components of this vector enhanced the function increasing its capacity and reliability in predicting the trends of stocks. In conclusion, the present study suggests a sound solution for effective and secure stock market forecasting in collaboration environments that can find its use in the financial domains and securities businesses.",18756883,AI
10.3389/feduc.2024.1451504,Enhancing English as a Foreign Language (EFL) learning in Saudi Arabia: the academic contribution of YouTube in EFL learning and cultural awareness,"The incorporation of technology in English as a Foreign Language (EFL) classroom has drastically transformed conventional learning models by offering innovative ways to boost students’ engagement and improve learning outcomes. This study investigates the impact of using YouTube as an educational tool to enhance EFL instruction in Saudi Arabia. A total of 200 EFL students were divided into two groups: An experimental group which used You Tube as a source of learning and another group which used normal curriculum. A mixed-methods approach was employed, combining quantitative data from a paired-sample t-test with qualitative feedback from students. The results for paired-sample t-test computations revealed a statistically significant difference (p = 0. 003) across the proficiency level indicating improvement in students’ speaking and listening skills at higher proficiency levels. Of the qualitative answers, motivational and participation enhancement were overemphasized. The research points that the integration of YouTube in EFL classrooms can lead to a remarkable increase in language learning especially in the learning area of listening and speaking abilities among the students. These results offer practical implications for educators seeking to integrate multimedia tools into their teaching strategies to promote more interactive and effective learning experiences.",2504284X,EDUCATION
10.1186/s40594-024-00515-1,From cognitive coach to social architect: shifts in learning assistants’ valued practices,"Learning assistants (LAs) are undergraduate students who serve as instructional assistants in STEM classrooms. In addition to engaging in active practice, they take a pedagogy seminar and regularly meet with a content instructor. While aspects of LAs’ pedagogical beliefs and actions have been investigated, there remains a gap in understanding how LAs make sense of their new instructional roles and how they negotiate between their experiences as students and their responsibilities as instructors. This study uses a sequential, exploratory mixed-methods approach, which includes constant comparative open-coding, thematic analysis, and epistemic network analysis, to analyze 178 reflections written by 89 LAs across five terms at two institutions. Here, we identify each LA’s expressed goals and intended actions at the start and the end of their first term as an LA. Using a community of practice framework, we seek to explicate the shifts in these LAs’ values as they become more central members of the LA community. LAs’ expressed roles shift from being cognitive coaches, where they focus on student thinking, sense-making, and understanding of disciplinary concepts, to being social architects, where their focus shifts to attending to the aspects of the environment that can support productive interactions for learning. A social architect prioritizes goals related to mutual trust, respect, & approachability, understanding and learning about students, and creating a sense of belonging. Similarly, their intended actions emphasize compassion, understanding, and facilitating group discussion. While all LAs studied exhibited this shift, it manifested in different ways and to different extents, as illustrated in detail by four selected cases. These cases illustrate how the shifts coupled to a change in language around teaching, becoming more specific and contextual. LAs express a shift in their valued practices over their first term as LAs related to their instructional role. The goal of student-centered instructional practice is often framed as becoming a better cognitive coach; however, this orientation does not foreground ideas around teaching practice that aim to foster engagement, belonging, and student agency. Implications for both the LA model and, more generally, for postsecondary STEM instructors are discussed.",21967822,EDUCATION
10.3389/fonc.2024.1475860,Preoperative subjective impairments in language and memory in brain tumor patients,"Background: Subjective reports can reveal relevant information regarding the nature of the impairment of brain tumor patients, unveiling potential gaps in current assessment practices. The co-occurrence of language and memory impairments has been previously reported, albeit scarcely. The aim of this study is therefore to understand the co-occurrence of subjective language and memory complaints in the preoperative state of brain tumor patients and its impact on Quality of Life (QoL).Methods: 31 brain tumor patients (12 LGG, 19 HGG) underwent a semi-structured interview to assess subjective complaints of language deficits, co-occurrences between language and memory dysfunction, and changes in QoL. Group and subgroup analyses were conducted to provide general and tumor grade specific data.Results: 48.4% of patients mentioned co-occurrence of language and memory impairments in reading, writing, and conversation. The HGG group reported co-occurrences in all three of these (reading: 31.6%; writing: 21.1%; conversation: 26.3%), while the LGG only described co-occurrences in reading (25%) and conversation (8.3%), although these were not statistically significant. All patients with co-occurring language and memory deficits reported these to be linked to reduced QoL (48.4%). In patients with an HGG, this number was slightly higher (52.6%) than in patients with an LGG (41.7%).Conclusion: Language impairments co-occur with memory dysfunction as perceived in patients’ daily life. Patients see these impairments as affecting their quality of life. Further attention to dedicated language and memory tasks seems necessary.",2234943X,ONCOLOGY
10.3389/feduc.2024.1379755,How schoolchildren use digital media in class and outside of school over several weeks: a quantitative case study with media diaries,"Introduction: Digital media play a central role in the lives of today’s schoolchildren, immersed in an increasingly digital world. Modern technologies blur the lines between formal school settings and informal settings outside of school. Although formats like bring-your-own-device align the use in the formal setting with informal usage, a disjunction exists between children’s interactions with digital technologies in their home environments and those within the educational setting. For bridging the gap between school learning and children’s lives outside of school, it is essential to explore the differences and similarities in media usage in both settings.Methods: In our case study, we examined schoolchildren’s motives and evaluations of digital media usage in both settings, addressing individual needs. Additionally, we explored several dimensions of digital literacy through self-assessment, identified associated learning opportunities within and outside the school environment, and captured self-reported learning gains. We collected this data over the course of several weeks in a longitudinal design with media diaries, aiming to estimate the extent of the fluctuation.Results: Eighty-four German schoolchildren aged between 10 and 16 years participated over a six-week period. We found differences but also similarities between media usage outside of school and in class. Digital media were less frequently used in class for entertainment, communication, and learning compared to outside of school, but no differences were reported regarding information search. Schoolchildren expressed above-average satisfaction with their media usage in both settings, but they perceived the usage of digital media outside of school as significantly more important than in class. Regarding their digital competencies, the schoolchildren displayed high self-confidence in most areas. Only in the areas of algorithms and programming, schoolchildren rated themselves as below average. While learning opportunities were identified in class and outside of school, the frequency of these opportunities varied across different digital skills. The self-reported learning gain in digital media usage remained consistently low in both settings. Across all analyses, there was no substantial temporal fluctuation in media usage over the study period.Discussion: The findings raise crucial considerations regarding the integration of digital media in the classroom, fostering a discussion on their implications for both research and educational practices.",2504284X,EDUCATION
10.1186/s40359-024-02120-x,Relative victimization scale: initial development and retrospective reports of the impact on mental health,"Bullying and victimization have been studied in many contexts and classified as peer victimization in school settings and parental or sibling victimization within family settings. Yet, current research is scarce on whether victimization occurring within family settings is specific to parental or sibling victimization. Thus, the current study aims to develop a scale assessing victimization conducted by relatives and provide support for its psychometric properties. Cross-sectional and longitudinal data were collected from university students (1622 and 1045 students, respectively) and participants responded to questionnaires via an online survey. EFA and CFA results demonstrated the unidimensionality of the Relative Victimization Scale (RVS) consisting of eight items. In terms of convergent validity, RVS scores were correlated with the scores on parental, sibling, and peer victimization scales and several psychological health outcomes including depression, anxiety, social anxiety, perceived stress, loneliness, negative and positive affect, life satisfaction, and resilience. Moreover, RVS explained a significant amount of variance beyond the contribution of parental, sibling, and peer victimization in those psychological health outcomes for the support of incremental validity. The findings of the study indicated the potential utility of the RVS in assessing the experience of relative victimization through offering support for internal consistency reliability and construct, longitudinal predictive, and incremental validity.",20507283,PSYCHOLOGY
10.3390/ai5040106,OTM-HC: Enhanced Skeleton-Based Action Representation via One-to-Many Hierarchical Contrastive Learning,"Human action recognition has become crucial in computer vision, with growing applications in surveillance, human–computer interaction, and healthcare. Traditional approaches often use broad feature representations, which may miss subtle variations in timing and movement within action sequences. Our proposed One-to-Many Hierarchical Contrastive Learning (OTM-HC) framework maps the input into multi-layered feature vectors, creating a hierarchical contrast representation that captures various granularities within a human skeleton sequence temporal and spatial domains. Using sequence-to-sequence (Seq2Seq) transformer encoders and downsampling modules, OTM-HC can distinguish between multiple levels of action representations, such as instance, domain, clip, and part levels. Each level contributes significantly to a comprehensive understanding of action representations. The OTM-HC model design is adaptable, ensuring smooth integration with advanced Seq2Seq encoders. We tested the OTM-HC framework across four datasets, demonstrating improved performance over state-of-the-art models. Specifically, OTM-HC achieved improvements of 0.9% and 0.6% on NTU60, 0.4% and 0.7% on NTU120, and 0.7% and 0.3% on PKU-MMD I and II, respectively, surpassing previous leading approaches across these datasets. These results showcase the robustness and adaptability of our model for various skeleton-based action recognition tasks.",26732688,AI
10.3390/ai5040107,Dynamic Multiobjective Optimization Based on Multi-Environment Knowledge Selection and Transfer,"Background: Dynamic multiobjective optimization problems (DMOPs) involve multiple conflicting and time-varying objectives, and dynamic multiobjective algorithms (DMOAs) aim to find Pareto optima that are closer to the real one in the new environment as soon as possible. In particular, the introduction of transfer learning in DMOAs has led to good results in solving DMOPs. However, the selection of valuable historical knowledge and the mitigation of negative transfer remain important problems in existing transfer learning-based DMOAs. Method: A DMOA based on multi-environment knowledge selection and transfer (MST-DMOA) is proposed in this article. First, by clustering historical Pareto optima, some representative solutions that can reflect the main evolutionary information are selected as knowledge of the environment. Second, the similarity between the historical and current environments is evaluated, and then the knowledge of multiple similar environments is selected as valuable historical knowledge to construct the source domain. Third, solutions with high quality in the new environment are obtained to form the target domain, which can better help historical knowledge to adapt to the current environment, thus effectively alleviating negative transfer. Conclusions: We compare the proposed MST-DMOA with five state-of-the-art DMOAs on fourteen benchmark test problems, and the experimental results verify the excellent performance of MST-DMOA in solving DMOPs.",26732688,AI
10.3389/fonc.2024.1437140,The role of systemic immune-inflammation index in predicting pathological complete response of breast cancer after neoadjuvant therapy and the establishment of related predictive model,"Objective: To investigate the role of systemic immune-inflammation index (SII) in complete pathological response (pCR) of breast cancer patients after neoadjuvant chemotherapy, and to establish and validate a nomogram for predicting pCR.Methods: Breast cancer patients were selected from the First Affiliated Hospital of Xi’an Jiaotong University from January 2020 to December 2023. The optimal cut-off value of SII was calculated via ROC curve. The correlation between SII and clinicopathological characteristics was analyzed by Chi-square test. Logistic regression analysis was performed to evaluate the factors that might affect pCR. Based on the results of Logistic regression analysis, a nomogram for predicting pCR was established and validated.Results: A total of 112 breast cancer patients were included in this study. 33.04% of the patients achieved pCR after neoadjuvant therapy. Chi-square test showed that SII was significantly correlated with pCR (P=0.001). Logistic regression analysis suggested that Ki-67 (P=0.039), therapy cycle (P<0.001), CEA (P=0.025) and SII (P=0.019) were independent predictors of pCR after neoadjuvant chemotherapy. A nomogram based on Ki-67, therapy cycle, CEA and SII showed a good predictive ability.Conclusion: Ki-67, therapy cycle, CEA and SII were independent predictors of pCR of breast cancer after neoadjuvant chemotherapy. The nomogram based on the above positive factors showed a good predictive ability.",2234943X,ONCOLOGY
10.1186/s40594-024-00513-3,"Leveraging professional learning communities in linking digital professional development and instructional integration: evidence from 16,072 STEM teachers","Background: Integration of digital tools and resources in STEM instruction has garnered significant attention due to its high potential. Digital professional development is identified as a pivotal factor for equipping teachers with necessary digital skills to effectively orchestrate digital resources. Notably, the role of professional learning communities is considered critical. However, the intricate relationships among digital professional development, professional learning communities, and digital instructional integration among STEM teachers remain underexplored. Utilizing partial least-squares–structural equation models (PLS–SEM), the present study examined links in digital professional development, professional learning communities, and digital instructional integration among STEM teachers (N = 16,072) who participated in the Programme for International Student Assessment (PISA) 2022. Results: Findings from the PLS–SEM analysis indicate that digital professional development exhibits a direct positive relationship with professional learning communities and digital instructional integration. Relatedly, professional learning communities is positively correlated with digital instructional integration. In terms of indirect effect, findings show that professional learning communities play a significant positive mediating role in linking digital professional development and digital instructional integration. Conclusions: This study reports new evidence on the influence of digital professional development on digital instructional integration through professional learning communities among 16,072 STEM teachers and concludes that, when STEM teachers regularly immerse themselves in professional learning communities, they are more likely to benefit from their digital professional development by integrating digital technologies in classroom instruction. Policymakers and educational leaders should consider promoting digital professional development and professional learning communities among STEM teachers, along with efforts to encourage digital instructional integration.",21967822,EDUCATION
10.1186/s40359-024-02116-7,Adaptation and validation of the Parents’ Self-stigma Scale into Turkish and its association with parenting stress and parental self-efficacy,"In the present era, parents frequently stigmatize themselves for their children’s negative behaviors and inadequate social skills. Parents’ self-stigma (PSS) may lead to a decrease in parental self-efficacy and quality of marital and family life. In light of these reasons, the principal objective of this study to assess the validity and reliability of the Turkish version of the PSS Scale (PSSS) as developed by Eaton et al. (2019) and to investigate the indirect effect that parenting stress has on the relationship between PSS and parental self-efficacy. We collected data from a total of 1,118 parents via random sampling, with the first part of the study involving 645 participants (Mage = 32.64 ± 7.28) and the second part of the study involving 473 participants (Mage = 27.43 ± 9.87). In the first part of the study, we employed structural equation modeling for the confirmatory factor analysis and Pearson’s correlation coefficient for the criterion-related validity, average variance extracted, and composite reliability analyses. Moreover, we calculated Cronbach’s alpha, McDonald’s omega, and Guttman split-half coefficients for the reliability analyses. In the second part of the study, we utilized Hayes’ bootstrapping method to assess the indirect effect of parenting stress on the relationship between PSS and parental self-efficacy. The first part of the study confirms the PSSS’s 11-item, 3-factor structure, showing the Turkish form to have acceptable goodness-of-fit indices, and found Cronbach’s alpha for the PSSS to be 0.89. Furthermore, the first part of the study demonstrates a significant negative correlation between marital life satisfaction and PSS. Meanwhile, the second part of the study has determined PSS to be positively related to parenting stress and negatively related to parental self-efficacy. The second part of the study also indicates parenting stress to have an indirect effect on the association between PSS and parental self-efficacy. The study indicates the Turkish version of the PSSS to be a valid and reliable instrument in Turkish culture for measuring parents’ PSS levels regarding their children, with higher scores indicating greater PSS. The scale can be effectively used in both research and clinical settings. The study also suggests parental stress to have a possible impact on the association between PSS and parental self-efficacy. Furthermore, addressing the variables of PSS and parenting stress in family-focused interviews and therapeutic interventions may contribute to increasing parental self-efficacy.",20507283,PSYCHOLOGY
10.1007/s44196-024-00672-9,Enhancing Expert Decision-Making for Wastewater Treatment Plants with Seidel Laplacian Energy and Cosine Similarity Measure in Intuitionistic Fuzzy Graphs,"Wastewater treatment facilities’ main goal is to protect the public and environment from the hazardous and poisonous materials found in wastewater. Water treatment facilities were developed to speed up the natural process of cleansing water. A novel cosine similarity measure across intuitionistic fuzzy graphs has been proven to be more effective than certain present ones in group decision-making issues using example verification. This paper provides a unique approach for calculating expert-certified, well-known scores by finding the ambiguous information of intuitionistic fuzzy preference relations as well as the regular cosine similarity grades from one separable intuitionistic fuzzy preference relation to another. The new technique considers both ""objective"" and ""subjective"" information provided by experts. Using intuitionistic fuzzy preference relations, we provide workable techniques for judging experts’ eligible reputational ratings. This can be used to raise or decrease the relevance of the stated criteria in an evaluation that takes into account several competing elements. We give a solution to a decisional problem by using two effective methods: the newly constructed cosine similarity measure and the Seidel Laplacian energy (SLe+) of an intuitionistic fuzzy graph. Finally, two working procedures and circumstances are offered to show the effectiveness and superiority of the proposed techniques.",18756883,AI
10.1007/s44196-024-00678-3,Random Oversampling-Based Diabetes Classification via Machine Learning Algorithms,"Diabetes mellitus is considered one of the main causes of death worldwide. If diabetes fails to be treated and diagnosed earlier, it can cause several other health problems, such as kidney disease, nerve disease, vision problems, and brain issues. Early detection of diabetes reduces healthcare costs and minimizes the chance of serious complications. In this work, we propose an e-diagnostic model for diabetes classification via a machine learning algorithm that can be executed on the Internet of Medical Things (IoMT). The study uses and analyses two benchmarking datasets, the PIMA Indian Diabetes Dataset (PIDD) and the Behavioral Risk Factor Surveillance System (BRFSS) diabetes dataset, to classify diabetes. The proposed model consists of the random oversampling method to balance the range of classes, the interquartile range technique-based outlier detection to eliminate outlier data, and the Boruta algorithm for selecting the optimal features from the datasets. The proposed approach considers ML algorithms such as random forest, gradient boosting models, light gradient boosting classifiers, and decision trees, as they are widely used classification algorithms for diabetes prediction. We evaluated all four ML algorithms via performance indicators such as accuracy, F1 score, recall, precision, and AUC-ROC. Comparative analysis of this model suggests that the random forest algorithm outperforms all the remaining classifiers, with the greatest accuracy of 92% on the BRFSS diabetes dataset and 94% accuracy on the PIDD dataset, which is greater than the 3% accuracy reported in existing research. This research is helpful for assisting diabetologists in developing accurate treatment regimens for patients who are diabetic.",18756883,AI
10.3389/feduc.2024.1378493,Using an app-based screening tool to predict deficits in written word spelling at school entry,"Introduction: The first year of schooling is crucial for the further development of spelling abilities in children, which makes early assessment and intervention essential. The aim of this study was to develop and validate an efficient and cost-free screening tool for identifying spelling problems in community school settings around the time of school entry.Methods: A broad range of precursors of spelling (vocabulary, grammar, letter knowledge, phonological awareness, phonological working memory, rapid automatized naming) were assessed in 522 Austrian first graders (6–7 years of age) in the first weeks of schooling. At the end of first grade, spelling abilities were assessed by newly developed spelling tasks based on the trochaic foot. By applying logistic regression with the least absolute shrinkage and selection operator (LASSO), we aimed to select a set of important predictors of spelling problems at the end of grade 1 (i.e., scoring below the 16th percentile in the spelling test).Results: Our analysis identified letter knowledge (i.e., an aspect of phonological information processing) and sentence repetition (i.e., a measure of grammatical knowledge) as important predictors of spelling problems. The screening tool has acceptable diagnostic accuracy [area under the curve (AUC) = 0.0.725 and DeLong 95% CI (0.666, 0.784)]. Further analyses indicated that the AUC differs neither between boys and girls nor between children with and without German as their first language.Discussion: These results suggest that administering the screening tool during the first weeks of schooling is a valid approach to identifying spelling deficits, which in turn enables early targeted pedagogical interventions. Practical implications for spelling instructions are discussed.",2504284X,EDUCATION
10.3390/ai5040109,Adaptive Exploration Artificial Bee Colony for Mathematical Optimization,"The artificial bee colony (ABC) algorithm is a famous swarm intelligence method utilized across various disciplines due to its robustness. However, it exhibits limitations in exploration mechanisms, particularly in high-dimensional or complex landscapes. This article introduces the adaptive exploration artificial bee colony (AEABC), a novel variant that reinspires the ABC algorithm based on real-world phenomena. AEABC incorporates new distance-based parameters and mechanisms to correct the original design, enhancing its robustness. The performance of AEABC was evaluated against 33 state-of-the-art metaheuristics across twenty-five benchmark functions and an engineering application. AEABC consistently outperformed its counterparts, demonstrating superior efficiency and accuracy. In a variable-sized problem (n = 10), the traditional ABC algorithm converged to 3.086 × 106, while AEABC achieved a convergence of 2.0596 × 10−255, highlighting its robust performance. By addressing the shortcomings of the traditional ABC algorithm, AEABC significantly advances mathematical optimization, especially in engineering applications. This work underscores the significance of the inspiration of the traditional ABC algorithm in enhancing the capabilities of swarm intelligence.",26732688,AI
10.3390/ai5040111,Enhancing Medical Image Classification with Unified Model Agnostic Computation and Explainable AI,"Background: Advances in medical image classification have recently benefited from general augmentation techniques. However, these methods often fall short in performance and interpretability. Objective: This paper applies the Unified Model Agnostic Computation (UMAC) framework specifically to the medical domain to demonstrate its utility in this critical area. Methods: UMAC is a model-agnostic methodology designed to develop machine learning approaches that integrate seamlessly with various paradigms, including self-supervised, semi-supervised, and supervised learning. By unifying and standardizing computational models and algorithms, UMAC ensures adaptability across different data types and computational environments while incorporating state-of-the-art methodologies. In this study, we integrate UMAC as a plug-and-play module within convolutional neural networks (CNNs) and Transformer architectures, enabling the generation of high-quality representations even with minimal data. Results: Our experiments across nine diverse 2D medical image datasets show that UMAC consistently outperforms traditional data augmentation methods, achieving a 1.89% improvement in classification accuracy. Conclusions: Additionally, by incorporating explainable AI (XAI) techniques, we enhance model transparency and reliability in decision-making. This study highlights UMAC’s potential as a powerful tool for improving both the performance and interpretability of medical image classification models.",26732688,AI
10.3389/frai.2024.1477447,Predicting patient reported outcome measures: a scoping review for the artificial intelligence-guided patient preference predictor,"Background: The algorithmic patient preference predictor (PPP) has been proposed to aid in decision making for incapacitated patients in the absence of advanced directives. Ethical and legal challenges aside, multiple practical barriers exist for building a personalized PPP. Here, we examine previous work using machine learning to predict patient reported outcome measures (PROMs) for capacitated patients undergoing diverse procedures, therapies, and life events. Demonstrating robust performance in predicting PROMs for capacitated patients could suggest opportunities for developing a model tailored to incapacitated ones.Methods: We performed a scoping review of PubMed, Embase, and Scopus using the PRISMA-ScR guidelines to capture studies using machine learning to predict PROMs following a medical event alongside qualitative studies exploring a theoretical PPP.Results: Sixty-eight studies used machine learning to evaluate PROMs; an additional 20 studies focused on a theoretical PPP. For PROMs, orthopedic surgeries (n = 33) and spinal surgeries (n = 12) were the most common medical event. Studies used demographic (n = 30), pre-event PROMs (n = 52), comorbidities (n = 29), social determinants of health (n = 30), and intraoperative variables (n = 124) as predictors. Thirty-four different PROMs were used as the target outcome. Evaluation metrics varied by task, but performance was overall poor to moderate for the best reported scores. In models that used feature importance, pre-event PROMs were the most predictive of post-event PROMs. Fairness assessments were rare (n = 6). These findings reinforce the necessity of the integrating patient values and preferences, beyond demographic factors, to improve the development of personalized PPP models for incapacitated patients.Conclusion: The primary objective of a PPP is to estimate patient-reported quality of life following an intervention. Use of machine learning to predict PROMs for capacitated patients introduces challenges and opportunities for building a personalized PPP for incapacitated patients without advanced directives.",26248212,AI
10.1007/s44196-024-00670-x,ExAq-MSPP: An Energy-Efficient Mobile Sink Path Planning Using Extended Aquila Optimization Algorithm,"Wireless sensor networks play a crucial role in gathering data from remote or hard-to-reach locations, enabling real-time monitoring and decision-making in a wide range of industries and applications. The mobile sink path planning (MSPP) enables mobile sinks (e.g., drones or rovers) to navigate through the environment, collecting data from different sensor nodes, ensuring comprehensive coverage, and adaptively addressing changing conditions. Still, the energy-efficient routing with minimal delay is the challenging aspect. This research focuses on improving data gathering in wireless sensor networks by introducing an efficient routing protocol. In this proposed protocol, sensor nodes are initially deployed using Voronoi diagrams to ensure uniform network coverage. The network is then divided into clusters using the low-energy adaptive clustering hierarchy (LEACH) algorithm for energy-efficient routing. To optimize the path planning of a mobile sink for data collection, we introduce the extended Aquila (ExAq) optimization algorithm, which uses a multi-objective fitness function considering factors such as delay, residual energy, link quality, priority, and distance. Simulation results demonstrate the effectiveness of the proposed ExAq-MSPP protocol in terms of reduced delay, improved network lifetime, higher packet delivery ratio, enhanced residual energy, and increased throughput compared to existing protocols with the values of 1.169, 99.857, 99.920, 0.997, and 255.306, respectively. Thus, the energy-efficient routing and optimizing path planning for mobile sinks, the proposed ExAq-MSPP protocol can extend network lifetime, increase data accuracy, and provide more robust performance under changing environmental conditions.",18756883,AI
10.3389/fpsyg.2024.1485278,The sorrow comes when I’m having moments of joy—experiences of parenting a live baby following a previous stillbirth: an interpretative phenomenological analysis,"Stillbirth can lead to complex and varied psychological outcomes for parents. Many choose to have another pregnancy following a stillbirth; however, little is known about the experience of parenting and bonding with the subsequent baby. Couples, who were the biological parents of a stillborn baby and at least one subsequent live baby aged under five, were recruited and interviewed individually. Data were analysed using interpretative phrenomenological analysis. Twelve individual interviews (of six couples) were conducted and four themes with nine subthemes were developed. Theme 1 “Back to the starting line: pregnancy as a means to an end” captured parents’ desire to bring a live baby home with pregnancy being experienced alongside fear, trauma, and grief. Theme 2 “Reality hits” encapsulated the experience of arriving home and feeling overwhelmed by the demands of a new-born baby. Theme 3 “Being a living and loss parent” captured the experience of being a parent to both a living and non-living baby with conflicting emotions. Theme 4 “Protection: ‘I need him there next to me, so I know he’s alive’” represented the fear some parents felt when parenting their live baby and included parents’ strategies to manage this anxiety. This study presents novel insight into the complexities of being a parent to a stillborn baby in tandem with a live baby, with difficulties arising in bonding, and managing emotional distress linked to trauma and grief. Potential implications for care includes a need for increased training for professionals providing postnatal care.",16641078,PSYCHOLOGY
10.3390/cancers16223773,The Efficacy of a Lower Dose of Everolimus in Patients with Advanced Neuroendocrine Tumors,"Background: Everolimus at 10 mg daily is approved to treat patients with advanced grade 1/2 neuroendocrine tumors (NETs), although it may lead to significant toxicity. Grade 3 or higher drug-related adverse events and drug discontinuation occur in approximately one-fourth of cases. However, phase I trials have demonstrated that doses from 5 mg daily efficiently inhibit NET cell signaling. Objectives and Methods: This multicenter retrospective study compared the time to treatment failure (TTF) in patients with NETs who received a mean daily dose of 7–10 mg (higher dose [HD]) or ≤6 mg (lower dose [LD]) of everolimus. Results: Ninety-two patients were included: 74 (80%) in the HD group and 18 (20%) in the LD group. At a median follow-up of 4.2 years, the median time to treatment failure (TTF) was 9.2 months for the HD and 7.2 months for the LD groups (p = 0.85). The TTF did not significantly differ between the LD and the HD groups (HR: 1.24; 95% CI: 0.68–2.25; p = 0.47), even after adjusting for age at treatment initiation, the NET grade, and the treatment line. Conclusion: Everolimus doses from 5 to 6 mg/day seem to be equally as effective as higher doses, but lower doses are potentially associated with less toxicity and lower costs. These findings support validation through a randomized clinical trial.",20726694,ONCOLOGY
10.3389/frai.2024.1453847,Inpainting of damaged temple murals using edge- and line-guided diffusion patch GAN,"Mural paintings are vital cultural expressions, enriching our lives by beautifying spaces, conveying messages, telling stories, and evoking emotions. Ancient temple murals degrade over time due to natural aging, physical damage, etc. Preserving these cultural treasures is challenging. Image inpainting is often used for digital restoration, but existing methods typically overlook naturally degraded areas, using randomly generated binary masks or small, narrow regions for repair. This study proposes a novel architecture to reconstruct large areas of naturally degraded murals, maintaining intrinsic details, avoiding color bias, and preserving artistic excellence. The architecture integrates generative adversarial networks (GANs) and the diffusion model, including a whole structure formation network (WSFN), a semantic color network (SCN), and a diffusion mixture distribution (DIMD) discriminator. The WSFN uses the original image, a line drawing, and an edge map to capture mural details, which are then texturally inpainted in the SCN using gated convolution for enhanced results. Special attention is given to globally extending the receptive field for large-area inpainting. The model is evaluated using custom-degraded mural images collected from Tamil Nadu temples. Quantitative analysis showed superior results than state-of-the-art methods, with SSIM, MSE, PSNR, and LPIPS values of 0.8853, 0.0021, 29.8826, and 0.0426, respectively.",26248212,AI
10.1186/s40594-024-00516-0,Employing automatic analysis tools aligned to learning progressions to assess knowledge application and support learning in STEM,"We discuss transforming STEM education using three aspects: learning progressions (LPs), constructed response performance assessments, and artificial intelligence (AI). Using LPs to inform instruction, curriculum, and assessment design helps foster students’ ability to apply content and practices to explain phenomena, which reflects deeper science understanding. To measure the progress along these LPs, performance assessments combining elements of disciplinary ideas, crosscutting concepts and practices are needed. However, these tasks are time-consuming and expensive to score and provide feedback for. Artificial intelligence (AI) allows to validate the LPs and evaluate performance assessments for many students quickly and efficiently. The evaluation provides a report describing student progress along LP and the supports needed to attain a higher LP level. We suggest using unsupervised, semi-supervised ML and generative AI (GAI) at early LP validation stages to identify relevant proficiency patterns and start building an LP. We further suggest employing supervised ML and GAI for developing targeted LP-aligned performance assessment for more accurate performance diagnosis at advanced LP validation stages. Finally, we discuss employing AI for designing automatic feedback systems for providing personalized feedback to students and helping teachers implement LP-based learning. We discuss the challenges of realizing these tasks and propose future research avenues.",21967822,EDUCATION
10.3390/educsci14111233,Assessing Student Teachers’ Motivation and Learning Strategies in Digital Inquiry-Based Learning,"Over the past two decades, teachers have adopted several teaching and learning strategies for motivating students to learn chemistry. Learning chemistry in context enables students to develop richer crosscutting learning experiences relevant to contributing to solving problems. A qualitative case study method was adopted to examine student teachers’ experiences in digital inquiry-based learning. Questionnaires with closed-ended and open-ended questions were used to evaluate student teachers’ motivational orientations and learning strategies during a general chemistry course for one month. The results show that student teachers utilized varied perspectives such as self-efficacy, task value, and intrinsic goals to elaborate their learning for knowledge construction and application when performing collaborative tasks. The approach enables students to receive maximum support and feedback from instructors who use pedagogical styles to self-direct them during class discussions, which enhances their active participation in learning with the learning materials. The findings provide a practical insight into instructional strategies in delivering chemistry concepts when students are motivated to use and adopt varied learning strategies.",22277102,EDUCATION
10.1186/s40359-024-02139-0,The effectiveness of multimedia mental health self-care program based on cyber space on the mental health of infertile women: a randomized controlled trial,"So far, some training interventions have been carried out to improve the mental health in women with infertility, but designing the need and evidence-based, as well as multimedia mental health self-care interventions based on cyber space has received less attention. Due to the spread of the internet and the role of self-care in improving mental disorders, this study was conducted to evaluate the effectiveness of the multimedia mental health self-care program on mental health and to assess the users' satisfaction. This study is a randomized controlled trial with pretest–posttest follow-up design. The sample was selected using a convenience sampling method (n = 90). The random number function was used to assign random numbers. The research instruments include a demographic, psychological Well-being, depression, anxiety, perceived stress, fertility problems and satisfaction with training questionnaire. Six weeks of intervention was conducted following the pre-test and the link of each session's content was sent to the participants, based on the training schedule, through Eitaa Messenger. The post-test and follow-up were conducted 1 week and 1 month post intervention. The data were analyzed using independent t-test and repeated measures ANOVA. A statistically significant difference was observed between the intervention and control group in the mean score of psychological well-being, perceived stress and infertility stress 1 week and 1 month post intervention and in the mean score of depression and anxiety 1 month post intervention. The intervention group scored higher than the control in psychological well-being but lower in perceived stress, depression, anxiety and infertility stress. The intervention had a positive effect and reduced the score of perceived stress, depression, anxiety and infertility in the intervention group over time. The score reduction continued until the follow-up stage. No significant time-interaction effect was observed on psychological well-being and on the control group. Satisfaction with the program and subscales was desirable. This program could significantly reduce the depression, anxiety, perceived stress and infertility stress and desirable satisfaction with the program was observed among users. This program can be used in designing the experimental and therapeutic interventions to improve mental-health self-care behaviors. RCT Registry: Iranian Registry of Clinical Trials; RCT registration number: IRCT20210526051410N1; Registration date: 2022–11-06. Last update: 2023–01-28",20507283,PSYCHOLOGY
10.3390/ai5040116,SIBILA: Automated Machine-Learning-Based Development of Interpretable Machine-Learning Models on High-Performance Computing Platforms,"As machine learning (ML) transforms industries, the need for efficient model development tools using high-performance computing (HPC) and ensuring interpretability is crucial. This paper presents SIBILA, an AutoML approach designed for HPC environments, focusing on the interpretation of ML models. SIBILA simplifies model development by allowing users to set objectives and preferences before automating the search for optimal ML pipelines. Unlike traditional AutoML frameworks, SIBILA is specifically designed to exploit the computational capabilities of HPC platforms, thereby accelerating the model search and evaluation phases. The emphasis on interpretability is particularly crucial when model transparency is mandated by regulations or desired for stakeholder understanding. SIBILA has been validated in different tasks with public datasets. The results demonstrate that SIBILA consistently produces models with competitive accuracy while significantly reducing computational overhead. This makes it an ideal choice for practitioners seeking efficient and transparent ML solutions on HPC infrastructures. SIBILA is a major advancement in AutoML, addressing the rising demand for explainable ML models on HPC platforms. Its integration of interpretability constraints alongside automated model development processes marks a substantial step forward in bridging the gap between computational efficiency and model transparency in ML applications. The tool is available as a web service at no charge.",26732688,AI
10.3390/ai5040117,Evaluating Anomaly Explanations Using Ground Truth,"The widespread use of machine and deep learning algorithms for anomaly detection has created a critical need for robust explanations that can identify the features contributing to anomalies. However, effective evaluation methodologies for anomaly explanations are currently lacking, especially those that compare the explanations against the true underlying causes, or ground truth. This paper aims to address this gap by introducing a rigorous, ground-truth-based framework for evaluating anomaly explanation methods, which enables the assessment of explanation correctness and robustness—key factors for actionable insights in anomaly detection. To achieve this, we present an innovative benchmark dataset of digital circuit truth tables with model-based anomalies, accompanied by local ground truth explanations. These explanations were generated using a novel algorithm designed to accurately identify influential features within each anomaly. Additionally, we propose an evaluation methodology based on correctness and robustness metrics, specifically tailored to quantify the reliability of anomaly explanations. This dataset and evaluation framework are publicly available to facilitate further research and standardize evaluation practices. Our experiments demonstrate the utility of this dataset and methodology by evaluating common model-agnostic explanation methods in an anomaly detection context. The results highlight the importance of ground-truth-based evaluation for reliable and interpretable anomaly explanations, advancing both theory and practical applications in explainable AI. This work establishes a foundation for rigorous, evidence-based assessments of anomaly explanations, fostering greater transparency and trust in AI-driven anomaly detection systems.",26732688,AI
10.3389/fpsyg.2024.1408929,Speech characteristics that differentiate stuttering and cluttering in Japanese speakers,"Background: Cluttering is a speech disorder distinct from stuttering. Despite this distinction, there is no established method to clearly differentiate the two disorders. This study aimed to use objective criteria to differentiate cluttering from stuttering in Japanese speakers.Methods: Participants were 32 consecutive native-Japanese speakers who visited the Keio University Hospital between July 2020 and January 2023 with a chief complaint of speech disfluency. One physician and two speech-language-hearing therapists concurred on a stuttering or cluttering diagnosis of the 32 patients based on recordings of the Kitsuon kensa-ho test. The frequencies of stuttering-like disfluencies (SDF) and normal disfluencies (NDF) were calculated from the Kitsuon kensa-ho, and the ratio of disfluencies (RDF) was calculated as the ratio of SDF to NDF. Differences between the cluttering and stuttering groups in the RDF and the mean articulatory rate (MAR) for oral reading and a monologue task were tested using the Mann–Whitney U test. ROC curves were used to determine the sensitivity and specificity that well-distinguished subjects with cluttering from those with stuttering; the experts’ diagnosis was the gold standard.Results: Of the 32 participants, 12 (38%) were diagnosed with cluttering and 20 (62%) with stuttering. The cluttering and stuttering groups were comparable in demographic characteristics. The RDF on monologue task had the highest sensitivity in diagnosing cluttering, and the MAR on monologue task had the highest specificity. Adopting provisional criteria of a monologue RDF greater than 1.2 and a monologue MAR greater than 7.5 produced a sensitivity of 0.92 and a specificity of 0.95.Conclusion: We conclude that combining monologue RDF and monologue MAR well-distinguished cluttering from stuttering. This method provides new objective diagnostic criteria, which can aid clinicians, therapists, and basic researchers.",16641078,PSYCHOLOGY
10.3390/ai5040118,Learning and Evolution: Factors Influencing an Effective Combination,"(1) Background: The mutual relationship between evolution and learning is a controversial argument among the artificial intelligence and neuro-evolution communities. After more than three decades, there is still no common agreement on the matter. (2) Methods: In this paper, the author investigates whether combining learning and evolution permits finding better solutions than those discovered by evolution alone. In further detail, the author presents a series of empirical studies that highlight some specific conditions determining the success of such combination. Results are obtained in five qualitatively different domains: (i) the 5-bit parity task, (ii) the double-pole balancing problem, (iii) the Rastrigin, Rosenbrock and Sphere optimization functions, (iv) a robot foraging task and (v) a social foraging problem. Moreover, the first three tasks represent benchmark problems in the field of evolutionary computation. (3) Results and discussion: The outcomes indicate that the effect of learning on evolution depends on the nature of the problem. Specifically, when the problem implies limited or absent agent–environment conditions, learning is beneficial for evolution, especially with the introduction of noise during the learning and selection processes. Conversely, when agents are embodied and actively interact with the environment, learning does not provide advantages, and the addition of noise is detrimental. Finally, the absence of stochasticity in the experienced conditions is paramount for the effectiveness of the combination. Furthermore, the length of the learning process must be fine-tuned based on the considered task.",26732688,AI
10.3390/ai5040119,"Machine Learning in Active Power Filters: Advantages, Limitations, and Future Directions","Machine learning (ML) techniques have permeated various domains, offering intelligent solutions to complex problems. ML has been increasingly explored for applications in active power filters (APFs) due to its potential to enhance harmonic compensation, reference signal generation, filter control optimization, and fault detection and diagnosis. This paper reviews the most recent applications of ML in APFs, highlighting their abilities to adapt to nonlinear load conditions, improve fault detection and classification accuracy, and optimize system performance in real time. However, this paper also highlights several limitations of these methods, such as the high computational complexity, the need for extensive training data, and challenges with real-time deployment in distributed power systems. For example, the marginal improvements in total harmonic distortion (THD) achieved by ML-based methods often do not justify the increased computational overhead compared to traditional control methods. This review then suggests future research directions to overcome these limitations, including lightweight ML models for faster and more efficient control, federated learning for decentralized optimization, and digital twins for real-time system monitoring. While traditional methods remain effective, ML-based solutions have the potential to significantly enhance APF performance in future power systems.",26732688,AI
10.3389/frai.2024.1457299,The impact of AI on education and careers: What do students think?,"Introduction: Providing one-on-one support to large cohorts is challenging, yet emerging AI technologies show promise in bridging the gap between the support students want and what educators can provide. They offer students a way to engage with their course material in a way that feels fluent and instinctive. Whilst educators may have views on the appropriates for AI, the tools themselves, as well as the novel ways in which they can be used, are continually changing.Methods: The aim of this study was to probe students' familiarity with AI tools, their views on its current uses, their understanding of universities' AI policies, and finally their impressions of its importance, both to their degree and their future careers. We surveyed 453 psychology and sport science students across two institutions in the UK, predominantly those in the first and second year of undergraduate study, and conducted a series of five focus groups to explore the emerging themes of the survey in more detail.Results: Our results showed a wide range of responses in terms of students' familiarity with the tools and what they believe AI tools could and should not be used for. Most students emphasized the importance of understanding how AI tools function and their potential applications in both their academic studies and future careers. The results indicated a strong desire among students to learn more about AI technologies. Furthermore, there was a significant interest in receiving dedicated support for integrating these tools into their coursework, driven by the belief that such skills will be sought after by future employers. However, most students were not familiar with their university's published AI policies.Discussion: This research on pedagogical methods supports a broader long-term ambition to better understand and improve our teaching, learning, and student engagement through the adoption of AI and the effective use of technology and suggests a need for a more comprehensive approach to communicating these important guidelines on an on-going basis, especially as the tools and guidelines evolve.",26248212,AI
10.1007/s00432-024-06009-5,CT-defined muscle density as a prognostic factor in multiple myeloma undergoing autologous stem cell therapy: a retrospective single center study,"Purpose: Skeletal muscle quality assessment can be performed by cross-sectional imaging. Skeletal muscle density (SMD) identified to be of prognostic relevance of several clinically outcomes in patients with hematological diseases. The purpose of the present study was to establish the effect of SMD on overall survival (OS) and progression-free survival (PFS) in patients with multiple myeloma (MM). Methods: All patients with MM were retrospectively analyzed between 2009 and 2019. 127 patients were included into the analysis. Whole-body computed tomography (CT) was used to calculate skeletal muscle index (SMI), SMD, albumin-gauge score and intramuscular adipose tissue content (IMAC). Results: Overall, 28 patients (22.0%) of the patient sample died. In the discrimination analysis muscle density was higher in non-survivors compared to survivors (mean 30.8 ± 12.5 versus 24.1 ± 15.8, p = 0.03) and IMAC was lower in non-survivors (− 0.66 ± 1.8 versus − 0.25 ± 0.21, p = 0.01). These differences, however, were not demonstrated in the logistic regression analysis, which could not show prognostic relevance for the investigated muscle density parameters on PFS or OS. Conclusion: CT-defined muscle density parameters have no prognostic relevance on survival in patients with MM undergoing autologous stem cell therapy, which was demonstrated in a comprehensive analysis. These results corroborate previous smaller studies that body composition might have a limited role in this tumor entity.",14321335,ONCOLOGY
10.1186/s40359-024-02190-x,The effect of questioning gender stereotype threat on girl’s standing long jump performance,"Over the past few years, the sport psychology literature has established that gender stereotype threat (ST) is one of the factors that can impair girls’ performance. However, few studies have attempted to annihilate these negative effects. The purpose of the current study was to investigate whether questioning gender ST can mitigate the classical decline in girls’ standing long jump (SLJ) performance. The participants were 120 girls (Mage = 10.74 ± 0.85 years), selected through convenience sampling and randomly assigned to three groups: the gender ST group (n = 40), the questioning group (n = 40), and the control group (n = 40). For all groups, baseline performance (i.e., SLJ) was measured by a female researcher following a warm-up period. In the experimental phase, the control group repeated the baseline conditions; the gender ST group completed the same test but was evaluated by a male examiner (i.e., implicit stereotype induction), while participants in the questioning group were assessed after receiving questioning statements while performing the task in front of a male examiner. The results of the present study showed that the induction of a gender ST leads to a decrease in SLJ in girls. Additionally, if these inducing conditions of gender ST are accompanied by a questioning condition, the negative effects of gender ST can be reduced, and SLJ in girls does not decline. Based on our findings, this intervention is recommended as a simple, inexpensive, and quick solution for mitigating the negative effects of gender ST on girl’s motor performance.",20507283,PSYCHOLOGY
10.1186/s40359-024-02193-8,The effects of digital CBT intervention on attentional bias and sleep quality of poor sleepers with insomnia symptoms,"Attentional bias is a salient manifestation of insomnia. Digital cognitive therapy for insomnia (dCBT-I) has been validated as effective in alleviating this cognitive dysfunction. However, the effect of dCBT-I on attentional bias among Chinese individuals with insomnia remains undiscussed. This research sought to investigate this effect via a pictorial dot-probe task. In Study 1, the pattern of attentional bias among poor sleepers (N = 52) and normal sleepers (N = 56) was assessed by the dot-probe task. In study 2, dCBT-I and conventional education were received by the experimental group (N = 42) and control group (N = 25), respectively. The dot-probe tasks and sleep quality assessments were completed at baseline and post-test. The results of Study 1 indicated that poor sleepers exhibited significant attentional bias, characterized by increased attentional vigilance. Compared to normal sleepers, they showed heightened attentional vigilance toward sleep-related cues. The results of Study 2 showed that both dCBT-I and conventional education led to improvements in PSQI scores. However, only dCBT-I training alleviated attentional vigilance toward sleep-related cues. Additionally, dCBT-I was uniquely effective in reducing feelings of fatigue. Poor sleepers had a significant attentional bias, marked by heightened vigilance toward sleep-related cues. Digital CBT-I effectively reduced attentional vigilance and fatigue, suggesting that dCBT-I targets the cognitive distortions associated with insomnia. ChiCTR2100053172 (registered 13/11/2021).",20507283,PSYCHOLOGY
10.3390/ejihpe14110192,Examining the Factor Structure and Validity of the Depression Anxiety Stress Scale-21,"Background: The prevalence of mental health disorders calls for valid and reliable instruments that are easy to administer and assess for clinicians and researchers. The Depression Anxiety Stress Scale-21 (DASS-21) is a commonly used instrument to assess psychological distress; however, model fit and internal reliability issues have been reported. Our objective was to assess the factorial and structural validity of the DASS-21. Methods: A confirmatory factor analysis (CFA) was conducted on the full sample (n = 1036) to assess the proposed three-factor DASS-21 using a priori cut-off values. Because model fit indices were not met, an exploratory factor analysis (EFA) was conducted to identify a parsimonious model. The resulting three-factor structure (i.e., DASS-9) was then assessed using CFA and multigroup invariance testing procedures. Results: The proposed three-factor DASS-21 did not meet model fit criteria. The DASS-9 did meet recommended model fit criteria and was invariant between sex, injury status, mental health diagnosis, and activity level groups. Statistically different group means were found between mental health diagnosis and activity level groups, while no differences between sex or injury status groups were found. Conclusions: The current study provides support to use a condensed DASS-21 instrument, such as the DASS-9. Future research is necessary to establish the DASS-9 prior to its adoption in research and clinical practice. Additionally, there is a need to identify and review all condensed versions of the DASS-21, so individuals know which instrument can be used for clinical or research purposes.",22549625,PSYCHOLOGY
10.1186/s40359-024-02200-y,Page: investigating the predictors of general psychological help seeking intention among people who attempted suicide by using structural equation modeling,"The aim of this study was to determine the role of suicide literacy, suicide stigma, perceived social support, and attitudes toward seeking professional psychological help (ATSPPH) in predicting general help-seeking intention among individuals who have attempted suicide by structural equation modeling. This cross-sectional study was conducted among 462 people who were referred to the hospital due to suicide attempt in one of the cities of eastern Iran in 2023. The sampling method in this study was consecutive sampling. The Pearson correlation, One-way ANOVA, and Independent-samples t-test were used to analyze data by SPSS software. Also, AMOS software was used for conducting structural equation modeling and checking the standardized direct effects and standardized indirect effects between variables. Only 0.9% (n = 4) of participants answered correctly more than 17 questions regarding suicide literacy. The structural equation modeling (SEM) results showed that suicide literacy, suicide stigma, perceived social support, and ATSPPH predicted 51% variance in the general help-seeking intention (R2 = 0.51, PGFI = 0.607, PCFI = 0.568, RMSEA = 0.064). The variables of suicide literacy (estimate total effect = 0.615), ATSPPH (estimate total effect = 0.368), perceived social support (estimate total effect = 0.123), and suicide stigma (estimate total effect = 0.033) had the greatest impact in predicting the general help-seeking intention. The SEM results highlight the importance of paying more attention to suicide literacy, reducing suicide stigma, promoting social support, improving the positive attitude toward mental health services, encouraging people who have attempted suicide to seek psychological help, and finally preventing suicide attempt.",20507283,PSYCHOLOGY
10.3390/educsci14121292,Essential Elements for Implementing AI Tools in Elementary School: A Systematic Literature Review,"The global use of Artificial Intelligence (AI) has attracted considerable attention, and its integration into educational systems is a priority that warrants further exploration. In collaboration with UNESCO, numerous organizations have proposed parameters advocating for the inclusion of AI in basic education systems. A systematic literature review (SLR) was conducted to identify these parameters from the existing research. Although these parameters have been mentioned in some studies, they are generally not prioritized in the research landscape. AI tools are primarily used to support students, while teachers typically employ a pedagogical approach centered on in-class activities. Additionally, essential conditions related to research requirements and involvement from the private and third sectors showed consistent adherence across the examined studies. However, it was found that only 52% of the studies included an ethical declaration regarding the data collected by AI during research development, especially regarding studies involving children. This review provides a guide for educational communities looking to enhance pedagogical practices through AI integration into their educational environments, but who may be uncertain about where to begin. Questions related to AI modality selection, pedagogical relevance, ethical considerations, and procedural guidelines for integrating AI into curricula are addressed through the insights provided in this review.",22277102,EDUCATION
10.3390/ai5040121,"Advancing Healthcare: Intelligent Speech Technology for Transcription, Disease Diagnosis, and Interactive Control of Medical Equipment in Smart Hospitals","Intelligent Speech Technology (IST) is revolutionizing healthcare by enhancing transcription accuracy, disease diagnosis, and medical equipment control in smart hospital environments. This study introduces an innovative approach employing federated learning with Multi-Layer Perceptron (MLP) and Gated Recurrent Unit (GRU) neural networks to improve IST performance. Leveraging the “Medical Speech, Transcription, and Intent” dataset from Kaggle, comprising a variety of speech recordings and corresponding medical symptom labels, noise reduction was applied using a Wiener filter to improve audio quality. Feature extraction through MLP and sequence classification with GRU highlighted the model’s robustness and capacity for detailed medical understanding. The federated learning framework enabled collaborative model training across multiple hospital sites, preserving patient privacy by avoiding raw data exchange. This distributed approach allowed the model to learn from diverse, real-world data while ensuring compliance with strict data protection standards. Through rigorous five-fold cross-validation, the proposed Fed MLP-GRU model demonstrated an accuracy of 98.6%, with consistently high sensitivity and specificity, highlighting its reliable generalization across multiple test conditions. In real-time applications, the model effectively performed medical transcription, provided symptom-based diagnostic insights, and facilitated hands-free control of healthcare equipment, reducing contamination risks and enhancing workflow efficiency. These findings indicate that IST, powered by federated neural networks, can significantly improve healthcare delivery, accuracy in patient diagnosis, and operational efficiency in clinical settings. This research underscores the transformative potential of federated learning and advanced neural networks for addressing pressing challenges in modern healthcare and setting the stage for future innovations in intelligent medical technology.",26732688,AI
10.3390/ai5040122,Empirical Evaluation and Analysis of YOLO Models in Smart Transportation,"You Only Look Once (YOLO) and its variants have emerged as the most popular real-time object detection algorithms. They have been widely used in real-time smart transportation applications due to their low-latency detection and high accuracy. However, because of the diverse characteristics of YOLO models, selecting the optimal model according to various applications and environments in smart transportation is critical. In this article, we conduct an empirical evaluation and analysis study for most YOLO versions to assess their performance in smart transportation. To achieve this, we first measure the average precision of YOLO models across multiple datasets (i.e., COCO and PASCAL VOC). Second, we analyze the performance of YOLO models on multiple object categories within each dataset, focusing on classes relevant to road transportation such as those commonly used in smart transportation applications. Third, multiple Intersection over Union (IoU) thresholds are considered in our performance measurement and analysis. By examining the performance of various YOLO models across datasets, IoU thresholds, and object classes, we make six observations on these three aspects while aiming to identify optimal models for road transportation scenarios. It was found that YOLOv5 and YOLOv8 outperform other models in all three aspects due to their novel performance features. For instance, YOLOv5 achieves stable performance thanks to its cross-stage partial darknet-53 (CSPDarknet53) backbone, auto-anchor mechanism, and efficient loss functions including IoU loss, complete IoU loss, focal loss, gradient harmonizing mechanism loss. Similarly, YOLOv8 outperforms others with its upgraded CSPDarknet53 backbone, anchor-free mechanism, and efficient loss functions like complete IoU loss and distribution focal loss.",26732688,AI
10.3390/ejihpe14120194,Negative Association Between Schizophrenia and Subsequent Cancer Diagnoses—A Retrospective Cohort Study from Germany,"Background: Since previous studies have reported contradictory findings regarding the relationship between schizophrenia and cancer, we evaluated the association between schizophrenia and cancer diagnoses. Methods: In this retrospective cohort study, the IQVIA Disease Analyzer database was utilized to examine the incidence of cancer among patients aged over 18 years diagnosed with schizophrenia in German general practices from 2005 to 2022. Patients with schizophrenia were compared with those without the condition, with adjustments made for age, sex, index year of diagnosis, average annual practitioners visit frequency, and comorbidity. Kaplan–Meier curves were used to analyze the 10-year cumulative incidence of schizophrenia and cancer in total amongst patients with and without schizophrenia. Univariate Cox regression analysis was performed to calculate Hazard Ratios (HR) of cancer risk and their 95% confidence intervals (CI) of cancer in total and of specific cancer types. Results: Patients with schizophrenia (N = 13.711) had a lower incidence of cancer diagnosis compared to those without (N = 68.555). Specifically, 10.4% of patients with schizophrenia and 12.5% of patients without the condition were diagnosed with cancer (p < 0.001). Cox regression analysis showed a significant association between schizophrenia and subsequent cancer in the total population (HR: 0.82; 95% CI: 0.76–0.90), and among men (HR: 0.70; 95% CI: 0.61–0.80), but not among women (HR: 0.94, 95% CI: 0.84–1.04). Analyses stratified by cancer type and sex revealed a strong and significant association between schizophrenia and a decreased risk of prostate cancer in men (HR: 0.38; 95% CI: 0.24–0.61). Furthermore, there was also a negative association between schizophrenia and colorectal cancer risk in men, but statistical significance was not reached (HR: 0.58; 95% CI: 0.37–0.93). Conclusions: This study demonstrates negative associations between schizophrenia and subsequent cancer, and more specifically in men for prostate and colorectal cancer. However, further research is required to explore the underlying reasons for these associations.",22549625,PSYCHOLOGY
10.3389/frai.2024.1493566,Exploring the utilization and deficiencies of Generative Artificial Intelligence in students’ cognitive and emotional needs: a systematic mini-review,"Despite advances in educational technology, the specific ways in which Generative Artificial Intelligence (GAI) and Large Language Models cater to learners’ nuanced cognitive and emotional needs are not fully understood. This mini-review methodically describes GAI’s practical implementations and limitations in meeting these needs. It included journal and conference papers from 2019 to 2024, focusing on empirical studies that employ GAI tools in educational contexts while addressing their practical utility and ethical considerations. The selection criteria excluded non-English studies, non-empirical research, and works published before 2019. From the dataset obtained from Scopus and Web of Science as of June 18, 2024, four significant studies were reviewed. These studies involved tools like ChatGPT and emphasized their effectiveness in boosting student engagement and emotional regulation through interactive learning environments with instant feedback. Nonetheless, the review reveals substantial deficiencies in GAI’s capacity to promote critical thinking and maintain response accuracy, potentially leading to learner confusion. Moreover, the ability of these tools to tailor learning experiences and offer emotional support remains limited, often not satisfying individual learner requirements. The findings from the included studies suggest limited generalizability beyond specific GAI versions, with studies being cross-sectional and involving small participant pools. Practical implications underscore the need to develop teaching strategies leveraging GAI to enhance critical thinking. There is also a need to improve the accuracy of GAI tools’ responses. Lastly, deep analysis of intervention approval is needed in cases where GAI does not meet acceptable error margins to mitigate potential negative impacts on learning experiences.",26248212,AI
10.1186/s40359-024-02197-4,Clinical decision making and moral distress among intensive care units nurses in Iran,"Intensive care units are often presented as environments where ethical issues are common and decisions can determine the life or death of patients, and these units have unique challenges due to critical health care. In these units, the relationship between the medical team and the patient’s relatives, their refusal of treatment, informed consent causes the nurses to have conflict in their decision making, therefore, this study aims to determine the level of clinical decision-making and moral distress and the relationship between them in intensive care units nurses. This cross-sectional study was conducted with a descriptive-analytical approach in 2023 in Gorgan city. The number of 198 nurses in the intensive care units of Gonbad Kavos hospitals in the north of Iran were investigated and evaluated using the Corley Moral Distress questionnaire (2002), and Laurie’s Clinical Decision questionnaire (2001) in 2023. Independent T-test and anova analysis of variance were used for bivariate analysis. The significance level in this study was considered 0.05. The results of the study showed that the mean and standard deviation of clinical decision making was 60.98 ± 10.25 (analytical-systematic level) and moral distress was 92.2 ± 23.61 (moderate level). There was a statistically significant relationship between clinical decision-making and nurses’ moral distress (P < 0.001 and r = 0.370). The moral distress score had a statistically significant relationship with marriage, employment status, education level, age, work experience and duration of employment in the special department. Also, the clinical decision score had a statistically significant relationship with employment status, education level, age and work experience. According to these results, it seems that more attention should be paid to the moral distress of nurses in intensive care units, and it is necessary to improve their decision-making towards intuitive interpretation, which is done by designing and compiling training programs and workshops for nurses can be done, so that we can provide optimal nursing services to the patients of this department.",20507283,PSYCHOLOGY
10.3390/cancers16233998,Prevalence of Abnormalities at Tandem Endoscopy in Patients Referred for Colorectal Cancer Screening/Surveillance Colonoscopy,"Introduction: Performing a tandem endoscopy and colonoscopy in selected individuals has advantages, such as the early detection of benign and/or precancerous foregut diseases; it is efficient, and it may allow added therapies. It may also have disadvantages, such as generating anxiety from false-positive screening, possible harm from further testing, and unproven cost-effectiveness. Aims: We aimed to examine the prevalence of foregut endoscopic and histologic abnormalities in subjects referred for screening/surveillance colonoscopy who also underwent a tandem endoscopy. We wanted to (1) assess implications for cancer detection, intervention, and surveillance of precancerous foregut abnormalities, (2) identify benign foregut lesions, and (3) generate data on the utilities of this tandem approach. Patients and Methods: A retrospective cohort study of consecutive subjects referred for screening or surveillance colonoscopy who also underwent an endoscopy. Based on national screening guidelines, responses to prompting questions, personal or family history, or other risk factors, subjects were assigned to tandem endoscopy with biopsies (modified Seattle and Sydney protocols), under one anesthesia. Results: Of the 1004 patients referred for colonoscopy, 317 (32%) underwent tandem endoscopy. There were 214 women and 103 men. There were 237 Whites, 16 Asians, 40 Blacks, and 24 Hispanics. Median age was 59 (range 19–85). At endoscopy, we identified actionable benign (45%) peptic, inflammatory, and H. pylori-related abnormalities, and premalignant findings (i.e., intestinal metaplasia, 27%, dysplasia, 2%, and cancer 0.9%), comparable to the premalignant (40.3%) and malignant (0.6%) colonoscopy yield. Conclusions: When implemented based on national screening guidelines, tandem EGD and colonoscopy combines Barrett’s esophagus and gastric cancer screening in one examination, and it has a high yield in a diverse US population.",20726694,ONCOLOGY
10.3390/ai5040124,Enhancing Traffic Accident Severity Prediction Using ResNet and SHAP for Interpretability,"Background/Objectives: This paper presents a Residual Neural Network (ResNet) based framework tailored for structured traffic accident data, aiming to improve accident severity prediction. The proposed model leverages residual learning to effectively model intricate relationships between numerical and categorical variables, resulting in a notable increase in prediction accuracy. Methods: A comparative analysis was performed with other Deep Learning (DL) architectures, including Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), Darknet, and Extreme Inception (Xception), showing superior performance of the proposed Resnet. Key factors influencing accident severity were identified, with Shapley Additive Explanations (SHAP) values helping to address the need for transparent and explainable Artificial Intelligence (AI) in critical decision-making areas. Results: The generalizability of the ResNet model was assessed by training it, initially, on a UK road accidents dataset and validating it on a distinct dataset from India. The model consistently demonstrated high predictive accuracy, underscoring its robustness across diverse contexts, despite regional differences. Conclusions: These results suggest that the adapted ResNet model could significantly enhance traffic safety evaluations and contribute to the formulation of more effective traffic management strategies.",26732688,AI
10.3389/fpsyg.2024.1390968,The risks of unconcern: low sensitivity to threat can have unfortunate consequences,"Each one of us is confronted with warnings of danger or threats to wellbeing in our everyday life, whether in the form of certain road signs, Public Service Announcements, ominous changes in bodily functioning, or cautionary tales heard from family or friends. There is great inter-individual variation in how people respond to such threats, with some people habitually tending to ignore or dismiss them, often to their peril. The first purpose of the present paper is to review several studies showing that individuals—most often men—who score very low on measures of trait anxiety are more likely to engage in behaviors that could jeopardize their physical wellbeing. The general hypothesis that is derived from that review is that when attention to everyday threats is chronically muted by way of a dispositional trait, the likelihood of proceeding down some dangerous path is increased. Those findings are then discussed within the broader context of personality theory to highlight the importance of recognizing the bipolarity of common traits. Here the case is made for replacing the term trait anxiety with the term threat sensitivity in order to capture the full breadth of this basic personality variable. A discussion of the neurobiological underpinnings of threat sensitivity is then presented with an emphasis on individual and sex differences in the workings of the defensive survival circuitry. Taken together, this paper has implications for two subfields within psychology. For the area of personality theory, this paper provides support for the adaptationist view with the argument that low threat sensitivity has both adaptive and maladaptive potential. For the area of health psychology, it is argued that some individuals who demonstrate a habitual tendency to neglect their physical wellbeing may be acting—at least in part—in accordance with their innate neurobiological constitution.",16641078,PSYCHOLOGY
10.3389/fpsyg.2024.1502199,Effect of match location on the playing style of teams coached by ‘Pep’ Guardiola,"Introduction: Analysis in football seeks to find the performance factors that bring teams closer to success.Methods: This study aims to analyze the playing styles of two teams managed by Pep Guardiola (F.C. Barcelona and Manchester City) based on match location (home or away). Two methods of analysis were used: descriptive statistics through chi-square tests to evaluate game characteristics and the polar coordinates technique to analyze the relationships between the different lines of each team (goalkeeper, defenders, midfielders, and forwards).Results: The results showed that F.C. Barcelona maintained a consistent playing style regardless of location, exhibiting significant differences only in actions that involved shots or header (p = 0.035), with better performance at home. In contrast, Manchester City displayed significantly different performance in action success (p < 0.001), level of play elaboration (p = 0.004), density (p = 0.033), duration (p = 0.036), and actions that included a shot (p = 0.001) depending on the location. Additionally, qualitative analyses revealed differences in the relationships among the team lines according to match location, with Manchester City displaying more variability in these interactions than F.C. Barcelona.Discussion: The study concludes that although Guardiola applies a consistent set of strategies, match location has a greater influence on Manchester City’s performance, suggesting that this team adjusts its playing style on the basis of contextual conditions. These findings highlight the importance of considering factors such as location when preparing tactics to increase the probability of success in elite football.",16641078,PSYCHOLOGY
10.3389/frai.2024.1427534,SkyMap: a generative graph model for GNN benchmarking,"Graph Neural Networks (GNNs) have gained considerable attention in recent years. Despite the surge in innovative GNN architecture designs, research heavily relies on the same 5-10 benchmark datasets for validation. To address this limitation, several generative graph models like ALBTER or GenCAT have emerged, aiming to fix this problem with synthetic graph datasets. However, these models often struggle to mirror the GNN performance of the original graphs. In this work, we present SkyMap, a generative model for labeled attributed graphs with a fine-grained control over graph topology and feature distribution parameters. We show that our model is able to consistently replicate the learnability of graphs on graph convolutional, attention, and isomorphism networks better (64% lower Wasserstein distance) than ALBTER and GenCAT. Further, we prove that by randomly sampling the input parameters of SkyMap, graph dataset constellations can be created that cover a large parametric space, hence making a significant stride in crafting synthetic datasets tailored for GNN evaluation and benchmarking, as we illustrate through a performance comparison between a GNN and a multilayer perceptron.",26248212,AI
10.3389/frai.2024.1463164,Sequence labeling via reinforcement learning with aggregate labels,"Sequence labeling is pervasive in natural language processing, encompassing tasks such as Named Entity Recognition, Question Answering, and Information Extraction. Traditionally, these tasks are addressed via supervised machine learning approaches. However, despite their success, these approaches are constrained by two key limitations: a common mismatch between the training and evaluation objective, and the resource-intensive acquisition of ground-truth token-level annotations. In this work, we introduce a novel reinforcement learning approach to sequence labeling that leverages aggregate annotations by counting entity mentions to generate feedback for training, thereby addressing the aforementioned limitations. We conduct experiments using various combinations of aggregate feedback and reward functions for comparison, focusing on Named Entity Recognition to validate our approach. The results suggest that sequence labeling can be learned from purely count-based labels, even at the sequence-level. Overall, this count-based method has the potential to significantly reduce annotation costs and variances, as counting entity mentions is more straightforward than determining exact boundaries.",26248212,AI
10.1186/s40359-024-02229-z,The relationship between perceived social support and social anxiety in Chongqing rural secondary school students: the chain mediating effect of core self-evaluation and shyness,"Adolescents in less economically developed areas are susceptible to social anxiety, so finding ways to effectively prevent and intervene in social anxiety could be a major step forward for poverty alleviation. However, little is known about the inner workings of social anxiety in this group. Exploring the risk and protective factors of social anxiety among adolescents in less developed rural areas is crucial for maintaining their mental health and improving their social adaptability. The purpose of this study is to explore the relationships among perceived social support, core self-evaluation, shyness and social anxiety among rural secondary school students and analyze the risk and protective factors of social anxiety. A total of 626 rural secondary school students are investigated with the Perceived Social Support Scale (PSSS), Core Self-Evaluation Scale (CSES), Shyness Scale (SS) and Social Avoidance and Distress Scale (SADS). Structural equation modeling is used to analyze the mediating effects of core self-evaluation and shyness. The results reveal that (1) the perceived social support and core self-evaluation of rural secondary school students are significantly negatively correlated with social anxiety, whereas their shyness is significantly positively correlated with social anxiety. There are significant gender differences in perceived social support, core self-evaluation, shyness and social anxiety. (2) There is a significant chain mediating effect of core self-evaluation and shyness between perceived social support and social anxiety, and the mediation model is cross-gender consistent. These results confirm that perceived social support and core self-evaluation are protective factors against social anxiety in rural secondary school students and that shyness is a risk factor for social anxiety. Moreover, perceived social support can indirectly affect social anxiety through core self-evaluation and shyness. Prevention and intervention of social anxiety can be carried out in three ways: improving the perceived ability of social support, enhancing positive self-evaluation, and reducing shyness and avoidance behaviors.",20507283,PSYCHOLOGY
10.3389/fpsyg.2024.1489997,Controlling the narrative: the relationship between narrative ability and executive functioning in children with developmental language disorder,"Children with developmental language disorder (DLD) experience problems in language comprehension and/or production. In particular, storytelling or narrative ability is often impaired, as this type of discourse involves all domains of language. These problems may lead to a lower quality of social interaction and mental health. Moreover, problems in oral narrative ability during early development have a negative effect on later literacy. However, telling a story involves more than language alone. Executive functioning is thought to play an important part in stimulating narrative ability, as linguistic utterances need to be planned in a temporal and causal order, and switching is needed between multiple characters and events in the story. Research has shown that children with DLD experience problems with executive functioning, independent of their language ability. Thus, the difficulties in storytelling may be caused by both impaired language and executive functioning, as both domains follow hierarchical developmental paths during the early childhood years. In this review, we discuss three components of narrative ability (comprehension, production of macrostructure and production of microstructure) and how they may be interconnected to the three core components of executive functioning (working memory, switching and inhibition) and attention. This review shows that updating and monitoring information in working memory plays an important part in all three components of narrative ability, across multiple studies. This result may give direction in the development of narrative assessment and intervention, and urge further research to disentangle the interplay between language and executive control in DLD.",16641078,PSYCHOLOGY
10.3390/ai5040128,From Language Models to Medical Diagnoses: Assessing the Potential of GPT-4 and GPT-3.5-Turbo in Digital Health,"Background: Large language models (LLMs) like GPT-3.5-Turbo and GPT-4 show potential to transform medical diagnostics through their linguistic and analytical capabilities. This study evaluates their diagnostic proficiency using English and German medical examination datasets. Methods: We analyzed 452 English and 637 German medical examination questions using GPT models. Performance metrics included broad and exact accuracy rates for primary and three-model generated guesses, with an analysis of performance against varying question difficulties based on student accuracy rates. Results: GPT-4 demonstrated superior performance, achieving up to 95.4% accuracy when considering approximate similarity in English datasets. While GPT-3.5-Turbo showed better results in English, GPT-4 maintained consistent performance across both languages. Question difficulty was correlated with diagnostic accuracy, particularly in German datasets. Conclusions: The study demonstrates GPT-4’s significant diagnostic capabilities and cross-linguistic flexibility, suggesting potential for clinical applications. However, further validation and ethical consideration are necessary before widespread implementation.",26732688,AI
10.1007/s44196-024-00696-1,Evaluation of Motorcycle Brands Using Multi-attribute Decision-Making Method Under Single-Valued Neutrosophic Cubic Hypersoft Set Environment,,18756883,AI
10.1007/s44196-024-00695-2,Efficient Prediction of Judicial Case Decisions Based on State Space Modeling,"With the rapid advancement of information technology and artificial intelligence, the digitization of legal texts has caused a swift increase in the volume of legal materials. Judges now face increased professional demands, larger information loads, and more complex case structures, which heightens their workload and demands. To enhance the quality and efficiency of judicial work and drive the modernization of the judicial system, the application of intelligent prediction models has become essential. This paper presents the MambaEffNet model, which integrates multiple modules such as Convolutional Neural Networks (CNN) and Multilayer Perceptrons (MLP). The core convolutional structure is improved using a state space model, and a multi-directional feature fusion structure is designed to enhance the performance of sequence feature extraction. Generative Adversarial Networks (GAN) are employed for data augmentation, to address the issue of missing features in judicial case predictions. The EfficientNetV2 architecture is used to optimize the kernel size and the expansion ratio of input and output channels. Experimental results demonstrate that the MambaEffNet model achieves a prediction accuracy of 92.05% on the Nigerian Supreme Court judgment dataset and performs excellently on other judicial datasets, significantly improving prediction accuracy and efficiency. Specifically, the MambaEffNet model increases the prediction accuracy for criminal and civil case judgments by 9.53% and 11.57%, respectively. Additionally, the model excels in handling long sequence data, effectively capturing key features and providing comprehensive decision support.",18756883,AI
10.1007/s44196-024-00630-5,Channel2DTransformer: A Multi-level Features Self-attention Fusion Module for Semantic Segmentation,"Semantic segmentation is a crucial technology for intelligent vehicles, enabling scene understanding in complex driving environments. However, complex real-world scenarios often contain diverse multi-scale objects, which bring challenges to the accurate semantic segmentation. To address this challenge, we propose a multi-level features self-attention fusion module called Channel2DTransformer. The module utilizes self-attention mechanisms to dynamically fuse multi-level features by computing self-attention weights between their channels, resulting in a consistent and comprehensive representation of scene features. We perform the module on the Cityscapes and NYUDepthV2 datasets, which contain a large number of multi-scale objects. The experimental results validate the positive contributions of the module in enhancing the semantic segmentation accuracy of multi-scale objects and improving the performance of semantic segmentation in complex scenes.",18756883,AI
10.1007/s44196-024-00694-3,Studying the Impact of Changing Consumer Behavior During Crisis Periods Through Store Classification,"Since customer behavior changes unpredictably during crisis periods such as pandemics, many sectors have been affected differently. The retail sector in particular has been one of the most affected sectors. Retail companies that could not determine the right strategies against customer behavior change were in a difficult situation, and some even had to close down. The inability of consumers to do physical shopping for reasons such as socializing, experiencing products and interacting during the pandemic process required an understanding of changing consumer needs. In this study, to determine the changes in customer purchasing behaviors during the pandemic period, using the sales data of a company operating in the women’s clothing sector and whose sales loss approached 50% during the pandemic period, separate stores were divided into clusters using machine learning methods for the pre-pandemic and pandemic period. The clusters formed were examined and the stores in different clusters were determined depending on customer purchasing behavior. The aim of the study is to ensure that the company segments its stores correctly to gain competitive advantage. Firms will be able to determine the right strategies against changing consumer behavior through a correct store segmentation. First, stores that do not belong to any classification group are clustered using unsupervised machine learning methods. No significant change was observed in the clusters formed before and during the pandemic. This indicated that the pandemic had a similar effect on all stores. Then, pre-pandemic, pandemic period and both periods data were analyzed using 7 different machine learning classification algorithms. The results obtained were compared. For all three analyses, the random forest algorithm gave the highest accuracy rate. The random forest algorithm with the highest accuracy was hybridized with 3 different classification algorithms. The hybrid model consisting of random forest and support vector machine gave the highest accuracy rate (90%) for the period including all data for store classification. Thanks to the hybrid model created with random forest and support vector machines, companies can be advantageous against other companies in the competitive environment by creating separate strategies for each store class.",18756883,AI
10.1007/s44196-024-00707-1,Correction: Artificial Intelligence in Aviation Safety: Systematic Review and Biometric Analysis,,18756883,AI
10.1007/s44196-024-00692-5,Deep Learning Algorithm for Optimized Sensor Data Fusion in Fault Diagnosis and Tolerance,"Environmental perception is one of the key technologies to realize autonomous vehicles. The fault diagnosis process involves identifying the fault that occurred or the cause of the out-of-control condition. Here, the major objective is to locate problems in detection by analysing previous data or sequential patterns of data that cause failure. This study evaluates the use of deep learning for improved sensor data fusion in fault identification and tolerance using the KITTI dataset. The input video from the dataset has been transformed to frames through median filtering. Next, feature extraction is applied to a preprocessed image, resulting in the fusion of sensor data. Data fusion is then carried out utilizing an enhanced RPN (region proposal network). The enhanced RPN also has a loss function (object detection loss, bounding box loss and target classification loss), an estimate of ROI and feature extraction network (FEN). Through the use of the COOT connected blue monkey optimization (CCBMO) model, the weight of the optimally enhanced RPN is established. Next, using global non-maximum suppression with both global and local confidence, fault identification and tolerance are carried out. From the analysis, it clearly shows that proposed method accomplished better results in terms of accuracy, precision and specificity of 97.78%, 93.76% and 93.43%, respectively, when compared with various conventional models with respect to diverse performance measures.",18756883,AI
10.1186/s40594-024-00520-4,"A decade of advancing development, diversity, engagement, and excellence in STEM education","From August 2014 to July 2024, the International Journal of STEM Education has completed ten full publication cycle years. In this editorial, I offer a brief reflection of the journal’s successful growth over the past decade. I also celebrate the collective achievements of all those involved and highlight the journal’s continued commitment to excellence, driven by the engagement of diverse researchers and readers from around the world.",21967822,EDUCATION
10.3389/feduc.2024.1376087,Extending access for all chemistry students with extended reality,"Equal access to instructor’s time and attention in chemistry classes and laboratories can be a barrier experienced by students from historically excluded groups. An instructor’s own biases will determine the nature of their interaction with students, and even well-meaning instructors can interact with students in slightly different ways, which might prevent certain students from having access to all the available instructional resources for the class. This is an additive problem, which may or may not be recognized in peer and student evaluations, and an issue that might escape self-reflection even in educators that are committed to diversity, inclusion, and justice. This issue conflates both actual and perceived biases, introducing a complex dynamic between instructor and student. Extended reality (XR) provides an avenue to generate materials that can be used to enhance or replace classroom instruction with a great degree of realism. In this paper we will discuss the implementation of a set of virtual reality (VR) organic chemistry labs. We will show that XR learning tools are by their very nature accessible and inclusive of a wide variety of students and will provide evidence from student reflections that shows that students from historically excluded groups find the XR content offered in our virtual reality labs more personal than in-person activities covering the same material.",2504284X,EDUCATION
10.3389/frai.2024.1502580,The effect of AI on pink marketing: the case of women’s purchasing behavior using mobile applications,"This research looks in detail at the dynamics of pink marketing and its effect on the purchase behavior of Saudi women through mobile applications, with an emphasis on Artificial Intelligence (AI) as a moderator. Furthermore, this study assesses the effects of customized pink marketing strategies – product, price, promotion, and place – on buying intentions and behaviors. A closed-ended questionnaire was adopted to measure constructs associated with women’s mobile app purchase behavior influenced by pink marketing and AI elements. Structural Equation Modeling (SEM) was the study tool used to examine how AI affects women’s consumer behavior and how it influences pink marketing. The results suggest that each component of the pink marketing mix significantly influences buying behavior, especially price and promotion. Additionally, AI has a significant moderating effect, improving the personalization and effectiveness of marketing activities. The results of this study highlight the essential role of AI in forming consumer engagement in the digital market, providing useful input for marketers who intend to target women in Saudi Arabia. This study complements the understanding of gender marketing in the digital era and provides a vision for the possibility of AI fundamentally changing traditional approaches.",26248212,AI
10.3389/feduc.2024.1465207,Examining the effect of AI-powered virtual-human training on STEM majors’ self-regulated learning behavior,"Introduction: Students pursuing science, technology, engineering, and math (STEM) majors often struggle with essential skills critical to their academic success and future careers. Traditional self-regulated learning (SRL) training programs, while effective, require significant time investments from both students and instructors, limiting their feasibility in large lecture-based STEM courses.Methods: This study investigates whether completion of three AI-powered virtual-human training modules—focused on planning, self-monitoring, and reflection—leads to increased use of corresponding MS Planner tools among STEM majors compared to a control group.Results: Results indicate that students who did not complete the first two training modules were less likely to use MS Planner features for planning and self-monitoring; however, the reflection module did not yield comparable results.Discussion: These findings highlight the potential of AI-powered virtual-human training as a scalable solution to enhance desirable learning behaviors among STEM majors, particularly in large and diverse classrooms. This research contributes to the understanding of effective interventions for fostering SRL behaviors in STEM education and suggests avenues for future refinement and implementation of digital training tools.",2504284X,EDUCATION
10.3389/frai.2024.1374323,Accuracy improvement in financial sanction screening: is natural language processing the solution?,"Sanction screening is a crucial banking compliance process that protects financial institutions from inadvertently engaging with internationally sanctioned individuals or organizations. Given the severe consequences, including financial crime risks and potential loss of banking licenses, effective execution is essential. One of the major challenges in this process is balancing the high rate of false positives, which exceed 90% and lead to inefficiencies due to increased human oversight, with the more critical issue of false negatives, which pose severe regulatory and financial risks by allowing sanctioned entities to go undetected. This study explores the use of Natural Language Processing (NLP) to enhance the accuracy of sanction screening, with a particular focus on reducing false negatives. Using an experimental approach, we evaluated a prototype NLP program on a dataset of sanctioned entities and transactions, assessing its performance in minimising false negatives and understanding its effect on false positives. Our findings demonstrate that while NLP significantly improves sensitivity by detecting more true positives, it also increases false positives, resulting in a trade-off between improved detection and reduced overall accuracy. Given the heightened risks associated with false negatives, this research emphasizes the importance of prioritizing their reduction. The study provides practical insights into how NLP can enhance sanction screening, while recognizing the need for ongoing adaptation to the dynamic nature of the field.",26248212,AI
10.3389/frai.2024.1482141,Toward explainable deep learning in healthcare through transition matrix and user-friendly features,"Modern artificial intelligence (AI) solutions often face challenges due to the “black box” nature of deep learning (DL) models, which limits their transparency and trustworthiness in critical medical applications. In this study, we propose and evaluate a scalable approach based on a transition matrix to enhance the interpretability of DL models in medical signal and image processing by translating complex model decisions into user-friendly and justifiable features for healthcare professionals. The criteria for choosing interpretable features were clearly defined, incorporating clinical guidelines and expert rules to align model outputs with established medical standards. The proposed approach was tested on two medical datasets: electrocardiography (ECG) for arrhythmia detection and magnetic resonance imaging (MRI) for heart disease classification. The performance of the DL models was compared with expert annotations using Cohen’s Kappa coefficient to assess agreement, achieving coefficients of 0.89 for the ECG dataset and 0.80 for the MRI dataset. These results demonstrate strong agreement, underscoring the reliability of the approach in providing accurate, understandable, and justifiable explanations of DL model decisions. The scalability of the approach suggests its potential applicability across various medical domains, enhancing the generalizability and utility of DL models in healthcare while addressing practical challenges and ethical considerations.",26248212,AI
10.3389/fpsyg.2024.1451431,Loss of empathy in stroke,"Background: Loss of empathy (LoE) is common among stroke survivors, yet often undiagnosed and thus untreated. LoE is related to the loss of a caring marital relationship, higher care burden and poorer quality of life in carers. The present study will evaluate the clinical and MRI correlates of LoE in a cohort of stroke survivors. The secondary objective is to describe the 12-month course of LoE.Methods: The current study is a prospective cohort study. We will recruit 246 subjects. Subjects and carers will receive a detailed assessment at a research clinic at 3, 9, and 15 months after stroke onset (T1/T2/T3). The Chinese version of the Interpersonal Reactivity Index (IRI), a 28-item personality assessment tool, will be completed by a carer for each subject. LoE is defined as an IRI total score of 39 or less. Patients will be examined by MRI including diffusion weighted imaging (DWI) within 1 week after the onset of stroke. A stepwise logistic regression will be performed to assess the importance of lesions in the regions of interest. To examine the predictors of LoE remission, the demographic, clinical and MRI variables of remitters and non-remitters at T2/T3 will be examined by logistic regression.Discussion: This project will be the first longitudinal study on LoE in stroke survivors. The results will shed light on the association between prefrontal cortex and subcortical lesions and LoE risk, symptom severity and outcome. The findings will provide data to advance our understanding of the pathogenesis and clinical course of LoE in stroke as well as other neurological conditions. They are thus likely to be applicable to the large population of neurological patients at risk of LoE and should also stimulate further research in this field.",16641078,PSYCHOLOGY
10.3389/frai.2024.1466321,Predicting financial distress in TSX-listed firms using machine learning algorithms,"Introduction: This study investigates the application of machine learning (ML) algorithms, a subset of artificial intelligence (AI), to predict financial distress in companies. Given the critical need for reliable financial health indicators, this research evaluates the predictive capabilities of various ML techniques on firm-level financial data.Methods: The dataset comprises financial ratios and firm-specific variables from 464 firms listed on the TSX. Multiple ML models were tested, including decision trees, random forests, support vector machines (SVM), and artificial neural networks (ANN). Recursive feature elimination with cross-validation (RFECV) and bootstrapped CART were also employed to enhance model stability and feature selection.Results: The findings highlight key predictors of financial distress, such as revenue growth, dividend growth, cash-to-current liabilities, and gross profit margins. Among the models tested, the ANN classifier achieved the highest accuracy at 98%, outperforming other algorithms.Discussion: The results suggest that ANN provides a robust and reliable method for financial distress prediction. The use of RFECV and bootstrapped CART contributes to the model’s stability, underscoring the potential of ML tools in financial health monitoring. These insights carry valuable implications for auditors, regulators, and company management in enhancing practices around financial oversight and fraud detection.",26248212,AI
10.3389/feduc.2024.1484999,"“Be yourself, rediscover yourself, and find new aspects of yourself”: newcomer youth integration in a francophone school system","Negative school integration experiences can compromise the healthy development of newcomer youth. Little research has explored what affects their experiences; even less has engaged youth in the research process. This study investigated the school integration experiences of French-speaking newcomer youth in a predominantly anglophone Canadian province using the Arts-Based Engagement Ethnography research method. We explored: (1) How do newcomer youth experience a public francophone school? and (2) How do these experiences influence their positive integration into the francophone school system in a predominantly anglophone province? Data from artifacts, interviews, and planned group discussions were organized into four structures: (a) navigating school integration challenges, (b) negotiating identity, (c) confronting biases, and (d) helping other newcomer youth. Underlying patterns painted a rich portrait of newcomer youth school integration experiences, which informed their emerging identity. Findings point to needed changes to supports and services offered to newcomer youth integrating into the francophone school system in a predominantly anglophone province.",2504284X,EDUCATION
10.3389/fonc.2024.1483435,METTL3 as a potential therapeutic target in gastric cancer,"Gastric cancer (GC) is one of the leading causes of cancer-related death worldwide. N6-methyladenosine (m6A) modification is the most prominent epigenetic modification of eukaryotic mRNAs, and methyltransferase-like 3 (METTL3), a core component of the methyltransferase complex, catalyzes m6A modification. The results of previous studies indicate that the expression level of METTL3 is significantly elevated in gastric cancer tissues and cells. In addition, fluctuations in m6A levels induced by METTL3 are closely associated with the malignant progression of tumors as well as the poor prognosis of patients with gastric cancer. In this review, we focus on the potential mechanism of METTL3 in gastric cancer, and through our analysis, we suggest that targeting METTL3 could be a new therapeutic tool for treating GC.",2234943X,ONCOLOGY
10.3389/feduc.2024.1510416,Coping and well-being in university students: sex and cultural differences,"For the psychological and personal well-being of university students, it is considered essential to study the coping strategies they use when faced with conflictive situations in the academic context and the resources that the institution offers to help them overcome these challenges. The objective of this work is to evaluate the effect of sex and culture on the different coping strategies that higher education students use in the face of the difficulties they face in the academic environment. For this purpose, the questionnaire “Coping Strategies Inventory (CSI)” was applied to a sample of 1,281 university students. The results indicate that there are significant differences in the problem-solving strategies used depending on gender and culture, finding interaction between these variables, with European women being the ones who use active strategies the most. On the contrary, men of Berber origin, are the ones who use less coping strategies, both active (emotional expression and social support) and passive (desiderative thinking), to resolve conflicts.",2504284X,EDUCATION
10.3389/fonc.2024.1453246,Mendelian randomization study of the relationship between blood and urine biomarkers and lung cancer,"Introduction: Identifying suitable biomarkers is crucial for exploring the pathogenesis, early screening, and therapeutic monitoring of lung cancer. This study aims to analyze comprehensively the associations between lung cancer and biomarkers in blood and urine.Methods: Bidirectional two-sample Mendelian randomization (MR) was used to evaluate the potential causal relationships between blood and urine biomarkers and lung cancer. We obtained Single nucleotide polymorphisms (SNPs) related to lung cancer from the 2021 Finnish database of genome-wide association studies, including small cell lung cancer (SCLC), total non-small cell lung cancer (NSCLC), lung adenocarcinoma (LAC), and lung squamous cell carcinoma (LSCC).Data on blood and urine biomarkers were derived from the UK Biobank cohort, comprising 376,807 participants.Results: We found a potential inverse causal relationship between total bilirubin and SCLC (β=-0.285, P=0.015, FDR=0.12). Urate was inversely associated with NSCLC (β=-0.158, P=0.004, FDR=0.036*). Serum calcium showed a possible inverse relationship with lung squamous cell carcinoma (β=-0.256, P=0.046, FDR=0.138), while urinary creatinine was positively associated (β=1.233, P=0.024, FDR=0.216). Non-albumin proteins (β=-0.272, P=0.020, FDR=0.180) and total protein (β=-0.402, P=0.009, FDR=0.072) were inversely related to lung squamous cell carcinoma. The AST/ALT ratio was positively associated with lung adenocarcinoma (β=0.293, P=0.009, FDR=0.072). Our reverse Mendelian randomization study found a positive causal association between small cell lung cancer and serum creatinine (β=0.022, P=0.002, FDR=0.018*), while it was inversely associated with the estimated glomerular filtration rate(eGFR)(β=-0.022, P=0.003, FDR=0.027*). A positive causal relationship was also observed with cystatin C (β=0.026, P=0.005, FDR=0.045*) and glycated hemoglobin HbA1c (β=0.013, P=0.014, FDR=0.028*). A negative causal relationship was observed with Gamma_glutamyltransferase (β=-0.013, P=0.019, FDR=0.152). For non-small cell lung cancer, a negative causal relationship was found with albumin (β=-0.024, P=0.002, FDR=0.016*), while a potentially positive causal relationship was observed with cystatin C (β=0.022, P=0.006, FDR=0.054). Possible negative causal relationships were also observed with phosphate (β=-0.013, P=0.008, FDR=0.072) and urinary potassium (β=-0.011, P=0.012, FDR=0.108), while a potential positive causal relationship was observed with C-reactive protein (β=0.013, P=0.040, FDR=0.280).Regarding lung squamous cell carcinoma, an inverse causal relationship was found with eGFR (β=-0.022, P=9.58e-06, FDR=8.62×10-5*), while a positive causal relationship was observed with serum creatinine (β=0.021, P=1.16e−4, FDR=1.05×10-3*). Potential positive causal relationships were observed with Urate (β=0.012, P=0.020, FDR=0.180), urea (β=0.010, P=0.046, FDR=0.141), and glycated hemoglobin HbA1c (β=0.020, P=0.049, FDR P=0.098), whereas a potential negative causal relationship was observed with sex hormone-binding globulin(SHBG) (β=-0.020, P=0.036, FDR=0.108).Lastly, adenocarcinoma was found to have a positive causal association with alkaline phosphatase (β=0.015, P=0.006, FDR=0.033*).Conclusion: Our study provides a robust theoretical basis for the early screening and therapeutic monitoring of lung cancer and contributes to understanding the pathogenesis of the disease.",2234943X,ONCOLOGY
10.3389/fonc.2024.1241221,Combining dosiomics and machine learning methods for predicting severe cardiac diseases in childhood cancer survivors: the French Childhood Cancer Survivor Study,"Background: Cardiac disease (CD) is a primary long-term diagnosed pathology among childhood cancer survivors. Dosiomics (radiomics extracted from the dose distribution) have received attention in the past few years to assess better the induced risk of radiotherapy (RT) than standard dosimetric features such as dose-volume indicators. Hence, using the spatial information contained in the dosiomics features with machine learning methods may improve the prediction of CD.Methods: We considered the 7670 5-year survivors of the French Childhood Cancer Survivors Study (FCCSS). Dose-volume and dosiomics features are extracted from the radiation dose distribution of 3943 patients treated with RT. Survival analysis is performed considering several groups of features and several models [Cox Proportional Hazard with Lasso penalty, Cox with Bootstrap Lasso selection, Random Survival Forests (RSF)]. We establish the performance of dosiomics compared to baseline models by estimating C-index and Integrated Brier Score (IBS) metrics with 5-fold stratified cross-validation and compare their time-dependent error curves.Results: An RSF model adjusted on the first-order dosiomics predictors extracted from the whole heart performed best regarding the C-index (0.792 ± 0.049), and an RSF model adjusted on the first-order dosiomics predictors extracted from the heart’s subparts performed best regarding the IBS (0.069 ± 0.05). However, the difference is not statistically significant with the standard models (C-index of Cox PH adjusted on dose-volume indicators: 0.791 ± 0.044; IBS of Cox PH adjusted on the mean dose to the heart: 0.074 ± 0.056).Conclusion: In this study, dosiomics models have slightly better performance metrics but they do not outperform the standard models significantly. Quantiles of the dose distribution may contain enough information to estimate the risk of late radio-induced high-grade CD in childhood cancer survivors.",2234943X,ONCOLOGY
10.1186/s40359-024-02132-7,A preparation program for psychological safety of hospitalized adolescents,"The study aimed to investigate the impact of an information-based preparation program on the psychological safety of adolescents admitted to pediatric wards, emphasizing the importance of enhancing patient safety. This quasi-experimental study was conducted among 98 adolescents admitted to pediatric wards at Namazi Hospital, managed by Shiraz University of Medical Sciences, in 2021. The participants were randomly assigned to either an intervention group or a control group using an electronic randomization table. The intervention group received an information-based preparation program, while the control group followed routine care. Adolescents completed the Psychological Safety Questionnaire after admission and at discharge. Data were analyzed using SPSS (Version 22), with a significance level of 0.05. The mean psychological safety scores before the intervention were 136.73 ± 17.30 in the control group and 141.03 ± 16.34 in the intervention group, with no significant difference between the two groups (p = 0.20). After the intervention, the mean scores were 136.65 ± 19.01 in the control group and 145.50 ± 14.05 in the intervention group. A comparison of the mean psychological safety scores showed a significant difference between the two groups after the intervention (p = 0.01). The findings of this study indicate that the information-based preparation program positively affected the psychological safety of hospitalized adolescents. Therefore, it is recommended that nurses incorporate this method into therapeutic programs for hospitalized adolescents to enhance their psychological safety effectively.",20507283,PSYCHOLOGY
10.3389/feduc.2024.1501899,Company-university intersections through service-learning (SL): a systematic review,"The most relevant intersections in society include the relationship between universities and companies for a projection toward the sustainable employability of future graduates. Among the possible intersections, Service-learning (SL) is an educational proposition that may help university students to develop their personal skills, offering them opportunities to learn and practice civic commitment, improving their sense of social and citizen responsibility, and combining academic and community-service learning in a constructed programme where participants train by working on real needs of the environment to optimize and transform the latter. The development of SL programmes in university departments related to technical areas is posing a challenge to faculty members and students, thus it is important to explore this lack of programmes. The main aim of the present study was to identify SL projects and their topics through a systematic review, following the guidelines of the «Preferred Reporting Items for Systematic Reviews and Meta-Analyses» (PRISMA) declaration in the knowledge areas of Architecture, Computer Science, Environmental Engineering, Software Engineering, Computer Engineering, Artificial Intelligence, and Computer Languages and Systems, from the year 2008 to the year 2023. This review includes 128 articles, which were analyzed with ATLAS. Ti 22. The categorical system employed in this work emerged from the topics of the programmes identified in the selected articles, which were verified by experts in the mentioned fields of knowledge. The agreed categories were: accessibility, learning, social groups, courses, devices, infrastructure, games, environment, landscaping, heritage, software and web. The most relevant conclusions highlight that most of the articles refer to theoretical aspects of SL, showing a lack of data on the practical development of SL programmes and their impact on employability. The largest number of SL programmes are developed in the areas of Architecture, Computer Science and Software Engineering. Regarding the topics that are addressed in research, most of the articles refer to social groups, software, learning and accessibility.",2504284X,EDUCATION
10.1186/s40594-024-00518-y,Creating better internships by understanding mentor challenges: findings from a series of focus groups,"Background: Despite demands to make higher education more relevant beyond academia, and a growing body of work testifying to the benefits of work-relevance programs (e.g., work-placements, or internships) for both students and the companies that host them, there is limited information available for those aiming to optimize these programs. For example, few have explored the challenges and needs of internship supervisors. Here, we focus on the experiences of supervisors in biology and geology programs across three Norwegian institutions. Specifically, through a series of focus groups, we asked internship supervisors about their motivations for serving as student mentors, any challenges they had faced, and what higher-education institutions could do to better prepare them for hosting students at their workplaces. Results: Key challenges faced by supervisors include the need to tailor placements to individual student needs and capabilities, navigating the constraints imposed by academic structures, and addressing communication gaps between students, institutions, and workplace supervisors. Internship supervisors suggest enhancing communication strategies to better define roles and expectations, increasing support and training for supervisors, and establishing clearer, more collaborative frameworks for setting learning objectives with students. Conclusions: The supervisors’ suggestions aim to ensure that internships are mutually beneficial, supporting both students' educational outcomes and the workplace needs. By focusing on the supervisor's perspective, we provide valuable insights into one aspect of implementing effective and rewarding internships (i.e., supervisor preparation), thereby suggesting pathways for future improvements in these high-impact educational practices.",21967822,EDUCATION
10.3389/feduc.2024.1401388,Navigating an uncertain interregnum,"This article seeks to identify trends in Steiner Waldorf education through the lens of Clarence Beeby’s work on educational myths. Beeby calls myths a form of communication between contemporaries or between generations, ways of conceptualizing education that can be understood quickly yet are flexible enough to accommodate a range of interpretations. A myth holds for a period and then transitions into a new myth that best suits changed times and changed circumstances. I reflect on what the myths of Waldorf education might be and take up Gramsci’s well-known quotation on change, “The crisis consists precisely of the fact that the old is dying and the new cannot be born; in this interregnum a great variety of morbid symptoms appear,” In writing this, Gramsci extended the interregnum beyond its usual papal connotation to include the socio-cultural condition as well. I use the notion to consider if Waldorf education is currently in an interregnum period and is displaying both “morbid symptoms” and promising signs of fresh development. In addition, I contemplate if these promising signs point toward a new myth that will allow Waldorf education to step beyond its century-old, colonial heritage.",2504284X,EDUCATION
10.3389/fpsyg.2024.1471658,How watching sports events empowers people’s sense of wellbeing? The role of chain mediation in social interaction and emotional experience,"Background: While engaging in sports is widely recognized for enhancing wellbeing, limited research has examined the effects of watching sports events on individuals’ subjective wellbeing. The mechanisms and pathways underlying this relationship remain unclear.Objectives: This study explores the correlation between watching sports events and the wellbeing of Chinese individuals, based on the theoretical framework of “spectator behavior → social interaction → emotional experience → happiness.” The aim is to investigate the mediating effects of social interaction and emotional experience, providing insights for promoting greater participation in sports events and supporting the healthy development of the sports industry.Methods: The study involved 885 participants from five representative provinces and cities in China. Assessment tools included the Physical Activity Rating Scale, Social Interaction Questionnaire, Emotional Experience Questionnaire, and Subjective Wellbeing Scale. Data were analyzed using Stata and the PROCESS plug-in of SPSS for comprehensive multivariate statistical analysis.Results: Watching sports events significantly and positively affects subjective wellbeing, social interaction, and emotional experience (p < 0.001). Three mediating pathways were identified: (1) watching sports events → social interaction → subjective wellbeing (effect size: 0.024), (2) watching sports events → emotional experience → subjective wellbeing (effect size: 0.011), and (3) watching sports events → social interaction → emotional experience → subjective wellbeing (effect size: 0.003).Conclusion: The direct impact of watching sports events on subjective wellbeing was positive. Indirect effects were facilitated by the mediating roles of social interaction and emotional experience, with the effect of social interaction being more substantial than that of emotional experience.Implications: These findings suggest that watching sports events can serve as a catalyst for enhancing wellbeing, primarily through fostering social connections and enriching emotional experiences. Practically, this indicates the potential value of encouraging viewership of sports events as a means of promoting community engagement and mental health, thus contributing to the holistic growth of the sports sector and public health initiatives.",16641078,PSYCHOLOGY
10.3389/fpsyg.2024.1463641,Predicting PTSD and complex PTSD from interpersonal violence in Japanese school-based extracurricular sports activities: using the International Trauma Questionnaire (ITQ),"Introduction: Victims of interpersonal violence in sports show various mental health concerns. However, no studies have quantitatively examined their primary complaints, considering psychological symptoms such as denial of self-concept and interpersonal challenges not captured by conventional post-traumatic stress disorder (PTSD). Recently, an association between interpersonal violence victimization and complex PTSD (CPTSD) has been noted in Japanese sports coaching situations, specifically for extracurricular sports activities. This study aimed to examine the applicability of the International Trauma Questionnaire (ITQ) and determine whether interpersonal violence victimization and related risk factors predicted PTSD and CPTSD in extracurricular sports activities in Japan.Methods: This study included 651 adults aged 18–25 who had previously participated in extracurricular sports activities in junior high and high school. The ITQ was examined using confirmatory factor analysis with maximum likelihood with robust standard errors, fit indices comparisons, a graded response model, differential item functioning, and rank correlation designs. A binomial logistic regression model with robust standard errors examined the association of PTSD and CPTSD with interpersonal violence victimization and related risk factors.Results: The optimal factor structure, measurement precision, and validity of the ITQ were confirmed. Physical and psychological violence victimization and the ITQ were positively correlated with PTSD, difficulties in emotion regulation, self-disgust, and interpersonal problems subscales, respectively. A high frequency of psychological and physical violence victimization experiences and self-identified LGB (lesbian, gay, or bisexual) were associated with PTSD and CPTSD diagnosability. Additionally, being a woman and in school life away from parents were associated solely with PTSD diagnosability.Discussion: This is the first quantitative study to examine CPTSD in a study on interpersonal violence in sports. Our findings can provide insights into desirable victim support and enhanced clinical care in interpersonal violence in a sports context.",16641078,PSYCHOLOGY
10.3389/frai.2024.1532896,Editorial: Generative AI in education,"In the field of education, there is a growing interest in the use of Generative Artificial Intelligence (Generative AI) to reshape the educational landscape. This Research Topic investigates the transformative potential of Generative AI in various aspects of education. The papers in this edited volume shed light on the latest discoveries, new insights, novel developments, and future challenges in this rapidly advancing field.By leveraging machine learning models, these intelligent systems extract useful insights from vast amounts of data, making them capable of delivering highly individualized content. They can analyze a learner's proficiency level, learning style, and pace, and then tailor the study material accordingly. Generative AI can adapt its content generation strategies to meet distinct preferences and learners’ needs. This can increase student engagement and comprehension, highlighting its potential to transform traditional teaching methodologies.This Research Topic also explores the use of Generative AI as part of AI tutors, capable of tailoring instructions and feedback dynamically based on each learner's progress. Acting as an ever-present mentor, Generative AI can offer learning aids beyond class hours, facilitating continuous learning and immediate doubt clarification. This can be crucial for learners encountering obstacles outside the typical school hours or during self-study periods. Anyway, to use Generative AI as a tutor, further research is needed to examine not only the accuracy of its answers but also their emotional content, as emotions play a crucial role in the learning process.This Research Topic includes 11 papers (Original Research: 6; Perspective: 2; Opinion: 2, and Mini-Review:1). These papers explore areas such as: (a) using Large Language Models (LLMs) to generate feedback, (b) the use and perceived usefulness of a Generative AI chatbot for schoolwork among adolescents, (c) the potential of Generative AI in supporting critical thinking and enhancing human interactions, (d) using ChatGPT to support pre-service mathematics teachers in constructing mathematical proofs, (e) opportunities and challenges of LLMs to model the “whole learner,” (h) exploring Generative AI for personalized educational assessment, (g) the use of AI-mentors in career exploration, (i) the responsible integration of AI in education, (j) the use of LLMs to automatically generate interactive listening tasks, (k) the potential of AI-enhanced robots to generate incorrect information and deceive students, and (l) a mini-review on Generative AI for supporting students' cognitive and emotional needs. The main contributions of these articles are described below.Comparing emotions in ChatGPT answers and human answers to the coding questions on Stack Overflow by Fatahi, Vassileva, and Roy (2024). This paper presents a study aimed to compare the emotional content in human and AI answers. Specifically, it examines the emotional aspects in answers from ChatGPT and humans to 2000 questions sourced from Stack Overflow, finding that ChatGPT's answers tend to be more positive, while human responses often express anger and disgust. Additionally, human emotions exhibit a broader spectrum than ChatGPT. The authors suggest that ChatGPT shows promise as a virtual tutor for students by answering queries and fostering collaboration. However, further research is needed on the emotional aspects of responses.Adolescents’ use and perceived usefulness of generative AI for schoolwork: exploring their relationships with executive functioning and academic achievement by Klarin et al. (2024). The article explores adolescents’ frequency of use and perceived usefulness of generative AI chatbots for schoolwork, focusing on their relationship with executive functioning (EF) and academic achievement. Two studies were conducted with adolescents. Findings indicate that older students use Generative AI tools as more frequently. Also, students facing more EF challenges perceive Generative AI tools as more useful for completing assignments. However, no significant link was found between the use of Generative AI and academic achievement. Future work involves exploring additional Generative AI issues such as potential gender differences, implications for academic equity and the impact on adolescent cognitive development.Using Generative AI in education: the case for critical thinking by Lee and Low (2024). This opinion article makes the case for focusing the use of Generative AI in enhancing students’ critical thinking and human interactions. The authors describe two case studies: (a) teaching communication skills and (b) teaching data structures and algorithms with AI chatbots. The two cases illustrate the potential use of Generative AI to enhance teaching and learning. The authors discuss the benefits of AI-based personalized feedback in improving student engagement and fostering strategic and critical use of AI tools. The article encourages the ethical and responsible use of generative AI in education with potential implications for the workforce.Using large language models to support pre-service teachers' mathematical reasoning—an exploratory study on ChatGPT as an instrument for creating mathematical proofs in geometry by Herrmann and Dilling (2024). LLMs can be a great source to extract knowledge. It thus appears natural to expect them to generate the texts of classical mathematical proofs. The authors, Marc Herrmann and Frederik Dilling, explore how pre-service teachers employ them to produce proofs. Using the lens of instrumental genesis, their study shows a variety of usage patterns with limited knowledge about the inner workings of the models. It sketches the road to become a teacher support instrument.Large language models for whole-learner support: opportunities and challenges by Mannekote et al. (2024) examines the transformative potential of LLMs in education through the...",26248212,AI
10.3389/fonc.2024.1449401,"A phase I study using bortezomib (Velcade), cladribine, and rituximab in treating patients over 50 years old with mantle cell lymphoma","Cladribine indirectly downregulates methylation of DNA, RNA, and histones by blocking the transfer of methyl groups from S-adenosyl-methionine. The cladribine and rituximab combination showed a synergetic effect in treating B-cell lymphomas. Bortezomib (Velcade) is a Food and Drug Administration (FDA)-approved proteasome inhibitor for treating mantle cell lymphoma (MCL). In this single-arm, phase I study, the safety, dose-limiting toxicity, and clinical activity of bortezomib, cladribine, and rituximab (VCR) combination treatment were evaluated in elderly MCL patients. Potential DNA methylation biomarkers for VCR treatment were also proposed. A standard 3 + 3 dose-escalation scheme was designed to determine the maximum tolerated dose of cladribine. The therapy consisted of six 28-day cycles. Most patients tolerated this regimen well. The overall response (OR) rate was 84.6%, and the complete remission (CR) rate was 84.6%. In the newly diagnosed subject cohort, the OR and CR were 100%, the 2-year overall survival rate was 84.6%, and the progression-free survival rate was 76.9%. The median age was 64 (54–81). The median time to first response was 3 (2.1–7.4) months. The median follow-up time was 43 (9–60) months. Low-grade hematological toxicity and mild fatigue were observed. No severe systemic toxicity was observed. Five hypermethylated regions located at gene promoters were identified as potential biomarkers for an effective treatment response. In conclusion, the VCR combination is a well-tolerated, low-toxicity, and highly effective regimen for the elderly with untreated MCL.Clinical Trial Registration: ClinicalTrials.gov, identifier NCT01439750.",2234943X,ONCOLOGY
10.1007/s44196-024-00702-6,Hyperplane-Assisted Multi-objective Particle Swarm Optimization with Twofold Proportional Assignment Strategy,"In the simultaneous optimization of multiple objectives, how to balance convergence promotion and diversity preservation in the evolutionary process is a key and challenging problem. In this research, a hyperplane-assisted multi-objective particle swarm optimization with a twofold proportional assignment strategy (tpahaMOPSO) is suggested to ameliorate the optimization performance of MOPSO. First, the external archive is maintained in combination with hyperplane-based convergence evaluation and shift-based density estimation to retain high-quality candidate solutions. Second, a twofold proportional assignment scheme is designed to search the surrounding region of candidate solutions with better potential to emphasize convergence and diversity, respectively. Third, the domination relationship and convergence difference are combined to select a more reasonable individual historical best and reduce the risk of particle aggregation. Finally, the proposed tpahaMOPSO was compared with ten representative and advanced multi-objective optimization algorithms on 22 widely used test functions with different characteristics. The simulation results present that the developed tpahaMOPSO got the best result in 11 benchmark functions for both IGD and HV criteria. Concurrently, the Friedman test was applied for ranking analysis and the proposed algorithm also obtained excellent statistical analysis results. The promising performance and strong competitiveness of the proposed tpahaMOPSO have been verified by different experimental studies.",18756883,AI
10.3389/frai.2024.1479905,Dense Paraphrasing for multimodal dialogue interpretation,"Multimodal dialogue involving multiple participants presents complex computational challenges, primarily due to the rich interplay of diverse communicative modalities including speech, gesture, action, and gaze. These modalities interact in complex ways that traditional dialogue systems often struggle to accurately track and interpret. To address these challenges, we extend the textual enrichment strategy of Dense Paraphrasing (DP), by translating each nonverbal modality into linguistic expressions. By normalizing multimodal information into a language-based form, we hope to both simplify the representation for and enhance the computational understanding of situated dialogues. We show the effectiveness of the dense paraphrased language form by evaluating instruction-tuned Large Language Models (LLMs) against the Common Ground Tracking (CGT) problem using a publicly available collaborative problem-solving dialogue dataset. Instead of using multimodal LLMs, the dense paraphrasing technique represents the dialogue information from multiple modalities in a compact and structured machine-readable text format that can be directly processed by the language-only models. We leverage the capability of LLMs to transform machine-readable paraphrases into human-readable paraphrases, and show that this process can further improve the result on the CGT task. Overall, the results show that augmenting the context with dense paraphrasing effectively facilitates the LLMs' alignment of information from multiple modalities, and in turn largely improves the performance of common ground reasoning over the baselines. Our proposed pipeline with original utterances as input context already achieves comparable results to the baseline that utilized decontextualized utterances which contain rich coreference information. When also using the decontextualized input, our pipeline largely improves the performance of common ground reasoning over the baselines. We discuss the potential of DP to create a robust model that can effectively interpret and integrate the subtleties of multimodal communication, thereby improving dialogue system performance in real-world settings.",26248212,AI
10.3389/frai.2024.1509179,A graph neural architecture search approach for identifying bots in social media,"Social media platforms, including X, Facebook, and Instagram, host millions of daily users, giving rise to bots automated programs disseminating misinformation and ideologies with tangible real-world consequences. While bot detection in platform X has been the area of many deep learning models with adequate results, most approaches neglect the graph structure of social media relationships and often rely on hand-engineered architectures. Our work introduces the implementation of a Neural Architecture Search (NAS) technique, namely Deep and Flexible Graph Neural Architecture Search (DFG-NAS), tailored to Relational Graph Convolutional Neural Networks (RGCNs) in the task of bot detection in platform X. Our model constructs a graph that incorporates both the user relationships and their metadata. Then, DFG-NAS is adapted to automatically search for the optimal configuration of Propagation and Transformation functions in the RGCNs. Our experiments are conducted on the TwiBot-20 dataset, constructing a graph with 229,580 nodes and 227,979 edges. We study the five architectures with the highest performance during the search and achieve an accuracy of 85.7%, surpassing state-of-the-art models. Our approach not only addresses the bot detection challenge but also advocates for the broader implementation of NAS models in neural network design automation.",26248212,AI
10.3389/fonc.2024.1476205,Penpulimab and Anlotinib in PDL1 high-expression pulmonary giant cell carcinoma with cerebral metastases: case report and review,"Pulmonary giant cell carcinoma (PGCC) is a rare subtype of non-small cell lung cancer (NSCLC) characterized by complex pathology, high rates of misdiagnosis or missed diagnosis, an aggressive clinical course, rapid progression, and poor prognosis. This case report describes a 67-year-old Chinese male with a left upper lobe lung mass, diagnosed via CT-guided lung biopsy as PGCC with symptomatic multiple cerebral metastases. The tumor showed strong PD-L1 positivity, and genetic testing revealed a TP53 exon 4 c.313G mutation. Treatment involved first-line therapy with Penpulimab injection combined with Anlotinib and concurrent cranial radiotherapy. Significant reduction in both the pulmonary and cerebral metastatic lesions was observed, with notable efficacy. As of June 2024, there has been no disease progression for 26 months, with the patient currently maintained on Anlotinib monotherapy. This case demonstrates the favorable efficacy of Penpulimab injection combined with Anlotinib in treating advanced PGCC. These findings indicate that this combination therapy may offer a promising new therapeutic option for this rare type of lung cancer.",2234943X,ONCOLOGY
10.1186/s40594-024-00519-x,Subtopic-specific heterogeneity in computer-based learning behaviors,"Background: Self-regulated learning (SRL) strategies can be domain specific. However, it remains unclear whether this specificity extends to different subtopics within a single subject domain. In this study, we collected data from 210 college students engaged in a computer-based learning environment to examine the heterogeneous manifestations of learning behaviors across four distinct subtopics in introductory statistics. Further, we explore how the time spent engaging in metacognitive strategies correlated with learning gain in those subtopics. Results: By employing two different analytical approaches that combine data-driven learning analytics (i.e., sequential pattern mining in this case), and theory-informed methods (i.e., coherence analysis), we discovered significant variability in the frequency of learning patterns that are potentially associated with SRL-relevant strategies across four subtopics. In a subtopic related to calculations, engagement in coherent quizzes (i.e., a type of metacognitive strategy) was found to be significantly less related to learning gains compared to other subtopics. Additionally, we found that students with different levels of prior knowledge and learning gains demonstrated varying degrees of engagement in learning patterns in an SRL context. Conclusion: The findings imply that the use—and the effectiveness—of learning patterns that are potentially associated with SRL-relevant strategies varies not only across contexts and domains, but even across different subtopics within a single subject. This underscores the importance of personalized, context-aware SRL training interventions in computer-based learning environments, which could significantly enhance learning outcomes by addressing the heterogeneous relationships between SRL activities and outcomes. Further, we suggest theoretical implications of subtopic-specific heterogeneity within the context of various SRL models. Understanding SRL heterogeneity enhances these theories, offering more nuanced insights into learners’ metacognitive strategies across different subtopics.",21967822,EDUCATION
10.3389/frai.2024.1477535,Reader’s digest version of scientific writing: comparative evaluation of summarization capacity between large language models and medical students in analyzing scientific writing in sleep medicine,"Introduction: As artificial intelligence systems like large language models (LLM) and natural language processing advance, the need to evaluate their utility within medicine and medical education grows. As medical research publications continue to grow exponentially, AI systems offer valuable opportunities to condense and synthesize information, especially in underrepresented areas such as Sleep Medicine. The present study aims to compare summarization capacity between LLM generated summaries of sleep medicine research article abstracts, to summaries generated by Medical Student (humans) and to evaluate if the research content, and literary readability summarized is retained comparably.Methods: A collection of three AI-generated and human-generated summaries of sleep medicine research article abstracts were shared with 19 study participants (medical students) attending a sleep medicine conference. Participants were blind as to which summary was human or LLM generated. After reading both human and AI-generated research summaries participants completed a 1–5 Likert scale survey on the readability of the extracted writings. Participants also answered article-specific multiple-choice questions evaluating their comprehension of the summaries, as a representation of the quality of content retained by the AI-generated summaries.Results: An independent sample t-test between the AI-generated and human-generated summaries comprehension by study participants revealed no significant difference between the Likert readability ratings (p = 0.702). A chi-squared test of proportions revealed no significant association (χ2 = 1.485, p = 0.223), and a McNemar test revealed no significant association between summary type and the proportion of correct responses to the comprehension multiple choice questions (p = 0.289).Discussion: Some limitations in this study were a small number of participants and user bias. Participants attended at a sleep conference and study summaries were all from sleep medicine journals. Lastly the summaries did not include graphs, numbers, and pictures, and thus were limited in material extraction. While the present analysis did not demonstrate a significant difference among the readability and content quality between the AI and human-generated summaries, limitations in the present study indicate that more research is needed to objectively measure, and further define strengths and weaknesses of AI models in condensing medical literature into efficient and accurate summaries.",26248212,AI
10.1186/s40359-024-02307-2,Application of the teaching games for understanding model to improve decision-making in sport learning: a systematic review and meta-analysis,"Issues related to sport teaching at different educational stages is a subject of wide interest. Teaching Games for Understanding has been established as the most effective way to teach students the elements related to the field of sport. The objectives of this study were (a) to examine the impact of the Teaching Games for Understanding model on decision-making in sports education and (b) to compare the effect of the interventions analysed according to educational stage. A systematic review and meta-analysis of studies published before August 2024 was conducted. A total of 4937 scientific studies were obtained. The quantitative synthesis consisted of 25 scientific articles (n = 1692). The studies were analyzed using three-level random effects models with variance estimation. Results were calculated as raw mean differences and Hedges’ g effect sizes. This model is suitable for decision-making in sports education (g = 0.82; CI 95% = [0.55; 1.09]). This pedagogical model was also found to be effective for working on decision-making in primary education (g = 0.6108; CI 95% = [0.3587; 0.8628]), secondary education (g = 0.7523; CI 95% = [0.2348; 1.2706]) and higher education (g = 0.8803 [CI 95% = 0.2851 to 1.4855]). Teaching games for understanding effectively addresses decision-making during sports learning. In addition, this pedagogical model is effective for facilitating decision-making according to the role and the moment of the game. The use of this model enables effective technical-tactical learning to solve various problematic actions in real game situations.",20507283,PSYCHOLOGY
10.1007/s00432-024-05984-z,Anticancer effects of PEP06 (TB01) in combination with Trifluridine/Tipiracil (TAS-102) in a xenograft model of human colorectal cancer,"Background Colorectal cancer (CRC) is the third most common cancer globally, with advanced stages presenting significant treatment challenges. Recently years, drug combination therapy has become a promising strategy for cancer treatment. Objective To evaluate the therapeutic efficacy of the combination of the anti-angiogenic drug PEP06 (TB01) and the cytotoxic drug Trifluridine/Tipiracil (TAS-102) in human CRC HCT-116 xenograft mouse model. And quantitative assessment of the interaction between TB01 and TAS-102 in the treatment based on pharmacological effects. Methods This study utilized the human CRC HCT-116 xenograft nude mouse model to evaluate the antitumor effects of TAS-102 and TB01, both as mono-therapies and in combination therapies. Results The combination therapy not only demonstrated significantly inhibited tumor growth in a dose-dependent manner, but also seems to reduce the common toxicity associated with such treatments, as shown by the maintenance of body weights in the treated mice. Conclusion The synergistic effect observed from the combined use of TAS-102 and TB01 suggests a promising new treatment avenue for refractory CRC patients, meriting further investigation and potential clinical application.",14321335,ONCOLOGY
10.1007/s00432-024-06050-4,Occupational adjustments and work ability of young adult cancer survivors: results from the AYA-Leipzig study,"Purpose: Adolescent and young adult cancer survivors (AYA-CS) face a long working life after treatment, yet factors related to a successful return to work remain largely unexplored. We therefore aimed to investigate the use of occupational adjustments and their impact on work ability upon return to work. Methods: As part of the AYA-LE study, we surveyed AYA-CS (aged 18–39 at diagnosis) who returned to work and assessed work ability (Work Ability Index) as well as use and benefit of occupational adjustments. We analyzed predictors of use and benefit of occupational adjustments on average 4 years post-diagnosis using multivariate linear and logistic regression. Results: Out of 438 AYA-CS, 389 (88.8%) returned to work after cancer diagnosis and were included in analyses. Mean work ability was M = 36.2 (SD = 6.9), 11.4% reported poor, 34.7% moderate, 41.4% good and 12.5% excellent work ability. Following treatment, 82.3% used occupational adjustments, most frequently: flexible working hours, gradual reintegration and reduced working hours. The probability of a reduction in working hours was found to be higher among older AYA-CS (≥ 30), female gender and with a fatigue index ≥ 11 (R2 = 0.073). A fatigue index < 11, elevated levels of pain and the presence of metastases/recurrence were associated with a lower benefit of reduced working hours (R2 = 0.183). Younger age (< 30) and stem cell transplant were associated with a lower benefit of support from colleagues (R2 = 0.077). Conclusion: Our results highlight the need for targeted occupational counselling throughout the treatment and even beyond the return-to-work process, considering individual and social factors.",14321335,ONCOLOGY
10.1186/s40359-024-02312-5,Assessing ambulance staff attitudes toward mental health conditions: translation and psychometric evaluation of the medical condition regard scale among ambulance staff,"Introduction: Ambulance staff play a crucial role in responding to mental health crises. However, negative regard toward patients with mental health conditions can hinder care. The Medical Condition Regard Scale (MCRS) assesses regards or attitudes but has not previously been validated for educated ambulance staff and has never been translated into Norwegian. This study aims to translate the instrument into Norwegian, test it on a population of ambulance staff, explore the psychometric properties of the Norwegian version, and measure regard for patients with psychosis. Method: The MCRS is an 11-item instrument with a Likert scale of 1–6. Possible sum scores range from 11 to 66 (higher score = more positive regards). We chose “psychosis” as the condition to investigate. Translation followed eight steps: (1) preparation, (2) forward translation, (3) backward translation, (4) first expert panel review, (5) harmonisation, (6) cognitive debriefing, (7) second expert panel review, and (8) writing of the final version. The instrument was tested and re-tested regarding the condition “psychosis” on a representative sample of 114 Norwegian ambulance staff in 2023, with a temporal gap of one month. We explored item scores and distribution, as well as floor and ceiling effects. We tested the internal consistency of the items using Cronbach’s Alpha and consistency in answers over time (test and re-test) using the Paired Sample-T test. We used factor analyses to explore the inter-item relationships of the items. Results: The 114 participants had a mean sum score of 47, which is mid-range. The scale has a ceiling effect on five items, which was not described in detail earlier. Two items regarding the monetary spending on patients with the given condition had the largest ceiling effects. However, the Norwegian translation showed adequate internal consistency (Cronbach’s Alpha = 0.82) and is reliable over time. Test and re-test showed no significant differences in the scale’s total score (Paired sample T-test, p > 0.05). Exploratory and confirmatory factor analyses indicate that the scale should be used as a one-dimensional instrument in a Norwegian setting in ambulance staff populations. Conclusion: The Norwegian translation of the MCRS is a reliable instrument for ambulance staff measuring medical condition regards. However, the ceiling effect limits the ability to discern differences among high-scoring individuals. Ambulance staff’s regard for patients with psychosis is medium positive (mid-range level), but slightly more positive than what is reported in the international literature regarding patients with mental health issues.",20507283,PSYCHOLOGY
10.1007/s00432-024-06058-w,Metabolomic profile and its association with the diagnosis of prostate cancer: a systematic review,"Objective: To determine the association of a metabolomic profile with the diagnosis of localized prostate cancer. Methods: We conducted a search strategy in MEDLINE (OVID), EMBASE, LILACS, and the Cochrane Central Register of Controlled Trials (CENTRAL) from 2008 to the present. We included Clinical trials and analytical and descriptive observational studies that reported metabolite results and metabolite profiles in serum, tissue, urine, and seminal fluid. All studies used metabolomic techniques such as MS and MRI to identify patients with localized prostate cancer compared with patients without cancer. We used QUADAS 2 to assess the risk of bias. Results: We found 1248 studies with the search strategy. Finally, 14 case–control studies were included. Serum was the primary sample to identify the metabolites. Low concern was found regarding applying the index test and the reference standard in assessing the risk of bias. The metabolites of interest associated with establishing a metabolomic profile in the diagnosis of localized prostate cancer were amino acids, lipids, androgens, estrogens, nucleotides, and histidine metabolism. Conclusion: Disturbances in the metabolism of fatty acids, amino acids, nucleotides, and steroid hormones were identified, suggesting the presence of localized prostate cancer. Importantly, serum samples showed an increase in amino acid levels. Glutamate and aspartic acid stand out among the amino acids that register high levels. In addition, glycine and serine were consistently decreased metabolites in the three kinds of biological samples analyzed.",14321335,ONCOLOGY
10.1007/s00432-024-06071-z,Case study of a neuroendocrine tumor of uncertain origin: single-cell transcriptomics unravels potential primary location,"Purpose Determining the primary origin of non-organ-confined neuroendocrine tumors (NETs) for accurate diagnosis and management. Neuroendocrine tumors are rare neoplasms with diverse clinical behaviors. Determining their primary origin remains challenging in cases of non-organ-confined NETs. This study explores the histogenesis of a retroperitoneal, non-functional NET localized between the duodenum and pancreatic head, utilizing advanced molecular diagnostics to elucidate its probable primary source. Methods Initial diagnostic methods, including imaging and histopathology, failed to resolve the tumor’s origin. The tumor was subjected to single-cell RNA sequencing (scRNA-seq) and whole exome sequencing (WES). Publicly available transcriptomic datasets from pancreatic and small intestine NETs were used to develop and validate a molecular gene signature for tissue-of-origin identification. Results The gene signature distinguished pancreatic and small intestine NETs with high accuracy. The tumor cells presented a molecular profile consistent with a pancreatic origin, likely derived from ectopic pancreatic tissue. Conclusions This case demonstrates the value of integrating scRNA-seq and WES for the molecular characterization of complex NETs. Identifying the tumor’s pancreatic origin informed a targeted management approach, avoiding unnecessary systemic treatment and underscoring the potential of single-cell approaches in personalized oncology.",14321335,ONCOLOGY
10.1186/s40359-024-02322-3,Investigating the effect of mindfulness training for stress management in military training: the relationship between the autonomic nervous system and emotional regulation,"Military personnel face an increased risk of developing mental disorders owing to the stressful environments they encounter. Effective stress management strategies are crucial to mitigate this risk. Mindfulness training (MT) is promising as a stress management approach in such demanding settings. This study uses a quantitative approach to investigate the impact of MT on the relationship between the autonomic nervous system (ANS) and emotional regulation. The study evaluated the effectiveness of MT in reducing stress among 86 military personnel. Participants were divided into two groups: MT (n = 42) and non-MT (n = 38). The study compared the two groups using measures of heart rate variability (HRV), a reliable indicator of ANS activity. The MT group exhibited a significant increase in HRV (14.4%, p = 0.001) and alpha asymmetry (AA) in the frontal lobe (45.7%, p < 0.001) compared to the non-MT group. Notably, the MT group achieved significantly higher scores on the parachute landing fall (PLF) training performance (p < 0.001). These improvements in HRV, AA, and PLF performance were strongly correlated. Furthermore, AA fully mediated the relationship between HRV and PLF training performance. The findings suggest that MT has a positive impact on stress resilience, potentially by mitigating anxiety and attention deficits induced by extreme stressors. These positive effects are facilitated by concurrent modulation of the frontal cortex and autonomic nervous system. Our findings provide insight into the neural mechanisms behind MT-induced stress reduction from the perspective of neuromodulation.",20507283,PSYCHOLOGY
10.1186/s40359-025-02347-2,"Psychological impact and coping mechanisms among sudanese medical students: a study on anxiety, depression, behavioral, and cognitive changes post COVID-19 lockdown and ongoing conflict","Mental health is crucial for overcoming obstacles, completing tasks, and contributing to society. Mental, social, and cognitive healths are included. In demanding fields like medicine, academic pressure can cause exhaustion, poor performance, and behavioral changes. Mental health must be addressed to improve student success and well-being. Medical students’ coping strategies, anxiety, depression, and behavioral changes in uncontrollable situations will be studied. A cross-sectional study involved 393 medical students from various universities in Khartoum. Data was collected using an online questionnaire to assess mental health responses during both controllable and uncontrollable situations across all academic years. Data analysis using SPSS 27 indicated minimal missing data (0.25%) among the 393 participants. PHQ-4 scores assessed psychological distress, anxiety, and depression. The study found that 74.2% of participants experienced behavioral, cognitive, and emotional changes. Significant associations were observed between PHQ-4 scores and these changes (p < .05) using Chi-Square testing. Most participants were females aged 20 to 22, primarily from the Medicine and Pharmacy departments. The study revealed that most individuals utilized pharmacological coping strategies following significant life changes due to uncontrollable situations. The study highlights that women experienced stress, dissatisfaction, concern, and anger more frequently than men during ongoing war and the post-COVID-19 lockdown. Medical students faced substantial challenges in behavior, emotions, and cognition during societal unrest, including fatigue, feelings of failure, and sleep disturbances. Over 74% reported multiple changes in their emotions and behaviors. Coping strategies included nicotine, sleeping aids, socializing, exercise, venting, meditation, and journaling.",20507283,PSYCHOLOGY
10.3389/feduc.2024.1502449,"A culturally relevant, imbued, and sustaining pedagogy framework for culturally connected math curriculum","This article introduces the CRISP (Culturally Relevant, Imbued, and Sustaining Pedagogy) framework in the context of a three-course sequence, “Indigenous Math I, II, and III,” taught at Turtle Mountain College. These three courses seek to revitalize mathematical ways of knowing embedded within the Turtle Mountain language(s) and culture(s). The Indigenous Math framework and Indigenous Math Education framework guide these three courses, as well as the Secondary Math Education bachelor’s degree program that spurred development of these courses. Discussing the relationship (i.e., connections, similarities, differences) between Western math and Indigenous math is central to these courses. The CRISP framework extends this discussion by describing four significant components of revitalizing and teaching Indigenous math. Multiple Indigenous math examples are shared as evidence for the value of the CRISP framework.",2504284X,EDUCATION
10.3389/feduc.2024.1485425,Drawing the future: gender and future occupational aspirations of young children in Sweden,"Introduction: Research on young children’s occupational aspirations and the factors shaping them is still limited, especially in early interventions addressing gender disparities in high-status fields like STEM.Methods: This is the first study in Sweden utilizing the Drawing the Future method, surveyed 1,832 children (aged 5–13) from 28 schools in Skåne region of southern, asking them to draw their dream jobs. This exercise was conducted in a classroom setting and facilitated by their class teacher.Results: Significant gender differences emerged, revealing distinct stereotypical patterns in children’s future occupational aspirations and influencing factors. Only three occupations—footballer, doctor, and police officer—were popular among both genders. Girls preferred people- or animal-centered roles, while boys leaned toward jobs involving “things” (p < 0.001). Girls felt they could pursue similar careers as boys, but boys showed more skepticism (p < 0.001). Influence patterns also varied by gender: 25% of girls were inspired by mothers, while 45% of boys were inspired by fathers (p = 0.02). Beyond immediate family, girls often sought career information from acquaintances, while boys turned to media (p < 0.001). STEM interest was limited, with “game developer” being the only STEM job on boys’ lists. Additionally, a larger proportion of boys ranked STEM subjects among their top 10 favorite school subjects, while girls preferred crafts, art, and English (p < 0.001).Discussion: These findings highlight the need for early, unbiased, evidence-based career interventions and policies to broaden children’s awareness of diverse job options and opportunities in the labor market.",2504284X,EDUCATION
10.1186/s40594-024-00521-3,How gamification boosts learning in STEM higher education: a mixed methods study,"The demand for professionals with expertise in Science, Technology, Engineering, and Mathematics (STEM) continues to grow. To meet this demand, universities are actively seeking strategies to engage more students in STEM disciplines and improve their learning outcomes. One promising approach is gamification, specifically using leaderboards. This study investigates the impact of leaderboard-based gamification on the learning performance of 175 students in a calculus course, with a focus on the mediating roles of autonomous motivation and self-efficacy, as well as potential moderating factors such as gender and gaming experience. A mixed-method research approach was employed, combining a pretest–posttest quasi-experimental design with nine qualitative interviews. A significant improvement in learning performance for students in the gamified condition was observed. However, no significant effects were found related to the mediating variables. Qualitative analysis supported these findings, revealing that students did not perceive an increase in autonomy within the gamified condition, and instead, themes of controlled motivation were prevalent. While the leaderboard provided a sense of achievement for most participants, the quantitative analysis did not show a strong correlation between self-efficacy and learning performance. This study suggests that leaderboard-based gamification can enhance learning performance in calculus courses at the university level. However, the findings highlight the importance of careful gamification design, particularly in how different game elements influence students' motivational aspects.",21967822,EDUCATION
10.3389/fonc.2024.1498524,Characterizing microbial communities and their correlation with genetic mutations in early-stage lung adenocarcinoma: implications for disease progression and therapeutic targets,"Background: Lung adenocarcinoma (LUAD), the most prevalent form of lung cancer. The transition from adenocarcinoma in situ (AIS), and minimally invasive adenocarcinoma (MIA) to invasive adenocarcinoma (IAC) is not fully understood. Intratumoral microbiota may play a role in LUAD progression, but comprehensive stage-wise analysis is lacking.Methods: Tumor and bronchoalveolar lavage fluid (BALF) samples from patients with AIS/MIA or IAC were collected for next-generation sequencing to characterize microbial diversity and composition. DNA extraction involved lysing samples with nuclease and protease, followed by homogenization and elution. Sequencing libraries were prepared and sequenced on the Illumina platform. Whole exome sequencing was performed to identify somatic mutations and genetic variants. Bioinformatics analysis, including taxonomic annotation with Kraken2 and de novo assembly with MEGAHIT, was conducted to process metagenomic data. Correlation analysis was performed to link microbial species with mutated genes using custom R scripts.Results: Metagenomic analysis revealed a distinct microbial profile in IAC compared to AIS/MIA, with increased abundance of Bacteroidetes and Firmicutes in the IAC group. Bosea sp. and Microbacterium paludicola, were less abundant in IAC, suggesting a potential protective role in early-stage disease. Conversely, Mycolicibacterium species were more prevalent in IAC, indicating a possible contribution to disease progression. Genetic sequencing identified PTPRZ1 strongly correlating with microbial composition, suggesting a mechanistic link between microbiota and genetic alterations in LUAD.Conclusion: This study characterizes microbial communities in various stages of LUAD, revealing links between microbiota and genetic mutations. The unique microbiota suggests its role in LUAD progression and as a therapeutic target.",2234943X,ONCOLOGY
10.3389/feduc.2024.1502396,The sound of science: a sonification learning experience in an Italian secondary school,"Introduction: The present article reports on a case study aimed at improving STEAM education in secondary schools. It discusses the use of sonification as a teaching strategy to integrate music into science learning, using different approaches from data audification to parameter mapping into aural models and to the rewriting of song lyrics based on STEM topics.Methods: A qualitative research study has been performed in a secondary school in the school district of Bari (South of Italy). More specifically, students’ and experts’ perceptions of experienced sonification activities have been collected through six rounds of focus group interviews.Results: While there was a good improvement in student achievement in science, it is worth noting how musical activities also led to some benefits for students involved in the sonification workshops. The integration of music with STEM disciplines has promoted more cooperation and empathy among the students. Additionally, musical inputs can help students discover and regain interest in music. However, the study also highlighted the differences in teacher training and content knowledge, suggesting the need for future research to consider broader samples and experimental designs.Discussion: Results and implications for educational research and practice are discussed considering the recent literature on STEAM. Finally, this study demonstrates the importance of a robust instructional design for sonification activities, so that they can be more effective, aligned with the school curriculum, and integrated into the classroom teaching-learning process.",2504284X,EDUCATION
10.3389/frai.2024.1546421,"Corrigendum: Person-based design and evaluation of MIA, a digital medical interview assistant for radiology","Corrigendum on: Denecke K, Reichenpfader D, Willi D, Kennel K, Bonel H, Nairz K, Cihoric N, Papaux D and von Tengg-Kobligk H (2024) Person-based design and evaluation of MIA, a digital medical interview assistant for radiology. Front. Artif. Intell. 7:1431156. doi: 10.3389/frai.2024.1431156 In the published article, there was an error in the Data Availability statement. We were missing to add the links to the repositories mentioned in the paper. The correct Data Availability statement appears below.",26248212,AI
10.3389/frai.2024.1499530,Robust predictive framework for diabetes classification using optimized machine learning on imbalanced datasets,"Introduction: Diabetes prediction using clinical datasets is crucial for medical data analysis. However, class imbalances, where non-diabetic cases dominate, can significantly affect machine learning model performance, leading to biased predictions and reduced generalization.Methods: A novel predictive framework employing cutting-edge machine learning algorithms and advanced imbalance handling techniques was developed. The framework integrates feature engineering and resampling strategies to enhance predictive accuracy.Results: Rigorous testing was conducted on three datasets—PIMA, Diabetes Dataset 2019, and BIT_2019—demonstrating the robustness and adaptability of the methodology across varying data environments.Discussion: The experimental results highlight the critical role of model selection and imbalance mitigation in achieving reliable and generalizable diabetes predictions. This study offers significant contributions to medical informatics by proposing a robust data-driven framework that addresses class imbalance challenges, thereby advancing diabetes prediction accuracy.",26248212,AI
10.3389/fpsyg.2024.1496140,Comprehensibility of gender-fair language in German-language video lectures,"In many languages, it is common to use masculine-only forms when all genders are meant or gender is irrelevant to the actual statement. This practice is criticized for making women and members of other genders, their achievements and interests, less visible. Gender-fair language is intended to represent all genders equally. Recently introduced forms such as the glottal stop and the gender star are intended to also represent people outside the male–female dichotomy on the linguistic surface. However, it is often argued that gender-fair language would make texts less comprehensible and less aesthetically appealing. The critics’ assumptions were tested in an experiment with 272 participants. Subjects watched a screencast on self-regulated learning and were randomly assigned to either a version using masculine-only forms or a version using the glottal stop and the gender star. Subsequently, participants rated the comprehensibility and aesthetic appeal of the video they had watched. Structural equation models show no statistically significant influence of the use of gender-fair language on the comprehensibility (β = −0.13) or the aesthetic appeal (β = −0.16) of the videos. The critics’ assumptions are therefore not supported. But further studies are needed, especially regarding the corresponding singular forms and with non-academic participants.",16641078,PSYCHOLOGY
10.3389/fpsyg.2024.1354545,Assessing self-determined motivation for drinking alcohol via the Comprehensive Relative Autonomy Index for Drinking,"Introduction: Self-Determination Theory (SDT) examines human motivation in multiple domains; however, the only existing measure assessing SDT-informed behavioral regulations for drinking focuses on responsible drinker behaviors, rather than drinking per se, which is important given the alignment between SDT and harm reduction approaches to alcohol use. The aim of this study was to test the structural validity of the SDT-informed Comprehensive Relative Autonomy Index for Drinking (CRAI-Drinking) among college students.Methods: Participants included two convenience samples with a total of 630 adult drinkers (Mage = 21.5, 55% female, 88% undergraduates). Participants rated drinking behavioral regulations on the 24 original CRAI-Drinking items on a 5-point Likert Scale. Multi-dimensional scaling analyses and factor analyses were used to investigate the underlying autonomy continuum and factor structure of the CRAI-Drinking.Results: In Sample 1 (n = 274), multi-dimensional scaling analyses confirmed that CRAI-Drinking item and subscale order aligned with SDT's autonomy continuum. Confirmatory factor analyses supported a five factor, 19-item model of the CRAI-Drinking with factors for intrinsic, identified, positive introjected, external, and amotivation regulations (Cronbach's α: 0.68–0.85). In Sample 2 (n = 356), a confirmatory factor analysis confirmed that the 19-item model fit was comparable to Sample 1.Discussion: This study provides evidence for the structural validity of CRAI-Drinking scores for assessing SDT-based behavioral regulations for drinking in adults.",16641078,PSYCHOLOGY
10.3389/frai.2024.1467218,SPEMix: a lightweight method via superclass pseudo-label and efficient mixup for echocardiogram view classification,"Introduction: In clinical, the echocardiogram is the most widely used for diagnosing heart diseases. Different heart diseases are diagnosed based on different views of the echocardiogram images, so efficient echocardiogram view classification can help cardiologists diagnose heart disease rapidly. Echocardiogram view classification is mainly divided into supervised and semi-supervised methods. The supervised echocardiogram view classification methods have worse generalization performance due to the difficulty of labeling echocardiographic images, while the semi-supervised echocardiogram view classification can achieve acceptable results via a little labeled data. However, the current semi-supervised echocardiogram view classification faces challenges of declining accuracy due to out-of-distribution data and is constrained by complex model structures in clinical application.Methods: To deal with the above challenges, we proposed a novel open-set semi-supervised method for echocardiogram view classification, SPEMix, which can improve performance and generalization by leveraging out-of-distribution unlabeled data. Our SPEMix consists of two core blocks, DAMix Block and SP Block. DAMix Block can generate a mixed mask that focuses on the valuable regions of echocardiograms at the pixel level to generate high-quality augmented echocardiograms for unlabeled data, improving classification accuracy. SP Block can generate a superclass pseudo-label of unlabeled data from the perspective of the superclass probability distribution, improving the classification generalization by leveraging the superclass pseudolabel.Results: We also evaluate the generalization of our method on the Unity dataset and the CAMUS dataset. The lightweight model trained with SPEMix can achieve the best classification performance on the publicly available TMED2 dataset.Discussion: For the first time, we applied the lightweight model to the echocardiogram view classification, which can solve the limits of the clinical application due to the complex model architecture and help cardiologists diagnose heart diseases more efficiently.",26248212,AI
10.3389/feduc.2024.1478541,"Play, reflect, cultivate social and emotional learning: a pathway to pre-service teacher SEL through playful pedagogies","Playful pedagogies, rooted in experiential learning, integrate play, humor, spontaneity, and levity to create engaging educational experiences. Playful pedagogies have been shown to support adults' emotional resilience and sense of belonging while reducing stress and anxiety. Despite these benefits, their use in education preparation programs (EPPs) remains underexplored. Given the increasing focus on teacher social and emotional learning (SEL), playful pedagogies hold significant potential for equipping future educators with the skills needed to foster both their own and their students' SEL growth. This paper advocates for a shift in teacher education from predominantly lecture-based instruction to a model that incorporates joy, humor, and experiential learning. We propose integrating playful pedagogies with a reflective learning cycle to enhance SEL competencies among pre-service teachers. Specifically, we introduce a conceptual model that combines a four-level pyramid of playful learning with an iterative reflection process. By integrating playful pedagogy into EPPs, we aim to foster resilience, creativity, and collaboration among future teachers, empowering them to create inclusive learning environments that nurture their students' holistic development.",2504284X,EDUCATION
10.1007/s44196-024-00612-7,Image Registration Using the Arithmetic Optimization Algorithm for Robotic Visual Servoing,"Visual servoing using image registration is a method employed in robotics to control the movement of a system using visual information. In this context, we propose a new intensity-based image registration algorithm (IBIR) that uses information derived from images acquired at different times or from different views to determine the parameters of the geometric transformations needed to align these images. The Arithmetic Optimization Algorithm (AOA) is used to optimize these parameters, minimizing the difference between the images to be aligned. The proposed algorithm, Intensity-Based Image Registration via Arithmetic Optimisation Algorithm (IBIRAOA), is robust to image data fluctuations and perturbations and can avoid local optima. Simulation results prove the importance and efficiency of the proposed algorithm in terms of computation time and similarity of aligned images compared to other methods based on various metaheuristics. In addition, our results confirm a significant improvement in the trajectory of the wheeled mobile robot, thus reinforcing the overall effectiveness of our method in practical navigation and robotic control applications.",18756883,AI
10.3389/feduc.2024.1468747,Innovative assessment based on multimedia proofs and social network sharing for introductory engineering courses,"Training and education quality are crucial worldwide even more in the area of technical vocation. The assessment validates the performance of the training and education process, however, the design of assessments that validate the acquisition of certain knowledge, abilities or competences is still unsolved and remains open for research. In this paper, the advance in new technologies is used in the assessment process in a step ahead. Since social media is a big part of the daily life for lots of students, an assessment method is proposed that uses social media as the learning motivation. In consequence, the proposed assessment method is completely aligned with the student way of life and this fact motivates the student learning process since generating new high impact social media contents is a very challenging task. The paper shows the results of an assessment innovation project in which the authors develop a methodology for evaluating laboratory practices that measures knowledge of introductory concepts in automatic control engineering courses. The innovation aims to actively involve students in the generation of social media resources through modern technologies that are attractive to them. Under this methodology, students are tasked with creating a series of short videos explaining how to solve a specific problem or elucidate a concept covered in theory lessons. These videos are shared with their peers via a social network. Lecturers evaluate videos considering the quality in the explanation of technical concepts and impact in the social network. Results show that the proposed assessment methodology increases student motivation compared to the traditional assessment process and increases marks.",2504284X,EDUCATION
10.3389/frai.2024.1464690,Fostering effective hybrid human-LLM reasoning and decision making,"The impressive performance of modern Large Language Models (LLMs) across a wide range of tasks, along with their often non-trivial errors, has garnered unprecedented attention regarding the potential of AI and its impact on everyday life. While considerable effort has been and continues to be dedicated to overcoming the limitations of current models, the potentials and risks of human-LLM collaboration remain largely underexplored. In this perspective, we argue that enhancing the focus on human-LLM interaction should be a primary target for future LLM research. Specifically, we will briefly examine some of the biases that may hinder effective collaboration between humans and machines, explore potential solutions, and discuss two broader goals—mutual understanding and complementary team performance—that, in our view, future research should address to enhance effective human-LLM reasoning and decision-making.",26248212,AI
10.3389/feduc.2024.1505020,Democracy is at risk: beliefs of Chilean teachers about the transmission of hate speech in teacher education,"Conversations about hate speech are a complex issue. It is not a new problem; on the contrary, society has been confronted with hate speech against specific communities at different moments. The present study aims to investigate the beliefs of Chilean teachers working in teacher education and their relationship with hate speech that may have occurred in their practice. The methodology was quantitative. The participants were 200 teachers. The data collection instrument was a survey to determine teachers’ beliefs. The results showed that teachers expressed concern about the problem and stated that action must be taken to combat hate speech. At the same time, they argued that their colleagues perpetuate and reproduce hate speech in their practice, which is also a complex situation that needs to be addressed. Finally, there is also a controversy about the limits of freedom of expression.",2504284X,EDUCATION
10.3389/frai.2024.1472411,The sociolinguistic foundations of language modeling,"In this article, we introduce a sociolinguistic perspective on language modeling. We claim that language models in general are inherently modeling varieties of language, and we consider how this insight can inform the development and deployment of language models. We begin by presenting a technical definition of the concept of a variety of language as developed in sociolinguistics. We then discuss how this perspective could help us better understand five basic challenges in language modeling: social bias, domain adaptation, alignment, language change, and scale. We argue that to maximize the performance and societal value of language models it is important to carefully compile training corpora that accurately represent the specific varieties of language being modeled, drawing on theories, methods, and descriptions from the field of sociolinguistics.",26248212,AI
10.3389/fpsyg.2024.1502222,Relationship between physical activity and college students’ life satisfaction: the chain mediating effect of psychological resilience and negative emotions,"Objective: As the academic pressure, employment competition and mental health problems faced by college students are becoming more and more prominent, paying attention to and improving the quality of life and well-being of college students has become an important issue of widespread concern in all walks of life. This study focuses on the correlation between physical activity and college students’ life satisfaction.Methods: A cross-sectional survey method was applied to 326 college students, using the Physical Activity Rating Scale, the Psychological Resilience Scale, the Depression-Anxiety-Stress Scale, and the Life Satisfaction Scale. For data analysis, demographic analysis of variance, correlation analysis, and chain mediating effect test were conducted sequentially.Results: There were significant differences in psychological resilience, negative emotions, and life satisfaction by gender, and psychological resilience by grade level; there were significant correlations between physical activity and psychological resilience, negative emotions, and life satisfaction among college students (r = 0.541, p < 0.001; r = −0.379, p < 0.001; r = 0.435, p < 0.001); and psychological resilience, negative emotions had significant mediating and chain mediating effects between physical activity and life satisfaction, where the mediating effect of psychological resilience was significantly stronger than the mediating effect of negative emotions and the chain mediating effect of both.Conclusion: There was a correlation between physical activity and life satisfaction among college students, and this relationship was partially mediated by psychological resilience and negative emotions.",16641078,PSYCHOLOGY
10.3389/frai.2024.1450477,Clinical entity-aware domain adaptation in low resource setting for inflammatory bowel disease,"The digitization of healthcare records has revolutionized medical research and patient care, with electronic health records (EHRs) containing a wealth of structured and unstructured data. Extracting valuable information from unstructured clinical text presents a significant challenge, necessitating automated tools for efficient data mining. Natural language processing (NLP) methods have been pivotal in this endeavor, aiming to extract crucial clinical concepts embedded within free-form text. Our research addresses the imperative for robust biomedical entity extraction, focusing specifically on inflammatory bowel disease (IBD). Leveraging novel domain-specific pre-training and entity-aware masking strategies with contrastive learning, we fine-tune and adapt a general language model to be better adapted to IBD-related information extraction scenarios. Our named entity recognition (NER) tool streamlines the retrieval process, supporting annotation, correction, and visualization functionalities. In summary, we developed a comprehensive pipeline for clinical Dutch NER encompassing an efficient domain adaptation strategy with domain-aware masking and model fine-tuning enhancements, and an end-to-end entity extraction tool, significantly advancing medical record curation and clinical workflows.",26248212,AI
10.3389/fpsyg.2024.1546881,Editorial: (Ir)Relevance in education: individuals as navigators of dynamic information landscapes,"Involve (1) surface features, such as colour or shape, (2) visual/auditory/tactile attractiveness, (3) information source, (4) intrinsic and extraneous cognitive load (i.e., the load induced by the complexity of the learning materials and the instruction-induced load, respectively; Chen et al., 2023), and (5) the relationships between concurrently available components of information (e.g., the foreground to the background, the colorful to the black-and-white). The individual-level processes rely on (1) individual goals and meaning ascribed to given information, (2) cognitive processes such as stimulus-driven (bottom-up) and goal-directed (top-down) attention, working memory, and longterm memory, (3) germane cognitive load (the amount of cognitive resources, e.g., working memory, devoted to the task at hand; Korbach et al., 2017), (4) metacognitive processes, (5) previous experience, (6) affect, (7) motivation, and ( 8) attitudes. The context of information relevance comprises a myriad of features that are not embedded within the goal-driven activity, but nevertheless influence individual performance, such as (1) time constraints and (2) the sociocultural background of learners, teachers, and researchers. Of note, information relevance changes dynamically, that is, hinges not only on individual goals, but also on the outcomes of individual actions that preceded the present instance in which the individual is judging information relevance.Numerous theoretical accounts of information relevance were conceived over the last century of psychological, educational, and computer science research, spanning decision making and judgment, attention and memory, critical information literacy, problem solving, and other. Some of these accounts, such as Cognitive Load Theory (Sweller, 2011), Self-Regulated Learning (Panadero, 2017), Leont'ev's Activity Theory (Leont'ev, 1979), or Cognitive-Affective Theory of Learning with Media (Moreno, 2005), guided the research presented in the Research Topic, partly overlapping with Figure 1. To our best knowledge, however, no theory has, to date, comprehensively accounted for all aspects of information relevance. Hopefully, the present Editorial and the Research Topic will inspire drafting and testing such novel, comprehensive theories that are yet to be developed.The Désiron and Schneider examined how high school and university students responded to colorful design when dealing with relevant information. The study built upon the Cognitive Load Theory, the Cognitive-Affective Theory of Learning with Media, and the Emotional Design Hypothesis to assess whether colorful design correlated with higher learning outcomes, and whether contrasting colors further lowered cognitive load. The results suggested that colorful designs indeed correlated with higher performance, and that color contrast lowered the participant-perceived extraneous but not the intrinsic cognitive load.Greeves and Oz looked into differences in relevance judgments of YouTube videos between college instructors and students. Despite several similarities across groups, such as prioritizing video accuracy, content creators' expertise, or video duration, the students seemed to value additional features that would suggest community support for the content and the creator far more than the instructors.Leclerq et al. employed analogical card sorting tasks to examine whether 4-to 6-year-old preschoolers could learn to use self-cueing strategies such as labeling and pointing to transfer rules across these tasks. In line with expectations, children trained on such strategies were more likely to spontaneously use them on the analogical task.Lederer et al. assessed judging relevance of anecdotal, correlational, and experimental evidence in causal reasoning in preservice teachers and psychology students. Despite typical differences in methodological training across educational and psychological study programs, the authors found comparable performance levels across the two groups.Rhodes et al. offered a new perspective on relevance of problem solving tasks by highlighting the importance of sociocultural factors on the researcher's and the participant's side. The authors recommended a checklist for researchers who wish to develop new problem solving tasks.(""what?""), subject (""for whom?""), asserter (""according to whom?), and a purpose (""to what end?"") when examining the relevance of learning key mathematical concepts for high school students. Despite initial low levels of self-perceived relevance of such concepts, the students who participated in the study were shown to assert the relevance of the key concepts after learning about real-life applications and using their own imagination.The present Research Topic offers a broad outlook on information relevance judgments in educational and professional settings, but it suffered some limitations. Future research on information relevance should aim at developing comprehensive theoretical frameworks of information relevance, increasingly involve both young and aging participants, not only students and beginner professionals, and foster relevant collaborations beyond the WEIRD context.",16641078,PSYCHOLOGY
10.3389/fonc.2024.1470824,Radiomics in rectal cancer: current status of use and advances in research,"Rectal cancer is a leading cause of morbidity and mortality among patients with malignant tumors in China. In light of the advances made in therapeutic approaches such as neoadjuvant therapy and total mesorectal excision, precise preoperative assessment has become crucial for developing a personalized treatment plan. As an emerging technology, radiomics has gained widespread application in the diagnosis, assessment of treatment response, and analysis of prognosis for rectal cancer by extracting high-throughput quantitative features from medical images. Radiomics thus demonstrates considerable potential for optimizing clinical decision-making. In this paper, we reviewed recent research focusing on advances in the use of radiomics for managing rectal cancer. The review covers TNM staging of tumors, assessment of neoadjuvant therapy outcomes, and survival prediction. We also discuss the challenges and prospects for future developments in translational medicine, particularly the need for data standardization, consistent feature extraction methodologies, and rigorous model validation.",2234943X,ONCOLOGY
10.3389/frai.2025.1481338,Machine learning techniques for predicting neurodevelopmental impairments in premature infants: a systematic review,"Background and objective: Very preterm infants are highly susceptible to Neurodevelopmental Impairments (NDIs), including cognitive, motor, and language deficits. This paper presents a systematic review of the application of Machine Learning (ML) techniques to predict NDIs in premature infants.Methods: This review presents a comparative analysis of existing studies from January 2018 to December 2023, highlighting their strengths, limitations, and future research directions.Results: We identified 26 studies that fulfilled the inclusion criteria. In addition, we explore the potential of ML algorithms and discuss commonly used data sources, including clinical and neuroimaging data. Furthermore, the inclusion of omics data as a contemporary approach employed, in other diagnostic contexts is proposed.Conclusions: We identified limitations and emphasized the significance of employing multimodal data models and explored various alternatives to address the limitations identified in the reviewed studies. The insights derived from this review guide researchers and clinicians toward improving early identification and intervention strategies for NDIs in this vulnerable population.",26248212,AI
10.3389/feduc.2024.1416255,Hispanic-serving HBCUs: towards an anti-colonial meso-relevant theory of organizational identity in sacred spaces of Black education,"Introduction: This study addresses demographic changes at HBCUs and proposes an anti-colonial organizational framework for Historically Black emerging Hispanic Serving Institutions (HB-eHSIs, also referred to as Hispanic-serving HBCUs) to support both Black and Brown students while preserving the historic mission of HBCUs.Methods: We use qualitative methodology and rely on 45–60 minute semi-structured interviews with 15 faculty and administrators from three Historically Black emerging HSIs in Texas to develop the proposed organizational framework.Results: Findings are highlighted through four key tenets, each operationalized based on themes from extant literature and the practices and organizational logics of Black and Brown faculty and staff at HBeHSIs: 1. Tending to white settler colonialism, 2. Tending to fiscal precarity, 3. Tending to sacred spaces, 4. Tending to fallacious notions of essentialism.Discussion: The proposed framework aims to foster solidarity between Black and Brown students and challenge oppressive systems through a radically inclusive approach to serving both communities. Recommendations include reexamining leadership structures, forming coalitions, and creating consortiums to support HBCUs’ evolving needs and diverse student populations. Findings also emphasize the need for dual federal designation for HB-eHSIs to secure funding and legitimacy.",2504284X,EDUCATION
10.1186/s40594-025-00526-6,Exploring how course social and cultural environmental features influence student engagement in STEM active learning courses: a control–value theory approach,"Background: Active learning, on average, increases student performance in STEM courses. Yet, there is also large variation in the effectiveness of these implementations. A consistent goal of active learning is moving students towards becoming active constructors of their knowledge. This emphasis means student engagement is of central importance. Thus, variation in student engagement could help explain variation in outcomes from active learning. In this study, we employ Pekrun’s Control–Value Theory to examine the impact of four aspects of course social and cultural environments on student engagement. This theory posits that social and cultural features of the course environment influence students’ appraisals of their ability to control their academic outcomes from the course and the value they see in those outcomes. Control and value in turn influence the emotions students experience in the course and their behaviors. We selected four features of the course environment suggested in the literature to be important in active learning courses: course goal structure, relevance of course content, students’ trust in their instructor, and perceived course competition. Results: We surveyed students in 13 introductory STEM courses. We used structural equation modeling to map how features of the course environment related to control, value, and academic emotions, as well as how control, value, and academic emotions influenced engagement. We found engagement was positively related to control and value as well as the emotion of curiosity. Engagement was negatively related to the emotion of boredom. Importantly, features of the course environment influenced these four variables. All features influenced control: goal structure, relevance, and instructor trust increased it, while competition decreased it. All features except competition were related positively to value. Relevance and instructor trust increased curiosity. Goal structure, relevance, and instructor trust all reduced boredom, while competition increased it. Conclusion: Overall, our study suggests that the way instructors structure the social and cultural environment in active learning courses can impact engagement. Building positive instructor–student relationships, reducing course competition, emphasizing mastery and the relevance of the course to students can all increase engagement in course activities.",21967822,EDUCATION
10.3389/fonc.2024.1502185,Trifluridine/tipiracil regimen in combination with bevacizumab for metastatic colorectal cancer in the third line: an expert opinion,"The prolongation of survival along with the preservation of quality of life, possibly avoiding harmful cumulative toxicities, is the primary therapeutic aim for patients with metastatic colorectal cancer (mCRC) in the third-line setting. Several therapeutic options are now available, although some differences across countries in drug approval and the optimal therapeutic sequencing associated with each peculiar patient subgroup represent a clinical challenge for oncologists. Among various options, the SUNLIGHT trial showed how the combination of trifluridine/tipiracil (FTD/TPI) with bevacizumab is effective with an easily manageable toxicity profile compared to FTD/TPI alone. Of note, the efficacy is confirmed independently from KRAS mutational status and also for patients who had breaks in anti-vascular endothelial growth factor (anti-VEGF) therapy. Herein, we describe the current state of the art in the landscape of treatments after the second progression in mCRC. Based on a critical review of the literature aimed to guide clinicians in their daily decision-making, we point out that the combination of FTD/TPI with bevacizumab produces a clinical benefit in unselected mCRC patients. Therefore, the FTD/TPI plus bevacizumab regimen can represent a new standard of care for the treatment of patients with refractory mCRC who have progressed after two lines of therapy.",2234943X,ONCOLOGY
10.3390/ai6020022,Just-in-Time News: An AI Chatbot for the Modern Information Age,"This study advances AI-powered news delivery by introducing an innovative chatbot capable of providing personalized news summaries and real-time event analysis. This approach addressed a critical gap identified through a comprehensive review of 52 AI chatbot studies. Unlike prior models limited to static information retrieval or predefined interactions, this chatbot harnesses generative AI and real-time data integration to deliver a dynamic and tailored news experience. Its unique architecture combines conversational AI, robotic process automation (RPA), a comprehensive news database (989,432 reports from 2342 sources spanning 27 October 2023 to 30 September 2024), and a large language model (LLM). Within this architecture, LLM generates dynamic queries against the News database for obtain tailored News for the users. Hence, this approach interprets user intent, and delivers LLM-based summaries of the fetched tailored news. Empirical testing with 35 users across 321 diverse news queries validated its robustness in navigating a combinatorial classification space of 53,916,650 potential news categorizations, achieving an F1-score of 0.97, recall of 0.99, and precision of 0.96. Deployed on Microsoft Teams and as a standalone web app, this research lays the foundation for transformative AI applications in news analysis, promising to revolutionize news consumption and empower a more informed citizenry.",26732688,AI
10.3389/frai.2024.1428716,Ocular Biometry OCR: a machine learning algorithm leveraging optical character recognition to extract intra ocular lens biometry measurements,"Given close relationships between ocular structure and ophthalmic disease, ocular biometry measurements (including axial length, lens thickness, anterior chamber depth, and keratometry values) may be leveraged as features in the prediction of eye diseases. However, ocular biometry measurements are often stored as PDFs rather than as structured data in electronic health records. Thus, time-consuming and laborious manual data entry is required for using biometry data as a disease predictor. Herein, we used two separate models, PaddleOCR and Gemini, to extract eye specific biometric measurements from 2,965 Lenstar, 104 IOL Master 500, and 3,616 IOL Master 700 optical biometry reports. For each patient eye, our text extraction pipeline, referred to as Ocular Biometry OCR, involves 1) cropping the report to the biometric data, 2) extracting the text via the optical character recognition model, 3) post-processing the metrics and values into key value pairs, 4) correcting erroneous angles within the pairs, 5) computing the number of errors or missing values, and 6) selecting the window specific results with fewest errors or missing values. To ensure the models’ predictions could be put into a machine learning-ready format, artifacts were removed from categorical text data through manual modification where necessary. Performance was evaluated by scoring PaddleOCR and Gemini results. In the absence of ground truth, higher scoring indicated greater inter-model reliability, assuming an equal value between models indicated an accurate result. The detection scores, measuring the number of valid values (i.e., not missing or erroneous), were Lenstar: 0.990, IOLM 500: 1.000, and IOLM 700: 0.998. The similarity scores, measuring the number of equal values, were Lenstar: 0.995, IOLM 500: 0.999, and IOLM 700: 0.999. The agreement scores, combining detection and similarity scores, were Lenstar: 0.985, IOLM 500: 0.999, and IOLM 700: 0.998. IOLM 500 was annotated for ground truths; in this case, higher scoring indicated greater model-to-annotator accuracy. PaddleOCR-to-Annotator achieved scores of detection: 1.000, similarity: 0.999, and agreement: 0.999. Gemini-to-Annotator achieved scores of detection: 1.000, similarity: 1.000, and agreement: 1.000. Scores range from 0 to 1. While PaddleOCR and Gemini demonstrated high agreement, PaddleOCR offered slightly better performance upon reviewing quantitative and qualitative results.",26248212,AI
10.1186/s40359-024-02297-1,Boy’s love fans versus non-fans in the sexual identity and neural response in the digital age’s young females,"With the omnipresence of online social media, Boys’ Love (BL) culture has found a burgeoning audience among young females. However, we know very little about the audience of this online cultural phenomena, also the potential implications of BL culture to female remain under-explored. Study 1 conducted a survey to investigate the BL audience’s demography data and attitudes to homosexual ect. The results of the questionnaire analysis showed that the sexual orientation and psychological gender of the female BL audiences are more diverse. In addition, we also find the audience spend a lot of time on BL. Study 2 focused on the BL senior fans to explore the neural and behavioral response of female while looking at Boys’ Love(BL) stimuli and Heterosexual love stimuli by fNIRS. Behavioral results showed that there was no main effect of reaction time and accuracy between the BL-fans and non-BL-fans. Neural results confirmed that the Oxy-Hb responses for BL-love stimuli in BL-fans was significantly lower than the non-BL-fans. In addition, the interaction effect showed that the Oxy-Hb responses was significantly higher for BL-love stimuli than for heterosexual love stimuli in non-BL-fans, and no difference was found in BL-fans. This finding, maybe along with the discovery that the more pornography a person was exposed to, the higher the brain dopamine threshold, and the subsequent weakening of the neural response to sexual stimulation. The research leads to the conclusion that long term exposed to Boys’ Love may decrease the reward sensitivity to BL stimuli and weakens the brain’s response of the right ventrolateral prefrontal cortex (rVLPFC) to BL stimuli.",20507283,PSYCHOLOGY
10.3389/fpsyg.2024.1515406,Identification of stress factors in returning migrants in Latvia,"This study investigates the psychological stress factors faced by return migrants before, during, and after their return to Latvia. Employing a Grounded Theory methodology, we conducted in-depth interviews with 21 return migrants and identified five key themes: pre-return context, identity, perceived social support, psychological wellbeing, and factors that help or hinder re-adjustment. Notably, psychological stress prior to return often exceeds post-return stress, highlighting the critical yet understudied pre-return phase. Key contributors to return migration stress include unmet expectations, feelings of alienation, identity struggles, and inadequate institutional support. By highlighting these stress factors, this research not only enhances the understanding of return migration from a psychological standpoint but also lays the foundational groundwork for the development of a comprehensive theoretical framework that encompasses a broader spectrum of factors influencing return migration stress. The study advocates for a holistic approach to supporting return migrants, emphasizing the integration of psychological resources with practical assistance to foster successful reintegration into their home country.",16641078,PSYCHOLOGY
10.3389/frai.2024.1496066,"Cyberinfrastructure for machine learning applications in agriculture: experiences, analysis, and vision","Introduction: Advancements in machine learning (ML) algorithms that make predictions from data without being explicitly programmed and the increased computational speeds of graphics processing units (GPUs) over the last decade have led to remarkable progress in the capabilities of ML. In many fields, including agriculture, this progress has outpaced the availability of sufficiently diverse and high-quality datasets, which now serve as a limiting factor. While many agricultural use cases appear feasible with current compute resources and ML algorithms, the lack of reusable hardware and software components, referred to as cyberinfrastructure (CI), for collecting, transmitting, cleaning, labeling, and training datasets is a major hindrance toward developing solutions to address agricultural use cases. This study focuses on addressing these challenges by exploring the collection, processing, and training of ML models using a multimodal dataset and providing a vision for agriculture-focused CI to accelerate innovation in the field.Methods: Data were collected during the 2023 growing season from three agricultural research locations across Ohio. The dataset includes 1 terabyte (TB) of multimodal data, comprising Unmanned Aerial System (UAS) imagery (RGB and multispectral), as well as soil and weather sensor data. The two primary crops studied were corn and soybean, which are the state's most widely cultivated crops. The data collected and processed from this study were used to train ML models to make predictions of crop growth stage, soil moisture, and final yield.Results: The exercise of processing this dataset resulted in four CI components that can be used to provide higher accuracy predictions in the agricultural domain. These components included (1) a UAS imagery pipeline that reduced processing time and improved image quality over standard methods, (2) a tabular data pipeline that aggregated data from multiple sources and temporal resolutions and aligned it with a common temporal resolution, (3) an approach to adapting the model architecture for a vision transformer (ViT) that incorporates agricultural domain expertise, and (4) a data visualization prototype that was used to identify outliers and improve trust in the data.Discussion: Further work will be aimed at maturing the CI components and implementing them on high performance computing (HPC). There are open questions as to how CI components like these can best be leveraged to serve the needs of the agricultural community to accelerate the development of ML applications in agriculture.",26248212,AI
10.3389/fpsyg.2024.1458460,The impact of artistic sports on academic self-efficacy,"Introduction: Artistic sports have a more positive impact on adolescents on the basis of basic sports. This study delves into the beneficial effects of Artistic sports compared to basic sports in enhancing academic self-efficacy in college students, and investigates the mediating roles of mindfulness, social anxiety, and academic procrastination in this process.Methods: A questionnaire survey was conducted among students in some universities in Gansu Province, collecting a total of 1,976 online questionnaires, including 263 males and 1,713 females, with 1,543 participants in Artistic sports courses and 433 participants in basic sports. Data processing was carried out using SPSS 26.0 software and its plugin PROCESS.Results: The analysis results indicate significant differences in mindfulness, social anxiety, academic procrastination, and academic self-efficacy among different types of sports training (ps < 0.05); significant correlations were found among all variables (ps < 0.001). Sports training types can directly predict academic self-efficacy (β = 0.069, t = 3.155, p < 0.01), further confirming that sports training types can directly predict academic self-efficacy. Moreover, mindfulness, social anxiety, and academic procrastination play a chain mediating role between Artistic sports and academic self-efficacy.Discussion: These findings highlight the potential value of Artistic sports in enhancing academic self-efficacy and provide practical guidance for education policymakers, school administrators, teachers, parents, and students to promote adolescent academic and psychological health development. It is recommended to enhance the promotion and training of Artistic sports.",16641078,PSYCHOLOGY
10.3389/frai.2024.1488359,Commentary: Implications of causality in artificial intelligence,"Luís Cavique's (2024) article, ""Implications of Causality in Artificial Intelligence,"" presents a compelling case for the importance of causalAI. By focusing on cause-and-effect relationships rather than mere correlations, causalAI offers a pathway to more transparent, fair, and reliable AI systems. Cavique argues that causalAI is the least criticized approach compared to responsible AI, fair AI, and explainable AI, largely due to its scientific rigor and potential to reduce biases. However, despite its promise, causalAI is not without challenges. This commentary aims to assess some of these limitations and potential criticisms of causalAI as presented by Cavique, arguing that while it holds substantial promise, its implementation and practical application may be more complex and fraught with difficulties than the author suggests.One of the primary challenges with causalAI lies in its complexity. CausalAI requires a deep understanding of causal inference and advanced statistical techniques, making it less accessible to most AI developers (Cox Jr., 2023). Unlike correlation-based methods, which are widely understood and now relatively easy to implement, causal models demand a high level of expertise. Arguably, only a select group of experts can effectively design, implement, and interpret these models. This complexity can create barriers to entry for many organizations and individuals who might want to engage in developing or using causalAI for benefiting from the transparency and fairness that causalAI promises. This could exacerbate existing disparities in AI literacy, and capacitation, and epistemic justice, potentially leading to an increased form of AI elitism, where only those with advanced skills, knowledge, and wealth of resources can fully participate in or critique causalAI development. This situation could undermine the broader goal of making its benefits accessible to a wide audience.CausalAI's reliance on high-quality, detailed data presents another significant challenge. Establishing causal relationships requires data that not only captures correlations but also provides the context needed to infer causality (Vallverdú, 2024). In many real-world applications, such data is either unavailable or prohibitively expensive to obtain. Causal AI requires high-quality data that captures both correlations and context (Vallverdú, 2024). In practice, such data is often scarce or costly, posing challenges for establishing accurate causal relationships Additionally, even when data is available, it may be incomplete or biased in ways that could skew causal inferences. The assumptions underlying causal models also warrant critical examination. CausalAI models often assume that all relevant variables have been identified and correctly measured. However, in practice, unmeasured confounders-variables that influence both the cause and effect-can distort causal estimates, leading to incorrect conclusions and as Rawal et al (2024) put it there is a lack of ground truth for validation. This reliance on potentially faulty assumptions could result in AI systems that, while appearing transparent and fair, are actually based on flawed reasoning. Furthermore, the process of identifying and validating causal relationships can be resource intensive and time-consuming. This raises questions about the scalability of causalAI, particularly in dynamic environments where data is constantly evolving, and causal relationships may shift over time. The effort required to maintain accurate causal models could outweigh the benefits, especially in fast-paced industries where quick decision-making is critical.Scalability is a major challenge for causal AI, as building and validating models is complex and resource-intensive. These models often require tailored adjustments for new contexts, limiting their generalizability compared to correlation-based methods. Scalability is a crucial consideration in the deployment of AI systems, and causalAI may struggle in this area. The process of building and validating causal models is not only complex, but also resource-intensive. As Cavique rightly notes, causalAI requires meticulous identification of causal variables and relationships, which may not easily generalize across different contexts or applications, particularly in sectors requiring a major data curation effort (such as the healthcare sector). This limitation could hinder the practical application of causalAI in scenarios where scalability and adaptability are key. Specificity required by causal models may limit their ability to generalize across different datasets or environments. While correlation-based models can often be applied broadly with minimal adjustments, causal models may need to be tailored to the particularities of each new situation. This lack of generalizability could make causalAI less appealing in settings where adaptability is needed.CausalAI is lauded for its potential to improve fairness and transparency in AI systems, but these benefits are not guaranteed. The causal relationships identified by AI systems are not immune to the biases present in the underlying data. If the data reflects existing societal biases or power dynamics, the causal models derived from it may inadvertently reinforce these issues. Put more Even when accurately identifying cause-and-effect relationships, they may perpetuate societal biases, potentially reinforcing inequities if not designed inclusively.simply, a causal model trained on biased data might correctly identify a causal relationship but still perpetuate unjust outcomes. Moreover, the iInterpretation of causal models can be influenced by the subjective perspectives of those designing or using them (Mittelstadt et al., 2019)-especially if the design of CausalAI is not inclusive and transparent, allowing for the active participation of stakeholders. This subjectivity introduces another layer of potential bias, as different stakeholders may have...",26248212,AI
10.3389/frai.2025.1506042,Gaussian process latent variable models-ANN based method for automatic features selection and dimensionality reduction for control of EMG-driven systems,"Electromyography (EMG) signals have gained significant attention due to their potential applications in prosthetics, rehabilitation, and human-computer interfaces. However, the dimensionality of EMG signal features poses challenges in achieving accurate classification and reducing computational complexity. To overcome such issues, this paper proposes a novel approach that integrates feature reduction techniques with an artificial neural network (ANN) classifier to enhance the accuracy of high-dimensional EMG classification. This approach aims to improve the classification accuracy of EMG signals while substantially reducing computational costs, offering valuable implications for all EMG-related processes on such data. The proposed methodology involves extracting time and frequency domain features from twelve channels of EMG signals, followed by dimensionality reduction using techniques such as PCA, LDA, PPCA, Lasso and GPLVM, and classification using an ANN. Our investigation revealed that LDA is not appropriate for this dataset. The dimensionality reduction models did not have any significant effect on the accuracy, but the computational cost decreased significantly. In individual comparisons, GPLVM had the shortest computational time (29 s), which was significantly less than that of all the other models (p < 0.05), with PCA following at approximately 35 s and Relief at approximately 57 s, while PPCA took approximately 69 s, and Lasso exhibited higher computational costs than all the models but lower computational costs than did the original set. Using the best-performing features, all possible sets of 2, 3, 4 and 5 features were tested, and the 5-feature set exhibited the best performance. This research demonstrates the effectiveness of dimensionality reduction and feature selection in improving the accuracy of movement recognition in myoelectric control.",26248212,AI
10.3389/frai.2025.1518850,Application of human-in-the-loop hybrid augmented intelligence approach in security inspection system,"A security inspection system exemplifies human-machine collaboration, and enhancing its safety and reliability through advanced technology remains a key research priority. While deep learning has incrementally improved the autonomous capabilities of security inspection equipment for automatic contraband detection, a gap persists between current technological capabilities and practical implementation. Recognizing that humans excel at learning, reasoning, and collaborating, while artificial intelligence offers normative, repeatable, and logical processing, we propose a human-in-the-loop hybrid augmented intelligence approach. This approach addresses the practical needs of security inspection systems by introducing a hybrid decision-making method that leverages two distinct strategies: “Reject-priority” and “Clear-priority.” These strategies play complementary roles in bolstering the decision-making process’s overall performance. Comparative experiments on a dataset from a specific security inspection site confirmed the hybrid method’s effectiveness, drawing several conclusions. This “Hybrid decision-making” method not only enhances risk perception, thereby widening the safety margin of the security inspection system, but also reduces the need for human labor, leading to increased efficiency and reduced labor costs. Additionally, it is less time-consuming, further improving the system’s overall efficiency. By integrating human and machine intelligence, this method significantly boosts decision-making effectiveness. Tailored to their unique characteristics, the method based on “Reject-priority” strategy is particularly well-suited for security inspection scenarios that demand stringent safety protocols, while the “Clear-priority” method is ideal for scenarios with high-volume traffic flow, where efficiency is paramount. As the volume of collected data grows, this approach will enable seamless adaptation of the method to evolving application needs.",26248212,AI
10.1007/s00432-025-06088-y,The role of cGAS-STING pathway in the development of radiation-induced lung injury,"Background and purpose Radiation-induced lung injury (RILI) limits the efficacy of thoracic radiotherapy. However, the underlying mechanism of RILI remains unclear. cGAS-STING pathway is reported to be involved in the recognization of cytosolic dsDNA and various inflammatory diseases. This study aimed to investigate the role of cGAS-STING pathway in the development of RILI. Materials and methods A pre-clinical mouse model of RILI was established by whole thorax irradiation and confirmed using H&E and Masson’s trichrome staining. STING agonist (DMXAA) and antagonist(C-176) were administrated to modulate cGAS-STING pathway in vivo. Western blot and ELISA were used to determine the expression levels of different proteins. Results Quantitation analysis showed dsDNA accumulation in lung tissue and western blot showed the up-regulation of cGAS and STING protein level post-irradiation, indicating pathway activation. Histological evaluation showed that C-176 administration ameliorated radiation-induced pulmonary inflammation and fibrosis, while DMXAA exhibited contrary effects. In further in vitro study, the release of dsDNA induced by radiation led to the activation of cGAS-STING pathway in RAW 264.7 cells, resulting in the polarization into M1 phenotype and pro-inflammatory production. Conclusion In summary, our data demonstrated a link between cGAS-STING pathway and the development of RILI, indicating its potential application in clinic.",14321335,ONCOLOGY
10.3389/frai.2024.1472236,Enhancing Africa’s agriculture and food systems through responsible and gender inclusive AI innovation: insights from AI4AFS network,"The integration of artificial intelligence (AI) technologies into agriculture holds urgent and transformative potential for enhancing food security across Sub-Saharan Africa (SSA), a region acutely impacted by climate change and resource constraints. This paper examines experiences from the Artificial Intelligence for Agriculture and Food Systems (AI4AFS) Innovation Research Network, which provided funding to innovative projects in eight SSA countries. Through a set of case studies, we explore AI-driven solutions for pest and disease detection across crops such as cashew, maize, tomato, and cassava, including a real-time health monitoring tool for Nsukka Yellow pepper. Using participatory design, and key informant interview, robust monitoring and evaluation, and incorporating ethical frameworks, the research prioritizes gender equality, social inclusion, and environmental sustainability in AI development and deployment. Our results demonstrate that responsible AI practices can significantly enhance agricultural productivity while maintaining low carbon footprints. This research offers a unique, localized perspective on AI’s role in addressing SSA’s agricultural challenges, with implications for global food security as demand rises and environmental resources shrink. Key recommendations include establishing robust policy frameworks, strengthening capacity-building efforts, and securing sustainable funding mechanisms to support long-term AI adoption. This work provides the global community, policymakers, and stakeholders with critical insights on establishing ethical, responsible, and inclusive AI practices that can be adapted to similar agricultural contexts worldwide, contributing to sustainable food systems on an international scale.",26248212,AI
10.3389/feduc.2025.1555200,"Editorial: Networks and knowledge brokering: advancing foundations, inviting complexity","Across this special issue, the contributing articles illuminate how knowledge brokerage and relational networks can be harnessed-and sometimes challenged-to strengthen evidenceinformed policy and practice in education. Their findings offer new insights into the interplay of theoretical concepts, methodological approaches, and ethical imperatives that shape this complex terrain. Several contributions highlight the distinctive roles and practices of knowledge brokers. For instance, Malin and Shewchuk (2024) emphasize that knowledge brokers are not merely neutral intermediaries; rather, they are ""actors whose activities and decisions must be understood contextually-e.g., in relation to the communities that are being connected and to brokers' placement within systems"" (p. 3). Similarly, Caduff et al. (2024) explore how brokers' relational ecosystems both broaden and constrain their ability to mobilize resources and facilitate innovation through the strong and weak social ties they cultivate.In pushing beyond conventional frameworks, some articles spotlight relational networks as sites of strategic innovation. Bohannon et al. (2024) demonstrate how boundary infrastructures, such as co-designed professional learning opportunities and flexible organizational routines, help rural districts adapt and learn in dynamic contexts. Turner et al. (2024) extend this line of thought by mapping social networks related to mental health supports in schools. Their analysis reveals how patterns of interaction and trust-building open or close pathways for critical knowledge flows.Equity and ethics also figure prominently. Malin and Shewchuk (2024) advocate for an equity-centered lens, urging brokers to foreground issues of representation, power, and justice in their work. This stance resonates with Friesen and Brown's (2024) exploration of teacherleaders' professional learning, where the growth of confidence and capabilities is tied closely to the careful, context-sensitive design of relational activities that honour diverse perspectives.Methodologically, these studies introduce varied research designs-ranging from social network analysis to in-depth qualitative case studies-that yield a rich understanding of how knowledge moves through and transforms educational ecosystems. Collectively, the articles underscore a need for more approaches that capture complexity rather than oversimplify.In terms of implications, the authors suggest that policymakers, leaders, and practitioners who aim to strengthen ties between research, policy, and practice must attend to the subtleties of relationships, resources, and values. Rather than a technical fix, advancing equitable and impactful knowledge brokerage requires sustained reflection, dialogue, and openness to contextspecific adaptations.In recent years, scholars and practitioners have recognized that addressing complex issues-ranging from mental health supports in schools to rural capacity-building-cannot be achieved by simplistic, top-down evidence dissemination alone. There is a renewed emphasis on building relational infrastructures that acknowledge the multi-level interplay of policies, practices, and diverse forms of expertise (MacKillop et al., 2020). The articles presented in this research topic both reinforce and deepen this perspective. By examining relational ecosystems, boundary infrastructures, and equity-centered approaches, they suggest that knowledge brokerage and relational networks are integral elements of educational change, not just beneficial add-ons. Their collective insights resonate with an emerging scholarship that views relational networks as essential to leveraging complexity and mobilizing knowledge in service of local and global educational aims (Penuel et al., 2020;Rodway et al., 2021).For policymakers and practitioners, these findings imply that designing more flexible, equity-aware systems is crucial. Rather than imposing standardized reforms, leaders might consider strategies such as co-designing professional learning that respects multiple knowledge systems and power differentials. Such approaches can help ensure that local expertise is not overshadowed by distant authorities-a point highlighted when Bohannon et al. (2024) found that ""even the best-intentioned external partners must negotiate shared ownership with rural educators"" (p. XX).For researchers, there is a fertile landscape for future inquiries. Comparative, crossdisciplinary work could elucidate how relational networks evolve in varying socio-political contexts. Longitudinal research might track the lasting impacts of network-based interventions, while other methods-such as critical ethnographies or participatory action research-could surface subtle power imbalances that shape learning processes over time. These studies prompt a renewed attentiveness to the human, relational dimension of educational change. The educational challenges faced worldwide call for approaches to change that value complexity and contextual nuance. By continuing to explore this terrain and by refining methodologies to capture the contours and dimensions of knowledge brokerage in relational networks, educational communities can move closer to realizing meaningful, sustained improvements that are both evidence-informed and locally resonant.",2504284X,EDUCATION
10.3389/feduc.2024.1421716,Spatial and social relevance perceptions by pre-service teachers of learning about oil palm management as a local or nonlocal socioscientific issue,"Introduction: Pre-service teachers (PST)' perceived relevance of learning about environmental socioscientific issues (SSI) can be an indicator for their motivation to act as change agents. Until now, science education (research) has often addressed the relevance for learning about SSI insufficiently differentiated regarding spatial and social dimensions. However, theoretical frameworks suggest that such differentiation enhances meaningful teaching and learning. This study investigated how local, national, and global subdimensions of spatial relevance as well as individual, societal, and professional subdimensions of social relevance influence PST' relevance perceptions of learning about SSI. Additionally, we examined how relevance perceptions vary depending on whether the SSI is local or nonlocal to PST. We specifically investigated Indonesian PST' relevance perceptions of learning about oil palm management (OPM), a local SSI for PST of one university and a nonlocal SSI for PST of two other universities.Methods: The PST participated in a 5-week socioscientific inquiry-based educational unit on OPM in curricular courses (N = 111). We followed a mixed-method approach, employing measurements of utility value. Utility value is a specific construct of perceived relevance, which refers to the usefulness of learning about objects for a person's life, profession, and society. Quantitatively, we conducted pretest-posttest-follow-up surveys on PST' perceived utility value for learning about OPM over time. Qualitatively, we analyzed responses to a utility value reflection task that was integrated into the unit.Results: Overall, the unit increased PST' utility value over time. Local PST perceived lower utility value for learning about OPM than nonlocal PST. In the task responses, local PST referred more to the local subdimension, whereas nonlocal PST referred more to the national subdimension. Nonlocal PST' societal and professional utility value increased stronger over time compared to local PST.Discussion: We discuss potential reasons for local PST' lower relevance perceptions, e.g., personal experiences and skepticism through local embeddedness. Our findings on relevance perceptions among local and nonlocal PST underscore the importance of spatial- and social-sensitive SSI education. We point out practical implications for promoting relevance perceptions considering local and nonlocal PST. Moreover, we suggest research directions for more differentiated relevance research in science education.",2504284X,EDUCATION
10.3389/fpsyg.2024.1463191,Acceptance of sexual attraction and its link to psychological distress and sexual offending among pedohebephilic clients: results from a preliminary analysis,"Introduction: Pedohebephilic disorder is characterized by intense sexual urges or fantasies involving children, which can lead to distress or sexual behavior with children. While theoretical and qualitative accounts suggest that accepting one’s pedohebephilic sexual interests may help mitigate both distress and problematic behaviors, the only published quantitative study to date has linked acceptance with behavior but did not analyze its effect on distress.Methods: We examined the relationship between acceptance of sexual interests and child sexual abuse (CSA), the use of child sexual exploitation material (CSEM), and psychological distress in 238 pedohebephilic and teleiophilic men outside the judicial system (i.e., in the “Dunkelfeld”).Results: Compared to teleiophilic individuals, pedohebephilic individuals showed lower acceptance of their sexual interests. No significant differences were found between groups regarding past sexual offending. In a subsample of 197 pedohebephilic individuals (n = 197), correlations with recent sexual behavior were minimal. In another subsample of pedohebephilic men (n = 84) with data on psychological distress, increased acceptance was associated with decreased psychological distress, although this association weakened among those reporting recent offenses.Discussion: Acceptance of one’s sexual interests is associated with reduced distress in pedohebephilic disorder among non-offending individuals. However, its role among offending individuals remains unclear. Efforts to improve measuring the acceptance of one’s sexual interests and further explore its role in pedohebephilic disorder are warranted.",16641078,PSYCHOLOGY
10.3389/fonc.2025.1500042,Clinical analysis of different intestinal reconstruction methods after primary cytoreductive surgery combined with rectal resection for advanced ovarian cancer,"Objective: To compare different intestinal reconstruction methods after intestinal resection for advanced ovarian malignancy.Methods: Retrospective data of patients with advanced ovarian malignancy were collected and then assigned into three groups: primary intestinal anastomosis, protective enterostomy and colostomy. General clinical characteristics, intraoperative findings and postoperative outcomes were compared between the three groups.Results: A total of 530 cases were included for final analysis. The colostomy group had a lower serum albumin level, larger volume of ascites, higher likelihood of multiple intestinal resections and lower likelihood of rectal resection, lower peritoneal cancer index, more intraoperative blood loss, transfusions and infusions, lower likelihood of optimal cytoreductive surgery and shorter interval time to chemotherapy than the other two groups (p < 0.05). The primary intestinal anastomosis group exhibited a larger blood transfusion volume, higher incidence rates of anastomotic leak and electrolyte disturbance, and longer times to first flatus, first feeding and drain removal than the other two groups (p < 0.05).Conclusions: Colostomy can be adopted for advanced ovarian cancer patients with a large ascites volume, hypoproteinemia, large intraoperative blood and fluid loss volumes, multiple intestinal resections, anastomoses located below the peritoneal reflection, high PCI and suboptimal cytoreductive surgery. For patients with good intraoperative and postoperative outcomes, one anastomosis, an anastomosis located above the peritoneal reflection, low PCI or optimal cytoreductive surgery, intestinal anastomosis can be carried out to restore the normal physiological function of the intestine. For patients with a large volume of ascites (≥500 mL), multiple anastomoses or an anastomosis located below the peritoneal reflection, intestinal anastomosis combined with protective enterostomy has an advantage over intestinal anastomosis alone.",2234943X,ONCOLOGY
10.1007/s00432-025-06094-0,Bibliometric analysis of liposarcomas treatment from 2004 to 2023,"Background Liposarcomas are mesenchymal malignant tumors characterized by varying degrees of adipocytic differentiation that comprises approximately 20% of soft tissue sarcomas. Despite advancements in this field, there remains a need for a comprehensive understanding of the mechanisms, diagnosis, and treatment of liposarcomas. Currently, there is a lack of bibliometric surveys on the development trajectory of liposarcomas treatment, research hotspots, and author and team collaboration. Methods In this study, we obtained publications from the Web of Science database from 2004 to 2023, with a specific focus on the treatment of liposarcomas. By utilizing bibliometric methods, the data were processed to facilitate visual analysis of various aspects, including authors, countries, institutions, cocitations, keywords, references, and gene characteristics. Results The number of publications on liposarcomas treatment has increased over the past two decades, from 39 in 2004 to 232 in 2023, with the United States of America contributing the most publications. Among the institutions, the Memorial Sloan Kettering Cancer Center had the highest volume of 87 publications. Notably, Alessandro Gronchi published 63 articles on the treatment of liposarcomas in the last 20 years. Cancers is the journal with the highest number of 57 publications. High-frequency keywords in these publications included “soft tissue sarcoma”, “liposarcoma”, “retroperitoneal sarcoma”, “surgery”, “dedifferentiated liposarcoma”, “trabectedin” and “radiotherapy”. Recent trends, identified through strong citation bursts from 2020 to 2023, include next-generation sequencing, radiotherapy, and patient-derived cell lines. High-frequency genes in the liposarcomas treatment field include TP53, MDM2, CDK4, DDIT3, and CD274. Conclusions The treatment of liposarcomas has garnered increasing attention worldwide in the last 20 years. The treatment approach has shifted from surgical resection to multidisciplinary therapy. The molecular and biological characteristics of different tumor subtypes have attracted more research attention, providing an important reference for the choice of treatment. The findings of this study contribute to providing a comprehensive understanding of liposarcomas treatment among researchers. Moreover, they offer valuable perspectives that can guide future research.",14321335,ONCOLOGY
10.1186/s40359-025-02411-x,Psychometric properties of the Chinese version of the body image life disengagement questionnaire in a sample of adolescents,"The negative consequences of body image concerns manifest in ways such as negative emotional experiences, eating disorders, and problems with social life. The Body Image Life Disengagement Questionnaire (BILD-Q) is an instrument for assessing the impact of body image concerns specifically on adolescents’ life disengagement. The objective of this study is to create a Chinese version of the BILD-Q and assess its validity and reliability with Chinese adolescents. A total of 593 adolescents were recruited, of whom 316 (Sample 1) completed only the BILD-Q and 277 (Sample 2) completed the BILD-Q, Eating Attitudes Test (EAT), and Body Appreciation Scale-2 (BAS-2). Data from Sample 1 were used for the item analysis, exploratory factor analysis (EFA), and test-retest reliability, while data from Sample 2 were used for the BILD-Q’s confirmatory factor analysis (CFA) and associations of BILD-Q with EAT and BAS-2. Both samples were used together for calculating descriptive statistics, measurement invariance, and internal consistency. EFA and CFA were used to verify the single-factor structure of the BILD-Q. Measurement invariance across genders was verified by multi-group CFA. The reliability of the instrument was verified using Cronbach’s alpha and the intraclass correlation coefficient (ICC). Finally, the convergent validity of the instrument was verified by correlating the BILD-Q scores with the EAT and BAS-2 scores. The results support a single-factor structure for the Chinese version of the BILD-Q, with good reliability (Cronbach’s alpha = 0.888, ICC value = 0.759). Gender invariance was established: no significant differences were found in BILD-Q scores between the male and female groups. Life disengagement was positively correlated with eating disorder psychopathology and negatively correlated with body appreciation, supporting the convergent validity of the BILD-Q. The Chinese version of the BILD-Q has strong psychometric properties when used with Chinese adolescents and can be used to assess the impact of body image concerns on their life disengagement.",20507283,PSYCHOLOGY
10.3389/fonc.2025.1482050,Advances in the treatment of glioma-related signaling pathways and mechanisms by metformin,"Metformin (MET) is a commonly used drug for the treatment of type 2 diabetes in the department of endocrinology. In recent years, due to the few clinically effective treatment options including glioma, some scholars have proposed the possibility of metformin in the treatment of glioma, and studies have shown that metformin has a certain inhibitory effect on this tumor. This review explores the multiple mechanisms through which metformin exerts its antitumor effects, focusing on signaling pathways such as AMPK/mTOR, ferroptosis, autophagy, apoptosis and chloride ion channels (CLIC1). Metformin’s inhibition of glioma proliferation involves complex cellular processes, including mitochondrial dysfunction, increased reactive oxygen species (ROS) production, and modulation of immune responses. Additionally, metformin affects glioma stem cells by inhibiting key pathways, including STAT3, mTOR, and AKT, and altering the tumor microenvironment. While preclinical studies suggest that metformin enhances radiosensitivity and reduces tumor recurrence, its clinical application remains in early stages, with further studies needed to optimize dosing regimens and understand its full therapeutic potential. This review provides a comprehensive analysis of metformin’s molecular mechanisms in glioma treatment and highlights its potential as a novel therapeutic strategy, especially for treatment-resistant gliomas.",2234943X,ONCOLOGY
10.3389/feduc.2024.1419362,Improving learning experience through process re-engineering: Khan Academy localization into Azerbaijani,"The localization of online educational platforms brings many benefits to the students and teachers such as access to different types of textual and video content. Nonetheless, it demands time and capital resources to localize any content. The aim of this research was to re-engineer the entire localization process of Khan Academy content into the Azerbaijani language and evaluate its impact on users’ learning experience. For this purpose, we implemented process re-engineering’s cycle of successive steps. Additionally, we carried out a survey to investigate the new localization process’s effect on users’ learning experience. Our study found that making the localization process more efficient decreased the time and resources needed. Additionally, this improved process positively affected how users experienced learning on the platform.",2504284X,EDUCATION
10.3389/fonc.2025.1497195,Early characterization and prediction of glioblastoma and brain metastasis treatment efficacy using medical imaging-based radiomics and artificial intelligence algorithms,"Among brain tumors, glioblastoma (GBM) is the most common and the most aggressive type, and brain metastases (BMs) occur in 20%–40% of cancer patients. Even with intensive treatment involving radiotherapy and surgery, which frequently leads to cognitive decline due to doses on healthy brain tissue, the median survival is 15 months for GBM and about 6 to 9 months for BM. Despite these treatments, GBM patients respond heterogeneously as do patients with BM. Following standard of care, some patients will respond and have an overall survival of more than 30 months and others will not respond and will die within a few months. Differentiating non-responders from responders as early as possible in order to tailor treatment in a personalized medicine fashion to optimize tumor control and preserve healthy brain tissue is the most pressing unmet therapeutic challenge. Innovative computer solutions recently emerged and could provide help to this challenge. This review will focus on 52 published research studies between 2013 and 2024 on (1) the early characterization of treatment efficacy with biomarker imaging and radiomic-based solutions, (2) predictive solutions with radiomic and artificial intelligence-based solutions, (3) interest in other biomarkers, and (4) the importance of the prediction of new treatment modalities’ efficacy.",2234943X,ONCOLOGY
10.1007/s00432-025-06101-4,Biomarker microRNA-371a-3p - expression in malignancies other than germ-cell tumours,"Purpose: microRNA-371a-3p (M371) is considered a highly sensitive and specific serum biomarker of testicular germ cell tumours (GCTs). However, little is known about the expression of M371 in nontesticular malignancies (NTMs), so far. As knowledge about the expression of the marker in other malignancies is a prerequisite for the clinical application of the test we aimed to explore the M371 expression in other cancers. Methods: M371 serum levels were measured in 137 patients with NTM of 12 different neoplastic entities using the IVDR-certified M371-Test for quantitative real-time PCR. Median M371 serum levels and percentages of M371 level elevations were calculated for the entire NTM group and for entity-specific subgroups. The results were compared with GCT patients (n = 20) and with tumour-free male controls (n = 20) using descriptive statistical methods. Results: Eight patients with NTMs had M371 serum level elevations, corresponding to a false-positive rate (FPR) of 5.84% (95% confidence intervals (CIs) 2.55–11.18%). Expression rates in GCTs and controls were 100% and zero, respectively. Thus, the specificity of the M371-Test for GCT is 94.90% (95% CI 90.21–97.77%) when all NTMs and tumour-free controls are considered. Remarkably, three out of 5 patients with multiple myeloma had elevated M371 levels. Conclusion: The false-positive rate of the M371-Test in other malignancies than GCT is very low, and almost identical with that in healthy males, corresponding to a high specificity of 94.9% for detection of GCT. The surprising finding of M371 elevations in patients with multiple myeloma needs further investigation.",14321335,ONCOLOGY
10.3389/frai.2025.1455341,Artificial intelligence applied to diabetes complications: a bibliometric analysis,"Background and aims: Artificial intelligence (AI)-driven medical assistive technology has been widely used in the diagnosis, treatment and prognosis of diabetes complications. Here we conduct a bibliometric analysis of scientific articles in the field of AI in diabetes complications to explore current research trends and cutting-edge hotspots.Methodology: On April 20, 2024, we collected and screened relevant articles published from 1988 to 2024 from PubMed. Based on bibliometric tools such as CiteSpace, Vosviewer and bibliometix, we construct knowledge maps to visualize literature information, including annual scientific production, authors, countries, institutions, journals, keywords and research hotspots.Results: A total of 935 articles meeting the criteria were collected and analyzed. The number of annual publications showed an upward trend. Raman, Rajiv published the most articles, and Webster, Dale R had the highest collaboration frequency. The United States, China, and India were the most productive countries. Scientific Reports was the journal with the most publications. The three most frequent diabetes complications were diabetic retinopathy, diabetic nephropathy, and diabetic foot. Machine learning, diabetic retinopathy, screening, deep learning, and diabetic foot are still being researched in 2024.Conclusion: Global AI research on diabetes complications is expected to increase further. The investigation of AI in diabetic retinopathy and diabetic foot will be the focus of research in the future.",26248212,AI
10.3389/feduc.2025.1518917,Australia's progress toward SDG4 targets for school-age students with disability,"Australia's progress toward achieving Sustainable Development Goal 4 (SDG4) for students with disability reveals both challenges and opportunities. Despite existing disability discrimination legislation, systemic barriers persist within government and non-government schooling sectors. A lack of a coordinated national strategy, combined with fragmented policies, has constrained efforts to promote inclusive education, leaving students with disability underserved, particularly in regional, rural, and remote areas. Underinvestment in mainstream schools has also created disparities in educational access and quality. Moreover, inadequate training of classroom teachers in these schools has continued to restrict the implementation of inclusive and individualized approaches, limiting educational outcomes for this student group. These students therefore continue to experience lower success and completion rates than their peers. This paper emphasizes the urgent need for systemic reforms, including targeted investments and a national policy framework aligned with SDG4, to address these issues. We argue that to achieve equitable, inclusive, and quality education for all students, collaborative effort across all levels of government and education sectors is required for Australia to realize sustainable progress toward its international commitments.",2504284X,EDUCATION
10.1186/s40594-025-00530-w,Retention in engineering pathways: an ecological belonging intervention supports help-seeking and continued enrollment,"Background: The demand for engineers in the workforce continues to rise, which requires increased retention and degree completion at the undergraduate level. Engineering educators need to better understand opportunities to retain students in engineering majors. A strong sense of belonging in engineering represents one important contributor to persistence. However, research has not investigated how academic help-seeking behaviors relate to belonging and downstream outcomes, such as persistence in engineering. Interventions to support and develop belonging show promise in increasing student retention, with particularly positive influences on women, Black, Latino/a/x, and indigenous students. As part of a larger research project, a quasi-experimental intervention to develop a classroom ecology of belonging was conducted at a large Midwestern university in a required first-year, second-semester engineering programming course. The 45-min intervention presented students with stories from past students and peers to normalize academic challenges within the ecology of the classroom as typical and surmountable with perseverance, time, and effort. Results: With treatment (n = 737) and control (n = 689) participant responses, we investigated how the intervention condition affected students' comfort with seeking academic help and feeling safe being wrong in class as influences on belonging. Using path analysis, a form of structural equation modeling, we measured the influence of these attitudinal variables on belonging and the influence of belonging beyond a student’s grade point average on enrollment as an engineering major the following fall. The path analysis supports the importance of academic help-seeking and feeling safe to be wrong for belonging, as well as the importance of belonging on continued enrollment. A group path analysis compared the treatment and control groups and demonstrated the positive impact of the intervention on enrollment for the treatment participants. Conclusions: The analyses demonstrate the importance of academic help-seeking in students’ sense of belonging in the classroom with implications for identifying effective tools to improve students’ sense of belonging through supporting help-seeking behaviors.",21967822,EDUCATION
10.1007/s00432-025-06104-1,Individual management and prognostic assessment for long-term outcomes using a novel classification system of craniopharyngiomas: a retrospective study of single institution,"Purpose This study aims to propose a classification system to more accurately understand the features and nature of different CPs, to investigate the correlation between different topographies of CPs and their surgical outcomes. Methods A retrospective analysis was conducted on 91 surgically resected CPs. They were categorized into six types based on their location and origin. Simultaneously, the patients were divided into four categories based on the degree of pituitary stalk(PS) preservation postoperatively. Statistical analysis was performed to compare the variables among the different tumor type groups. Results A total of 91 patients were included. The follow-up data for 59 cases were complete. Tumor volume varied significantly, with the suprasellar-third ventricle type II and ectopic type exhibiting larger volumes (P < 0.05). The choice of surgical approach differed significantly. The recurrence rates were significantly lower for the intrasellar-suprasellar type, suprasellar-third ventricle type II, and third ventricle type (P < 0.05). Patients with intra-stalk tumor growing pattern have a lower degree of PS preservation than those with peri-stalk pattern (P < 0.05). Patients’ BMI after surgery was generally higher than before, and the incidence of pituitary dysfunction increased significantly. The proportion of long-term endocrine dysfunction was significantly higher in patients with complete disconnection of PS compared to those with preservation of the PS(P < 0.05). Conclusions This system holds significant importance in foretelling the rates of recurrence, alterations in postoperative body weight, long-term endocrine status, and potential complications. Furthermore, this study identified preoperative pituitary function status and specific surgical approaches as potential protective factors.",14321335,ONCOLOGY
10.3389/frai.2025.1446590,Strategic technological innovation through ChatMu: transforming information accessibility in Muhammadiyah,"This study examines the effectiveness of the ChatMu application in improving access to information for members of Muhammadiyah, a prominent socio-religious organization. The research employs a mixed-methods approach, combining qualitative and quantitative analyses to evaluate the application’s performance, usability, and user satisfaction. Findings reveal that ChatMu significantly enhances the accessibility and accuracy of Muhammadiyah-related information, highlighting its potential as an innovative tool for addressing community-specific information needs. However, several usability challenges were identified, including navigation inefficiencies and inconsistencies in content delivery. These limitations suggest the need for further refinement to optimize user experience and functionality. Despite these issues, ChatMu demonstrates strong capabilities in providing relevant and reliable information, fostering digital literacy, and supporting information dissemination within the Muhammadiyah community. The study concludes that ChatMu represents a promising application of chatbot technology in empowering communities through improved access to knowledge. Future development efforts should focus on comprehensive usability testing, maintaining information relevance, and incorporating advanced interactive features to enhance engagement. With continuous improvements, ChatMu has the potential to become an effective medium for advancing literacy and knowledge-sharing in the Muhammadiyah community.",26248212,AI
10.1007/s44196-025-00741-7,An Enhanced LSTM Approach for Detecting IoT-Based DDoS Attacks Using Honeypot Data,"One of the widening perils in network security is the Distributed Denial of Service (DDoS) attacks on the Internet of Things (IoT) ecosystem. This paper presents an enhanced Intrusion Detection System (IDS) through the proposal of an enhanced version of the long short-term memory (LSTM) model to detect DDoS attacks using honeypot-generated data. The proposed model aggregates the Conv1D, Bidirectional Long Short-Term Memory (Bi-LSTM), Bidirectional Gated Recurrent Unit (Bi-GRU), and dropout layers to extract temporal and spatial features from IoT traffic effectively. We tested the efficacy of the proposed system on a real-world IoT-DH dataset, which showed a remarkable accuracy of 99.41%, with an AUC score of 0.9999. A comparative analysis with other baseline models, such as LSTM, Bidirectional LSTM (Bi-LSTM), Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN), Feedforward Neural Network (FNN), and Temporal Convolutional Network (TCN), proved that enhanced LSTM outperformed the other models. This indicates the robustness of the proposed model in correctly detecting DDoS attacks with high generalization capability for unseen traffic data. The contribution of this paper will be an addition to the deep learning techniques applied for the solution of intrusion detection systems (IDS), which will also allow the building and implementation of more efficient security mechanisms in IoT environments.",18756883,AI
10.3389/feduc.2025.1427083,Adaptive learning in bionics: transforming science education,"Introduction: Adaptive learning platforms offer innovative teaching approaches by tailoring educational content to individual learner’s needs, abilities, and paces.Methods: This study investigates the effects of an adaptive digital learning platform on user experience, motivation, and learning outcomes among 56 sixth-grade students from two German grammar schools. Students completed three bionics-focused modules— “polar bear”, “heat transfer”, and “temperature and heat”—integrated into science lessons. Data from questionnaires and performance tests assessed prior knowledge, learning success, cognitive activation, and situational interest.Results: The findings indicate that 98% of students found digital media motivating, with 81% favoring a hybrid mix of traditional and digital teaching methods. Positive emotional responses were reported by 62% of participants, though 38% experienced uncertainty. The “polar bear” module achieved the highest learning gain (+41%), followed by “heat transfer” (+23%) and “temperature and heat” (+13%) module.Discussion: These results suggest that adaptive digital learning platforms can enhance learning outcomes and cognitive engagement, particularly when the content aligns with student interests and needs.",2504284X,EDUCATION
10.1007/s00432-025-06107-y,"Psychosocial distress, perceived need and utilization of psycho- social support services in patients in the early phase after the first cancer diagnosis","Purpose: Due to the growing number of new oncological diagnosis and the accompanying psychosocial burden, needs-based psycho-oncological care is important. Adequate planning of psycho-oncological support services is therefore becoming increasingly important. In order to better implement psycho-oncological support services, we investigate psychosocial distress, perceived need and utilization of psycho-oncological support offers in newly diagnosed cancer patients. Methods: Based on a multicenter prospective study, we assessed the cross-sectional data on psychosocial distress, perceived need and utilization of psycho- social support in patients with different tumor entities within 2 months after initial diagnosis. Psychosocial distress was assessed using the Distress Thermometer (DT). Results: Of 1,003 eligible patients who completed the questionnaire (53.0% men, mean age 60.3 years) 39.7% (n = 390) showed above-threshold psychosocial stress (DT: scores ≥ 5) and 21% (n = 207) indicated a perceived need for psycho- social support. 13.5% (n = 136) showed both, psychosocial distress and perceived need for psycho- social support. 15.2% (n = 150) out of all participating patients used psycho-oncology service, 60.7% (n = 597) were willing to accept such an offer. Women were significantly more likely to be psychosocially distressed and to express a need for support. They were also significantly more likely to seek and be willing to accept psycho- social support. Conclusion: Although most patients would accept a psycho- social service, regardless of whether there is psychosocial distress or a need is perceived, the actual utilization was relatively low. It can therefore be assumed that barriers, e.g. structural or personal ones, prevent access. These should be investigated in more detail in future studies.",14321335,ONCOLOGY
10.3389/frai.2025.1398885,From Llama to language: prompt-engineering allows general-purpose artificial intelligence to rate narratives like expert psychologists,"Introduction: Artificial intelligence (AI) has tremendous potential for use in psychology. Among the many applications that may benefit from development of AI applications is narrative-personality assessment. Use of these tools and research methods is notably time-consuming and resource intensive. AI has potential to address these issues in ways that would greatly reduce clinician and researcher burden. Nonetheless, it is unclear if current AI models are sufficiently sophisticated to perform the complex downstream tasks, such as narrative assessment.Methodology: The purpose of this study is to explore if an expert-refined prompt generation process can enable AI-empowered chatbots to reliably and accurately rate narratives using the Social Cognition and Object Relations scales – Global Rating Method (SCORS-G). Experts generated prompt inputs by engaging in a detailed review of SCORS-G training materials. Prompts were then improved using an systematic process in which experts worked with Llama-2-70b to refine prompts. The utility of the prompts was then tested on two AI-empowered chatbots, ChatGPT-4 (OpenAI, 2023) and CLAUDE-2-100k, that were not used in the prompt refinement process.Results: Results showed that the refined prompts allowed chatbots to reliably rate narratives at the global level, though accuracy varied across subscales. Averaging ratings from two chatbots notably improved reliability for the global score and all subscale scores. Experimentation indicated that expert-refined prompts outperformed basic prompts regarding interrater reliability and absolute agreement with gold standard ratings. Only the expert-refined prompts were able to generate acceptable single-rater interrater reliability estimates.Discussion: Findings suggest that AI could significantly reduce the time and resource burdens on clinicians and researchers using narrative rating systems like the SCORS-G. Limitations and implications for future research are discussed.",26248212,AI
10.3389/fonc.2025.1514009,Biomarkers of inflammation and colorectal cancer risk,"Globally, colorectal malignancy ranks among the most prevalent forms of cancer and stands as the third principal cause of cancer-associated mortality. Recent studies indicate that inflammatory processes play a significant role in the initiation and advancement of various malignancies, colorectal cancer included. It explores inflammatory biomarkers, with C-reactive protein (CRP) being a key focus. While CRP’s elevation during inflammation is linked to tumorigenesis, studies on its association with CRC risk are inconsistent, showing gender and methodological differences. Interleukin-6 (IL-6), TNF - α, and their receptors also play roles in CRC development, yet research findings vary. Adiponectin and leptin, secreted by adipocytes, have complex associations with CRC, with gender disparities noted. In terms of screening, non-invasive methods like fecal occult blood tests (FOBTs) are widely used, and combining biomarkers with iFOBT shows potential. Multi-omics techniques, including genomics and microbiomics, offer new avenues for CRC diagnosis. Overall, while evidence highlights the significance of inflammatory biomarkers in CRC risk prediction, larger prospective studies are urgently needed to clarify their roles due to existing inconsistencies and methodological limitations.",2234943X,ONCOLOGY
10.1186/s40594-024-00524-0,Facilitation of students’ disembedding in an online visual arts and mathematics education program,"Disembedding is a crucial spatial thinking skill in visual arts and mathematics education. It is important in creating and analyzing artworks by separating a figure from its background, as well as for solving geometric problems where shapes must be viewed from new perspectives. Drawing upon research in psychology, arts, and mathematics education, the present study aimed to facilitate students’ disembedding in an online educational program employing the teaching experiment methodology. This program utilized concrete movement artworks, particularly those by Max Bill. Seven sixth-grade students participated remotely in this program, utilizing GeoGebra Classroom. The analysis of video data (talks and drawings) and written notes over three sessions revealed that this online educational program, which was designed for the specific context of visual arts and mathematics, offered students opportunities for the individual and group observation of diverse artworks, the tracing of shape contours, and guided attention to new perceptual organizations of shapes through prompting questions. Overall, this had the potential to facilitate students’ disembedding. This overall process challenged students’ initial simplistic shape organizations based on Gestalt principles, leading to the identification of primary and secondary structures, as well as reversible figures. This research sheds light on the concept of disembedding skills rooted in Gestalt psychology, and its connection to the figure-ground phenomenon observed in both artistic and mathematical contexts. This research offers theoretical and practical contributions. First, it suggests an emerging trajectory of disembedding and proposes methods for nurturing students’ disembedding skills. Second, this study serves as an example for art and mathematics educators in schools and informal learning environments (e.g., art museums) to support students’ spatial thinking. This study contributes to the development of educational programs that facilitate students’ spatial thinking in the context of STEAM (Science, Technology, Engineering, Arts, and Mathematics) education.",21967822,EDUCATION
10.3389/feduc.2025.1523797,A systematic review of the utility of assistive technologies for SEND students in schools,"The systematic review investigates the effect of various educational technologies on the learning outcomes of diverse student populations, particularly focusing on assistive technology interventions for students with disabilities. The comprehensive analysis covers literature from 2012 to 2023. The study highlights the potential of AR and assistive technologies in fostering inclusive and engaging learning environments. Despite positive findings, the review emphasizes the imperative for further research to refine the implementation of these technologies and enhance their effectiveness. The systematic review of five databases provides crucial insights into the effectiveness of various assistive technologies. Mobile devices, iPads, and AR interventions emerge as frequently utilized tools. Research activity peaked in 2013 and 2018 and subsequently declined. Twelve studies focus on Autism Spectrum Disorder and emphasize the prioritization of ASD in assistive technology interventions. The research highlights the importance of adopting a holistic perspective on educational inclusion, emphasizing collaborative efforts among teachers, diverse teaching methods, and technology integration. Despite the promise shown by assistive technologies, the review acknowledges their limitations and advocates for ongoing research and innovation to refine their application across diverse educational contexts. The findings stress the importance of a nuanced interpretation of evidence, considering the challenges posed by the limited number of eligible studies. The review calls for careful consideration of future research directions to bolster the comprehensiveness and reliability of evidence synthesis in assistive technology interventions for students with disabilities.",2504284X,EDUCATION
10.3390/ai6020040,Deep Learning and Reinforcement Learning for Assessing and Enhancing Academic Performance in University Students: A Scoping Review,"University students often face challenges in managing academic demands and difficulties like time management, task prioritization, and effective study strategies. This scoping review investigates the application of Deep Learning (DL) and Reinforcement Learning (RL) in evaluating and enhancing academic performance, focusing on their practical applications, limitations, and future potential. Using PRISMA guidelines, 27 empirical studies published between 2014 and 2024 were analyzed. These studies utilized advanced DL and RL technologies, including neural networks and adaptive algorithms, to support personalized learning and performance prediction across diverse university contexts. Key findings highlight DL’s ability to accurately predict academic outcomes and identify at-risk students, with models achieving high accuracy in areas like dropout prediction and language proficiency assessments. RL proved effective in optimizing learning pathways and tailoring interventions, dynamically adapting to individual student needs. The review emphasizes significant improvements in grades, engagement, and learning efficiency enabled by AI-driven systems. However, challenges persist, including scalability, resource demands, and the need for transparent and interpretable models. Future research could focus on diverse datasets, multimodal inputs, and long-term evaluations to enhance the applicability of these technologies. By integrating DL and RL, higher education can foster personalized, adaptive learning environments, improving academic outcomes and inclusivity.",26732688,AI
10.3389/frai.2025.1523390,Adaptive Neuro-Fuzzy Inference System guided objective function parameter optimization for inverse treatment planning,"Intensity-Modulated Radiation Therapy requires the manual adjustment to numerous treatment plan parameters (TPPs) through a trial-and-error process to deliver precise radiation doses to the target while minimizing exposure to surrounding healthy tissues. The goal is to achieve a dose distribution that adheres to a prescribed plan tailored to each patient. Developing an automated approach to optimize patient-specific prescriptions is valuable in scenarios where trade-off selection is uncertain and varies among patients. This study presents a proof-of-concept artificial intelligence (AI) system based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) to guide IMRT planning and achieve optimal, patient-specific prescriptions in aligned with a radiation oncologist's treatment objectives. We developed an in-house ANFIS-AI system utilizing Prescription Dose (PD) constraints to guide the optimization process toward achievable prescriptions. Mimicking human planning behavior, the AI system adjusts TPPs, represented as dose-volume constraints, to meet the prescribed dose goals. This process is informed by a Fuzzy Inference System (FIS) that incorporates prior knowledge from experienced planners, captured through “if-then” rules based on routine planning adjustments. The innovative aspect of our research lies in employing ANFIS's adaptive network to fine-tune the FIS components (membership functions and rule strengths), thereby enhancing the accuracy of the system. Once calibrated, the AI system modifies TPPs for each patient, progressing through acceptable prescription levels, from restrictive to clinically allowable. The system evaluates dosimetric parameters and compares dose distributions, dose-volume histograms, and dosimetric statistics between the conventional FIS and ANFIS. Results demonstrate that ANFIS consistently met dosimetric goals, outperforming FIS with a 0.7% improvement in mean dose conformity for the planning target volume (PTV) and a 28% reduction in mean dose exposure for organs at risk (OARs) in a C-Shape phantom. In a mock prostate phantom, ANFIS reduced the mean dose by 17.4% for the rectum and by 14.1% for the bladder. These findings highlight ANFIS's potential for efficient, accurate IMRT planning and its integration into clinical workflows.",26248212,AI
10.3389/feduc.2025.1528924,Conceptual model of sustainable development of pedagogical staff competences in quality assurance of higher education,"Creating strategies to improve the quality of higher education is the key task of higher education institutions in the conditions of rapid changes in the content of competencies, in particular IT-competencies, as well as in the conditions of turbulence in the external environment, in particular epidemics, military conflicts, etc. The article describes the conceptual model of sustainable development of teachers’ competences in ensuring the quality of higher education in higher education institutions. The sustainability of the development of teachers’ methodological competences is ensured by monitoring their activities based on the results of professional development and acquisition of the appropriate level of competence, as well as on the results of teaching by these teachers of relevant educational components in academic groups of higher education students. In order to reduce the risks of failing to pass the course, some participants of the competence project proposed to form a pool of potential project participants. Methods of optimization theory were used to solve the problem of selecting participants in the competence project. Also, the methodology of project management and pedagogical modeling was used to form the structure of the competence project and to plan its implementation. The assessment of methodological competences of university lecturers is crucial for building sustainable inter-university scientific and educational communities. Based on the results of the pilot implementation of the first stage of the competence project, project participants were selected on the basis of this conceptual model and training was organized to improve the level of competence in the field of education quality management. The results of training of teachers according to the described conceptual model allow to increase the level of their methodological competence. The obtained result requires clarification after completing the second stage of the competency-based project. Thus, the authors proposed an innovative approach to improving the level of competence of teachers of higher education institutions, which is focused on the effective assimilation of learning outcomes not only directly by teachers, but also by students of academic groups in which these teachers teach.",2504284X,EDUCATION
10.3389/feduc.2025.1512557,Engagement factors affect academic success through study approaches among physical education and sport university students: a mediation analysis,"Introduction: University students should engage with the study and ensure they adopt productive study approaches, but the nature of relationships between engagement and study approaches are under-researched. The study aimed to investigate how emotional, cognitive, and behavioral engagement affect academic success through study approaches among physical education and sports students.Methods: Online forms were submitted by 488 students in physical education and sports (age range 19–25 years, Mean = 21 ± 1.5 year). They completed surveys regarding their academic engagement, study approaches, and grade point average (GPA). Analyses of associations were conducted through linear regression analysis and mediation analysis.Results: Results from the linear regression analysis showed correlations between academic engagement factors, study approach variables, and GPA, with higher GPA correlating with higher scores on behavioral engagement, cognitive engagement, surface theory task, and deep theory task, and with lower scores on surface practical task. The analysis of total and direct effects revealed positive associations between all academic engagement factors and GPA. Emotional engagement exhibited a positive association with GPA mediated by study approaches. All engagement dimensions appear to influence academic success among these students.Conclusion: The influence of emotional engagement on academic success appears in part to be operating through its effects on study approaches. The study can enable educators in monitoring and enhancing student engagement, thereby supporting students in their pursuit of high academic performance in physical education and sport.",2504284X,EDUCATION
10.3390/cancers17040705,Correlation of GNAS Mutational Status with Oncologic Outcomes in Patients with Resected Intraductal Papillary Mucinous Neoplasms,"Background: Intraductal papillary mucinous neoplasms (IPMNs) are pre-malignant pancreatic lesions that may progress to invasive pancreatic ductal adenocarcinoma (PDAC). IPMN-associated invasive carcinoma (iIPMN) has been associated with more favorable survival outcomes compared to non-iIPMN-derived PDAC. Here, we aim to investigate the genetic landscape of IPMNs to assess their relevance to oncologic outcomes. Methods: This retrospective study used a large single-institution prospectively maintained database. Patients who underwent curative-intent pancreatic resection between 2016 and 2022 with histologically confirmed diagnosis of IPMN were included. Demographic, pathologic, molecular, and oncologic outcome data were recorded. Kaplan–Meier survival analyses were performed. PDAC data from public genetic databases were used for mutational correlation analysis. p-value ≤ 0.05 was considered as significant. Results: A total of thirty-nine patients with resected IPMN with complete clinical and sequencing data were identified and included in the final cohort. The male-to-female distribution was 21:18, and the mean age was 70.1 ± 9.1 years. GNAS mutations occurred in 23.1% of patients, and 89.7% of patients had iIPMN. In iIPMN patients, GNAS mutation was strongly associated with improved disease-free survival: all GNAS-mutant patients survived to follow-up with significantly fewer recurrences than in GNAS wild-type (WT) patients (p = 0.013). Mutated GNAS closely co-occurred with wild-type KRAS (p < 0.001), and further analysis of large genomic PDAC datasets validated this finding (OR 3.47, p < 0.0001). Conclusions: Our study suggests prognostic value of mutational status in malignant resected IPMNs. WT GNAS, mutant P53, and mutant KRAS each correlate with recurrence and decreased survival. Further studies are required to validate these preliminary observations.",20726694,ONCOLOGY
10.1186/s40594-025-00532-8,Quantifying ento-literacy: development and validation of an international insect-focused attitude and knowledge survey instrument,"Background: In an era of precipitous insect declines, effective entomology education is especially needed to support firsthand knowledge of nature. Understanding what students know and feel about insects is instrumental to teaching and curriculum development. This study describes the development and validation of a new survey instrument, EntoEdu, measuring ‘entomology literacy’, based on attitude and knowledge, in a cross-cultural context. For the survey validation we use data collected from students in Czechia (CZ), a country known for its entomophilia, and the United States of America (US) to demonstrate the utility of this survey and to address the questions: how do entomology attitude and knowledge differ across national affiliation and study domain, and how are entomology attitude and knowledge correlated in the context of these differences? Results: Based on responses from 635 first-year college students, we demonstrate high reliability and evidence of validity of the EntoEdu instrument. Factor analysis supports five independent attitudinal categories within the instrument: Intention to Engage with Insects, Attitude toward Behavior, Control Belief, Hobby, and Disgust. In this study population, average attitude scores did not differ with nationality, whereas knowledge scores were higher in CZ than in the US. In both countries, attitude and knowledge scores were higher among biology students than those in other study domains, and attitude and knowledge were positively correlated. Conclusions: The EntoEdu instrument, based on globally recognizable insect taxa, ecology, and behavior, has been developed for broad utility in assessing attitudes toward and knowledge of insects at the post-secondary level, with potential for use at both lower (K-12) and higher (advanced university) levels. The instrument is presented here in two language versions and can be translated into additional languages for comparison of results across test populations in additional countries. In our initial test population we find attitude and knowledge to be correlated, both of which are influenced by nationality, with Czechs more knowledgeable about insects than their US counterparts. We anticipate that this instrument will facilitate entomology assessment to help tailor biology education programs to students’ actual, rather than assumed, entomology knowledge and attitudes, and for tracking change over time.",21967822,EDUCATION
10.3389/fpsyg.2025.1522098,"Perceived restorativeness and environment quality in relation to well-being, residential satisfaction, and sense of community: an analysis in Northeast Italy","Introduction: Residential satisfaction consists of pleasure derived from living in a place according to one’s needs, expectations, and outcomes. The present study examines the role of sociodemographic variables, perceived residential quality indicators, and restorativeness in predicting i) well-being, ii) residential satisfaction, and iii) sense of communities in northeast Italy.Methods: A total of 100 residents (47 women) in various cities in northeast Italy and 211 (112 women) residents in Piazzola sul Brenta (PD) took part in two studies. They answered demographic questions about self-reported restorativeness, residential environment quality, residential satisfaction, mental well-being, and sense of community.Results: After accounting for age, gender, and income, the results showed that perceived restorativeness enhances sense of community in the Northeast and Piazzola sul Brenta samples and predicts psychological well-being and residential satisfaction in Piazzola sul Brenta. Architectural and functional aspects contribute, respectively, to residential satisfaction and sense of community in both samples, and functional factors predict residential satisfaction for the Northeast sample. Place attachment plays a positive role in residential satisfaction and sense of community in the Northeast and Piazzola sul Brenta.Discussion: The study reveals a link between perceived restorativeness and residential satisfaction and well-being, providing insight for professionals and policy to improve urban quality.",16641078,PSYCHOLOGY
10.1186/s40359-025-02477-7,Parental psychological control and adolescent smartphone addiction: roles of reactance and resilience,"Problematic smartphone use is a prevalent issue addressed in this study. The research delves into factors associated with problematic smartphone use, employing the self-determination theory. Specifically, the study analyzes the relationship between parental psychological control and problematic smartphone use and investigates psychological reactance as a mediating factor. Moreover, psychological resilience is considered a moderating factor in the relationship between parental psychological control and problematic smartphone use, based on the diathesis-stress model and cognitive model of resilience. A total of 1300 (M = 14.22, SD = 1.29) Chinese adolescents were surveyed in a cross-sectional study. They completed self-report questionnaires including the Parental Psychological Control Questionnaire, the Smartphone Addiction Scale, the Psychological Resistance Scale, and the Adolescent Resilience Scale. A moderated mediation model was examined to test predictions. Correlation analysis reveals a positive correlation between parental psychological control, psychological reactance, and problematic smartphone use, and a negative correlation with psychological resilience. Moderation mediation analysis demonstrates that psychological resilience diminishes the direct association between parental psychological control, psychological reactance, and problematic smartphone use, thereby mitigating their relationship. The findings support the moderation mediation model, indicating that psychological resilience plays a crucial role in safeguarding adolescents from the adverse effects of problematic smartphone use induced by parental psychological control.",20507283,PSYCHOLOGY
10.1186/s40594-025-00533-7,A decade of research contributions and emerging trends in the International Journal of STEM Education,"In this editorial, we review 400 articles and reviews published in the International Journal of STEM Education during its first decade (2014–2023). Using bibliometric analysis, we examine these publications to assess the journal’s major contributions to STEM education research and identify emerging trends over the years. The results present a dynamic picture of the growth of STEM education, highlighting key topics, such as STEM integration, equity, and emerging technologies. These findings also reveal evolving “hot topics” that reflect the shifting interests of researchers in the field. This review suggests that many areas of STEM education research are still in the growth phase. We encourage readers to use these insights as a foundation for developing future research agendas and advancing STEM education globally.",21967822,EDUCATION
10.3389/feduc.2025.1467482,Research on task design in pre-service mathematics teacher education: a scoping review,"Tasks are central to every facet of mathematics education. In this scoping review, we bring together research focused on task design in the context of pre-service mathematics teacher education. We perform a qualitative content analysis of 112 peer-reviewed studies published between 2001 and 2023. The results of our review describe a diverse field of research, identify connections between works reflecting different demographics, aims, and methodological and theoretical commitments, and finally, through the application of the MEDSS task design action framework, foreground the different practical actions pre-service teaches must take to effectively design tasks. These include the practical actions of modifying, evaluating, developing, selecting, and sequencing (MEDSS) tasks. We believe the results of this study will be of value to mathematics teacher educators and researchers.",2504284X,EDUCATION
10.3389/feduc.2025.1473331,Continuing education of academic women in STEM: perspectives on mentoring and professional roles,"Despite ongoing efforts towards gender equity, the gender gap in STEM (Science, Technology, Engineering, and Mathematics) remains significant today. This article explores the motivations and perceptions of women in different professional roles within STEM fields regarding the importance of mentoring in fostering interest and participation in STEM careers, thus contributing to continuing engineering education. Based on qualitative data from 19 semi-structured interviews with women in managerial, research, teaching, and external academic and professional roles, the study delves into their motivations for pursuing STEM careers, their interest in promoting diversity, and the role of mentoring in supporting their professional development. The thematic analysis results are grouped into a hierarchical structure comprising one meta-theme, four primary, and six subthemes. The participants emphasized that their primary motivation for STEM involvement was contributing to society and promoting economic growth. Additionally, they advocated for greater diversity and challenged traditional gender roles in these areas. The participants highlighted the importance of closing the gender gap and recognizing the capabilities and new perspectives that women brought. Although these women faced obstacles such as glass ceilings, having a mentorship opportunity was identified as a critical tool for women’s empowerment and training. The insights contribute to advancing strategies for promoting gender equity and diversity in STEM fields, with implications for researchers, universities, and organizations seeking to support women’s participation and advancement in STEM careers. Further research is recommended to explore the perspectives of women in other roles and the effectiveness of mentoring programs in fostering gender diversity in STEM.",2504284X,EDUCATION
10.3389/frai.2024.1510410,Environment sustainability with smart grid sensor,"Environmental sustainability is a pressing global concern, with energy conservation and efficient utilization playing a key role in its achievement. Smart grid technology has emerged as a promising solution, facilitating energy efficiency, promoting renewable energy integration, and fostering consumer engagement. But the addition of intelligent sensors to these grids has the potential to greatly increase the level of sustainability initiatives. This paper highlights the role of smart grid sensors in addressing challenges like energy losses, demand-response limitations, and renewable energy integration. It explains how these sensors enable real-time monitoring, fault detection, and optimal load management to improve grid performance and reduce environmental impact. This also study looks at how AI with smart grid sensor can perform real-time data monitoring, optimal energy distribution, and proactive decision support from smart grid sensors might improve environmental sustainability. Furthermore, it examines advancements in sensor technologies in India, including pilot projects like the BESCOM initiative in Bangalore and Tata Power-DDL’s renewable energy trading in Delhi, to showcase their practical applications and outcomes. Smart sensors provide accurate tracking of energy usage trends, enhance load distribution, and advance the sensible application of renewable energy resources. These sensors aid in cutting down on energy waste and carbon emissions by interacting with customers and enabling demand-response systems. This study addresses the critical role of smart sensors in overcoming the shortcomings of conventional grids and guaranteeing a more resilient, efficient, and sustainable energy future through an extensive analysis of the literature. Grid-enabled systems, such as electric water heaters with sensor, can achieve energy savings of up to 29%. The integration of renewable energy sources through sensors enhances system efficiency, reduces reliance on fossil fuels, and optimizes supply and demand. Utilizing Internet of Things (IoT) technology enables precise monitoring of air quality, water consumption, and resource management, significantly improving environmental oversight. This integration can lead to a reduction in greenhouse gas emissions by up to 20% and water usage by 30%. Lastly, the paper discusses how integrating artificial intelligence with smart grid sensors can enhance predictive maintenance, energy management, and cybersecurity, further strengthening the case for their deployment.",26248212,AI
10.1186/s40359-025-02441-5,Validation of the Arabic version of the Gratitude Questionnaire (GQ-4) in a sample of non-clinical adults,"Although gratitude is a culturally-sensitive construct, it has yet received limited research attention in Arab countries, hence hindering the understanding of its features, correlates, and cross-cultural specificities. To fill this gap, we sought to examine the psychometric properties of an Arabic translation of the 6-item Gratitude Questionnaire (GQ) in an Arabic-speaking sample of adults from the general population of Lebanon. We conducted a web-based survey including 601 participants (mean age 29.91 ± 12.61, 62.7% females). The forward-backward translation method was used for the translation and adaptation of the GQ-6 into the Arabic language. Findings indicated that a four-item version of the GQ achieved adequate fit statistics with the removal of the two reverse-scored third and sixth items. We found a McDonald Omega coefficient for the total 4-item GQ (GQ-4) scores of 0.88, thus attesting for the good reliability of the scale. Multiple-group Confirmatory Factor Analysis showed that the scale structure was invariant across male and female respondents at the configural, metric, and scalar levels. Females exhibited significantly higher gratitude scores compared to males. Finally, discriminant validity of the Arabic GQ-4 was evidenced through positive significant correlations with social support levels. The Arabic adaptation of the GQ showed good psychometric qualities, suggesting that it is suitable for measuring people’s disposition toward gratitude in Arab backgrounds. Offering the Arabic GQ-4 as a brief, simple, cost-effective, valid, and reliable measure of gratitude to the Arabic-speaking community could help raise awareness about gratitude as a key component for achieving good mental health and wellbeing in Arab contexts.",20507283,PSYCHOLOGY
10.3390/educsci15030268,Building Community Among K-8 Teachers Through a University-Educator Network Partnership,"At this time of national divisiveness in the U.S., it is more important than ever for youth to have teachers who can facilitate critical conversations about race, immigration, gender, and other fraught issues in their classrooms. In this article, we detail how an innovative partnership among key education stakeholders in the state of Oregon fostered a sense of community and continued learning for kindergarten through eighth grade teachers to address these issues. We did so by developing and facilitating a professional development (PD) sequence focused on anti-racist critical literacy. More than 125 educators from 24 districts around the state participated in the sequence between 2021 and 2024. We begin by situating this work in the literature, then providing an overview of the partnership. Finally, we share the perspectives of 19 educators who spoke in interviews about their experience of the PD. We offer this as an example of how colleges of education can establish and nurture partnerships with other stakeholders to ensure that teachers feel supported in their efforts to further social justice, especially for those who lack community or administrative “backup”, as is the case for many educators in rural parts of the U.S.",22277102,EDUCATION
10.3390/ai6030043,GeNetFormer: Transformer-Based Framework for Gene Expression Prediction in Breast Cancer,"Background: Histopathological images are often used to diagnose breast cancer and have shown high accuracy in classifying cancer subtypes. Prediction of gene expression from whole-slide images and spatial transcriptomics data is important for cancer treatment in general and breast cancer in particular. This topic has been a challenge in numerous studies. Method: In this study, we present a deep learning framework called GeNetFormer. We evaluated eight advanced transformer models including EfficientFormer, FasterViT, BEiT v2, and Swin Transformer v2, and tested their performance in predicting gene expression using the STNet dataset. This dataset contains 68 H&E-stained histology images and transcriptomics data from different types of breast cancer. We followed a detailed process to prepare the data, including filtering genes and spots, normalizing stain colors, and creating smaller image patches for training. The models were trained to predict the expression of 250 genes using different image sizes and loss functions. GeNetFormer achieved the best performance using the MSELoss function and a resolution of 256 × 256 while integrating EfficientFormer. Results: It predicted nine out of the top ten genes with a higher Pearson Correlation Coefficient (PCC) compared to the retrained ST-Net method. For cancer biomarker genes such as DDX5 and XBP1, the PCC values were 0.7450 and 0.7203, respectively, outperforming ST-Net, which scored 0.6713 and 0.7320, respectively. In addition, our method gave better predictions for other genes such as FASN (0.7018 vs. 0.6968) and ERBB2 (0.6241 vs. 0.6211). Conclusions: Our results show that GeNetFormer provides improvements over other models such as ST-Net and show how transformer architectures are capable of analyzing spatial transcriptomics data to advance cancer research.",26732688,AI
10.3390/ai6030044,Artificial Intelligence Adoption in Public Administration: An Overview of Top-Cited Articles and Practical Applications,"Background: The adoption of artificial intelligence (AI) in public administration (PA) has the potential to enhance transparency, efficiency, and responsiveness, ultimately creating greater public value. However, the integration of AI into PA faces challenges, including conceptual ambiguities and limited knowledge of the practical applications. This study addresses these gaps by offering an overview and categorization of AI research and applications in PA. Methods: Using a dataset of 3149 documents from the Scopus database, this study identifies the top 200 most-cited articles based on citation per year. It conducts descriptive and content analyses to identify the existing state, applications, and challenges regarding AI adoption. Additionally, selected AI use cases from the European Commission’s database are categorized, focusing on their contributions to public value. The analysis centers on three governance dimensions: internal processes, service delivery, and policymaking. Results: The findings provide a categorized understanding of AI concepts, types, and applications in PA, alongside a discussion of best practices and challenges. Conclusion: This study serves as a resource for researchers seeking a comprehensive overview of the current state of AI in PA and offers policymakers and practitioners insights into leveraging AI technologies to improve service delivery and operational efficiency.",26732688,AI
10.3389/frai.2025.1557894,Predicting therapy dropout in chronic pain management: a machine learning approach to cannabis treatment,"Introduction: Chronic pain affects approximately 30% of the global population, posing a significant public health challenge. Despite their widespread use, traditional pharmacological treatments, such as opioids and NSAIDs, often fail to deliver adequate, long-term relief while exposing patients to risks of addiction and adverse side effects. Given these limitations, medical cannabis has emerged as a promising therapeutic alternative with both analgesic and anti-inflammatory properties. However, its clinical efficacy is hindered by high interindividual variability in treatment response and elevated dropout rates.Methods: A comprehensive dataset integrating genetic, clinical, and pharmacological information was compiled from 542 Caucasian patients undergoing cannabis-based treatment for chronic pain. A machine learning (ML) model was developed and validated to predict therapy dropout. To identify the most influential factors driving dropout, SHapley Additive exPlanations (SHAP) analysis was performed.Results: The random forest classifier demonstrated robust performance, achieving a mean accuracy of 80% and a maximum of 86%, with an AUC of 0.86. SHAP analysis revealed that high final VAS scores and elevated THC dosages were the most significant predictors of dropout, both strongly correlated with an increased likelihood of discontinuation. In contrast, baseline therapeutic benefits, CBD dosages, and the CC genotype of the rs1049353 polymorphism in the CNR1 gene were associated with improved adherence.Discussion: Our findings highlight the potential of ML and pharmacogenetics to personalize cannabis-based therapies, improving adherence and enabling more precise management of chronic pain. This research paves the way for the development of tailored therapeutic strategies that maximize the benefits of medical cannabis while minimizing its side effects.",26248212,AI
10.3389/feduc.2025.1477509,Becoming a resilient scientist series: an intervention program,"Compared to the general population, science trainees experience challenges and heightened stressors that often lead to adverse mental health outcomes. With COVID-19, the stressors of social distancing, isolation, truncated lab time, and uncertainty about the future have all likely exacerbated these issues. Now, more than ever, practical and effective interventions are vitally needed to address the core causes of stress among science trainees and increase their resilience. This paper introduces a new resilience program targeted to biomedical trainees and scientists - Becoming a Resilient Scientist Series (BRS), a 5-part workshop complemented by facilitated group discussions all aimed at bolstering resilience, particularly in the context of academic and research environments. To assess the program’s efficacy, participants completed resilience measures and related assessments before and after completing the series. The results suggest that BRS is associated with improvements in trainee resilience (primary outcome) and with reductions in perceived stress, anxiety, and work-related presenteeism, as well as enhancements in adaptability, self-awareness, and self-efficacy (secondary outcomes). Furthermore, program participants reported a high level of satisfaction, a strong willingness to recommend the program to others, and perceived positive changes in their resilience skills. To the best of our knowledge, this is the first resilience program designed explicitly for biomedical trainees and scientists, tailored to their unique professional culture and work environment.",2504284X,EDUCATION
10.3390/cancers17050750,Clinical Characteristics and Long-Term Prognosis of Colorectal Mucosa-Associated Lymphoid Tissue Lymphoma According to the Endoscopic Classification and Treatment Modality: A Multicenter Study,"Background/Objectives: The clinical characteristics of colorectal mucosa-associated lymphoid tissue (MALT) lymphoma remain poorly defined, and there is no standardized treatment for the disease. Therefore, we investigated the clinical characteristics of colorectal MALT lymphoma and its prognosis based on different treatment modalities. Methods: A retrospective analysis was performed on patients diagnosed with colorectal MALT lymphoma from 2003 to 2021 across six hospitals in Korea’s Busan–Ulsan–Gyeongnam area. Macroscopic findings classified all cases into polyposis type, mass-forming type, subepithelial lesion type, and inflammatory type. Results: Fifty-one patients were enrolled. The median age was 59 years, and 27 patients (52.9%) were male. Five patients (9.8%) were stage IV at initial diagnosis. As for the endoscopic type, the polyposis type was the most common (39.2%). There was no statistically significant difference in disease progression according to the endoscopic type (p = 0.813). Three cases of disease progression were confirmed in stage I after treatment, and one of them died due to disease progression. No disease progression was identified in other stages. According to the treatment modality, disease progression was identified in 1 of 16 patients who underwent endoscopic resection and 2 of 16 patients who underwent chemotherapy. There was no disease progression in the observation group. However, there was no statistically significant difference in disease progression according to treatment modality (p = 0.889). Conclusions: Colorectal MALT lymphoma showed good prognosis regardless of the initial stage, endoscopic type, or treatment modality.",20726694,ONCOLOGY
10.3389/fonc.2025.1532421,Clinical outcomes of avelumab and pembrolizumab in advanced urothelial cancer: an observational multicenter retro-prospective study on patients undergoing treatment in clinical practice (AVePEm study),"Introduction and objectives: Patients (pts) with metastatic urothelial carcinoma (mUC) gain substantial benefit from immunotherapy exposure. If they do not experience disease progression after 4-6 cycles of first-line platinum-based chemotherapy (PBC), they may benefit from immunotherapy as maintenance treatment with Avelumab; otherwise, Pembrolizumab is an approved second-line therapy after disease progression on first-line chemotherapy. However, no clinical trial data currently demonstrate which treatment strategy offers superior survival outcomes.Patients and methods: This is a multicenter, observational, retro-prospective study involving pts with mUC who did not progress after 4-6 cycles of PBC: GroupA received Avelumab and GroupB Pembrolizumab. The primary endpoints were overall survival (OS) and progression-free survival (PFS), with neutrophil-to-lymphocyte ratio (NLR) ≥3 at the baseline of PBC and at the start of immunotherapy in predicting outcome, adverse events (AEs), subsequent therapies after the immunotherapy strategy, and costs associated with these treatments as secondary endpoints.Results: From August 2019 to October 2024, we identified 30 pts. Of those, 53% were in GroupA and 47% in GroupB. The mOS in GroupA was 27 mo and in GroupB 26 mo and the mPFS of immunotherapy was 7.5 mo and 5.5 mo. At the time of data analysis, 33% (n=10) of pts were alive and 27% (n=8) on treatment, with 38% (n=3) still receiving Avelumab, and 50% (n=4) and 12% (n=1) on subsequent therapies after Avelumab and Pembrolizumab, respectively. Approximately 55% of patients in both groups had a baseline neutrophil-to-lymphocyte ratio (NLR) ≥3 at the baseline of PBC. No statistically significant association was found between NLR, whether considered as a continuous or dichotomous variable, and overall survival or progression free survival. Both treatments were well tolerated, with Grade 3 AEs in 1 pt on Avelumab and 3 on Pembrolizumab, and no Grade 4 AEs reported.Conclusions: The two immunotherapy strategies showed no significant differences in OS and PFS. Of note, more pts were on Avelumab treatment at the data cut-off. AEs were similar in the two groups. Further investigation and follow-up are warranted to gain definitive conclusions on optimal mUC management in the era of immunotherapy and immunoconjugates.",2234943X,ONCOLOGY
10.3389/frai.2025.1527299,A novel approach to Indian bird species identification: employing visual-acoustic fusion techniques for improved classification accuracy,"Accurate identification of bird species is essential for monitoring biodiversity, analyzing ecological patterns, assessing population health, and guiding conservation efforts. Birds serve as vital indicators of environmental change, making species identification critical for habitat protection and understanding ecosystem dynamics. With over 1,300 species, India's avifauna presents significant challenges due to morphological and acoustic similarities among species. For bird monitoring, recent work often uses acoustic sensors to collect bird sounds and an automated bird classification system to recognize bird species. Traditional machine learning requires manual feature extraction and model training to build an automated bird classification system. Automatically extracting features is now possible due to recent advances in deep learning models. This study presents a novel approach utilizing visual-acoustic fusion techniques to enhance species identification accuracy. We employ a Deep Convolutional Neural Network (DCNN) to extract features from bird images and a Long Short-Term Memory (LSTM) network to analyze bird calls. By integrating these modalities early in the classification process, our method significantly improves performance compared to traditional methods that rely on either data type alone or utilize late fusion strategies. Testing on the iBC53 (Indian Bird Call) dataset demonstrates an impressive accuracy of 94%, highlighting the effectiveness of our multi-modal fusion approach.",26248212,AI
10.1186/s40359-025-02433-5,Career adaptability and graduates’ mental health: the mediating role of occupational future time perspective in higher education in China,"This study examines the mediating role of Occupational Future Time Perspective (OFTP) in the relationship between Career Adaptability and Mental Health among college graduates. Using a three-month, three-time-point survey of Chinese graduates (N = 905, ages 25–30), we found that Career Adaptability has a significant direct effect on Mental Health. Among OFTP dimensions, Focus on Opportunities emerged as a key mediator, highlighting its role in linking Career Adaptability to positive mental health outcomes. However, Perceived Remaining Time and Focus on Limitations did not show significant mediation effects. These findings underscore the value of fostering opportunity-focused perspectives in career counseling and educational interventions to support graduates’ mental health.",20507283,PSYCHOLOGY
10.3389/fonc.2025.1547054,Efficacy and prognostic impact of preoperative risk factors for salvage liver transplantation and repeat hepatectomy in patients with early-stage recurrent hepatocellular carcinoma: a propensity score-matched analysis,"Background: The optimal treatment strategy for recurrent hepatocellular carcinoma (rHCC) remains unclear. This study is based on cases of rHCC after liver resection, aiming to evaluate the influence of preoperative risk factors on the long-term prognosis of patients with rHCC by comparing patients who underwent salvage liver transplantation (SLT) with those who underwent repeat hepatectomy (RH).Methods: We retrospectively analyzed 401 consecutive patients with rHCC who underwent SLT or RH between March 2015 and December 2022. Next, we performed propensity score matching, subgroup analyses, and both univariate and multivariate analyses. In addition, Kaplan–Meier analysis was used to estimate the overall survival (OS) and recurrence-free survival (RFS) after recurrence.Results: The 1-, 3-, and 5-year OS and RFS rates in the SLT group were significantly higher than those in the RH group (p=0.0131 and p=0.0010, respectively), and similar results were observed after propensity score matching. In the presence of zero or one risk factors, the OS and RFS in the SLT group were significantly better than those in the RH group (p=0.0386 and p=0.0117, respectively). However, in the presence of two to four risk factors, no significant differences in OS or RFS were detected between the two groups (p=0.1119 and p=0.1035, respectively).Conclusion: Our analysis identified a number of risk factors that were strongly correlated with a long term prognosis for patients with rHCC who underwent SLT and RH: multiple tumors, a maximum tumor diameter ≥5 cm, microvascular invasion, and a recurrence time ≤2 years. Our findings provide important reference guidelines for organ allocation and clinical decision-making.",2234943X,ONCOLOGY
10.3390/educsci15030299,Metacognitive Monitoring in Written Communication: Improving Reflective Practice,"Educational programs aimed at developing metacognitive skills usually focus on students, neglecting the development of teachers by teaching metacognitively aware instructional methods. The effectiveness of such development programs is well-established, but there is a gap between research findings and their application in schools. A framework for a training program was developed in the context of an international partnership project aimed at enhancing the metacognitive abilities of both children and teachers. The final form of classroom activities was developed at the country level using action research methods with the involvement of teachers. After implementing a 3-week educational program involving 35 experimental and 19 control groups from Romanian public schools, a comparison of pre- and post-test scores indicated a significant increase in the number of children in the experimental group with improved efficiency in metacognitive monitoring in reading. Teachers’ metacognitive awareness significantly improved after the Teacher Training Program, as indicated by a comparison of the pre- and post-training results of the Metacognitive Awareness Inventory for Teachers (MAIT). No correlation was found between teachers’ development scores (as expressed by differences between pre- and post-intervention MAIT results) and the number of students from their classes whose progress in metacognitive monitoring significantly increased. The cyclical process of the action research methodology proved to be useful for increasing the efficiency of the intervention program. However, due to methodological limitations, the results are primarily interpretable within a local context. The results confirm expert recommendations aimed at integrating the targeted development of metacognitive teaching skills into both pre-service and in-service teacher training programs.",22277102,EDUCATION
10.3390/ai6030049,Integration of Artificial Intelligence in K-12: Analysis of a Three-Year Pilot Study,"A three-year pilot study investigated the effectiveness of artificial intelligence (AI) as a motivational tool for teaching programming concepts within the Croatian Informatics curriculum. The study was conducted in schools through the extracurricular activity EDIT CodeSchool with the Development of Intelligent Web Applications (RIWA) module. Twelve schools in Split-Dalmatia County in the Republic of Croatia participated, resulting in 112 successfully completed student projects. The program consisted of two phases: (1) theoretical instruction with examples and exercises, and (2) project-based learning, where students developed final projects using JavaScript and the ml5.js library. The study employed project analysis and semi-structured student interviews to assess learning outcomes. Findings suggest that AI-enhanced learning can effectively support programming education without increasing instructional hours, providing insights for integrating AI concepts into existing curricula.",26732688,AI
10.3390/educsci15030309,Self-Regulation and Teacher Feedback in Problem-Based Learning on the Water Hardness,"Problem-Based Learning has been recognized as a fundamental approach in Science Education. Studies show that the success of this approach depends on students’ ability to self-regulate their learning and on teacher feedback. However, research on how these aspects interact in formal science teaching contexts remains limited. This study aims to address this gap by investigating two questions: (1) What self-regulation strategies are used by different student groups when solving a problem related to water hardness? (2) How do different types of teacher feedback influence students’ problem-solving processes? The study involved 27 students and their Physics and Chemistry teacher. Students participated in an activity that required solving a problem related to water hardness. Data were collected through audio recordings, and the content of the transcriptions was analyzed. The results showed connections between self-regulation strategies and teacher feedback during the problem-solving process. Groups with high participation employed diverse self-regulation strategies, successfully solved the problem, and received varied teacher feedback. The group with the lowest participation received the least feedback from the teacher. Future research should focus on examining how different types of teachers’ feedback during specific interventions for less-participative groups influence the development of their self-regulation strategies.",22277102,EDUCATION
10.3390/cancers17050874,Real-World Insights into the Impact of Durvalumab on Stage III Unresectable Non-Small Cell Lung Cancer—A Narrative Review,"Introduction and Aim: Stage III Non-Small Cell Lung Cancer (NSCLC) has a poor prognosis, with median survival ranging from 9 to 34 months. The PACIFIC trial demonstrated that durvalumab after platinum-based chemoradiotherapy (CRT) improves overall survival (OS) and progression-free survival (PFS). This review evaluates real-world evidence (RWE) on durvalumab’s efficacy and safety, focusing on patient characteristics, prognostic factors, treatment protocols, and outcomes beyond progression. Materials and Methods: A literature search of PubMed, Embase, and Google Scholar identified 49 observational studies published from January 2017 to August 2024 on unresectable stage III NSCLC. Clinical trials, early-stage disease, and alternative treatments were excluded. Results: Compared to the PACIFIC trial, real-world patients were older, had poorer ECOG performance (≥2), and more comorbidities like COPD. Despite this, durvalumab provided consistent survival benefits. Positive prognostic factors included non-squamous histology, high PD-L1 expression, and timely durvalumab initiation (≤42 days post-CRT). Most radiotherapy regimens mirrored PACIFIC (54–66 Gy). Concomitant CRT was used in 90% of cases, with sequential CRT for frail patients. Chemotherapy regimens varied. Immune-mediated pneumonitis was a major adverse event, with incidence rates between 15% and 100%. Severe cases led to treatment discontinuation, impacting survival. Treatment beyond progression remains uncertain, with limited benefits from immunotherapy rechallenge. Conclusions: RWE supports durvalumab’s efficacy, emphasizing the need for personalized treatment strategies and further research to improve long-term outcomes.",20726694,ONCOLOGY
10.3390/ai6030051,Sentence Interaction and Bag Feature Enhancement for Distant Supervised Relation Extraction,"Background: Distant supervision employs external knowledge bases to automatically match with text, allowing for the automatic annotation of sentences. Although this method effectively tackles the challenge of manual labeling, it inevitably introduces noisy labels. Traditional approaches typically employ sentence-level attention mechanisms, assigning lower weights to noisy sentences to mitigate their impact. But this approach overlooks the critical importance of information flow between sentences. Additionally, previous approaches treated an entire bag as a single classification unit, giving equal importance to all features within the bag. However, they failed to recognize that different dimensions of features have varying levels of significance. Method: To overcome these challenges, this study introduces a novel network that incorporates sentence interaction and a bag-level feature enhancement (ESI-EBF) mechanism. We concatenate sentences within a bag into a continuous context, allowing information to flow freely between them during encoding. At the bag level, we partition the features into multiple groups based on dimensions, assigning an importance coefficient to each sub-feature within a group. This enhances critical features while diminishing the influence of less important ones. In the end, the enhanced features are utilized to construct high-quality bag representations, facilitating more accurate classification by the classification module. Result: The experimental findings from the New York Times (NYT) and Wiki-20m datasets confirm the efficacy of our suggested encoding approach and feature improvement module. Our method also outperforms state-of-the-art techniques on these datasets, achieving superior relation extraction accuracy.",26732688,AI
10.3389/frai.2025.1504281,Transfer learning-based hybrid VGG16-machine learning approach for heart disease detection with explainable artificial intelligence,"Heart disease is a leading cause of mortality worldwide, making accurate early detection essential for effective treatment and management. This study introduces a novel hybrid machine-learning approach that combines transfer learning using the VGG16 convolutional neural network (CNN) with various machine-learning classifiers for heart disease detection. A conditional tabular generative adversarial network (CTGAN) was employed to generate synthetic data samples from actual datasets; these were evaluated using statistical metrics, correlation analysis, and domain expert assessments to ensure the quality of the synthetic datasets. The dataset comprises tabular data with 13 features, which are reshaped into an image-like format and resized to 224x224x3 to meet the input requirements of the VGG16 model. Feature extraction is performed using VGG16, and the extracted features are then fused with the original tabular data. This combined feature set is then used to train various machine learning models, including Support Vector Machines (SVM), Gradient Boosting, Random Forest, Logistic Regression, K-nearest neighbors (KNN), and Decision Trees. Among these models, the VGG16-Random Forest hybrid achieved notable results across all evaluation metrics, including 92% accuracy, 91.3% precision, 92.2% recall, 91.82% specificity, 92.2% sensitivity, and 91.75% F1-score. The hybrid models were also evaluated using unseen datasets to assess the generalizability of the proposed approaches, with the VGG16-Random Forest combination showing relatively promising results. Additionally, explainability is integrated into the model using SHAP values, providing insights into the contribution of each feature to the model’s predictions. This hybrid VGG16-ML approach demonstrates the potential for highly accurate and interpretable heart disease detection, offering valuable support in clinical decision-making processes.",26248212,AI
10.3389/feduc.2025.1510872,Improving sense of belonging in biomedical engineering students through student-faculty lunches,"Introduction: Full undergraduate experience in biomedical engineering should feature cordial interactions between students and faculty as well as a good sense of belonging. However, both factors remain elusive for many students, rendering their undergraduate experience suboptimal. We designed the organized student-faculty lunches to promote informal student-faculty interactions and the formation of belonging among the student participants.Methods: During each lunch, an average of four student participants were paired with one faculty and a student assistant. Lunches were provided at no cost to all participants. Invites for students were based on matching interests during recruitment. A mixed-methods survey, including eight identical Likert-scale questions and up to three free-response questions, was distributed three times: before, immediately after, and 1 month after the lunch. We collected a total of 42 responses for the post-survey and 28 responses for the one-month survey. Four students participated in a 30-minute interview. We used paired t-tests to analyze the Likert-scale questions across the three surveys. We performed regression analysis to quantify the equity in the outcomes of these lunches. We obtained guidelines for conducting these lunches in the future through regression analysis and thematic coding of the surveys and the interviews.Results: We found that the student-faculty lunches generated significant positive impact across all eight Likert-scale questions across three domains of belonging: academic, social, and personal space. Improvements in survey questions within the social and personal space domains tend to be longer lasting and more statistically significant. The regression analyses revealed that our interventions resulted in better parity in sense of belonging among students with different years of academic experience, ethnic identities, and gender identities. These analyses also suggest that the most effective lunch is conducted in the middle of the Winter quarter with an Assistant Professor. Coding analyses revealed that the students were highly satisfied with the lunches and the current format of facilitation, while noting the benefits of these lunches in reducing the interaction barriers between students and faculty. We intend to perform more qualitative analyses on aspects of equity and faculty demographics concerning their impact on the outcomes of these lunches.",2504284X,EDUCATION
10.3389/feduc.2025.1553898,Integrating global perspectives in biomedical science education: the role of project-based learning in addressing Western-centric paradigms and enhancing student preparedness for global health challenges,"Biomedical Sciences education has traditionally focused on Western paradigms, often overlooking the health challenges faced in less economically developed countries. Integrating global perspectives is essential, yet institutional guidelines lack clear directives for doing so. This perspective paper proposes a project-based learning (PBL) approach within undergraduate biomedical sciences modules, which focuses on tropical infectious diseases to promote decolonized learning by contrasting the Global North and South. In this model, students will work collaboratively to learn problem-solving techniques relevant to real-world issues like tropical diseases. Although in theory PBL is a useful way of learning, there are potential challenges with group dynamics and engagement. This paper discusses the various benefits and limitations of implementing this approach.",2504284X,EDUCATION
10.1186/s40359-025-02439-z,Exploring gender differences in workload and job performance: insights from junior high school teachers,"Notable gender disparities exist in the workload and performance of junior high school teachers, although the specific ways in which these disparities manifest have not been fully elucidated. This study examines how specific aspects of teachers’ workload are related to gender differences in aspects of work performance. The study used survey data from 1135 junior high school educators. Teacher workload was assessed using the NASA Task Load Index. Teachers’ work performance was evaluated in terms of task performance and contextual performance. Demographic data included gender, teaching experience, teaching grade, titles, school ownership, rural school designation, marital status, whether they had children, were internal teachers, were multidisciplinary teachers, and whether they were the main subject teachers. Oaxaca–Blinder decomposition was used to analyze the specific contribution and mechanism of workload to the gender gap in work performance. The findings revealed distinct gender differences in work performance, with male teachers demonstrating higher task performance and female teachers reporting higher contextual performance, which mediated the observed disparity. Further analysis indicated that marital status also plays a role, with single teachers experiencing a more pronounced gender gap. These insights signify that gender is a pivotal factor in junior high school teachers’ workload and performance. The study advocates for a deeper investigation within the “gender-workload-capacity development” framework to assist educators in making informed decisions and to foster a more equitable work environment.",20507283,PSYCHOLOGY
10.1186/s40359-025-02522-5,Coarse matching was sufficient to capture attention by working memory representations unless matching features with the target,"Background: In most theoretical frameworks, the effectiveness of attentional selection relies significantly on the perceptual similarity between the target template and visual input. Nevertheless, ambiguity exists surrounding whether attentional capture triggered by irrelevant representations in Working Memory (WM) is influenced by the perceptual similarity levels of features between WM content and its matching distractors. Methods: We designed a hybrid WM and visual search task, varying such perceptual similarity of colors across three levels: exact, high-similar, and low-similar matching. To quantify the extent of the capture effect, we compared these conditions against a neutral baseline (i.e., completely different color) using eye movement and behavioral data in two experiments. Results: We consistently observed robust attentional capture effects across two experiments, evident in both eye movement indices and manual reaction times. In Experiment 1, where WM representations solely matched features to visual search distractors (task-irrelevant scenario), we found that changes in perceptual similarity did not influence attentional capture. Conversely, in Experiment 2, where WM representations had the potential to match the visual search target (task-relevant scenario), we observed a significantly more robust attentional capture effect for high-similar matching compared to low-similar matching conditions. Conclusions: These findings imply that coarse matching between distractors and WM contents is sufficient to capture attention, unless the matching features potentially correspond to the visual target. Furthermore, task relevance sharpens perceptual sensitivity to visual input, highlighting distinct mechanisms underlying attentional capture by irrelevant representations and target templates within WM.",20507283,PSYCHOLOGY
10.1186/s40594-025-00537-3,"The impact of AI-assisted pair programming on student motivation, programming anxiety, collaborative learning, and programming performance: a comparative study with traditional pair programming and individual approaches","This study investigates the impact of AI-assisted pair programming on undergraduate students’ intrinsic motivation, programming anxiety, and performance, relative to both human–human pair programming and individual programming approaches. A quasi-experimental design was conducted over two academic years (2023–2024) with 234 undergraduate students in a Java web application development course. Intact class sections were randomly assigned to AI-assisted pair programming (using GPT-3.5 Turbo in 2023 and Claude 3 Opus in 2024), human–human pair programming, or individual programming conditions. Data on intrinsic motivation, programming anxiety, collaborative perceptions, and programming performance were collected at three time points using validated instruments. Compared to individual programming, AI-assisted pair programming significantly increased intrinsic motivation (p < .001, d = 0.35) and reduced programming anxiety (p < .001), producing outcomes comparable to human–human pair programming. AI-assisted groups also outperformed both individual and human–human groups in programming tasks (p < .001). However, human–human pair programming fostered the highest perceptions of collaboration and social presence, surpassing both AI-assisted and individual conditions (p < .001). Mediation analysis revealed that perceived usefulness of the AI assistant significantly mediated the relationship between the programming approach and student outcomes, highlighting the importance of positive perceptions in leveraging AI tools for educational benefits. No significant differences emerged between the two AI models employed, indicating that both GPT-3.5 Turbo and Claude 3 Opus provided similar benefits. While AI-assisted pair programming enhances motivation, reduces anxiety, and improves performance, it does not fully match the collaborative depth and social presence achieved through human–human pairing. These findings highlight the complementary strengths of AI and human interaction: AI support can bolster learning outcomes, yet human partners offer richer social engagement. As AI capabilities advance, educators should integrate such tools thoughtfully, ensuring that technology complements rather than replaces the interpersonal dynamics and skill development central to effective programming education.",21967822,EDUCATION
10.1186/s40359-025-02513-6,"Moral transgressions, psychological well-being, and family conflict in the context of the COVID-19 pandemic: The role of self-forgiveness","The COVID-19 pandemic led many individuals to experience moral transgressions, exacerbating feelings of guilt and remorse. This study explored the role of the self-forgiveness of such transgressions in explaining their associations with psychological well-being and family conflict. We hypothesized that (a) higher levels of self-forgiveness would be associated with greater psychological well-being and reduced family conflict, (b) the perceived relevance of moral transgressions would be positively associated with self-forgiveness and indirectly associated with psychological well-being and family conflict through the mediation of self-forgiveness, and (c) the relationships between the variables of interest could vary across age. Adults (N = 277; M age = 30.04) completed anonymous online questionnaires assessing the relevance of transgressions committed, forgiveness and unforgiveness of self, psychological well-being, and family conflict during the first COVID-19 lockdown in Italy. Structural equation modeling revealed that transgression relevance was positively associated with both forgiveness and unforgiveness of self, and indirectly related to psychological well-being and family conflict via self-forgiveness. Greater forgiveness of self was related to greater eudaimonic well-being, whereas greater unforgiveness of self was linked to increased family conflict and reduced eudaimonic well-being. The findings also indicated that age moderated the relationship between forgiveness of self and hedonic well-being, with the association weakening as age increased. The results highlight the importance of promoting self-forgiveness to enhance psychological resilience and familial stability, particularly during challenging times.",20507283,PSYCHOLOGY
10.1007/s44196-025-00755-1,Lattice-Based Decision Models for Green Urban Development: Insights from $$L_{q}*$$ q-Rung Orthopair Multi-fuzzy Soft Set,"Location selection is a critical process in decision-making for projects that involve multiple criteria, such as urban planning, industrial site development, or green building projects. Multiple criteria decision making (MCDM) is a systematic approach that evaluates and ranks potential alternatives based on a set of often conflicting criteria. This study focuses on selecting the optimal urban location for a green building project by employing the \(L_{q}*\) q-rung orthopair multi-fuzzy soft-MCDM(\(L_{q}*\) q-ROMFS) techniques. The \(L_{q}*\) q-ROMFS set combines elements from two distinct theories with lattice ordering parameters: q-rung orthopair fuzzy set and multi-fuzzy soft set. It provides a mathematical framework with multiple parameters that effectively represents problems involving multi-dimensional data within a dataset. We expand this concept by establishing the algebraic structures of \(L_{q}*\) q-ROMFS sets, including properties like modularity and distributivity, while also analyzing their homomorphism under lattice mappings. Finally, leveraging the \(L_{q}*\) q-ROMFS matrix, we propose both a choice matrix and a weighted choice matrix to effectively address the selection of the optimal urban location for a green building project.",18756883,AI
10.1186/s40359-025-02494-6,The use of video feedback to promote developmentally supportive parent–child interactions with young children with ASD or at risk: study protocol for a randomized controlled trial (VIFEPOPA-RCT),"Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by difficulties in social communication and interaction, and repetitive and restrictive behaviors and interests from an early age. ASD often negatively affects caregiver-child interactions, caregiver emotional well-being and self-efficacy, and quality of family life. Positive caregiver–child interactions are crucial for good developmental outcomes, leading to the development of Parent-Mediated Interventions (PMIs). PMIs tend to follow an expert model where professionals provide direct instruction on treatment techniques and parental behaviors. However, research supports a shift towards a more collaborative and reflective approach, using coaching strategies that highlight caregiver strengths and encourage self-reflection. This study tests a video-feedback intervention (VFI) with parents of young children at risk of ASD. A randomized controlled trial (RCT) with 60 families, recruited from Early Intervention Centers in Spain, meeting inclusion criteria: adequate use of internet, child aged 24–36 months with a high risk of ASD (M-CHAT-R score ≥ 8), and participant primary caregiver (mother or father) with high anxiety, depression, or parental stress (score ≥ 1 SD above M), and low or medium–low developmentally supportive parental behaviors (PICCOLO score ≤ 40). Families will be randomly assigned to an intervention group (receiving usual services plus VFI) or a control group (usual services). The intervention includes twelve bi-weekly 90-min sessions over six months, with the caregiver. Outcome measures include parenting behaviors, emotional state, self-efficacy, family quality of life, and child development collected at pre-intervention, post- intervention and six-month follow-up. The study will assess whether the intervention enhances developmentally supportive parental behaviors, emotional well-being, self-efficacy, and family quality of life, with a secondary positive impact on child development. If proven effective, it could be a cost-effective intervention with both short and long-term benefits. ClinicalTrials.gov Identifier NCT06604988. Registered on September 17, 2024. Retrospectively registered.",20507283,PSYCHOLOGY
10.3389/feduc.2025.1523124,Basic psychological needs satisfaction as a mediator of the effects of a formative assessment practice on behavioral engagement and autonomous motivation,"Formative assessment has been suggested as a means of supporting student motivation. However, empirical studies have shown mixed effects of formative assessment interventions on students’ motivation, making it necessary to understand the mechanisms underlying these effects. We analyzed a formative classroom practice implemented by a 10th-grade first-language teacher during 7 months. Teacher logs, classroom observations and a teacher interview were used to collect data for characterizing the formative assessment practice. Changes in students’ satisfaction regarding the basic psychological needs of perceived autonomy, competence and relatedness, as well as changes in student motivation manifesting as engagement in learning activities and autonomous types of motivation, were measured by pre- and post-questionnaires in the intervention class and four comparison classes. Since the intraclass correlation values ICC(1) and ICC(2) were low, we treated the comparison classes as one group and t-tests were used in the significance testing of the differences in changes in psychological needs satisfaction and motivation between the intervention class and the comparison classes. Path analysis was conducted to investigate whether a possible influence of the intervention on autonomous motivation and behavioral engagement would be mediated by basic psychological needs satisfaction. The analysis of the classroom practice in the intervention class identifies that both teacher and students were proactive agents in formative assessment processes. The analysis of the quantitative data shows that students’ psychological needs satisfaction increased more in the intervention class than in the comparison classes, and that this needs satisfaction mediated an effect on students’ behavioral engagement and autonomous motivation.",2504284X,EDUCATION
10.1007/s00432-025-06135-8,Impact of interdisciplinary tumor boards (ITB) and personalized treatment on survival outcomes in metastatic castration-resistant prostate cancer,"Purpose: Interdisciplinary tumor boards (ITB) are essential in optimizing treatment recommendations for metastatic castration-resistant prostate cancer (mCRPC) by incorporating oncology guidelines, clinical trials, and patient-specific factors to ensure individualized care. This study examines clinical parameters that influence ITB recommendations, evaluates their adherence to guidelines, and assesses their impact on patient survival. Methods: In a retrospective analysis, data from 187 mCRPC patients discussed at an ITB in a tertiary care center in 2018 were evaluated. Patient- and disease-specific factors were correlated with adherence to National Comprehensive Cancer Network® (NCCN®) guidelines and overall survival (OS). The impact of clinical parameters on survival outcomes was assessed through univariate and multivariate analyses. Results: The median patient age was 72.8 years, with a median prostate-specific antigen (PSA) level of 65.0 ng/ml. Guideline-compliant recommendations were given in 42.9% of cases, while 57.1% received individualized recommendations. Clinical trial eligibility was noted in 24.8% of patients. Individualized ITB recommendations were associated with significantly longer OS (38.3 vs. 21.2 months, p = 0.03). Shorter OS correlated with renal impairment (p = 0.007), symptomatic metastases (p < 0.0001), and visceral metastases (p < 0.0001). Limitations include the retrospective design, lack of follow-up on therapy adherence, and absence of progression-free survival (PFS) data. Conclusion: ITB discussions improve survival in mCRPC patients, mainly due to personalized approaches and better access to clinical trials. Visceral and symptomatic metastases as well as renal impairment are risk factors for reduced OS, emphasizing the need for careful management of these high-risk patients. The results support the expanded use of ITB to improve mCRPC treatment outcomes.",14321335,ONCOLOGY
10.3389/fpsyg.2025.1532937,An encounter with death: a comparative thematic and content analysis of naturalistic DMT experiences and the near-death experience,"Introduction: Classical near-death experiences (NDEs) refer to states of disconnected consciousness characterised by a range of features occurring in the context of being close to death. Various psychedelic substances, such as N,N-dimethyltryptamine (DMT), consistently replicate NDE features and may be considered ‘near-death-like experiences.’ However, a systematic qualitative analysis comparing the specifics of content with the broader themes of both psychedelic and NDEs has yet to be conducted.Methods: We report the third thematic and content analysis of the DMT experience from a naturalistic field study, focusing on themes related to death and dying. Based on 36 semi-structured interviews, this analysis is then directly compared, qualitatively and in terms of content frequency, with a novel extension of a previous thematic analysis of 34 written NDE narratives.Results: The ‘canonical NDE themes’ identified across the DMT experiences included Translocation, Bright Light(s), Sense of Dying, The Void, Disembodiment, Tunnel-like Structures, Light Being-esque Entities, Deceased Family, Life Review-like, and Hyper-empathic Experiences. A total of 95% of participants reported at least one of these. Twelve ‘less typical NDE motifs’ were also noted. Five classical NDE features were entirely absent from DMT, while DMT exhibited an even broader array of experience features that were absent from NDEs. DMT clearly shares a more basic phenomenological structure with NDEs but shows differences in the prevalence of certain features. Furthermore, DMT did not present any immediately recognisable linear sequencing of themes. Overall, DMT is distinctly unique in its qualitative content, characterised by its more prodigious and stereotypical nature, which includes kaleidoscopic, extraterrestrial, transcultural, fluctuating, and overwhelming elements.Discussion: When examining the comparability between DMT and NDEs at a fundamentally more nuanced level of qualitative content (as opposed to broad themes or questionnaire items), the two experiences clearly diverge. However, a minority of NDEs, which are themselves unique, do share significant content with DMT. Taken together, DMT could be considered an ‘NDE-mimetic.’ The weaker comparability is likely due not only to differences in context but also to the complex neural processes occurring near death, in which endogenous DMT may only play a small role. In light of this level of parallelism with NDEs, some potential clinical applications of DMT are also discussed.",16641078,PSYCHOLOGY
10.3389/frai.2025.1554325,The relevance of lead prioritization: a B2B lead scoring model based on machine learning,"In business-to-business (B2B) companies, marketing and sales teams face significant challenges in identifying, qualifying, and prioritizing a large number of leads. Lead prioritization is a critical task for B2B organizations because it allows them to allocate resources more effectively, focus their sales force on the most viable and valuable opportunities, optimize their time spent qualifying leads, and maximize their B2B digital marketing strategies. This article addresses the topic by presenting a case study of a B2B software company's development of a lead scoring model based on data analytics and machine learning under the consumer theory approach. The model was developed using real lead data generated between January 2020 and April 2024, extracted from the company's CRM, which were analyzed and evaluated by fifteen classification algorithms, where the results in terms of accuracy and ROC AUC showed a superior performance of the Gradient Boosting Classifier over the other classifiers. At the same time, the feature importance analysis allowed the identification of features such as “source” and “lead status,” which increased the accuracy of the conversion prediction. The developed model significantly improved the company's ability to identify high quality leads compared to the traditional methods used. This research confirms and complements existing theories related to understanding the application of consumer behavior theory and the application of machine learning in the development of B2B lead scoring models. This study also contributes to bridging the gap between marketers and data scientists in jointly understanding lead scoring as a critical activity because of its impact on overall marketing strategy performance and sales revenue performance in B2B organizations.",26248212,AI
10.1007/s00432-025-06154-5,"Semaglutide, a glucagon-like peptide-1 receptor agonist, inhibits oral squamous cell carcinoma growth through P38 MAPK signaling pathway","Aims Researches have shown that diabetes mellitus (DM) can promote the risk and progression of oral squamous cell carcinoma (OSCC). Semaglutide, a glucagon-like peptide-1 receptor agonist, is currently employed to treat type 2 diabetes mellitus (T2DM) and obesity. This study intends to explore the potential effects and mechanism of Semaglutide on OSCC. Methods The expression of GLP-1R in OSCC cells and tissues was evaluated by qRT-PCR, western blot and immunohistochemistry assays. Cell proliferation, invasion, migration and apoptosis abilities were determined by relevant experiments. Western blot was employed to verify the expression of relevant proteins and examine the effect of Semaglutide on the MAPK signaling pathway. The xenograft transplantation model of OSCC was established to examine the anti-cancer effects of Semaglutide in vivo and immunohistochemistry assays were performed on tumor tissues. Results GLP-1R expression was elevated in OSCC cells and tissues as compared with that in normal. Semaglutide effectively inhibited the proliferation, migration and invasion of OSCC cells while concurrently promoting apoptosis. Moreover, Semaglutide specifically activated the P38 MAPK signaling pathway without significant influence on ERK1/2 or SAPK/JNK, and its pro-apoptotic effects in OSCC cells was related to P38 pathway activation. Animal experiments verified the inhibitory effect of Semaglutide on OSCC tumors in mice. Conclusions Semaglutide exerts inhibitory actions on OSCC and may induce apoptosis in OSCC cells via the P38 MAPK signaling pathway. This study has significant implications for the treatment of patients with diabetes who are also afflicted by OSCC.",14321335,ONCOLOGY
10.3390/ai6030053,Trade-Offs in Navigation Problems Using Value-Based Methods,"Deep Q-Networks (DQNs) have shown remarkable results over the last decade in scenarios ranging from simple 2D fully observable short episodes to partially observable, graphically intensive, and complex tasks. However, the base architecture of a vanilla DQN presents several shortcomings, some of which were mitigated by new variants focusing on increased stability, faster convergence, and time dependencies. These additions, on the other hand, bring increased costs in terms of the required memory and lengthier training times. In this paper, we analyze the performance of state-of-the-art DQN families in a simple partially observable mission created in Minecraft and try to determine the optimal architecture for such problem classes in terms of the cost and accuracy. To the best of our knowledge, the analyzed methods have not been tested on the same scenario before, and hence a more in-depth comparison is required to understand the real performance improvement they provide better. This manuscript also offers a detailed overview of state-of-the-art DQN methods, together with the training heuristics and performance metrics registered during the proposed mission, allowing researchers to select better-suited models to solving future problems. Our experiments show that Double DQN networks are capable of handling partially observable scenarios gracefully while maintaining a low hardware footprint, Recurrent Double DQNs can be a good candidate even when the resources must be restricted, and double-dueling DQNs are a well-performing middle ground in terms of their cost and performance.",26732688,AI
10.3390/educsci15030339,Procedural Learning in Mixed Reality: Assessing Cognitive Load and Performance,"Immersive technologies offer promising advancements in medical education, particularly in procedural skill acquisition. However, their implementation often lacks a foundation in learning theories. This study investigates the application of the split-attention principle, a multimedia learning guideline, in the design of knot-tying procedural content using a mixed reality (MR) technology, specifically Microsoft HoloLens 2. A total of 26 participants took part in a between-group design experiment comparing integrated and split-source formats for learning arthroscopic knots, with the performance and the cognitive load assessed. The initial hypotheses were not confirmed, as results did not show significant differences in performance during recall, nor in extraneous and germane cognitive load. However, the findings on intrinsic cognitive load highlight the complexity of participant engagement and the cognitive demands of procedural learning. To better capture the split-attention effect, future research should address the high element interactivity in MR representations. The study provides some foundation for designing procedural simulation training that considers both learners’ needs and cognitive processes in highly immersive environments. It contributes to the ongoing exploration of instructional design in MR-based medical education, emphasizing both the potential and challenges of multimedia learning principles in advanced technological contexts.",22277102,EDUCATION
10.3390/ejihpe15030032,"Sex, Resilience and Psychological Well-Being in Mexican University Students","Mental health is currently highly relevant in society and one of the factors that could contribute to its improvement is psychological well-being, hence the importance of conducting studies that focus on analyzing variables that predict psychological well-being. Therefore, the goal of this research is to use models of structural equations to analyze the relationships among the variables of sex and resilience for psychological well-being. The total sample was 1190 Mexican university students, with an average age of 20.66 years (SD = 1.89). The results indicate that the resilience factors (strength and confidence, family support, and social support) are the variables with the greatest explanatory power on psychological well-being. It also highlights the mediating capacity of the strength and confidence factor between the other two resilience factors (family support, social support) and perceived psychological well-being. The implications of the study are that sex and two of the dimensions of resilience (family support and social support) show an indirect and positive effect on the perception of psychological well-being through the strength and confidence factor. Therefore, when implementing interventions to improve psychological well-being, these factors should be considered in order to have a greater positive impact on the population that is being studied. Future research should replicate these findings in larger samples.",22549625,PSYCHOLOGY
10.3389/frai.2025.1491958,Code generation system based on MDA and convolutional neural networks,"Introduction: The software industry has rapidly evolved with high performance. This is owing to the implementation of good programming practices and architectures that make it scalable and adaptable. Therefore, a strong incentive is required to develop the processes that initiate this project.Method: We aimed to provide a platform that streamlines the development process and connects planning, structuring, and development. Specifically, we developed a system that employs computer vision, deep learning, and MDA to generate source code from the diagrams describing the system and the respective study cases, thereby providing solutions to the proposed problems.Results and discussion: The results demonstrate the effectiveness of employing computer vision and deep learning techniques to process images and extract relevant information. The infrastructure is designed based on a modular approach employing Celery and Redis, enabling the system to manage asynchronous tasks efficiently. The implementation of image recognition, text analysis, and neural network construction yields promising outcomes in generating source code from diagrams. Despite some challenges related to hardware limitations during the training of the neural network, the system successfully interprets the diagrams and produces artifacts using the MDA approach. Plugins and DSLs enhance flexibility by supporting various programming languages and automating code deployment on platforms such as GitHub and Heroku.",26248212,AI
10.3390/ai6030054,A Bibliometric Analysis on Artificial Intelligence in the Production Process of Small and Medium Enterprises,"Industry 4.0 represents the main paradigm currently bringing great innovation in the field of automation and data exchange among production technologies, according to the principles of interoperability, virtualization, decentralization and production flexibility. The Fourth Industrial Revolution is driven by structural changes in the manufacturing sector, such as the demand for customized products, market volatility and sustainability goals, and the integration of artificial intelligence and Big Data. This work aims to analyze, from a bibliometric point of view of journal papers on Scopus, with no time limitation, the existing literature on the application of AI in SMEs, which are crucial elements in the industrial and economic fabric of many countries. However, the adoption of modern technologies, particularly AI, can be challenging for them, due to the intrinsic structure of this type of enterprise, despite the positive effects obtained in large organizations.",26732688,AI
10.3390/ai6030055,Integrating Pose Features and Cross-Relationship Learning for Human–Object Interaction Detection,"Background: The main challenge in human–object interaction detection (HOI) is how to accurately reason about ambiguous, complex, and difficult to recognize interactions. The model structure of the existing methods is relatively single, and the image input may be occluded and cannot be accurately recognized. Methods: In this paper, we design a Pose-Aware Interaction Network (PAIN) based on transformer architecture and human posture to address these issues through two innovations: A new feature fusion method is proposed, which fuses human pose features and image features early before the encoder to improve the feature expression ability, and the individual motion-related features are additionally strengthened by adding to the human branch; the Cross-Attention Relationship fusion Module (CARM) better fuses the three-branch output and captures the detailed relationship information of HOI. Results: The proposed method achieves 64.51%AProle#1, 66.42%AProle#2 on the public dataset V-COCO and 30.83% AP on HICO-DET, which can recognize HOI instances more accurately.",26732688,AI
10.3390/ai6030056,"Emotion-Aware Embedding Fusion in Large Language Models (Flan-T5, Llama 2, DeepSeek-R1, and ChatGPT 4) for Intelligent Response Generation","Empathetic and coherent responses are critical in automated chatbot-facilitated psychotherapy. This study addresses the challenge of enhancing the emotional and contextual understanding of large language models (LLMs) in psychiatric applications. We introduce Emotion-Aware Embedding Fusion, a novel framework integrating hierarchical fusion and attention mechanisms to prioritize semantic and emotional features in therapy transcripts. Our approach combines multiple emotion lexicons, including NRC Emotion Lexicon, VADER, WordNet, and SentiWordNet, with state-of-the-art LLMs such as Flan-T5, Llama 2, DeepSeek-R1, and ChatGPT 4. Therapy session transcripts, comprising over 2000 samples, are segmented into hierarchical levels (word, sentence, and session) using neural networks, while hierarchical fusion combines these features with pooling techniques to refine emotional representations. Attention mechanisms, including multi-head self-attention and cross-attention, further prioritize emotional and contextual features, enabling the temporal modeling of emotional shifts across sessions. The processed embeddings, computed using BERT, GPT-3, and RoBERTa, are stored in the Facebook AI similarity search vector database, which enables efficient similarity search and clustering across dense vector spaces. Upon user queries, relevant segments are retrieved and provided as context to LLMs, enhancing their ability to generate empathetic and contextually relevant responses. The proposed framework is evaluated across multiple practical use cases to demonstrate real-world applicability, including AI-driven therapy chatbots. The system can be integrated into existing mental health platforms to generate personalized responses based on retrieved therapy session data. The experimental results show that our framework enhances empathy, coherence, informativeness, and fluency, surpassing baseline models while improving LLMs’ emotional intelligence and contextual adaptability for psychotherapy.",26732688,AI
10.3389/fpsyg.2025.1545943,From contemplation to serenity: how yoga meditation improves the mental health of female college students?,"Objective: This study aims to investigate the impact of yoga meditation on the mental health of female college students, focusing on how meditation improves emotional regulation, alleviates stress and strengthens psychological resilience.Methods: Employing a combination of quantitative assessment and qualitative analysis, the study measured participants’ emotional states, stress levels, and psychological resilience across multiple time points to track participants’ mental health changes dynamically. In-depth interviews and analysis of meditation journals were also conducted.Results: Yoga meditation significantly reduced anxiety, depression, and perceived stress while enhancing emotional regulation and self-awareness. Meditation positively influenced neuroplasticity, inducing beneficial changes in brain regions associated with emotional control and cognitive flexibility. Additionally, improved autonomic nervous system function was observed, with increased parasympathetic activity and reduced sympathetic response. Meditation strengthened psychological resilience in female college students, improved stress-coping strategies, and sustained positive mental health benefits even after the intervention.Conclusion: Yoga meditation is an effective mental health intervention, bolstering emotional regulation and reducing stress among female college students. Integrating yoga meditation into campus mental health programs is recommended to provide students with greater practice opportunities and personalized guidance.",16641078,PSYCHOLOGY
10.3389/feduc.2025.1481708,Technologies applied to education in the learning of English as a second language,"This systematic review, conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, evaluates the efficacy of emerging digital technologies—namely virtual reality (VR), augmented reality (AR), and adaptive learning technologies (ALT)—in enhancing vocabulary acquisition within English as a second language (ESL) education. By addressing a notable gap in the literature, this review explores how these technologies mitigate common learning challenges and improve educational outcomes. Through a critical analysis of recent empirical studies across diverse educational stages, it synthesizes findings to assess their impact on vocabulary retention and overall academic performance. The results indicate that these technologies enhance vocabulary acquisition and increase student motivation and engagement, significantly impacting educational practices and policymaking. This review highlights the transformative potential of VR, AR, and ALT in ESL education by providing immersive and personalized learning experiences that address traditional barriers in language acquisition.",2504284X,EDUCATION
10.3389/frai.2025.1540646,InGSA: integrating generalized self-attention in CNN for Alzheimer's disease classification,"Alzheimer's disease (AD) is an incurable neurodegenerative disorder that slowly impair the mental abilities. Early diagnosis, nevertheless, can greatly reduce the symptoms that are associated with the condition. Earlier techniques of diagnosing the AD from the MRI scans have been adopted by traditional machine learning technologies. However, such traditional methods involve depending on feature extraction that is usually complex, time-consuming, and requiring substantial effort from the medical personnel. Furthermore, these methods are usually not very specific as far as diagnosis is concerned. In general, traditional convolutional neural network (CNN) architectures have a problem with identifying AD. To this end, the developed framework consists of a new contrast enhancement approach, named haze-reduced local-global (HRLG). For multiclass AD classification, we introduce a global CNN-transformer model InGSA. The proposed InGSA is based on the InceptionV3 model which is pre-trained, and it encompasses an additional generalized self-attention (GSA) block at top of the network. This GSA module is capable of capturing the interaction not only in terms of the spatial relations within the feature space but also over the channel dimension it is capable of picking up fine detailing of the AD information while suppressing the noise. Furthermore, several GSA heads are used to exploit other dependency structures of global features as well. Our evaluation of InGSA on a two benchmark dataset, using various pre-trained networks, demonstrates the GSA's superior performance.",26248212,AI
10.3390/ai6030058,Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices?,"Accurate and reliable crop yield prediction is essential for optimizing agricultural management, resource allocation, and decision-making, while also supporting farmers and stakeholders in adapting to climate change and increasing global demand. This study introduces an innovative approach to crop yield prediction by incorporating spatially lagged spectral data (SLSD) through the spatial-lagged machine learning (SLML) model, an enhanced version of the spatial lag X (SLX) model. The research aims to show that SLSD improves prediction compared to traditional vegetation index (VI)-based methods. Conducted on a 19-hectare cornfield at the ARS Grassland, Soil, and Water Research Laboratory during the 2023 growing season, this study used five-band multispectral image data and 8581 yield measurements ranging from 1.69 to 15.86 Mg/Ha. Four predictor sets were evaluated: Set 1 (spectral bands), Set 2 (spectral bands + neighborhood data), Set 3 (spectral bands + VIs), and Set 4 (spectral bands + top VIs + neighborhood data). These were evaluated using the SLX model and four decision-tree-based SLML models (RF, XGB, ET, GBR), with performance assessed using R2 and RMSE. Results showed that incorporating spatial neighborhood data (Set 2) outperformed VI-based approaches (Set 3), emphasizing the importance of spatial context. SLML models, particularly XGB, RF, and ET, performed best with 4–8 neighbors, while excessive neighbors slightly reduced accuracy. In Set 3, VIs improved predictions, but a smaller subset (10–15 indices) was sufficient for optimal yield prediction. Set 4 showed slight gains over Sets 2 and 3, with XGB and RF achieving the highest R2 values. Key predictors included spatially lagged spectral bands (e.g., Green_lag, NIR_lag, RedEdge_lag) and VIs (e.g., CREI, GCI, NCPI, ARI, CCCI), highlighting the value of integrating neighborhood data for improved corn yield prediction. This study underscores the importance of spatial context in corn yield prediction and lays the foundation for future research across diverse agricultural settings, focusing on optimizing neighborhood size, integrating spatial and spectral data, and refining spatial dependencies through localized search algorithms.",26732688,AI
10.3390/ai6030059,Clinical Applicability of Machine Learning Models for Binary and Multi-Class Electrocardiogram Classification,"Background: This study investigates the application of machine learning models to classify electrocardiogram signals, addressing challenges such as class imbalances and inter-class overlap. In this study, “normal” and “abnormal” refer to electrocardiogram findings that either align with or deviate from a standard electrocardiogram, warranting further evaluation. “Borderline” indicates an electrocardiogram that requires additional assessment to distinguish benign variations from pathology. Methods: A hierarchical framework reformulated the multi-class problem into two binary classification tasks—distinguishing “Abnormal” from “Non-Abnormal” and “Normal” from “Non-Normal”—to enhance performance and interpretability. Convolutional neural networks, deep neural networks, and tree-based models, including Gradient Boosting Classifier and Random Forest, were trained and evaluated using standard metrics (accuracy, precision, recall, and F1 score) and learning curve convergence analysis. Results: Results showed that convolutional neural networks achieved the best balance between generalization and performance, effectively adapting to unseen data and variations without overfitting. They exhibit strong convergence and robust feature importance rankings, with ventricular rate, QRS duration, and P-R interval identified as key predictors. Tree-based models, despite their high performance metrics, demonstrated poor convergence, raising concerns about their reliability on unseen data. Deep neural networks achieved high sensitivity but suffered from overfitting, limiting their generalizability. Conclusions: The hierarchical binary classification approach demonstrated clinical relevance, enabling nuanced diagnostic insights. Furthermore, the study emphasizes the critical role of learning curve analysis in evaluating model reliability, beyond performance metrics alone. Future work should focus on optimizing model convergence and exploring hybrid approaches to improve clinical applicability in electrocardiogram signal classification.",26732688,AI
10.1007/s00432-025-06157-2,Elevated platelet distribution width and diabetes may serve as preoperative predictors of microvascular invasion in primary hepatocellular carcinoma,"Background and objective Hepatocellular carcinoma (HCC) is one of the malignancies with increasing incidence globally, and microvascular invasion (MVI) is a crucial determinant of prognosis in patients. This study aimed to investigate platelet distribution width (PDW) and diabetes mellitus as indicators for predicting preoperative MVI in HCC, providing more accurate predictive tools for clinicians to guide treatment strategies and improve patient survival and quality of life. Methods A retrospective study was conducted, including 1357 patients who underwent hepatectomy for HCC between January 2008 and December 2014 at the Eastern Hepatobiliary Surgery Hospital in China. Clinical, pathological, and radiological data, including PDW and diabetes status, were collected. Univariate and multivariate logistic regression analyses were performed to identify risk factors for MVI and establish a predictive model. The predictive performance of the model was evaluated through nomograms and internal validation. Results Univariate analysis revealed significant associations between MVI and diabetes mellitus, presence of liver cirrhosis, prealbumin level, tumor diameter, number of tumors, HBV DNA viral load > 104, and PDW ≥ 17. Multivariate logistic regression analysis identified diabetes mellitus, liver cirrhosis, prealbumin level, tumor diameter, number of tumors, HBV DNA viral load > 104, and PDW ≥ 17 as independent risk factors for MVI. Based on these findings, a predictive model was established, demonstrating high predictive accuracy and stability in both the training and validation cohorts. Conclusion This study confirmed PDW and diabetes mellitus as reliable indicators for predicting preoperative MVI in HCC and established a corresponding predictive model. Future research should further explore the underlying mechanisms and enhance clinical validation to advance the field of HCC treatment.",14321335,ONCOLOGY
10.1186/s40359-025-02581-8,Psychometric properties of the Persian version of the ambivalent ageism scale (benevolent and hostile) in the adult population in Iran,"With the growing population of older adults and the prevalence of negative attitudes towards them, the issue of ageism and its health and economic impacts in both benevolent and hostile contexts warrants special attention. It is crucial to examine the attitudes of other age groups towards older adults across different societies. Particularly, the benevolent dimension of ageism, which has been less explored in research, requires more focus. Therefore, this study aims to conduct a psychometric evaluation of The Ambivalent Ageism Scale among the adult population in Iran. This methodological study was conducted in comprehensive health centers in Gorgan city in 2023. A total of 381 eligible adults participated. The Ambivalent Ageism Scale (AAS) was utilized, and the psychometric assessment included translation, face validity, and content validity. Additionally, exploratory factor analysis and confirmatory factor analysis were performed. The reliability of the scale was evaluated using the internal consistency method. The research findings were analyzed using SPSS and AMOS software version 24. Qualitative face and content validity assessments led to textual and editorial modifications of the items. The Content Validity Ratio (CVR), Item-Content Validity Index (I-CVI), and Kappa (K*) scores were acceptable for all items. In the exploratory factor analysis (EFA), similar to the original questionnaire, three factors were extracted, accounting for approximately 54% of the total variance. The fit indices in the confirmatory factor analysis (CFA) indicated an acceptable model fit. During CFA, four items were eliminated. The reliability of the entire questionnaire was deemed acceptable with a Cronbach’s alpha coefficient of 0.763. Consequently, the Persian version of the Ambivalent Ageism Scale was confirmed with nine items. The Persian version of The Ambivalent Ageism Scale demonstrates sufficient validity and reliability for measuring attitudes towards aging within Iranian society. Given the cultural adaptation of this tool, the questionnaire can be utilized to assess adults’ views and attitudes towards older adults in both hostile and benevolent dimensions. Furthermore, it can aid in formulating family-oriented policies for older adult care and facilitate improvements in the quality of care for this population group.",20507283,PSYCHOLOGY
10.3390/ai6030062,AI-Driven Telerehabilitation: Benefits and Challenges of a Transformative Healthcare Approach,"Artificial intelligence (AI) has revolutionized telerehabilitation by integrating machine learning (ML), big data analytics, and real-time feedback to create adaptive, patient-centered care. AI-driven systems enhance telerehabilitation by analyzing patient data to personalize therapy, monitor progress, and suggest adjustments, eliminating the need for constant clinician oversight. The benefits of AI-powered telerehabilitation include increased accessibility, especially for remote or mobility-limited patients, and greater convenience, allowing patients to perform therapies at home. However, challenges persist, such as data privacy risks, the digital divide, and algorithmic bias. Robust encryption protocols, equitable access to technology, and diverse training datasets are critical to addressing these issues. Ethical considerations also arise, emphasizing the need for human oversight and maintaining the therapeutic relationship. AI also aids clinicians by automating administrative tasks and facilitating interdisciplinary collaboration. Innovations like 5G networks, the Internet of Medical Things (IoMT), and robotics further enhance telerehabilitation’s potential. By transforming rehabilitation into a dynamic, engaging, and personalized process, AI and telerehabilitation together represent a paradigm shift in healthcare, promising improved outcomes and broader access for patients worldwide.",26732688,AI
10.1186/s40359-025-02600-8,Psychometric properties of the Persian version of the suicidal intrusions attributes scale (SINAS) in patients with suicidal attempt,"The Suicidal Intrusions Attributes Scale (SINAS) is a brief self-report measure designed to assess the frequency, distress, and controllability of suicidal intrusions—vivid, uncontrollable mental images and thoughts related to suicide or its aftermath. Despite its clinical relevance, its psychometric properties remain underexplored. This study aimed to evaluate the psychometric properties of the Persian version of the SINAS. A cross-sectional design was employed. 304 outpatients (aged 18 to 65, M = 27.27, SD = 8.53) including 243 males and 61 females with a history of suicide attempts were recruited using a convenience sampling method from psychiatric clinics and hospitals in Tehran. Participants completed the SINAS along with the Beck Depression Inventory-II (BDI-II) to assess depressive symptoms, the Beck Hopelessness Scale (BHS) to measure negative expectations about the future, the Beck Scale for Suicide Ideation (BSSI) to evaluate suicidal thoughts and intentions, and the Suicide Behaviors Questionnaire-Revised (SBQ-R) to assess past suicidal behaviors and future risk. Confirmatory factor analysis supported a one-factor structure of the SINAS, which was invariant across gender groups. The scale demonstrated strong internal consistency and good test-retest reliability over a two-week interval. Additionally, the SINAS showed significant associations with depressive symptoms, hopelessness, suicide ideation, and suicide risk behaviors, supporting its convergent validity. Overall, the findings indicate that the Persian version of the SINAS is a valid and reliable instrument for assessing suicidal intrusions in both clinical and research settings in Iran.",20507283,PSYCHOLOGY
10.1007/s44196-025-00781-z,A Deep Learning Model Leveraging Time-Series System Call Data to Detect Malware Attacks in Virtual Machines,"A Tenant Virtual Machine (TVM) user in the cloud may misuse its computing power to launch malware attack against other tenant VMs, Host OS, Hypervisor, or any other computing devices/resources inside the cloud environment of a Cloud Service Provider. The security solutions deployed within the TVM may not be reliable, as malware can disable them or remain undetected due to its hidden nature. Therefore, security solutions deployed outside the virtual machine are necessary. This research proposes deploying an Intrusion Detection System (IDS) at the Hypervisor layer, utilizing time series system call data and employing a Convolutional Neural Network (CNN) model to accurately detect the presence of malicious (malware) computer programs within virtual machines. The raw VMM system call traces are transformed into novel Time Series System Call patterns and utilized by a deep learning algorithm for training and building the classifier model. A deep learning model, CNN, is used to build the classifier model for detecting intrusions with high accuracy. It is capable of detecting both known and unknown malware. The CNN model is compared with machine learning algorithms for the results and discussions, and it outperforms ML algorithms in terms of intrusion detection accuracy when utilizing novel time series system call data..",18756883,AI
10.3390/ejihpe15030037,Linguistic and Cognitive Abilities in Children with Dyslexia: A Comparative Analysis,"Introduction: Dyslexia is a prevalent learning disorder that significantly affects the child population. It is often accompanied by deficits in language processes, cognition, and executive functioning, all of which are crucial for reading development. Children with dyslexia frequently exhibit difficulties in phonological processing, semantics, morphosyntax, and also in cognitive areas such as working memory, inhibition, planning, and attention. Objective: The primary objective of this study was to compare the linguistic, cognitive, and executive functioning abilities between children diagnosed with dyslexia and those with typical reading development. Methodology: A total of 120 children were selected and divided into two groups: the G-DYSLEXIA group (n = 60), consisting of children diagnosed with dyslexia, and the G-CONTROL group (n = 60), with typical reading development. Language, cognition, and executive functions were assessed using standardized tests: CELF-5, WISC-V, and ENFEN. Statistical analyses included descriptive statistics, independent sample t-tests, and Chi-square tests to compare the performance between these two groups. Results: The study revealed significant differences between the two groups in all dimensions assessed. Specifically, children with dyslexia showed markedly lower performance in linguistic, cognitive, and executive functioning measures compared with their peers with typical development. Conclusion: Children with dyslexia present a distinct clinical profile characterized by significant difficulties in language processing, cognition, and executive functions. These challenges interfere with their reading acquisition and academic performance, limiting their integration into educational environments and impacting their overall quality of life.",22549625,PSYCHOLOGY
10.3390/educsci15030375,Technology-Enhanced Language Learning: Subtitling as a Technique to Foster Proficiency and Intercultural Awareness,"Computer-Assisted Language Learning (CALL) is an umbrella term that encompasses diverse technologies with the purpose of enhancing language learning. In the existing literature on CALL, intercultural awareness and the pedagogical use of multimedia products have received less attention. This study explores how the process of creating subtitles for short clips may enhance language skills and intercultural awareness when implemented through lesson plans designed following the framework proposed by the TRADILEX project. A pre-experimental longitudinal design was implemented. The sample consisted of 43 participants who were enrolled in a B2 English course at the University of Córdoba (Spain). During the course, participants consistently attended theoretical sessions. The intervention took place during the practical sessions from February to April 2024, involving four subtitling-based lesson plans on literature and gender. After the intervention, the practical sessions shifted to a traditional, textbook-based format from April to June 2024. The instruments employed to assess the effectiveness of the intervention consisted of a commercial test by MacMillan and the ERI scale on interculturality. The results showed that after the intervention, there was a significant improvement in language proficiency, which increased at a slower rate during the traditional sessions. However, when it comes to intercultural awareness, there was a peak of attainment after the intervention, but attrition rapidly took place. Regarding the pedagogical implications of this study, subtitling could be an appropriate technique that allows contact with the L2 culture and shows positive effects in terms of proficiency.",22277102,EDUCATION
10.3390/ejihpe15030039,The Moving Mandala: Exploring the Pro-Social Effects of Musical and Non-Musical Synchrony in Children in a Virtual World,"Synchronous movement between individuals has been shown to increase pro-sociality, such as closeness and generosity. To date, synchrony research tests these effects using a variety of movement tasks, including musical and non-musical coordination. However, musical versus non-musical synchrony may have separable pro-social effects. To test this, we had 60 children immersed in an augmented reality space called the ‘Moving Mandala’ where they moved asynchronously with only visual cues, synchronously with only visual cues or synchronously with musical and visual cues. We then tested for differences in pro-social effects using sharing and proxemics tasks. Results showed that while the synchrony version of the mandala led to greater closeness in the proxemics task, the musical synchrony led to more pro-sociality on the sharing task. The implications of these findings are discussed.",22549625,PSYCHOLOGY
10.3390/cancers17061021,"Correction: Zossou et al. Radiomics-Based Classification of Tumor and Healthy Liver on Computed Tomography Images. Cancers 2024, 16, 1158",,20726694,ONCOLOGY
10.3390/ejihpe15030041,Risk Assessment Profiles for Caregiver Burden in Family Caregivers of Persons Living with Alzheimer’s Disease: An Exploratory Study with Machine Learning,"Alzheimer’s disease (AD) places a profound global challenge, driven by its escalating prevalence and the multifaceted strain it places on individuals, families, and societies. Family caregivers (FCs), who are pivotal in supporting family members with AD, frequently endure substantial emotional, physical, and psychological demands. To better understand the determinants of family caregiving strain, this study employed machine learning (ML) to develop predictive models identifying factors that contribute to caregiver burden over time. Participants were evaluated across sociodemographic clinical, psychophysiological, and psychological domains at baseline (T1; N = 130), six months (T2; N = 114), and twelve months (T3; N = 92). Results revealed three distinct risk profiles, with the first focusing on T2 data, highlighting the importance of distress, forgiveness, age, and heart rate variability. The second profile integrated T1 and T2 data, emphasizing additional factors like family stress. The third profile combined T1 and T2 data with sociodemographic and clinical features, underscoring the importance of both assessment moments on distress at T2 and forgiveness at T1 and T2, as well as family stress at T1. By employing computational methods, this research uncovers nuanced patterns in caregiver burden that conventional statistical approaches might overlook. Key drivers include psychological factors (distress, forgiveness), physiological markers (heart rate variability), contextual stressors (familial dynamics, sociodemographic disparities). The insights revealed enable early identification of FCs at higher risk of burden, paving the way for personalized interventions. Such strategies are urgently needed as AD rates rise globally, underscoring the imperative to safeguard both patients and the caregivers who support them.",22549625,PSYCHOLOGY
10.3390/educsci15030395,Creativity and Preservice Teachers: A Literature Review of an Underexplored Field (2014–2024),"This systematic literature review examines the relationship between creativity and preservice teachers in scientific publications from 2014 to 2024. Using the PRISMA methodology, 27 empirical articles were selected based on their relevance to the research focus. The study provides both a bibliometric overview of the field and a substantive analysis of existing knowledge. Key findings reveal significant dispersion within the field, a proliferation of diverse definitions of creativity, and limited attention to the specific characteristics of preservice teachers in the research. Four central themes emerged: beliefs about creativity, personal characteristics, the creative processes, and teaching for creativity. These themes highlight the fragmented yet evolving nature of the discourse. The paper underscores the necessity of more comprehensive research approaches that transcend methodological individualism and better capture the domain-specific nature of creativity in preservice teachers. By integrating these perspectives, the study aims to advance a more cohesive understanding of how creativity can be cultivated in teacher preparation.",22277102,EDUCATION
10.3390/ai6040063,FedBirdAg: A Low-Energy Federated Learning Platform for Bird Detection with Wireless Smart Cameras in Agriculture 4.0,"Birds can cause substantial damage to crops, directly affecting farmers’ productivity and profitability. As a result, detecting bird presence in crop fields is crucial for effective crop management. Traditional agricultural practices have used various tools and techniques to deter pest birds, while digital agriculture has advanced these efforts through Internet of Things (IoT) and artificial intelligence (AI) technologies. With recent advancements in hardware and processing chips, connected devices can now utilize deep convolutional neural networks (CNNs) for on-field image classification. However, training these models can be energy-intensive, especially when large amounts of data, such as images, need to be transmitted for centralized model training. Federated learning (FL) offers a solution by enabling local training on edge devices, reducing data transmission costs and energy demands while also preserving data privacy and achieving shared model knowledge across connected devices. This paper proposes a low-energy federated learning framework for a compact smart camera network designed to perform simple image classification for bird detection in crop fields. The results demonstrate that this decentralized approach achieves performance comparable to a centrally trained model while consuming at least 8 times less energy. Further efficiency improvements, with a minimal tradeoff in performance reduction, are explored through early stopping.",26732688,AI
10.3390/cancers17071079,Adenoid Cystic Carcinoma of the Breast: A Narrative Review and Update on Management,"Rare breast malignancies represent a challenge for treatment decision making given the lack of evidence-based guidelines. As a particularly uncommon tumor, adenoid cystic carcinomas are especially challenging. Although, histopathologically, they share the same tumor molecular profile as hormone receptor-negative and HER2 nonamplified carcinomas with aggressive physiology, adenoid cystic carcinomas generally have a favorable prognosis. Thus, there is evidence to suggest that more aggressive treatment regimens may not provide better therapeutic effects. In this review, we discuss ACCB with the goal of highlighting pathophysiology, clinical features, and treatment strategies. Existing data support consideration for adjuvant radiation with the omission of axillary staging and systemic therapies.",20726694,ONCOLOGY
10.1186/s40359-025-02578-3,A socially prescribed creative play intervention for new parents: investigating post traumatic stress around birth and changes in postnatal depression and reflective function,"Background: Parenthood is a key transition period which involve emotional, social and physical adjustments. Social prescribing is a method that connects people to community-based activities, groups, and services to addressing various needs impacting their health and wellbeing. This pilot investigation aimed to assess whether a curated socially prescribed creative play programme would impact upon new parents’ social connection, mental health and reflective function through a programme designed to support these changes. Methods: This study was part of a 5-week long socially prescribed creative play programme at a family theatre company in the North of England, aimed at providing social capital to families while teaching creative play. In total, 57 parents (M = 30.73, SD = 6.20) completed baseline and post-intervention measures of birth trauma experiences (City Birth Trauma Scale), postnatal depression (Edinburgh Postnatal Depression Scale) reflective function (Reflective Functioning Questionnaire), and qualitative, open-ended questions on social opportunities. Descriptive analyses were completed using t-tests and chi-square tests, while repeated measures ANOVAs were used to answer questions around the main analyses. Results: The participants experienced a statistically significant reduction in postnatal depression scores following the intervention, but no changes were found in reflective function or birth trauma scores; secondly, birth trauma scores predicted later depression scores as well as reflective functioning uncertainty scores (but not certainty scores). Qualitative analysis found social opportunities were not why parents came but was, after attending, their favourite part of the socially prescribed programme. Those parents reporting on social opportunities were more likely to reference their own needs while non-social activities were associated with their child’s needs. Conclusions: Socially prescribed creative play programmes for new parents could be a “waiting well” intervention. A longer duration and trauma informed focus would need to be considered in future cohorts.",20507283,PSYCHOLOGY
10.3390/ai6040064,SMART Restaurant ReCommender: A Context-Aware Restaurant Recommendation Engine,"With the rise of e-commerce and web application usage, recommendation systems have become important to our daily tasks. They provide personalized suggestions to assist with any task under consideration. While various machine learning algorithms have been developed for recommendation tasks, existing systems still face limitations. This research focuses on advancing context-aware recommendation sytems by leveraging the capabilities of Large Language Models (LLMs) in conjunction with real-time data. The research exploits the integration of existing real-time data APIs with LLMs to enhance the capabilities of the recommendation systems already integrated into smart societies. The experimental results demonstrate that the hybrid approach significantly improves the user experience and recommendation quality, ensuring more relevant and dynamic suggestions.",26732688,AI
10.3389/feduc.2025.1541475,Adapting to crisis and unveiling the digital shift: a systematic literature review of digital competence in education related to COVID-19,"Nowadays, with technology penetrating into every aspect of our life, the ways to acquire knowledge has been greatly revolutionized. The outbreak of the Coronavirus (COVID-19) has accelerated digital informatization in education and the educational model has been transformed substantially. The demand for digital competence is at record high. The purpose of this study is to systematically explore digital competence in different national educational contexts during the COVID-19 pandemic (2019–2021), to provide academics with the current state of digital competence in education and main research trends in digital competence in education during this period, elucidate the impact of pandemic on digital competence, and explore the limitations in the implementation of digital competence in educational research. The results indicate that most research on digital competence in educational contexts related to COVID-19 focused on the current state of the digital competence of teachers and students, especially those in higher education and formal learning context. Still, with the situation compounded, the researchers furthered their study by investigating the factors that influenced digital competence in order to address educational challenges in a pandemic context. In addition, teachers and students were still not well equipped as for digital competence though their digital awareness and digital readiness in the teaching and learning process increased. It is recommended to promote and enhance digital competence training in order to improve students’ achievement and the quality of education.",2504284X,EDUCATION
10.3390/educsci15040415,Client Violence Against Educational Workers: A Systematic Review,"Client-initiated workplace violence in educational settings is a global issue affecting both teaching and non-teaching employees, such as instructional assistants, counselors, and administrators, among other school workers. Although studies on violence in educational settings have primarily focused on students, there has been growing interest in examining violence against teachers and, more recently, against teaching assistants and other educational professionals. This systematic review aims to analyze studies from diverse educational settings to examine the characteristics, causes, effects, and coping strategies associated with violence perpetrated by students, parents, or guardians, with the goal of informing and advancing prevention strategies. Following the PRISMA 2020 guidelines, a systematic literature review was conducted, analyzing studies across various educational environments to examine the characteristics, causes, effects, and coping strategies of violence perpetrated by students, parents, or guardians. This review revealed a significant prevalence of physical, psychological, and verbal assaults. However, most studies originated from Anglo-Saxon contexts, limiting their generalizability to diverse cultural and educational settings. The lack of research in other languages and in underrepresented regions highlights critical gaps in understanding this issue globally. The revision conclude that workplace violence in educational settings demands urgent and comprehensive responses involving all stakeholders. Implementing targeted prevention strategies and fostering a culture of respect are essential to ensure safe and healthy learning environments.",22277102,EDUCATION
10.3390/ai6040066,One-Shot Autoregressive Generation of Combinatorial Optimization Solutions Based on the Large Language Model Architecture and Learning Algorithms,"Large Language Models (LLMs) have immensely advanced the field of Artificial Intelligence (AI), with recent models being able to perform chain-of-thought reasoning and solve complex mathematical problems, ranging from theorem proving to ones involving advanced calculus. The success of LLMs derives from a combination of the Transformer architecture with its attention mechanism, the autoregressive training methodology with masked attention, and the alignment fine-tuning via reinforcement learning algorithms. In this research, we attempt to explore a possible solution to the fundamental NP-hard problem of combinatorial optimization, in particular, the Traveling Salesman Problem (TSP), by following the LLM approach in terms of the architecture and training algorithms. Similar to the LLM design, which is trained in an autoregressive manner to predict the next token, our model is trained to predict the next node in a TSP graph. After the model is trained on random TSP graphs with known near-optimal solutions, we fine-tune the model using Direct Preference Optimization (DPO). The tour generation in a trained model is autoregressive one-step generation with no need for iterative refinement. Our results are very promising and indicate that, for TSP graphs up to 100 nodes, a relatively small amount of training data yield solutions within a few percent of the optimal. This optimization improves if more data are used to train the model.",26732688,AI
10.3390/ejihpe15040048,Understanding the Use of Social and Emotional Learning in Elementary Schools: A Theory of Planned Behaviour Perspective,"Research has demonstrated that social–emotional learning (SEL) positively influences myriad domains of children’s development. However, the underlying mechanisms influencing teachers’ adoption of SEL remain underexplored. Guided by the Theory of Planned Behaviour (TPB), this quantitative cross-sectional study sought to elucidate the factors that motivate teachers to adopt SEL teaching practices. The study’s sample included 166 volunteer teachers in Luxembourg, recruited as part of a nationwide educational survey. Of these, 82.5% were women. Participants were recruited through convenience sampling, ensuring diversity in socio-economic backgrounds, grade levels, and student needs. Although these findings are based on self-reported data, they offer novel insights by quantifying teachers’ engagement with SEL, with over 50% already implementing related activities. Structural equation modelling shows that the TPB model accounted for 49% of the variance in teachers’ intentions and 44% of the variance in the adoption of SEL practices. Higher intention and self-efficacy predicted more frequent SEL implementation. Teachers with positive SEL attitudes and higher self-efficacy showed greater intention to implement SEL. These findings underscore the significance of cultivating positive attitudes and self-efficacy to facilitate the effective implementation of SEL in educational settings. The role of teacher gender and audience, as well as implications for teaching, professional development, and SEL research, are discussed.",22549625,PSYCHOLOGY
10.3389/frai.2025.1558938,Enhancing structured data generation with GPT-4o evaluating prompt efficiency across prompt styles,"Large language models (LLMs), such as GPT-4o, provide versatile techniques for generating and formatting structured data. However, prompt style plays a critical role in determining the accuracy, efficiency, and token cost of the generated outputs. This paper explores the effectiveness of three specific prompt styles–JSON, YAML, and Hybrid CSV/Prefix–for structured data generation across diverse applications. We focus on scenarios such as personal stories, receipts, and medical records, using randomized datasets to evaluate each prompt style's impact. Our analysis examines these prompt styles across three key metrics: accuracy in preserving data attributes, token cost associated with output generation, and processing time required for completion. By incorporating structured validation and comparative analysis, we ensure precise evaluation of each prompt style's performance. Results are visualized through metrics-based comparisons, such as Prompt Style vs. Accuracy, Prompt Style vs. Token Cost, and Prompt Style vs. Processing Time. Our findings reveal trade-offs between prompt style complexity and performance, with JSON providing high accuracy for complex data, YAML offering a balance between readability and efficiency, and Hybrid CSV/Prefix excelling in token and time efficiency for flat data structures. This paper explores the pros and cons of applying the GPT-4o LLM to generate structured data. It also provides practical recommendations for selecting prompt styles tailored to specific requirements, such as data integrity, cost-effectiveness, and real-time processing needs. Our findings contribute to research on how prompt engineering can optimize structured data generation for AI-driven applications, as well as documenting limitations that motivate future work needed to improve LLMs for complex tasks.",26248212,AI
10.1186/s40359-025-02620-4,Exploring the factors influencing the adoption of artificial intelligence technology by university teachers: the mediating role of confidence and AI readiness,"This study aims to explore the mediating role of confidence and artificial intelligence (AI) readiness in university teachers’ behavioral intention to adopt AI technology, providing empirical support for enhancing teachers’ willingness to use AI technology from both theoretical and practical perspectives. This study used a random sampling method to conduct an online survey of 504 university teachers, assessing the impact of subjective norms on behavioral intention. The survey included scales for subjective norms, confidence, AI readiness, and behavioral intention. Data analysis was performed using AMOS 26, SPSS Statistics 27 software and Model 6 from the PROCESS 4.0 plugin, aiming to investigate the mediating role of confidence and AI readiness between subjective norms and behavioral intention. Subjective norms were found to have a significant positive correlation with behavioral intention. Subjective norms indirectly influenced behavioral intention through confidence or AI readiness. Confidence and AI readiness played a chain-mediating role in the relationship between subjective norms and behavioral intention (β = 0.0324, 95% CI: [0.0129, 0.0551]), accounting for 12.87% of the total effect. This study reveals the positive role of subjective norms in university teachers’ behavioral intention to adopt AI technology, indicating that subjective norms not only directly enhance behavioral intention but also exert indirect effects through both single and chain mediation of confidence and AI readiness. The findings highlight the critical role of confidence and AI readiness in the relationship between subjective norms and behavioral intention, suggesting that to effectively increase university teachers’ willingness to use AI technology, it is important to focus on improving their confidence in and readiness for AI technology, thereby strengthening the positive impact of subjective norms.",20507283,PSYCHOLOGY
10.3390/ai6040068,Voice-AttentionNet: Voice-Based Multi-Disease Detection with Lightweight Attention-Based Temporal Convolutional Neural Network,"Voice data contain a wealth of temporal and spectral information and can be a valuable resource for disease classification. However, traditional methods are often not effective in capturing the key features required for the classification of multiple disease classes. To address this challenge, we propose a voice-based multi-disease detection approach with a lightweight attention-based temporal convolution neural network (Voice-AttentionNet) designed to analyze speech data for multi-class disease classification. Our model utilizes the temporal convolution neural network (CNN) architecture to extract high-resolution temporal features, while incorporating attention mechanisms to highlight disease-related patterns. Extensive experiments have been conducted on our dataset, including speech samples from patients with multiple illnesses. The results show that our method achieves the most advanced performance with an average classification accuracy of 91.61% on six datasets and is superior to the existing classical models. These findings highlight the potential of combining attention mechanisms with temporal CNNs in the use of speech data for disease classification. Moreover, this study provides a promising direction for deploying AI-driven diagnostic tools in clinical scenarios.",26732688,AI
10.3389/frai.2025.1568210,AI in business operations: driving urban growth and societal sustainability,"Approximately 30% of smart city applications will use artificial intelligence (AI) by the end of 2025, thereby radically altering the urban sustainability landscape in the future (Yan et al., 2023). The advent of AI in reshaping traditional businesses into sustainable operations is evident. Whenever AI is brought to the forefront, it is considered a cornerstone in the business domain, enabling a transition towards more innovative and sustainable practices (Appio et al., 2024). Incorporating AI into business practices has many facets. According to Grand View Research (2023), the global AI market size was anticipated at USD 196.63 billion in 2023 and is expected to grow at a CAGR of 36.6% from 2024 to 2030. The recent fanfare surrounding AI has elevated it to a key enabler of sustainable development, prompting many companies to prioritize and integrate it into their business operations; hence, there is a stark difference between traditional and new practices. In tandem with this evolution, urban growth and societal dynamics are experiencing profound changes as AI-driven solutions come to the fore in various aspects of modern society (Shahidi Hamedani et al., 2024). AI applications in city government, transforming conventional cities into efficient ones (Ortega-Fernández et al., 2020), have significantly shifted from functional systems to more sustainable and intelligent ones. Furthermore, from another perspective, the role of AI in optimizing business processes has surpassed comparison with its implication for improving logistics operational capabilities and reducing environmental impacts (Jorzik et al., 2024a) till manufacturing reduces downtime, all of which contribute to the growth of urban economics. In the meantime, with the speedy pace of adoption of AI in business operations, it is also imperative to amalgamate with sustainable practices. Acting on this matter requires a thoughtful approach that aligns AI with social, economic, and environmental sustainability.The intersection of AI role and business operations has recently gained widespread attention. Some studies (Chen et al., 2024;Shahzadi et al., 2024)focused on AI's role in supply chain management, highlighting its role in minimizing inefficiencies and improving logistics by utilizing AI more often;supply chains become leaner and reduced carbon footprints, paving the path to sustainable operations. It is estimated that by 2026, 60% of businesses will adopt AI-powered warehouse solutions instead of just 10% in 2020 (MHI, 2024).In line with this shift, (Dilmegani & Ermut, 2025) note that businesses also invest heavily in warehouse robots to enhance their supply chain management through AI technology. Robots can manage operations more efficiently and accurately by automating picking, packing, sorting, and inventory management, thus saving labor costs and accelerating order processing. Amazon, for instance, has deployed more than 200,000 robots in its warehouses to optimize operations.AI can be used to optimize resource utilization, automate processes for improved efficiency, and enable real-time monitoring that aligns with sustainability goals (Waltersmann et al., 2021). As sustainable supply chain management focuses on reducing waste and enhancing traceability, AI-driven technologies such as machine learning and big data analytics have been pivotal in achieving these goals. (Tsolakis et al., 2023) Companies like eBay leverage AI for machine translation, enhancing decision-making and operational efficiency . Similarly, Vodafone employs AI-driven analytics to personalize services, exemplifying its transformative impact. (Jorzik et al., 2024a).These technologies help reduce forecasting errors, minimize excess inventory, and lower energy consumption. (Sharma et al., 2020) Likewise, Smart grid protection sensors can detect defects up to 80% more accurately than traditional sensors, reducing losses and improving the system's reliability by adjusting to grid conditions dynamically (Mahadik, Sheetal et al., 2025). These applications contribute to urban economic growth by fostering technological innovation. AI leverages advanced techniques like deep reinforcement learning (DRL) to optimize dynamic business operations (Shuford, 2024). DRL improves supply chain management through adaptive routing and inventory optimization, dynamically adjusting to real-time changes in demand and logistics; with the help of DRL, researchers can develop systems that can dynamically adapt to changes, optimize resource utilization, and facilitate multi-objective decision-making for instance, (Dehaybe et al., 2024).In addition, it enables businesses to prevent equipment failures and minimize downtime, thereby streamlining workflows significantly (Mohan et al., 2021). Moreover, in urban centers, these advancements catalyze economic growth and foster innovation. In other words, a key contribution of AI is to facilitate smart urban development and efficient resource allocation, thereby ensuring that cities are resilient and economically prosperous (Li et al., 2024). In developing smart cities, AI has a transformative impact on urbanization trends. Through the application of AI, urban infrastructure can be optimized by improving energy efficiency, streamlining transportation, and managing housing needs; AI makes it possible to reduce traffic congestion and advance mobility in transportation systems, such as prescriptive traffic management and autonomous vehicles (Regona et al., 2024).In cities like Singapore, AI manages real-time traffic and monitors energy consumption, setting urban efficiency benchmarks (Padhiary et al., 2025). On a similar note, Tennet TSO, a German transmission system operator, has been utilizing AI-based forecasting and IBM Watson's cognitive computing platform to anticipate renewable energy generation in real time, allowing real-time grid adjustments and maximizing clean energy use. (Mahadik, Sheetal et al., 2025) 3Nowadays,...",26248212,AI
10.3389/frai.2025.1426455,Analyzing handwriting legibility through hand kinematics,"Introduction: Handwriting is a complex skill that requires coordination between human motor system, sensory perception, cognitive processing, memory retrieval, and linguistic proficiency. Various aspects of hand and stylus kinematics can affect the legibility of a handwritten text. Assessing handwriting legibility is challenging due to variations in experts' cultural and academic backgrounds, which introduce subjectivity biases in evaluations.Methods: In this paper, we utilize a deep-learning model to analyze kinematic features influencing the legibility of handwriting based on temporal convolutional networks (TCN). Fifty subjects are recruited to complete a 26-word paragraph handwriting task, designed to include all possible orthographic combinations of Arabic characters, during which the hand and stylus movements are recorded. A total of 117 different spatiotemporal features are recorded, and the data collected are used to train the model. Shapley values are used to determine the important hand and stylus kinematics features toward evaluating legibility. Three experts are recruited to label the produced text into different legibility scores. Statistical analysis of the top 6 features is conducted to investigate the differences between features associated with high and low legibility scores.Results: Although the model trained on stylus kinematics features demonstrates relatively high accuracy (around 76%), where the number of legibility classes can vary between 7 and 8 depending on the expert, the addition of hand kinematics features significantly increases the model accuracy by approximately 10%. Explainability analysis revealed that pressure variability, pen slant (altitude, azimuth), and hand speed components are the most prominent for evaluating legibility across the three experts.Discussion: The model learns meaningful stylus and hand kinematics features associated with the legibility of handwriting. The hand kinematics features are important for accurate assessment of handwriting legibility. The proposed approach can be used in handwriting learning tools for personalized handwriting skill acquisition as well as for pathology detection and rehabilitation.",26248212,AI
10.3389/feduc.2025.1562391,"Digital learning in the 21st century: trends, challenges, and innovations in technology integration","The integration of digital technologies into education represents a significant evolution in the pedagogical landscape, with the potential to enhance accessibility, engagement, and personalization in learning. This review synthesizes current trends, challenges, and innovations within digital learning, emphasizing the impact of artificial intelligence (AI), virtual reality (VR), and online platforms on student achievement. It highlights the importance of addressing technical, pedagogical, and socioeconomic challenges to ensure equitable access to technology. Successful initiatives like the Open University illustrate digital learning's potential to improve educational outcomes. The review also anticipates future directions, including the expanding role of AI, VR, mobile learning, and blockchain in education. It concludes with strategic recommendations for educators and policymakers to adopt best practices, prioritize infrastructure development, and focus on continuous professional development to leverage the benefits of digital learning. As education enters an era of digital transformation, a collaborative approach among stakeholders will be essential in creating an inclusive and effective learning environment for the future.",2504284X,EDUCATION
10.3389/feduc.2025.1570389,"Integrating artificial intelligence into pre-clinical medical education: challenges, opportunities, and recommendations","As AI technologies continue to advance and influence healthcare, it is imperative that medical education evolves to equip future physicians with the necessary skills and understanding of AI applications. In pre-clinical curricula, AI tools can streamline administrative processes, enhance teaching methodologies, and provide personalized learning experiences for students. Moreover, AI has the potential to shape students' professionalism, ethical decision-making, and critical thinking skills, which are essential for their future roles in the medical field. However, this shift also raises critical challenges, such as the need for ethical guidelines, adequate infrastructure, and avoiding overreliance on AI. Recent studies have shown a significant gap in formal AI education within medical studies, while the general attitudes of students towards AI is positive [1] This paper is based on a comprehensive narrative review of current literature and expert discussions. It aims to identify the key areas affected by AI integration in pre-clinical medical education, and to provide recommendations to maximize its benefits while mitigating associated risks.Universities face significant organizational challenges in integrating AI, such as ensuring ethical AI usage, addressing data privacy concerns, and meeting infrastructural requirements. Developing comprehensive policies to guide AI's role in academic settings is essential, including its application in exams, theses, teaching, and clinical decision-making tools [1][4]. Policy development requires good cooperation between academic self-governance bodies (academic freedom) and university management (management of personnel and financial resources, and enforcement of rules) [2].One significant opportunity presented by AI integration is the optimization of administrative tasks. AI-driven data analysis can improve resource management, allowing universities to allocate resources more efficiently and effectively [5][6]. Additionally, AI can enhance global collaboration in medical education by facilitating communication and information sharing across institutions worldwide. Implementing digital learning infrastructures, such as virtual simulation labs and AIassisted learning platforms, has the potential to improve teaching efficiency and provide innovative educational experiences for students [7][8].However, several challenges persist. Universities must invest in digital technologies while balancing traditional educational needs to prevent over-reliance on AI [8][9]. Ensuring equal and fair access to AI tools for all students is crucial to avoid disparities in educational opportunities. The freedom of teaching should not be impaired by university-wide adjustments. Establishing ethical frameworks is imperative to promote the responsible use of AI, especially concerning patient data in AI models [8][10] [11][12]. Addressing these ethical considerations is essential for safeguarding data privacy and upholding academic integrity.At the program management level, aligning the needs of students and educators regarding AI usage in education is crucial. This alignment impacts curriculum design, coordination among educators, and the preparation of students for future job roles in an AI-influenced healthcare environment [13].One of the primary challenges is ensuring that curricula remain relevant amid AI's growing impact on healthcare. This necessitates significant restructuring of courses to integrate AI tools while maintaining the essential human elements of medical education, such as patient interaction and ethical decision-making [10] [14][15] [16]. Program managers must balance the incorporation of new technologies with the preservation of core medical competencies to provide a comprehensive education under conditions in which these core competencies are continually reassessedConversely, AI offers opportunities to develop innovative course structures that include experiential components. For instance, AI simulations for clinical decision-making can enhance learning outcomes by providing students with practical, hands-on experience in a controlled environment. Additionally, AI can help identify future job market needs, enabling study programs to adapt their curricula and train students in AI-driven medical technologies [1][6][17]. This proactive approach ensures that graduates are better prepared for the evolving demands of the healthcare sector.For teaching staff, integrating AI into medical curricula demands the acquisition of new skills and methodologies, as well as an understanding of how to balance AI with traditional teaching methods. AI tools such as virtual tutors and simulation resources have the potential to greatly enhance the learning experience, but only when applied appropriately. Therefore, educators need to be trained adequately to use these tools effectively, and they need to be willing to receive that training [6][10].Opportunities for educators include utilizing AI-enhanced teaching tools, including virtual simulations and real-time feedback systems, which provide more personalized and adaptive learning experiences for students [14][19]. AI can also streamline assessment and grading processes, allowing educators to devote more time to developing students' higher-order thinking skills [5]. By reducing administrative burdens, educators can focus on facilitating critical analysis, problem-solving abilities, and clinical reasoning.Nevertheless, challenges persist. Training educators in AI usage is essential to ensure they can leverage these tools effectively and confidently integrate them into their teaching practices [5][8].Additionally, ethical concerns regarding the use of AI in education, such as issues of academic integrity and potential biases in AI algorithms, need to be carefully managed [18]. Educators must be equipped not only with technical skills but also with an understanding of the ethical implications of AI to guide students...",2504284X,EDUCATION
10.3390/cancers17071157,Estimating the Morbidity of Robot-Assisted Radical Cystectomy Using the Comprehensive Complication Index: Data from the Asian Robot-Assisted Radical Cystectomy Consortium,"Background/Objectives: The Clavien–Dindo classification (CDC) grades the most severe post-operative complication and may not comprehensively reflect cumulative surgical morbidity. Our objective was to investigate the potential incremental role of the comprehensive complication index (CCI) over the CDC in defining the quality of robot-assisted radical cystectomy (RARC). Methods: Data were extracted from the Asian RARC Consortium database. Complications were classified using the CCI (CCI = 0, CCI < 75th and ≥75th percentile) and CDC. Adverse peri-operative outcomes such as length of stay >14 days (LOS > 14 days), estimated blood loss >350 mL (EBL > 350 mL), time to solid food intake >4 days (TFI > 4 days) and 30-day readmission rates were analyzed. The area under the curve (AUC) of the receiver operating characteristic (ROC) curves for CCI and CDC were compared for the various adverse outcomes. Results: The peri-operative complication rate was 44.4%, comprising 11.6% with severe complications (CDC ≥ III). The mean CCI was 10.2 (±13.5) while median CCI was 0 (IQR 0–21). There were 7.6% of patients with >one perioperative complication. On adjusted analysis, CCI ≥ 75th percentile was significantly associated with greater LOS (>14 days) (OR 2.21, 95% CI 1.47–3.31, p < 0.001) compared to when CCI = 0. There were no significant differences in the AUC between CDC and CCI in predicting LOS > 14 days, TFI > 4 days, 30-day readmission or EBL > 350 mL. Conclusions: In our multi-institutional cohort, the CCI did not provide additional discrimination over CDC, and this is likely related to the limited number of complications that occurred per individual in the Asian RARC cohort. Hence, the perceived advantages of CCI over CDC are contextual.",20726694,ONCOLOGY
10.3389/fonc.2025.1524714,Identification of MAD2L1 as a novel biomarker for hepatoblastoma through bioinformatics and machine learning approaches,"Objective: This study aims to identify potential biomarkers for Hepatoblastoma (HB) using bioinformatics and machine learning, and to explore their underlying mechanisms of action.Methods: We analyzed the datasets GSE131329 and GSE133039 to perform differential gene expression analysis. Single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network analysis (WGCNA) were utilized to identify gene modules linked to gene set activity. Protein-protein interaction (PPI) networks were constructed to identify hub genes, while random forest and support vector machine models were employed to screen for key diagnostic genes. Survival and immune infiltration analyses were conducted to assess the prognostic significance of these genes. Additionally, the expression levels, biological functions, and mechanisms of action of the selected genes were validated in HB cells through relevant experimental assays.Results: We identified 1,377 and 1,216 differentially expressed genes in datasets GSE131329 and GSE133039, respectively. ssGSEA and WGCNA analyses identified 234 genes significantly linked to gene set activity. PPI analysis identified 20 core Hub genes. Machine learning highlighted three key diagnostic genes: CDK1, CCNA2, and MAD2L1. Studies have demonstrated that MAD2L1 is significantly overexpressed in HB and is associated with prognosis. WGCNA revealed that MAD2L1 is enriched in gene sets related to E2F_ TARGETS and G2M_CHECKPOINT. Experimental assays demonstrated that MAD2L1 knockdown significantly inhibits the proliferation, migration, and invasion of HB cell lines, and that MAD2L1 promotes cell cycle progression through the regulation of E2F.Conclusion: Our study identifies MAD2L1 as a novel potential biomarker for HB, providing new strategies for early diagnosis and targeted therapy in HB.",2234943X,ONCOLOGY
10.3390/cancers17071179,"Inducing Targeted, Caspase-Independent Apoptosis with New Chimeric Proteins for Treatment of Solid Cancers","Background: Most newly developed anticancer treatments trigger tumor cell death through apoptosis, for which involvement of caspases activity is essential. However, numerous mutations in apoptotic pathways that lead to cancer and favor resistance to apoptosis are known; most are related to caspase-dependent apoptosis pathways and thus have low efficacy. To overcome these limitations, we constructed a novel chimeric protein, GnRH-AIF, using a gonadotropin-releasing hormone (GnRH) analog as a targeting moiety and the apoptosis-inducing factor (AIF) in its cleaved form as a killing moiety, fused at the cDNA level. AIF has a crucial role in the caspase-independent apoptotic pathway. A wide variety of solid tumors overexpress GnRH-receptors (GnRH-R) that are targeted by the new GnRH-AIF chimeric protein. Methods and Results: In this study, we constructed, expressed, and highly purified GnRH-AIF chimeric proteins. We demonstrated the ability of the chimera to enter and specifically and very efficiently kill solid cancer cell lines overexpressing GnRH-R. Most importantly, upon its entry, GnRH-AIFs translocate to the nucleus where it causes DNA fragmentation leading to a direct caspase-independent apoptotic death. As AIFs lack nuclease activity, our findings also emphasize that cell death induced by GnRH-AIF is dependent on the presence of the ENDOG and PPIA proteins, known to participate in the formation of a DNA–degradosome complex. Finally, we demonstrated the high anti-tumor efficacy of the GnRH-AIF ex vivo, in a human, colon cancer organoid model. Conclusions: Our study shows the potential of using a GnRH-AIF chimeric protein as a novel approach to treat solid cancers that overexpress GnRH-R, via a caspase-independent apoptotic pathway.",20726694,ONCOLOGY
10.3390/cancers17071191,Significance of 5-ALA-Guided Fluorescence in Resection of Invasive Intracranial Meningiomas: Findings from a Prospective Clinical Study,"Background: In cases of intracranial meningiomas invading into surrounding tissues, determining the resection boundary can be challenging and often makes complete resection difficult. In such situations, the introduction of novel intraoperative techniques to identify infiltrative tumor components is desirable to improve the extent of tumor resection. Methods: A prospective clinical study was conducted on patients with intracranial meningiomas suspected of infiltration into the surrounding tissues. After completing the tumor resection under conventional white-light microscopy, intraoperative fluorescence diagnosis using 5-aminolevulinic acid (5-ALA) was performed to determine whether additional resection of the unintended residual tumor was feasible. Results: Intraoperative fluorescence diagnosis enabled additional resection of the residual tumor in 38.5% of the 13 enrolled cases and 45.5% of the 11 cases in which the tumor exhibited fluorescence positivity. Among the additional resected specimens, tumor infiltration was observed in all fluorescence-positive lesions of the bone and dura mater, whereas tumor cells were detected in only 33.3% of the fluorescence-positive areas in the adjacent brain parenchyma. Conclusions: Intraoperative fluorescence diagnosis using 5-ALA enhanced the extent of the resection of invasive meningiomas. Future large-scale studies are warranted to determine whether 5-ALA fluorescence diagnosis contributes to reducing tumor recurrence and improving overall survival in patients with invasive intracranial meningiomas.",20726694,ONCOLOGY
10.3389/feduc.2025.1550969,The impact of study abroad social interactions on post-return relationships with international students: Japanese students’ perceptions of recategorization,"Previous research has focused on how students adapt to the host country during study abroad. However, less is known about how these experiences influence students’ social engagement upon returning home. This study explores how Japanese students’ social interactions abroad influence their relationships with international students in Japan after their return. Using a qualitative approach based on grounded theory, semi-structured interviews were conducted with 24 Japanese students who had studied abroad for one academic year. The findings suggest that social interactions abroad facilitate recategorization, a process in which individuals redefine group boundaries and develop a broader shared identity. This process was influenced by four key factors: language and social skills, motivation, opportunities, and perceived fit. Through this process, Japanese students expanded their group boundaries and formed a shared identity with international students in Japan as individuals with study abroad experience. As a result, they developed more positive attitudes toward international students, heightened empathy, and a stronger motivation to engage with and help international students. These findings indicate that recategorization can occur through the formation of a new social identity based on shared experiences rather than direct intergroup contact, highlighting the long-term impact of study abroad on students’ intercultural engagement. This study underscores Japanese students’ tendency to identify with international students in Japan rather than with host nationals upon their return.",2504284X,EDUCATION
10.3390/ejihpe15040050,Evaluating the Effects of Sensorimotor Training on the Physical Capacities of Older People,"Background: Physical activity (PA) plays a crucial role in improving the quality of life (QoL) in older people, particularly by enhancing their balance and movement coordination. Objective: This study aimed to assess the effects of sensorimotor training intervention in older adults. Methods: A total of 90 participants, divided into a Control Group (n = 44) and Experimental Group (n = 46) were involved in a 24-week sensorimotor training program. The physical capacities of the participants were assessed both before and after the intervention program. Strength and flexibility were measured using the “Rikli and Jones” protocol (1999), while agility and speed were assessed through “Timed-up-and-go” tests. Taking into account the participants’ gender, a descriptive analysis of the sample was conducted to describe the data using the mean and standard deviation. Student’s T test was performed to compare the differences between the groups according to the first and second data collection moments (before and after the intervention). Jamovi software (v. 2.5.2.0) was used to develop the statistical analysis, using a p-value of less than 0.05 to assess the statistical significance. Results: The Experimental Group showed significant improvements across all the analyzed variables following the intervention (p < 0.005), indicating substantial gains in physical capacities. In contrast, the Control Group in the “sitting and reaching” test did not show a significant difference between the groups highlighting the lack of improvement without intervention. According to the effect size of the sample, it was observed that the parameters “reach behind your back (right)” and “reach behind your back (left)” showed the highest effect size comparing the Control Group and Experimental Group (ES: 0.60, 0.71). Conclusions: The findings highlight the practical clinical impact of implementing tailored physical activity programs for older adults. Such interventions are critical for enhancing QoL, reducing the risk of falls, injuries, and chronic illnesses, and promoting overall health, independence, and well-being. Integrating sensorimotor training into the routine care for older people can support healthy aging and functional independence.",22549625,PSYCHOLOGY
10.3389/frai.2025.1542320,An optimized system for predicting energy usage in smart grids using temporal fusion transformer and Aquila optimizer,"This research presents an optimized system for predicting energy usage in smart grids by integrating the Temporal Fusion Transformer (TFT) with the Aquila Optimizer (AO). The study addresses the growing need for accurate energy consumption forecasts in smart grids, driven by the increasing adoption of renewable energy and real-time data collection through smart meters. The TFT model leverages self-attention mechanisms to handle complex time-series data, improving forecasting accuracy across various time horizons. To enhance predictive performance, the Aquila Optimizer, a nature-inspired algorithm, is employed to fine-tune critical hyperparameters, ensuring optimal model convergence and performance. The proposed AO-TFT model is evaluated against traditional models like LSTM and CNN-BiLSTM, demonstrating superior accuracy, lower RMSE, and faster computation times. The research also analyses the impact of various factors, including building types, weather conditions, and load variations on energy prediction. The proposed AO-TFT model achieved a significantly lower RMSE of 0.48 and MAE of 0.31, demonstrating superior accuracy compared to traditional models. Future work is suggested to explore hybrid optimization techniques and real-time adaptive models for dynamic grid management.",26248212,AI
10.3390/ai6040072,"Multimodal Data Fusion for Tabular and Textual Data: Zero-Shot, Few-Shot, and Fine-Tuning of Generative Pre-Trained Transformer Models","In traffic safety analysis, previous research has often focused on tabular data or textual crash narratives in isolation, neglecting the potential benefits of a hybrid multimodal approach. This study introduces the Multimodal Data Fusion (MDF) framework, which fuses tabular data with textual narratives by leveraging advanced Large Language Models (LLMs), such as GPT-2, GPT-3.5, and GPT-4.5, using zero-shot (ZS), few-shot (FS), and fine-tuning (FT) learning strategies. We employed few-shot learning with GPT-4.5 to generate new labels for traffic crash analysis, such as driver fault, driver actions, and crash factors, alongside the existing label for severity. Our methodology was tested on crash data from the Missouri State Highway Patrol, demonstrating significant improvements in model performance. GPT-2 (fine-tuned) was used as the baseline model, against which more advanced models were evaluated. GPT-4.5 few-shot learning achieved 98.9% accuracy for crash severity prediction and 98.1% accuracy for driver fault classification. In crash factor extraction, GPT-4.5 few-shot achieved the highest Jaccard score (82.9%), surpassing GPT-3.5 and fine-tuned GPT-2 models. Similarly, in driver actions extraction, GPT-4.5 few-shot attained a Jaccard score of 73.1%, while fine-tuned GPT-2 closely followed with 72.2%, demonstrating that task-specific fine-tuning can achieve performance close to state-of-the-art models when adapted to domain-specific data. These findings highlight the superior performance of GPT-4.5 few-shot learning, particularly in classification and information extraction tasks, while also underscoring the effectiveness of fine-tuning on domain-specific datasets to bridge performance gaps with more advanced models. The MDF framework’s success demonstrates its potential for broader applications beyond traffic crash analysis, particularly in domains where labeled data are scarce and predictive modeling is essential.",26732688,AI
10.3390/ejihpe15040055,"Ethical Climate, Intrinsic Motivation, and Affective Commitment: The Impact of Depersonalization","Although affective commitment has been the focus of numerous studies, we know relatively little about certain factors that drive or hinder its progress. In this sense, this study contributes to the knowledge on the subject by establishing a relationship between a benevolent ethical climate and affective commitment, taking into account the mediating effect of intrinsic motivation. Furthermore, we highlight depersonalization as an aspect that can hinder these relationships when it assumes a moderating function. The sample was established through 448 employees of the Colombian electrical sector. The mediating effect was confirmed through a four-step method. The moderated mediation model was examined using SEM structural equations. The results show that a benevolent ethical climate is positively related to affective commitment and that intrinsic motivation is a mediating factor that justifies this relationship. However, depersonalization moderates the mediation between benevolent ethical climate, intrinsic motivation, and affective commitment. Specifically, the positive effect of the benevolent ethical climate on affective commitment is halted when depersonalization is high. The positive relationship between intrinsic motivation and affective commitment is interrupted when depersonalization is medium or high. Finally, as depersonalization progresses, the positive relationship between a benevolent ethical climate and intrinsic motivation is reduced. Therefore, organizations in the Colombian electrical sector must take measures that, in addition to avoiding social isolation, behave as indicators that warn when employees’ behaviors change significantly.",22549625,PSYCHOLOGY
10.1186/s40359-020-00440-2,Evaluation of the effect of fatigue on the coping behavior of international truck drivers,"Background: Fatigue can affect the behavior of drivers. While the driver must be able to respond and cope appropriately to the critical situations, which is known as the ability to cope with a crisis. It is likely that the fatigue can change the people’s coping style and thereby increase the chance of the crashes. Therefore, the present study aimed to investigate the effects of fatigue on the coping behavior of international truck drivers. Methods: This study was conducted on 239 of international truck drivers employed in Iran. The Endler and Parker coping strategies questionnaire (CISS) and Persian version of the Fatigue Multidimensional Fatigue Inventory (MFI) were used to evaluate the coping styles of the drivers and the drivers’ fatigue, respectively. Results: The mean values of the total fatigue before and after traveling were 36.77 and 76.13, respectively. The mean values of coping styles of the problem-oriented, emotion-oriented, and avoidance before traveling were 53.66, 40.91, and 38.17, respectively, and those after traveling were 45.59, 51.18, and 36.45, respectively. The chi-square test demonstrated that there was a significant difference in the coping style of drivers before and after the trip (P < 0.001), and the percent of individuals with emotion-oriented increased. Conclusions: In general, the results showed that fatigue due to traveling could change the coping styles of subjects from problem-oriented to emotion-oriented and avoidance. This can increase the statistics of driving accidents.",20507283,PSYCHOLOGY
10.3389/frai.2025.1543603,Emotional prompting amplifies disinformation generation in AI large language models,"Introduction: The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. While these developments offer significant opportunities for improving communication, such as in health-related crisis communication, they also pose substantial risks by facilitating the creation of convincing fake news and disinformation. The widespread dissemination of AI-generated disinformation adds complexity to the existing challenges of the ongoing infodemic, significantly affecting public health and the stability of democratic institutions.Rationale: Prompt engineering is a technique that involves the creation of specific queries given to LLMs. It has emerged as a strategy to guide LLMs in generating the desired outputs. Recent research shows that the output of LLMs depends on emotional framing within prompts, suggesting that incorporating emotional cues into prompts could influence their response behavior. In this study, we investigated how the politeness or impoliteness of prompts affects the frequency of disinformation generation by various LLMs.Results: We generated and evaluated a corpus of 19,800 social media posts on public health topics to assess the disinformation generation capabilities of OpenAI’s LLMs, including davinci-002, davinci-003, gpt-3.5-turbo, and gpt-4. Our findings revealed that all LLMs efficiently generated disinformation (davinci-002, 67%; davinci-003, 86%; gpt-3.5-turbo, 77%; and gpt-4, 99%). Introducing polite language to prompt requests yielded significantly higher success rates for disinformation (davinci-002, 79%; davinci-003, 90%; gpt-3.5-turbo, 94%; and gpt-4, 100%). Impolite prompting resulted in a significant decrease in disinformation production across all models (davinci-002, 59%; davinci-003, 44%; and gpt-3.5-turbo, 28%) and a slight reduction for gpt-4 (94%).Conclusion: Our study reveals that all tested LLMs effectively generate disinformation. Notably, emotional prompting had a significant impact on disinformation production rates, with models showing higher success rates when prompted with polite language compared to neutral or impolite requests. Our investigation highlights that LLMs can be exploited to create disinformation and emphasizes the critical need for ethics-by-design approaches in developing AI technologies. We maintain that identifying ways to mitigate the exploitation of LLMs through emotional prompting is crucial to prevent their misuse for purposes detrimental to public health and society.",26248212,AI
10.3389/frai.2025.1546064,"Legal regulation of AI-assisted academic writing: challenges, frameworks, and pathways","Introduction: The widespread application of artificial intelligence in academic writing has triggered a series of pressing legal challenges.Methods: This study systematically examines critical issues, including copyright protection, academic integrity, and comparative research methods. We establishes a risk assessment matrix to quantitatively analyze various risks in AI-assisted academic writing from three dimensions: impact, probability, and mitigation cost, thereby identifying high-risk factors.Results: The findings reveal that AI-assisted writing challenges fundamental principles of traditional copyright law, with judicial practice tending to position AI as a creative tool while emphasizing human agency. Regarding academic integrity, new risks, such as “credibility illusion” and “implicit plagiarism,” have become prominent in AI-generated content, necessitating adaptive regulatory mechanisms. Research data protection and personal information security face dual challenges in data security that require technological and institutional innovations.Discussion: Based on these findings, we propose a three-dimensional regulatory framework of “transparency, accountability, technical support” and present systematic policy recommendations from institutional design, organizational structure, and international cooperation perspectives. The research results deepen understanding of legal attributes of AI creation, promote theoretical innovation in digital era copyright and academic ethics, and provide practical guidance for academic institutions in formulating AI usage policies.",26248212,AI
10.1186/s40359-025-02667-3,The role of mind wandering and anxiety in the association between internet addiction and hyperactivity-impulsivity: a serial mediation model,"Hyperactivity-Impulsivity have significant negative effects on adolescents’ academic performance, physical and mental health, and social relationships. This study aims to deeply explore the relationship between Hyperactivity-Impulsivity in adolescents and Internet Addiction. Unlike previous studies, this study further explores a potential serial mediation model involving Mind Wandering and Anxiety. A total of 2042 adolescents completed assessments using the Internet Addiction Test (IAT), the Mind Wandering Questionnaire (MWQ), the Generalized Anxiety Disorder 2(GAD-2), and the ASRS short scale to evaluate Internet Addiction, Mind Wandering, Anxiety, and Hyperactivity-Impulsivity, respectively. Internet Addiction, Mind Wandering, and Anxiety significantly influence adolescents’ Hyperactivity-Impulsivity (p <.001). Mediation analysis further indicates that Internet Addiction is associated with Hyperactivity-Impulsivity through the serial mediating effects of Mind Wandering and Anxiety(p <.01). These findings highlight Mind Wandering and Anxiety as key mediators in the link between Internet Addiction and Hyperactivity-Impulsivity in adolescents. This study sheds light on how Internet Addiction influences Hyperactivity-Impulsivity among adolescents and underscores the importance of preventive measures. We recommend implementing interventions aimed at fostering healthy Internet usage habits and providing robust mental health support to safeguard adolescents’ physical and mental well-being.",20507283,PSYCHOLOGY
10.3389/fonc.2025.1560008,FGFR3-TACC3 fusion gene promotes glioblastoma malignant progression through the activation of STAT3 signaling pathway,"Objective: The Fibroblast growth factor receptors 3-transforming acidic coiled-coil-containing protein 3 (FGFR3-TACC3, F3-T3) oncogenic fusion gene, identified in malignant tumors such as gliomas and bladder cancer, has been particularly noted in recurrent gliomas where it is considered to drive malignant progression, thus presenting itself as a viable therapeutic target. However, the precise mechanism by which F3-T3 facilitates the malignant progression of glioma is not fully understood.Methods: Correction analysis of STAT3 and FGFR3 with major glioma mutation types and pan-cancer analysis was conducted using The Cancer Genome Atlas (TCGA) database. A series of phenotypic experiments, including CCK-8, EdU, colony-formation assay, wound healing assay, and transwell assay were conducted to detect the effects of F3-T3 on proliferation, invasion, and migration of glioma cells. The association between F3-T3 and epithelial-mesenchymal transition (EMT) was investigated through enrichment analysis of the E-MTAB-6037 gene chip database and confirmed by western blot. The underling mechanism were further inferred and validated through RNA sequencing, E-MTAB-6037 gene chip data, and western blot. The relationship between p-STAT3 expression and the WHO grade of glioma was evaluated using immunohistochemistry (IHC) and tissue microarray analysis. Furthermore, the results of vivo experiments and IHC has confirmed the impact of F3-T3 on glioma malignant progression and activation of the STAT3 signaling pathway.Results: The experimental results from this study indicate that F3-T3 accelerates the epithelial-mesenchymal transition (EMT) process in glioma cells, thereby promoting their proliferation, invasion, and migration capabilities. Mechanistically, it was determined through RNA sequencing that the signal transducer and activator of transcription 3 (STAT3) signaling pathway is crucial for the malignant progression of F3-T3. This finding was further supported through follow-up experiments conducted after STAT3 knockdown. The role of the STAT3 pathway in gliomas was also reinforced through bioinformatic analysis and immunohistochemistry (IHC) on tissue microarrays (TMA). Further in vivo experiments corroborated the role of F3-T3 in enhancing glioma growth and progression.Conclusion: F3-T3 facilitates the proliferation, invasion, migration and EMT of glioma cells, thereby promoting their malignant progression through STAT3 signaling activation. These findings highlight its potential as a therapeutic target for glioma treatment.",2234943X,ONCOLOGY
10.3389/frai.2025.1478068,The role of AI for MRI-analysis in multiple sclerosis—A brief overview,"Magnetic resonance imaging (MRI) has played a crucial role in the diagnosis, monitoring and treatment optimization of multiple sclerosis (MS). It is an essential component of current diagnostic criteria for its ability to non-invasively visualize both lesional and non-lesional pathology. Nevertheless, modern day usage of MRI in the clinic is limited by lengthy protocols, error-prone procedures for identifying disease markers (e.g., lesions), and the limited predictive value of existing imaging biomarkers for key disability outcomes. Recent advances in artificial intelligence (AI) have underscored the potential for AI to not only improve, but also transform how MRI is being used in MS. In this short review, we explore the role of AI in MS applications that span the entire life-cycle of an MRI image, from data collection, to lesion segmentation, detection, and volumetry, and finally to downstream clinical and scientific tasks. We conclude with a discussion on promising future directions.",26248212,AI
10.1186/s40359-025-02666-4,Effect of stressors on depressive mood among long-term high-altitude workers: a moderated mediation analysis,"Diathesis-stress theory of depression is well known, which stresses that stressor is an inducing factor for depression in general population. High altitude, a combination of variety of stressors, is a special environment that may cultivate more depression. However, how different types of stressors contribute to depression and its underlying mechanisms in high-altitude populations remain unrevealed. The study aimed to reveal the effect of different stressors on depressive mood among long-term high-altitude workers in China and further explore the mediation of emotion regulation and moderation of parent-child alienation. 2065 Chinese workers at altitude of approximate 4200 m completed a cross-sectional survey with the Baker Depression Inventory-II scale, the Emotional Regulation scale, the Parent-child Alienation scale, and the Stressors scale (i.e., environmental factors, low social support, working challenges, accommodation, personal affairs, and cognitive factors). Correlation analysis showed positive correlations between stressors and depressive mood (r = 0.05–0.94, p < 0.05). Regression analysis indicated that low social support stressor was the strongest predictor of depressive mood (β = 0.21), while working challenges, personal affairs, and cognitive factors also positively predicted depressive mood. The mediating model showed that expression inhibition played a partial mediating (promoting) role between stressors and depressive mood, accounting for 3.13% of total variance. The moderating model showed that parent-child alienation played a moderating role in the model (β = 0.01, p < 0.001); a lower level of parent-child alienation effectively alleviated the impacts of stressors on depressive mood. Stressors (working challenges, personal affairs, cognitive factors, and especially low social support) positively predict the depressive mood of long-term high-altitude workers in China. Expression inhibition plays a promoting mediation in the relationship between stressors and depressive mood. A good parent-child relationship alleviates the negative impact of stressors on depressive mood. Findings provide new empirical support for diathesis-stress theory and attract further attention to less expression inhibition and better parent-child relationships in depression prevention.",20507283,PSYCHOLOGY
10.3390/ejihpe15040058,Lost in Thought or Just Lonely? Everyday Cognitive Competence in Middle Adulthood,"Everyday cognitive competence refers to the ability to manage cognitively demanding tasks essential for maintaining functional independence. While cognitive abilities are well explored in explaining individual differences in everyday cognitive competence, growing attention has been directed toward the impact of non-cognitive factors like loneliness. This study aims to investigate how executive function (EF) components—updating, inhibition, and task shifting—predict everyday cognitive competence and whether loneliness explains the additional variance beyond EF processes. To account for the multifaceted nature of everyday cognitive competence, both performance-based (Everyday Problems Test—EPT) and self-reported measures (Cognitive Failures Questionnaire—CFQ) were administrated. The sample included 176 middle-aged adults (ages 43–65), a group suitable for investigating predictors of everyday cognitive competence in the early stages of cognitive aging. The findings reveal that updating is a significant predictor of the performance on the EPT, while loneliness is not. When self-reported cognitive lapses are considered, loneliness emerges as a significant predictor. The lack of a relationship between the EPT and CFQ, along with their differing associations with EF, loneliness, and sociodemographic factors, suggests they assess distinct aspects of everyday cognitive competence. This highlights the need for a multidimensional assessment framework to gain a comprehensive understanding of everyday cognitive competence in middle-aged adults.",22549625,PSYCHOLOGY
10.3390/ai6040074,Beautimeter: Harnessing GPT for Assessing Architectural and Urban Beauty Based on the 15 Properties of Living Structure,"Beautimeter is a new tool powered by generative pre-trained transformer (GPT) technology, designed to evaluate architectural and urban beauty. Rooted in Christopher Alexander’s theory of centers, this work builds on the idea that all environments possess, to varying degrees, an innate sense of life. Alexander identified 15 fundamental properties, such as levels of scale and thick boundaries, that characterize living structure, which Beautimeter uses as a basis for its analysis. By integrating GPT’s advanced natural language processing capabilities, Beautimeter assesses the extent to which a structure embodies these 15 properties, enabling a nuanced evaluation of architectural and urban aesthetics. Using ChatGPT4o, the tool helps users generate insights into the perceived beauty and coherence of spaces. We conducted a series of case studies, evaluating images of architectural and urban environments, as well as carpets, paintings, and other artifacts. The results demonstrate Beautimeter’s effectiveness in analyzing aesthetic qualities across diverse contexts. Our findings suggest that by leveraging GPT technology, Beautimeter offers architects, urban planners, and designers a powerful tool to create spaces that resonate deeply with people. This paper also explores the implications of such technology for architecture and urban design, highlighting its potential to enhance both the design process and the assessment of built environments.",26732688,AI
10.3390/ai6040075,History-Aware Multimodal Instruction-Oriented Policies for Navigation Tasks,"The rise of large-scale language models and multimodal transformers has enabled instruction-based policies, such as vision-and-language navigation. To leverage their general world knowledge, we propose multimodal annotations for action options and support selection from a dynamic, describable action space. Our framework employs a multimodal transformer that processes front-facing camera images, light detection and ranging (LIDAR) sensor’s point clouds, and tasks as textual instructions to produce a history-aware decision policy for mobile robot navigation. Our approach leverages a pretrained vision–language encoder and integrates it with a custom causal generative pretrained transformer (GPT) decoder to predict action sequences within a state–action history. We propose a trainable attention score mechanism to efficiently select the most suitable action from a variable set of possible options. Action options are text–image pairs and encoded using the same multimodal encoder employed for environment states. This approach of annotating and dynamically selecting actions is applicable to broader multidomain decision-making tasks. We compared two baseline models, ViLT (vision-and-language transformer) and FLAVA (foundational language and vision alignment), and found that FLAVA achieves superior performance within the constraints of 8 GB video memory usage in the training phase. Experiments were conducted in both simulated and real-world environments using our custom datasets for instructed task completion episodes, demonstrating strong prediction accuracy. These results highlight the potential of multimodal, dynamic action spaces for instruction-based robot navigation and beyond.",26732688,AI
10.3390/ai6040077,Enhancing the Classification of Imbalanced Arabic Medical Questions Using DeepSMOTE,"The growing demand for telemedicine has highlighted the need for automated healthcare services, particularly in medical question classification. This study presents a deep learning model designed to address key challenges in telemedicine, including class imbalance and accurate routing of Arabic medical questions to the correct specialties. The model combines AraBERTv0.2-Twitter, fine-tuned for informal Arabic, with Bidirectional Long Short-Term Memory (BiLSTM) networks to capture deep semantic relationships in medical text. We used a labeled dataset of 5000 Arabic consultation records from Altibbi, covering five key medical specialties selected for their clinical relevance and frequency. The data underwent preprocessing to remove noise and normalize text. We employed stratified sampling to ensure representative distribution across the selected medical specialties. We evaluate multiple models using macro precision, macro recall, macro F1-score, weighted F1-score, and G-Mean. Our results demonstrate that DeepSMOTE combined with cross-entropy loss achieves the best performance. The findings offer statistically significant improvements and have practical implications for improving screening and patient routing in telemedicine platforms.",26732688,AI
10.1186/s40359-025-02682-4,"Addressing the associative stigma of psychiatry and psychiatrists: a survey on the attitudes of medical and nursing students and doctors in Verona, Italy","Negative societal attitudes toward mental health often contribute to misconceptions and stereotypes about psychiatry, a phenomenon known as “associative stigma”. This stigma can hinder collaboration between psychiatrists and other specialists and deter students from pursuing psychiatry as a career. This study focused on one of the three main components of stigma by examining attitudes toward psychiatry and psychiatrists among medical and nursing students, as well as doctors, and identifying factors that influence these attitudes. A cross-sectional survey was conducted among medical and nursing students at the University of Verona and doctors affiliated to the Medical Professional Association of Verona. Attitudes toward psychiatry were assessed using the Attitude to Psychiatry Scale. Regression analysis evaluated the relationship between participants’ characteristics and their attitudes toward psychiatry and psychiatrists. A total of 511 medical students, 394 nursing students, and 638 doctors participated in the study. While students had generally positive attitudes towards psychiatry, they perceived it as lacking full respect within medial community (84% medical, 76% nursing), having low prestige (63.5% medical, 65.9% nursing), and receiving insufficient encouragement in university courses (39% medical, 41.7% nursing). Doctors also expressed positive attitudes, though to a lesser extent than students. Their primary concerns related to patient care: 81% reported feeling emotionally drained when treating psychiatric patients, and 58.2% felt that patients were not appreciative of the care received. Female students and doctors, students who had taken psychiatric courses, and doctors in non-surgical specialties exhibited more positive attitudes. This study revealed generally positive attitudes towards psychiatry, underscoring its relevance as a medical specialty. However, concerns regarding the discipline’s perceived status and respect within the medical field highlight areas for targeted interventions to enhance its image and encourage greater interest among students and professionals.",20507283,PSYCHOLOGY
10.1007/s00432-025-06176-z,Revealing tumor microenvironment communication through m6A single-cell analysis and elucidating immunotherapeutic potentials for cutaneous melanoma (CM),"Background The methylation of N6-methyladenosine (m6A) RNA plays a crucial role in the genetic regulation of various cancers. While m6A modifications have been extensively studied in the tumor microenvironment (TME) of several malignancies, their role in cutaneous melanoma (CM) remains unexplored. Methods Using Non-negative matrix factorization (NMF) analysis on single-cell RNA-seq data (GSE215121) from three CM samples obtained from public databases, 26 m6A RNA methylation regulators were utilized to determine TME subclusters, their expression, and function. Results Six distinct TME cell types were identified and NMF clustering further revealed unique m6A-based subpopulations of cancer-associated fibroblasts and T cells. The prognostic model demonstrated strong predictive capabilities, particularly for fibroblast and T cell m6A clusters, and highlighted COL3A1 as a critical regulator of melanoma-fibroblast interactions. Conclusion Highlighting the COL3A1 gene as a critical link and potential therapeutic target in melanoma could offer new avenues for targeted therapies and improve prognostic assessments in cutaneous melanoma.",14321335,ONCOLOGY
10.3390/cancers17081299,“Somewhat of an Adult”: Understanding the “Dance” of Competing Tensions Parents Manage While Caring for an Adolescent or Young Adult (AYA) Diagnosed with Hematologic Malignancy,"Background: Parents supporting AYAs with blood cancer juggle dual, competing roles as cancer caregiver and parent, which may heighten distress as they feel pulled simultaneously in two opposing directions. Likewise, AYAs encounter paradoxical needs as they revert to being more dependent on their parents to prioritize their survival while their developmental trajectory toward independence is disrupted. Parents need help understanding the underlying tensions they face in caregiving to reduce their distress and promote their connectedness with their AYA. Using a dialectical lens, we identified tensions parents encountered while caregiving in three contexts (clinical, family, and online communication) to inform a targeted psychosocial intervention. Methods: In partnership with The Leukemia & Lymphoma Society, we recruited 20 parents for in-depth interviews. Parents cared for adolescents aged 15–18 (n = 10) or emerging adults aged 19–29 (n = 10) diagnosed >3 months prior and in active treatment or within 2 years since treatment ended. Transcripts were thematically analyzed. Results: Parents described four ongoing tensions they needed to negotiate as they cared for their AYA: (1) being the driver versus passenger in their child’s care; (2) coping with cancer together as a family versus separately; (3) deciding to reveal versus conceal information; and (4) expecting normative developmental and disease trajectories versus disrupted trajectories. These tensions characterize the complex caregiving “dance” parents navigate in all three care contexts. Conclusions: Psychosocial education can normalize these tensions for parents to promote healthier coping and reduce distress while enhancing connectedness with their AYA. As caregiver–patient outcomes are interrelated, it may improve AYAs’ well-being.",20726694,ONCOLOGY
10.3390/cancers17081333,Oncologic Outcomes of Young Breast Cancer Patients According to Tumor Biology,"Background/Objectives: Young women frequently present with more aggressive breast cancer tumors. This retrospective study analyzed the oncological outcomes of patients under the age of 40 according to the tumor biology. Methods: Group comparisons were performed via the log-rank test. Recurrence and survival rates are presented according to the Kaplan–Meier method. Results: In total, 88 women (mean age 36) were included, but two presented with bilateral cancer, resulting in 90 tumors. Triple-negative carcinoma was most common, with 26.7% (n = 24); 11.1% (n = 10) were luminal A; 23.3% (n = 21) were luminal B HER2-negative; 15.6% (n = 14) were luminal B HER2-positive; and 6.7% (n = 6) were HER2-positive (non-luminal). Moreover, 26.1% (n = 23) of patients experienced recurrence (mean 40 months), with the highest recurrence rate in the HER2-positive (50%) and triple-negative (30.4%) groups. The 3- and 5-year recurrence-free survival rates were 84.9% and 77.3%, and the overall survival rates were 93.1% and 90.3%, respectively. No statistically significant differences in oncological outcomes were observed (p = 0.164). Conclusions: The results show that young women tend to have triple-negative and fast-growing breast carcinomas, with worse overall survival in the triple-negative group. More research is needed on the pathomechanisms of breast cancer development in young women, especially those leading to disease progression and resistance to therapy.",20726694,ONCOLOGY
10.3390/ejihpe15040063,Psychometric Properties of the Adverse Childhood Experiences Abuse Short Form (ACE-ASF) for Ecuadorian Youth,"Adverse childhood experiences, such as abuse, are a risk factor for mental health and poor socio-emotional development in adulthood. Assessing these experiences in specific populations allows for the identification of patterns and the implementation of preventive interventions. Objective: To evaluate the psychometric properties of the abbreviated version of the Adverse Childhood Experiences Abuse Form (ACE-ASF) in Ecuadorian youth, aiming to ensure the validity, reliability, and consistency of the instrument in accurately measuring abuse dimensions in this Ecuadorian population. Methodology: An instrumental study was conducted on the psychometric properties of the eight-item ACE-ASF, applying it to a sample of 840 university students (52.1% females and 47.9% males). The evaluation focused on analyzing the factorial structure and internal consistency of the instrument in this sample. Results: The two-factor model showed a satisfactory fit across all levels of invariance (configural, metric, scalar, and strict), with acceptable fit indices (CFI, TLI, GFI, RMSEA, and SRMR). The internal consistency was adequate, as assessed using the McDonald’s omega and Cronbach’s alpha coefficients. Convergent and discriminant validity were confirmed using the AVE and HTMT indices, ensuring proper differentiation between the dimensions assessed. Conclusion: The ACE-ASF proved to be a valid and reliable instrument for assessing abuse experiences in Ecuadorian youth. Its two-factor structure reflects distinct yet related dimensions, providing a useful tool for identifying adverse childhood experiences in this population.",22549625,PSYCHOLOGY
10.3390/ejihpe15040064,Teachers’ Perceptions and Preparedness for Teaching English as a Foreign Language to Students with Developmental Dyslexia: A Systematic Review,"Students with developmental dyslexia (DD) face significant challenges when learning English as a foreign language (EFL), highlighting the need for targeted support in educational systems. EFL teachers’ perceptions and preparedness regarding DD are crucial for effective instruction and improved learning outcomes in inclusive classrooms. However, no systematic review has yet explored EFL teachers’ perceptions and preparedness to teach students with DD. This systematic review, conducted in accordance with the PRISMA guidelines, examines existing research between 2005 and 2025 on EFL teachers’ perceptions and preparedness to teach students with DD. Studies were retrieved from databases including APA PsycNet, Crossref, ERIC, ProQuest, PubMed, and Scopus databases. Of 17,798 results, 16 studies met the inclusion criteria. The findings reveal mixed EFL teachers’ perceptions toward DD and inadequate training specific to DD. Moreover, practical teaching strategies and targeted interventions remain underrepresented in the literature. Most teachers lack formal DD-specific training, leading to insufficient classroom support. This review emphasizes the urgent need for improved in-service training and the development of effective resources. Future research should prioritize developing and evaluating practical teaching strategies and professional development programs on teacher preparedness in EFL contexts.",22549625,PSYCHOLOGY
10.1186/s40359-025-02548-9,A psycho-behavioral perspective research for elderly leisure sports participation via big-data and comparative analyses,"The health of the elderly and the need for research to support them has never been more important. This study aims (a) to analyze the participation behavior of the elderly in leisure sports through big-data analysis and (b) to compare and analyze the motivations, limitations, and satisfaction of participation in leisure sports by age group. First, big-data analysis using text-mining technique was conducted using the TEXTOM program to collect and analyze data between May 1, 2023 and November 24, 2024. Next, a survey was conducted among adults aged 20 years and older who regularly participate in leisure sports to determine their motivations, limitations, and satisfaction with leisure participation. From June to December 2024, the data of 301 participants were collected and analyzed using SPSS 28.0. Specifically, this study analyzed the validity and reliability of the data and then compared and analyzed the three age groups through multivariate analysis of variance. Big-data analysis identified key terms and four clusters related to senior leisure sports participation: (a) Policy, (b) Welfare, (c) Senior Sports, and (d) Employment. The results of the comparative study through the questionnaire showed that compared to younger participants in leisure sports, the elderly showed higher results in the factors of self-challenge motive, social interaction motive, and leisure participation satisfaction, but lower results in the factor of cost constraints. This means that the elderly participate in leisure sports for challenge and social interaction, are more satisfied, and are less constrained by cost. The scientific and objective results of this study could be used as a resource to specifically understand the leisure sports participation behavior of the elderly.",20507283,PSYCHOLOGY
10.1186/s40359-025-02492-8,Empowering leadership and occupational burnout: the moderated mediation model,"This study examines the impact of empowering leadership on occupational burnout through the mediating role of workaholism and the moderating effect of psychological hardiness in the relationship between empowering leadership and occupational burnout. The present study employs empowerment and hardiness theory. Further, the moderated mediation hypothesis was also investigated. Survey responses from 212 permanent employees (nurses) in the healthcare industry were gathered using the temporal separation (two time-lags with one month between the first and second lags) to test the proposed hypotheses. Different statistical analysis techniques, confirmatory factor analysis, discriminant and convergent validity and PROCES-macro were used. The current study findings shows that empowering leadership significantly reduces occupational burnout. Furthermore, the results of the study confirm that workaholism plays a crucial role as a mediator between empowering leadership and occupational burnout in the workplace. Additionally, the findings shows that empowering leadership burdens nurses by making them work excessively, which causes occupational burnout in the workplace. Furthermore, psychological hardiness is a significant moderator in the relationship between workaholism and occupational burnout. Finally, the moderated mediation model results showed that nurses with high psychological hardiness adjust and manage well with intense workloads, i.e., workaholism, when emboldened through their leaders which leads to reduction in occupational burnout. The findings emphasize the potential advantages and hazards of empowering leadership in the nursing profession and the management of healthcare. This study builds on earlier research by empirically investigating how workaholism and psychological hardiness influence the relationship between empowering leadership and occupational burnout in the nursing profession of Pakistan.",20507283,PSYCHOLOGY
10.3389/fonc.2025.1513774,Efficacy and safety of immune checkpoint inhibitors for brain metastases of non-small cell lung cancer: a systematic review and network meta-analysis,"Background: Previous studies have demonstrated that immune checkpoint inhibitors (ICIs) significantly improve prognosis in lung cancer patients with brain metastases (BMs). This systematic review and network meta-analysis aims to evaluate the efficacy and safety of 10 ICIs recommended by the 2024 Chinese Society of Clinical Oncology guidelines for treating non-small cell lung cancer (NSCLC) without driver genes, focusing on NSCLC patients presenting with BMs.Materials and methods: A comprehensive literature search of PubMed, Embase, and the Cochrane Library was conducted through June 2024 to identify eligible controlled trials and head-to-head randomized controlled trials investigating 10 ICIs in NSCLC patients with BMs. Pairwise and network meta-analyses were performed using hazard ratios (HRs) and relative risks (RRs) with 95% confidence intervals (CIs). Treatment efficacy was ranked hierarchically through the surface under the cumulative ranking curve (SUCRA).Results: Sixteen trials from 11 studies, encompassing 1,274 NSCLC patients with BMs, were included. The meta-analysis demonstrated that ICIs significantly improved overall survival (OS: HR, 0.66; 95% CI, 0.52–0.85; P = 0.001) and progression-free survival (PFS: HR, 0.67; 95% CI, 0.54–0.84; P < 0.001). SUCRA ranking identified pembrolizumab as the most effective agent for OS improvement (SUCRA 71%), while camrelizumab showed superior PFS benefits (SUCRA 92%). ICIs were associated with increased objective response rates (RR: 1.52; 95% CI, 1.13–2.06; P = 0.006), but elevated risks of immune-mediated adverse events (RR: 2.50; 95% CI, 1.46–4.30; P = 0.001) and grade 3–5 immune-mediated adverse events and infusion reaction (RR: 6.39; 95% CI, 1.53–26.69; P = 0.011).Conclusion: ICIs demonstrate superior survival benefits compared to chemotherapy in NSCLC patients with BMs, with pembrolizumab and camrelizumab emerging as optimal choices for OS and PFS improvement, respectively. However, vigilant monitoring of immune-mediated adverse events and infusion reactions remains critical in clinical practice.",2234943X,ONCOLOGY
10.3390/ai6040081,The Impact of Ancient Greek Prompts on Artificial Intelligence Image Generation: A New Educational Paradigm,"Background/Objectives: This article explores the use of Ancient Greek as a prompt language in DALL·E 3, an Artificial Intelligence software for image generation. The research investigates three dimensions of Artificial Intelligence’s ability: (a) the sense and visualization of the concept of distance, (b) the mixing of representational as well as mythic contents, and (c) the visualization of emotions. More specifically, the research not only investigates AI’s potentialities in processing and representing Ancient Greek texts but also attempts to assess its interpretative boundaries. The key question is whether AI can faithfully represent the underlying conceptual and narrative structures of ancient literature or whether its representations are superficial and constrained by algorithmic procedures. Methods: This is a mixed-methods experimental research design examining whether a specified Artificial Intelligence software can sense, understand, and graphically represent linguistic and conceptual structures in the Ancient Greek language. Results: The study highlights Artificial Intelligence’s possibility in classical language education as well as digital humanities regarding linguistic complexity versus AI’s power in interpretation. More specifically, the research not only investigates AI’s potentialities in processing and representing Ancient Greek texts but also attempts to assess its interpretative boundaries. The key question is whether AI can faithfully represent the underlying conceptual and narrative structures of ancient literature or whether its representations are superficial and constrained by algorithmic procedures. The study highlights Artificial Intelligence’s possibility in classical language education as well as digital humanities regarding linguistic complexity versus AI’s power in interpretation. Conclusions: The research is a step toward a more extensive discussion on Artificial Intelligence in historical linguistics, digital pedagogy, as well as aesthetic representation by Artificial Intelligence environments.",26732688,AI
10.1186/s40359-025-02707-y,Navigating stigma and somatization: a qualitative exploration of mental health experiences among middle-aged adults in rural China,"This study investigated the experiences of stigma and somatization among middle-aged adults with mental health issues. Using frameworks of public stigma, self-stigma, affiliate stigma, and somatization (both presenting and functional), the study explores how individuals navigate the stigma associated with mental health. Interviews were conducted with middle-aged adults in rural areas, and the data were analyzed using Interpretative Phenomenological Analysis (IPA) to gain insights into their lived experiences. The findings reveal that mental health stigma in rural China significantly influences how individuals express mental distress, often leading to somatization. Patients tend to frame their mental health issues in terms of physical symptoms, such as headaches or fatigue, to avoid stigma. The study also highlights the role of cultural norms in shaping these expressions, particularly within the context of close-knit rural communities where mental health issues is stigmatized. The implications for education and policy are discussed, emphasizing the need for improved public mental health education and more equitable distribution of healthcare resources between urban and rural areas. This study contributes to the understanding of mental health stigma in rural China and offers practical suggestions for addressing mental health challenges in underserved communities.",20507283,PSYCHOLOGY
10.3390/educsci15040510,Development and Validation of a Questionnaire on Students’ Mathematics Capital: A Tool to Explore Opportunities in the Mathematics Classroom,"Understanding students’ opportunities in mathematics education requires tools that capture the social and cultural dimensions shaping their engagement with the subject. One way to conceptualise these opportunities is through the notion of mathematics capital, which encompasses the resources and dispositions that students bring to their mathematical experiences. This study introduces and validates a questionnaire designed to measure secondary students’ mathematics capital, adapting the well-established science capital framework to the mathematical domain. Grounded in Bourdieu’s concept of capital, the questionnaire operationalises mathematics capital across mathematical forms of cultural capital, mathematics-related behaviours and practices, and mathematics-related forms of social capital. The questionnaire was administered to 119 students in an Italian secondary school as part of a broader study on mathematical memes. Statistical analyses, including correlation tests and Cronbach’s alpha, confirm the instrument’s reliability and internal coherence, highlighting the influence of both school and extracurricular environments. The questionnaire provides educators with a practical tool to better understand students’ engagement with mathematics and to inform strategies for fostering equity in mathematics education. By making mathematics capital a measurable construct, this research contributes to discussions on how cultural and social factors shape students’ trajectories in mathematics and beyond.",22277102,EDUCATION
10.3390/ai6040084,"Artificial Intelligence in Ovarian Cancer: A Systematic Review and Meta-Analysis of Predictive AI Models in Genomics, Radiomics, and Immunotherapy","Background/Objectives: Artificial intelligence (AI) is increasingly influencing oncological research by enabling precision medicine in ovarian cancer through enhanced prediction of therapy response and patient stratification. This systematic review and meta-analysis was conducted to assess the performance of AI-driven models across three key domains: genomics and molecular profiling, radiomics-based imaging analysis, and prediction of immunotherapy response. Methods: Relevant studies were identified through a systematic search across multiple databases (2020–2025), adhering to PRISMA guidelines. Results: Thirteen studies met the inclusion criteria, involving over 10,000 ovarian cancer patients and encompassing diverse AI models such as machine learning classifiers and deep learning architectures. Pooled AUCs indicated strong predictive performance for genomics-based (0.78), radiomics-based (0.88), and immunotherapy-based (0.77) models. Notably, radiogenomics-based AI integrating imaging and molecular data yielded the highest accuracy (AUC = 0.975), highlighting the potential of multi-modal approaches. Heterogeneity and risk of bias were assessed, and evidence certainty was graded. Conclusions: Overall, AI demonstrated promise in predicting therapeutic outcomes in ovarian cancer, with radiomics and integrated radiogenomics emerging as leading strategies. Future efforts should prioritize explainability, prospective multi-center validation, and integration of immune and spatial transcriptomic data to support clinical implementation and individualized treatment strategies. Unlike earlier reviews, this study synthesizes a broader range of AI applications in ovarian cancer and provides pooled performance metrics across diverse models. It examines the methodological soundness of the selected studies and highlights current gaps and opportunities for clinical translation, offering a comprehensive and forward-looking perspective in the field.",26732688,AI
10.3390/cancers17081356,Intraoperative Radiation Therapy (IORT) in Gynecologic Cancers: A Scoping Review,"Objective: We aimed to analyze the current literature for IORT in gynecological cancers and summarized clinical outcomes regarding patient selection. Methods: A systematic search was conducted utilizing PUBMED, Embase, and CINAHL to identify studies following PRISMA-ScR guidelines. A PICOS structure was utilized: population: patients with epithelial gynecological cancers; intervention: IORT; C: a comparator was not required, as we aimed to analyze patient selection; outcome: clinical outcomes and overall survival; and S: experimental and quasi-experimental analytical observational studies and descriptive observational studies, excluding case series published in English and limited to the last 10 years. Data extraction was conducted for patient selection, IORT, oncological outcomes, and morbidity. Results: A total of 707 results were identified, and 509 studies were uploaded to Covidence for screening after removing duplications. Of the 21 eligible studies, 9 were included in the final review. The total number of patients included was 348. The studies were retrospective single-institution studies, except for one. There was significant heterogeneity in their design and protocols. IORT was exclusively used for recurrent and advanced stage gynecological cancers adjunct to pelvic exenteration or laterally extended endopelvic resections with variable indications across institutions. The mean number of IORT patients per study was 2.8 per year. Survival rates were variable and dependent on the surgical margin. Endometrial cancer had a favorable outcome compared to vulvar and cervical cancers. Conclusions: Current clinical practice, as demonstrated by the research, is consistent with NCCN guidelines that endorse the application of IORT in instances of recurrent cervical, vaginal, and vulvar malignancies; however, there are no established recommendations for primary tumors. The analysis shows that there are gaps in our knowledge, mainly regarding the status of the margins, the criteria used to choose patients, and the outcomes that are specific to each histology. The standardization of protocols and prospectively powered studies are needed to refine patient selection criteria.",20726694,ONCOLOGY
10.3390/ai6040085,CacheFormer: High-Attention-Based Segment Caching,"Efficiently handling long contexts in transformer-based language models with low perplexity is an active area of research. Numerous recent approaches like Linformer, Longformer, Performer, and Structured state space models (SSMs), have not fully resolved this problem. All these models strive to reduce the quadratic time complexity of the attention mechanism while minimizing the loss in quality due to the effective compression of the long context. Inspired by the cache and virtual memory principle in computers, where in case of a cache miss, not only the needed data are retrieved from the memory, but the adjacent data are also obtained, we apply this concept to handling long contexts by dividing it into small segments. In our design, we retrieve the nearby segments in an uncompressed form when high segment-level attention occurs at the compressed level. Our enhancements for handling long context include aggregating four attention mechanisms consisting of short sliding window attention, long compressed segmented attention, dynamically retrieving top-k high-attention uncompressed segments, and overlapping segments in long segment attention to avoid segment fragmentation. These enhancements result in an architecture that outperforms existing SOTA architectures with an average perplexity improvement of 8.5% over similar model sizes.",26732688,AI
10.3390/educsci15040511,ChatGPT in Education: Challenges in Local Knowledge Representation of Romanian History and Geography,"The integration of AI tools like ChatGPT in education has sparked debates on their benefits and limitations, particularly in subjects requiring region-specific knowledge. This study examines ChatGPT’s ability to generate accurate and contextually rich responses to assignments in Romanian history and geography, focusing on topics with limited digital representation. Using a document-based analysis, this study compared ChatGPT’s responses to local archival sources, monographs, and topographical maps, assessing coverage, accuracy, and local nuances. Findings indicate significant factual inaccuracies, including misidentified Dacian tribes, incorrect historical sources, and geographic errors such as misplaced landmarks, elevation discrepancies, and incorrect infrastructure details. ChatGPT’s reliance on widely digitized sources led to omissions of localized details, highlighting a fundamental limitation when applied to non-digitized historical and geographic topics. These results suggest that while ChatGPT can be a useful supplementary tool, its outputs require careful verification by educators to prevent misinformation. Future research should explore strategies to improve AI-generated educational content, including better integration of regional archives and AI literacy training for students and teachers. The study underscores the need for hybrid AI-human approaches in education, ensuring that AI-generated text complements rather than replaces verified academic sources.",22277102,EDUCATION
10.1186/s40359-025-02729-6,Spiritual orientation and mental health: an SEM analysis of meaning and death attitudes as mediators in Turkish religious officials,"This study examines the relationships between spiritual orientation, meaning in life, attitudes towards death, and indicators of psychological health (depression, anxiety, and stress) among 348 Muslim religious officials in Turkey (28% female). Using structural equation modelling (SEM), the results showed that spiritual orientation directly and indirectly reduces psychological distress by enhancing personal meaning and fostering more accepting attitudes towards death. Results showed a moderate positive association between spiritual orientation and meaning in life, and weak but significant negative associations between meaning/attitudes towards death and psychological symptoms. As one of the first empirical studies to examine the mediating role of death attitudes in this population, the research highlights the theoretical relevance of existential frameworks such as logotherapy. The study offers practical implications for the development of culturally sensitive psychoeducational and spiritual counselling programmes aimed at supporting the mental health of religious professionals exposed to grief and death-related stressors.",20507283,PSYCHOLOGY
10.1186/s40594-025-00543-5,Study of an effective machine learning-integrated science curriculum for high school youth in an informal learning setting,"This study evaluates the effectiveness of a machine learning (ML) integrated science curriculum implemented within the Science Research Mentorship Program (SRMP) for high school youth at the American Museum of Natural History (AMNH) over 2 years. The 4-week curriculum focused on ML knowledge gain, skill development, and self-efficacy, particularly for under-represented youth in STEM. ML is increasingly prevalent in STEM fields, making early exposure to ML methods and artificial intelligence (AI) literacy crucial for youth pursuing STEM careers. However, STEM fields, particularly those focused on AI research and development, suffer from a lack of diversity. Learning experiences that support the participation of under-represented groups in STEM and ML are essential to addressing this gap. Participant learning was assessed through pre- and post-surveys measuring ML knowledge, skills, and self-efficacy. Results from the implementation of the curriculum show that participants gained understanding of ML knowledge and skills (p < 0.001, d = 1.083) and self-efficacy in learning ML concepts (p = 0.004, d = 0.676). On average, participants who identified as female and non-white showed greater learning gains than their white male peers (ML knowledge: p < 0.001, d = 1.191; self-efficacy: p = 0.006, d = 0.631), decreasing gaps in ML knowledge, skills, and self-efficacy identified in pre-survey scores. The ML-integrated curriculum effectively enhances students’ understanding and confidence in ML concepts, especially for under-represented groups in STEM, and provides a model for future ML education initiatives in informal science settings. We suggest that policy makers and school leaders take into account that high school age youth can learn ML concepts through integrated curricula while maintaining an awareness that curriculum effectiveness varies across demographic groups.",21967822,EDUCATION
10.3389/frai.2025.1553220,Handling missing data of using the XGBoost-based multiple imputation by chained equations regression method,"This study introduces an XGBoost-MICE (Multiple Imputation by Chained Equations) method for addressing missing data in mine ventilation parameters. Using historical ventilation system data from Shangwan Coal Mine, scenarios with different missing rates (5, 10, and 15%) and iteration numbers (30 and 50) were simulated to validate the accuracy and effectiveness of the approach. The results demonstrate that as the missing rate increased from 5 to 15%, the Mean Squared Error (MSE) rose from 0.0445 to 0.3254, while the Explained Variance decreased from 0.988309 to 0.943267. Additionally, the Mean Absolute Error (MAE) increased by 0.29. Iteration experiments on the “frictional resistance per 100 meters” attribute showed convergence of MSE and MAE after six iterations. Overall, the XGBoost-MICE method exhibited high imputation accuracy and stable convergence across various missing data scenarios, providing robust technical support for optimizing intelligent mine ventilation systems.",26248212,AI
10.3389/frai.2025.1458707,Detection and classification of ChatGPT-generated content using deep transformer models,"Introduction: The rapid advancement of AI, particularly artificial neural networks, has led to revolutionary breakthroughs and applications, such as text-generating tools and chatbots. However, this potent technology also introduces potential misuse and societal implications, including privacy violations, misinformation, and challenges to integrity and originality in academia. Several studies have attempted to distinguish and classify AI-generated textual content from human-authored work, but their performance remains questionable, particularly for AI models utilizing large language models like ChatGPT.Methods: To address this issue, we compiled a dataset consisting of both human-written and AI-generated (ChatGPT) content. This dataset was then used to train and evaluate a range of machine learning and deep learning models under various training conditions. We assessed the efficacy of different models in detecting and classifying AI-generated content, with a particular focus on transformer-based architectures.Results: Experimental results demonstrate that the proposed RoBERTa-based custom deep learning model achieved an F1-score of 0.992 and an accuracy of 0.991, followed by DistilBERT, which yielded an F1-score of 0.988 and an accuracy of 0.988. These results indicate exceptional performance in detecting and classifying AI-generated content.Discussion: Our findings establish a robust baseline for the detection and classification of AI-generated textual content. This work marks a significant step toward mitigating the potential misuse of AI-powered text generation tools by providing a reliable approach for distinguishing between human and AI-generated text. Future research could explore the generalizability of these models across different AI-generated content sources and address evolving challenges in AI text detection.",26248212,AI
10.3389/fonc.2025.1522237,Family resilience in patients with gynecological malignant tumors after radical hysterectomy: based on the Walsh family resilience framework,"Aim: Explore and analyze the family resilience of patients with gynecological malignancies after radical hysterectomy, providing a theoretical basis for the formulation of future intervention measures.Methods: Using a phenomenological descriptive qualitative research method, 17 patients who underwent radical surgery for gynecological malignancies were selected for semi-structured interviews. Data analysis and theme extraction were conducted using Colaizzi data analysis method and NVivo V.12.Results: Three themes and eight sub-themes were extracted: family belief system (confront surgical challenges head-on, attribute positive significance to adversity, stay positive), family organization model (timely adjustment of family roles, family cohesion, get support and help from others), and family communication and problem solving skills (communicate to eliminate negative emotions, collaborative problem solving).Conclusion: This study indicates that the family belief system is the solid foundation of family resilience, the family organizational pattern serves as a buffer when the family faces adversity, and positive communication and collaborative problem solving create a positive feedback loop that enhances family resilience. Future interventions could enhance patients’ family resilience from the perspective of family strengths.",2234943X,ONCOLOGY
10.3390/ejihpe15050065,"Predicting Workplace Hazard, Stress and Burnout Among Public Health Inspectors: An AI-Driven Analysis in the Context of Climate Change","The increasing severity of climate-related workplace hazards challenges occupational health and safety, particularly for Public Health and Safety Inspectors. Exposure to extreme temperatures, air pollution, and high-risk environments heightens immediate physical threats and long-term burnout. This study employs Artificial Intelligence (AI)-driven predictive analytics and secondary data analysis to assess hazards and forecast burnout risks. Machine learning models, including eXtreme Gradient Boosting (XGBoost 3.0), Random Forest, Autoencoders, and Long Short-Term Memory (LSTMs), achieved 85–90% accuracy in hazard prediction, reducing workplace incidents by 35% over six months. Burnout risk analysis identified key predictors: physical hazard exposure (β = 0.76, p < 0.01), extended work hours (>10 h/day, +40% risk), and inadequate training (β = 0.68, p < 0.05). Adaptive workload scheduling and fatigue monitoring reduced burnout prevalence by 28%. Real-time environmental data improved hazard detection, while Natural Language Processing (NLP)-based text mining identified stress-related indicators in worker reports. The results demonstrate AI’s effectiveness in workplace safety, predicting, classifying, and mitigating risks. Reinforcement learning-based adaptive monitoring optimizes workforce well-being. Expanding predictive-driven occupational health frameworks to broader industries could enhance safety protocols, ensuring proactive risk mitigation. Future applications include integrating biometric wearables and real-time physiological monitoring to improve predictive accuracy and strengthen occupational resilience.",22549625,PSYCHOLOGY
10.1186/s40359-025-02743-8,"The relationship of fear of pain, pain anxiety, and fear-avoidance beliefs with perceived stress in surgical patients with postoperative kinesiophobia","Kinesiophobia is one of the most prevalent postoperative problems with negative effects on patient mobility. Fear of pain (FOP), pain anxiety (PA), and fear of avoidance beliefs (FABs) are influential factors on postoperative mobility and may be affected by perceived stress (PS). The present study examined whether perceived stress serves to mediate the relationship between fear of pain, pain anxiety, and fear of avoidance beliefs with kinesiophobia (fear of movement) in postoperative patients. The study was conducted in the neurosurgery, general surgery, and orthopedic wards of a hospital in Amol, Iran. A total of 330 patients (178 men and 152 women), aged 18 to 74 years, who had undergone various surgical procedures, were included. Participants were recruited using a consecutive sampling technique over a defined period to account for the staggered timing of surgeries and ensure broader representation. All patients were assessed six hours post-surgery using validated instruments, including the Tampa Scale for Kinesiophobia, Pain Anxiety Symptoms Scale, Fear of Pain Questionnaire, Fear-Avoidance Beliefs Questionnaire, and Perceived Stress Scale. The majority of the sample were men (53.9%), married (80%), with a mean age of 44.38 (SD = 13.49) years. Of the participants, 119 (36.1%) underwent orthopedic surgery, 139 (42.1%) underwent abdominal surgery, and 72 (21.8%) underwent surgery for discopathy. The path analysis revealed that kinesiophobia exhibited a significant relationship with FABs (β = 0.206; p < 0.001; 95% CI: 0.009 to 0.017) and PA (β = 0.474; p < 0.001; 95% CI: 0.021 to 0.031), while no significant relationship was found with FOP (β = 0.072; p = 0.408; 95% CI: -0.011 to 0.011). Also, the findings indicated that PS as mediator had a significant relationship with FABs (ß = 0.191; P < 0.001; 95% CI: 0.009 to 0.017), PA (ß = 0.393; P < 0.001;95% CI: 0.021 to 0.031), and kinesiophobia (ß = 0.812; P < 0.001; 95% CI: 0.021 to 0.031. The study found that pain anxiety and fear-avoidance beliefs are key factors contributing to kinesiophobia after surgery. Addressing these fears is important for improving postoperative mobility. Perceived stress mediated the relationship between these factors and kinesiophobia. Managing stress may be a helpful intervention to improve outcomes for postoperative patients. Healthcare providers should assess and address psychological factors like pain anxiety and fear-avoidance beliefs to promote better recovery and mobility in patients after surgery.",20507283,PSYCHOLOGY
10.1186/s40594-025-00545-3,"Processes, challenges, and teacher roles in developing and implementing collaborative STEM curricula: case studies of two Taiwanese schools","A key research gap in current STEM education lies in the need for a more in-depth exploration of STEM teachers as curriculum designers, particularly in how they collaborate in designing STEM curricula and their roles within that process. This study selected two high-performing STEM teaching teams for investigation and employed a naturalistic approach along with a case study methodology to examine how STEM teachers collaborate to develop and implement STEM curricula in real teaching contexts. After 8 months of data collection and analysis, the main findings are as follows: (1) there are discrepancies between the tasks emphasized at each stage of the collaborative STEM curriculum model by high-performing STEM teaching teams and those outlined in theoretical models. In addition, the resources and drivers valued by these teams are not accounted for in the theoretical models. (2) Both high-performing STEM teaching teams faced several challenges during collaborative curriculum design and implementation, including difficulties with scheduling, limited time for lesson preparation, challenges in assessing higher-order thinking, and integrating team members. The main challenge faced by both schools was the absence of common meeting times for interdisciplinary collaboration. This highlights the need for strategic scheduling and institutional support to enable teacher collaboration in STEM education. (3) The three main roles within STEM teaching teams are leaders, core teachers, and participating teachers. However, in practice, core teachers and participating teachers often do not fulfill the responsibilities they are expected to undertake. This study also discusses potential research limitations and offers relevant suggestions for future research. The study also identified a significant discrepancy between theory and practice. While the PADPIE model outlines a structured six-stage design stages, schools frequently skip or merge stages due to time and resource limitations. An inconsistency was noted in the enactment of teacher roles. While formal assignments such as leaders, core teachers, and participating teachers were established, many core and participating teachers often lacked clarity and initiative in their responsibilities. These findings highlight the need to bridge the gap between theoretical models and real-world implementation.",21967822,EDUCATION
10.3390/ai6050088,Evaluating the Efficacy of Deep Learning Models for Identifying Manipulated Medical Fundus Images,"(1) Background: The misuse of transformation technology using medical images is a critical problem that can endanger patients’ lives, and detecting manipulation via a deep learning model is essential to address issues of manipulated medical images that may arise in the healthcare field. (2) Methods: The dataset was divided into a real fundus dataset and a manipulated dataset. The fundus image manipulation detection model uses a deep learning model based on a Convolution Neural Network (CNN) structure that applies a concatenate operation for fast computation speed and reduced loss of input image weights. (3) Results: For real data, the model achieved an average sensitivity of 0.98, precision of 1.00, F1-score of 0.99, and AUC of 0.988. For manipulated data, the model recorded sensitivity of 1.00, precision of 0.84, F1-score of 0.92, and AUC of 0.988. Comparatively, five ophthalmologists achieved lower average scores on manipulated data: sensitivity of 0.71, precision of 0.61, F1-score of 0.65, and AUC of 0.822. (4) Conclusions: This study presents the possibility of addressing and preventing problems caused by manipulated medical images in the healthcare field. The proposed approach for detecting manipulated fundus images through a deep learning model demonstrates higher performance than that of ophthalmologists, making it an effective method.",26732688,AI
10.3389/fpsyg.2025.1491265,Impact of microlearning on developing soft skills of university students across disciplines,"Introduction: This study explores the effectiveness of microlearning in developing key soft skills among university students across four academic disciplines: humanities and arts (HA), business studies (BS), medical sciences (MS), and technical and engineering (TE). Addressing the disconnect between academic training and industry expectations, the research investigates how microlearning interventions influence the development of teamwork skills (TWS), leadership skills (LS), communication skills (CS), time management skills (TMS), and emotional intelligence (EI). The study also aims to identify which disciplines benefit most from microlearning for each specific skill.Methods: A total of 384 Chinese university students participated in this study, with a questionnaire recovery rate of 93.23% and near-equal representation from each discipline. Participants completed pre- and post-intervention surveys following tailored microlearning modules. Statistical analyses—including paired sample t-tests, independent sample t-tests, and effect size calculations—were employed to test five hypotheses related to soft skill development across disciplines.Results: Findings indicate that leadership-focused microlearning modules significantly benefited TE and MS students, while EI training was particularly effective for BS students. Notable improvements in CS and TMS were observed among BS and TE students, aligning with skills demanded in corporate project management. Overall, microlearning interventions produced measurable enhancements in specific soft skills, with variation across academic disciplines.Discussion: The results suggest that integrating structured, discipline-specific microlearning into university curricula can effectively bridge academic-industry skill gaps. Faculty are encouraged to adopt scenario-based microlearning strategies to enhance student engagement. Higher education institutions should prioritize microlearning experience in student development and recruitment. Additionally, EdTech providers are urged to develop AI-powered interactive platforms to personalize learning, while students should proactively engage in targeted microlearning to improve academic and career outcomes.",16641078,PSYCHOLOGY
10.3389/fpsyg.2025.1579787,"If not police, then who? Building a new workforce for community behavioral health crisis response","Introduction: Communities across the United States and elsewhere are working to implement alternatives to law enforcement as primary responders to behavioral health crises. These efforts can only be successful if there is a skilled workforce prepared to take on this role. We argue that this workforce must be developed, and propose a new, credentialed Community Behavioral Health Crisis Responder (CBHCR) role.Methods: Guided by a 13-member advisory board with expertise across behavioral health, crisis services, and law enforcement, we conducted a literature review, key informant interviews, and focus groups to identify the foundational values, competencies, and skills for this proposed role.Results: Interview and focus group participants discussed desired characteristics of CBHCRs and emphasized values such as cultural humility, a nonjudgmental approach, and the importance of lived experience broadly defined. Competencies and skills included engagement and communication strategies that enhance safety and trust, suicide prevention, conflict resolution, and situational awareness. Participants highlighted the need to train CBHCRs to provide compassionate, trauma-informed crisis intervention, de-escalation, support, and connection to needed resources. In conjunction with our advisory board and external experts, we used the findings to iteratively refine the values, competencies, and skills of CBHCRs.Discussion: We discuss the next steps in creating this new, skilled and credentialed crisis response workforce.",16641078,PSYCHOLOGY
10.3390/ai6050091,A Hybrid and Modular Integration Concept for Anomaly Detection in Industrial Control Systems,"Effective anomaly detection is essential for realizing modern and secure industrial control systems. However, the direct integration of anomaly detection within such a system is complex due to the wide variety of hardware used, different communication protocols, and given industrial requirements. Many components of an industrial control system allow direct integration, while others are designed as closed systems or do not have the required performance. At the same time, the effective usage of available resources and the sustainable use of energy are more important than ever for modern industry. Therefore, in this paper, we present a modular and hybrid concept that enables the integration of efficient and effective anomaly detection while optimising the use of available resources under consideration of industrial requirements. Because of the modular and hybrid properties, many functionalities can be outsourced to the respective devices, and at the same time, additional hardware can be integrated where required. The resulting flexibility allows the seamless integration of complete anomaly detection into existing and legacy systems without the need for expensive centralised or cloud-based solutions. Through a detailed evaluation within an industrial unit, we demonstrate the performance and versatility of our concept.",26732688,AI
10.1007/s00432-025-06210-0,Clinical pathological characteristics and prognostic analysis of renal primitive neuroectodermal tumours: a multicentre retrospective study of 16 cases in Northwest China,"Objective Renal primitive neuroectodermal tumours (rPNETs) are extremely rare and highly aggressive malignancy, posing significant diagnostic and therapeutic challenges. This study aims to describe the clinicopathological characteristics, treatment strategies, and survival outcomes of 16 cases of rPNET from multiple centers in Northwest China, and to explore potential prognostic factors. Methods A multicenter retrospective study was conducted, including 16 patients diagnosed with rPNET across five hospitals in Northwest China. Immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) were employed to assess the expression of molecular markers, including P53, BCL-2, Ki-67, and EWSR1 gene rearrangements. Survival analysis was performed using the Kaplan-Meier method, and prognostic factors were evaluated using univariate and multivariate Cox regression models. Results The median age of the patients was 39 years, with a median Ki-67 proliferation index of 50%. P53 mutations were detected in 87.0% of cases, and BCL-2 positive expression was observed in 56.25% of cases. The median overall survival (OS) was 14 months. Univariate analysis revealed that age, tumor stage, BCL-2 expression, and Ki-67 index were significantly associated with OS. Multivariate analysis identified high Ki-67 expression (HR = 1.100, 95% CI: 1.030–1.174, p = 0.004) and negative BCL-2 expression (HR = 0.151, 95% CI: 0.026–0.888, p = 0.037) as independent risk factors for poor prognosis. Kaplan-Meier survival curves demonstrated that the median OS was significantly shorter in patients with high Ki-67 expression (12 months) compared to those with low Ki-67 expression (20 months) (Log-rank test, P < 0.01). Similarly, the median OS was significantly shorter in the BCL-2 negative group (10 months) compared to the BCL-2 positive group (24 months) (Log-rank test, P < 0.05). Conclusion The absence of rosette structures does not exclude the diagnosis of rPNET. BCL-2 and Ki-67 expression are significant prognostic factors, with high Ki-67 expression and negative BCL-2 expression associated with worse outcomes. These findings highlight the importance of molecular markers in risk stratification and treatment planning for rPNET.",14321335,ONCOLOGY
10.3389/fonc.2025.1507677,Copy number gain of MET gene with low level in a metastatic lung adenocarcinoma patient represents response to salvage treatment with savolitinib and osimertinib: a case report,"Background: Mesenchymal–epithelial transition (MET) amplification is one of the molecular mechanisms of abnormal MET oncogenic signaling in non-small cell lung cancer (NSCLC), significantly contributing to tumor cell survival, proliferation, metastasis, and drug resistance. The results of the TATTON trial showed that the combination of savolitinib and osimertinib can prolong the survival of patients with advanced EGFR-TKI-resistant NSCLC and high-level acquired MET amplification.Case presentation: We present a case of an NSCLC patient who exhibited acquired MET amplification with a gene copy number (GCN) of 3 following resistance to EGFR-TKI. The patient achieved a substantial response to salvage therapy with savolitinib and osimertinib, resulting in a 7-month progression-free survival (PFS).Conclusions: We considered that a regimen of savolitinib + osimertinib combination sometimes may still be potentially beneficial for NSCLC patients with low-GCN-level MET amplification. However, it needs further confirmation in a larger cohort.",2234943X,ONCOLOGY
10.3389/fonc.2025.1502062,Radiomics model based on dual-energy CT venous phase parameters to predict Ki-67 levels in gastrointestinal stromal tumors,"Objective: To develop and validate a radiomics model based on the features of the Dual-Energy CT (DECT) venous phase iodine density maps and effective atomic number maps to predict Ki-67 expression levels in gastrointestinal stromal tumors (GISTs).Methods: A total of 91 patients with GIST were retrospectively analyzed, including 69 patients with low Ki-67 expression (≤5%) and 22 patients with high Ki-67 expression (>5%). Four clinical features (gender, age, maximum tumor diameter, and tumor location) were extracted to construct a clinical model. The venous phase enhanced CT iodine density maps and effective atomic number maps of DSCT were used to build radiomics models. Logistic regression was used to combine radiomics features with clinical features to build a combined model. Finally, the optimal model’s discrimination, calibration, and clinical decision curve were validated using the Bootstrap method.Results: The combined model was identified as the best model, with high predictive performance. The model’s discrimination had an AUC of 0.982 (95% CI, 0.9603-1). The calibration test showed a Hosmer-Lemeshow test P-value of 0.99. The clinical decision curve demonstrated a probability threshold range of 15% to 98%, with a high net benefit.Conclusion: The nomogram model combining clinical features and radiomics (iodine density map radscore + effective atomic number map radscore) has the highest accuracy for preoperative prediction of Ki-67 expression in GISTs.",2234943X,ONCOLOGY
10.3390/ai6050093,Personalized Non-Player Characters: A Framework for Character-Consistent Dialogue Generation,"Generating character-consistent and personalized dialogue for Non-Player Characters (NPCs) in Role-Playing Games (RPGs) poses significant challenges, especially due to limited memory retention and inconsistent character representation. This paper proposes a framework for generating personalized dialogues based on character-specific knowledge. By combining static knowledge fine-tuning and dynamic knowledge graph technology, the framework generates dialogue content that is more aligned with character settings and is highly personalized. Specifically, the paper introduces a protective static knowledge fine-tuning approach to ensure that the language model does not generate content beyond the character’s cognitive scope during conversations. Additionally, dynamic knowledge graphs are employed to store and update the interaction history between NPCs and players, forming unique “experience-response” patterns. During dialogue generation, the paper first parses player input into an Abstract Meaning Representation (AMR) graph, retrieves relevant memory nodes from the knowledge graph, and constructs a fused graph structure. This integrated graph is encoded via a graph neural network to generate high-dimensional semantic vectors, which are then used to retrieve and supplement knowledge from the vector database. Ultimately, the model generates personalized responses consistent with the NPC’s identity. Experimental results demonstrate that the framework significantly enhances the authenticity of NPC dialogues and player immersion and performs well on multiple large-scale language models.",26732688,AI
10.3389/frai.2025.1529814,Precision enhancement in wireless capsule endoscopy: a novel transformer-based approach for real-time video object detection,"Background: Wireless Capsule Endoscopy (WCE) enables non-invasive imaging of the gastrointestinal tract but generates vast video data, making real-time and accurate abnormality detection challenging. Traditional detection methods struggle with uncontrolled illumination, complex textures, and high-speed processing demands.Methods: This study presents a novel approach using Real-Time Detection Transformer (RT-DETR), a transformer-based object detection model, specifically optimized for WCE video analysis. The model captures contextual information between frames and handles variable image conditions. It was evaluated using the Kvasir-Capsule dataset, with performance assessed across three RT-DETR variants: Small (S), Medium (M), and X-Large (X).Results: RT-DETR-X achieved the highest detection precision. RT-DETR-M offered a practical trade-off between accuracy and speed, while RT-DETR-S processed frames at 270 FPS, enabling real-time performance. All three models demonstrated improved detection accuracy and computational efficiency compared to baseline methods.Discussion: The RT-DETR framework significantly enhances precision and real-time performance in gastrointestinal abnormality detection using WCE. Its clinical potential lies in supporting faster and more accurate diagnosis. Future work will focus on further optimization and deployment in endoscopic video analysis systems.",26248212,AI
10.3390/ai6050094,Robust Single-Cell RNA-Seq Analysis Using Hyperdimensional Computing: Enhanced Clustering and Classification Methods,"Background. Single-cell RNA sequencing (scRNA-seq) has transformed genomics by enabling the study of cellular heterogeneity. However, its high dimensionality, noise, and sparsity pose significant challenges for data analysis. Methods. We investigate the use of Hyperdimensional Computing (HDC), a brain-inspired computational framework recognized for its noise robustness and hardware efficiency, to tackle the challenges in scRNA-seq data analysis. We apply HDC to both supervised classification and unsupervised clustering tasks. Results. Our experiments demonstrate that HDC consistently outperforms established methods such as XGBoost, Seurat reference mapping, and scANVI in terms of noise tolerance and scalability. HDC achieves superior accuracy in classification tasks and maintains robust clustering performance across varying noise levels. Conclusions. These results highlight HDC as a promising framework for accurate and efficient single-cell data analysis. Its potential extends to other high-dimensional biological datasets including proteomics, epigenomics, and transcriptomics, with implications for advancing bioinformatics and personalized medicine.",26732688,AI
10.3390/ejihpe15050069,"Effect of an Educational Intervention on Pupil’s Knowledge, Attitudes, Perceptions, and Behavior on Air Pollution in Public Schools in Pristina","This interventional study aimed to assess the effectiveness of a school-based environmental education program on improving knowledge, attitudes, perceptions, and behavior related to air pollution among pupils in low-middle schools in Pristina, Kosovo. Air pollution is a pressing issue in Kosovo, particularly in urban areas, making it essential to raise awareness from an early age. As one of the first initiatives of its kind in the country, this study offers valuable insights into the impact of educational interventions on students’ understanding of environmental issues. The study involved an intervention group of fifth to ninth grade students who participated in a structured environmental education program, with data collected through pre-test, post-test, and follow-up assessment. We used a quantitative questionnaire with four sections—demographics, knowledge, perceptions, attitudes, and behavior. The findings revealed a significant improvement in knowledge and perceptions about air pollution among students in the intervention group, highlighting the crucial role of education in raising environmental awareness. However, the intervention had limited impact on changing attitudes and no significant effect on pro-environmental behavior, echoing challenges found in previous studies. Parental education, particularly maternal education, was found to play a substantial role in shaping attitudes, while gender and parental education positively influenced perceptions. The study also identified a negative association between higher grade levels and both knowledge and perception scores. Despite its success in enhancing knowledge, the short intervention period and challenges in participant engagement limited the program’s ability to drive long-term behavioral change. These findings emphasize the need for more sustained and comprehensive interventions to address the complex relationship between knowledge, attitudes, and environmental behaviors.",22549625,PSYCHOLOGY
10.3390/ai6050096,Automated Pruning Framework for Large Language Models Using Combinatorial Optimization,"Currently, large language models (LLMs) have been utilized in many aspects of natural language processing. However, due to their significant size and high computational demands, large computational resources are required for deployment. In this research, we focus on the automated approach for size reduction of such a model. We propose the framework to perform the automated pruning based on combinatorial optimization. Two techniques were particularly studied, i.e., particle swarm optimization (PSO) and whale optimization algorithm (WOA). The model pruning problem was modeled as a combinatorial optimization task whose the goal is to minimize model size while maintaining model accuracy. The framework systematically explores the search space to identify the most optimal pruning configurations, removing redundant or non-contributory parameters. The two optimizations, PSO and WOA, were evaluated for their ability to efficiently navigate the search space. As a result, with PSO, the proposed framework can reduce the model size of Llama-3.1-70B by 13.44% while keeping the loss of model accuracy at 19.25%; with WOA, the model size reduction is 12.07% with 22.81% loss of model accuracy. Since accuracy degradation may occur during pruning process, the framework integrates the post-process to recover the model accuracy. After this process, the pruned model loss can reduce to 12.72% and 14.83% using PSO and WOA, respectively.",26732688,AI
10.3390/ejihpe15050070,"The Influence of Loneliness, Social Support and Income on Mental Well-Being","Mental well-being is a multifaceted concept that reflects emotional stability, psychological resilience and social connectedness. This study examines how demographic factors, perceived loneliness, and social support influence mental well-being in Spain. Participants were surveyed online and provided personal information along with responses to the University of California, Los Angeles (UCLA) Loneliness Scale, the Medical Outcomes Study Social Support Survey (MOS-SSS), and the Warwick–Edinburgh Mental Well-Being Scale (WEMWBS). Our findings support previous research on mental well-being in Spain and again show significant associations between income, loneliness, social support and overall mental health. In particular, perceived loneliness was found to be a strong predictor of mental well-being. Furthermore, income and social support were found to partially mediate the relationship between loneliness and mental well-being. These findings highlight the critical role of social connections and financial stability in promoting mental health. Overall, this research contributes to the growing understanding of the factors influencing mental well-being and provides valuable insights for improving mental health outcomes.",22549625,PSYCHOLOGY
10.1007/s44196-025-00827-2,Min3GISG: A Synergistic Feature Selection Framework for Industrial Control System Security with the Integrating Genetic Algorithm and Filter Methods,"Industrial control systems (ICS) are crucial for automating and optimizing industrial operations but are increasingly vulnerable to cyberattacks due to their interconnected nature. High-dimensional ICS datasets pose challenges for effective anomaly detection and classification. This study aims to enhance ICS security by improving attack detection through an optimized feature selection framework that balances dimensionality reduction and classification accuracy. The study utilizes the HAI dataset, comprising 54,000 time series records with 225 features representing normal and anomalous ICS behaviors. A hybrid feature selection approach integrating wrapper and filter methods was employed. Initially, a Genetic Algorithm (GA) identified 118 relevant features. Further refinement was conducted using filter-based methods—Symmetrical Uncertainty (SU), Information Gain (IG), and Gain Ratio (GR)—leading to a final subset of 104 optimal features. These features were used to train classification models (Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM)) with a 70:30 train-test split and tenfold cross-validation. The proposed feature selection method significantly improved classification accuracy, achieving 98.86% (NB), 99.91% (RF), and 97.97% (SVM). Compared to the full dataset (225 features), which yielded 97.51%, 99.93%, and 96.17%, respectively, our optimized feature subset maintained or enhanced classification performance while reducing computational complexity. This research demonstrates the effectiveness of a hybrid feature selection approach in improving ICS anomaly detection. By reducing feature dimensionality without compromising accuracy, the proposed method enhances ICS security, offering a scalable and efficient solution for real-time attack detection.",18756883,AI
10.3389/fpsyg.2025.1491759,The Illusory Health Beliefs Scale: validation using exploratory structural equation modeling and multidimensional Rasch analysis,"The Illusory Health Beliefs Scale (IHBS) is a multidimensional instrument that evaluates endorsement of scientifically unsubstantiated, illusory health-oriented notions. These beliefs are important because they potentially influence attitudes/actions to the detriment of personal wellbeing/health. Preceding research examining IHBS item performance at the unidimensional subscale level identified five dimensions (Religious/Spiritual, Superstition, Precognitive, Health Myths, Skepticism), and an independent Health Pseudoscience subscale. The present paper extended latent structure analysis by employing exploratory structural equation modeling (ESEM) and multidimensional Rasch analysis. Concurrently, statistical appraisal tested convergent validity via relationships with related health-based constructs (i.e., health locus of control, HLC and beliefs about complementary and alternative medicine, CAM). A sample of 2,138 completed the IHBS (1,016 males, 1,113 females, seven non-binary, two preferred not to disclose). Following minor scale modification, ESEM reported good data-fit for a six-factor model. With the exception of Skepticism, which was negatively associated, IHBS subfactors correlated positively with HLC and CAM. These outcomes supported the supposition that the IHBS measures perceived and illusory health control. Rasch analysis designated sufficient multidimensionality and satisfactory subscale functioning. Strong associations indicated that IHBS dimensions assessed related but discrete aspects of illusory health beliefs. High associations among paranormal-based dimensions (Religious/Spiritual, Superstition, and Precognitive) suggested the need for greater content separation. Moreover, the poor reliability of Skepticism designated the need to develop a more efficacious assessment of this dimension.",16641078,PSYCHOLOGY
10.3390/cancers17101613,Molecular Mechanisms of Drug Resistance in Clear Cell Renal Cell Carcinoma,"Renal cell carcinoma (RCC) accounts for about 3% of all human tumors. Alterations of oxygen, lipids, iron, and energy metabolism are involved in carcinogenesis, development, and expansion. Thirty percent of patients affected by clear cell renal cell carcinoma (ccRCC) will develop relapses or distance metastases (mRCC), dramatically reducing their life expectancy. Current first-line therapies for mRCC patients are based on treatment with immune checkpoint inhibitors (ICIs) alone and in combination with each other or with tyrosine kinase inhibitors (TKIs). However, only 20% of patients show a mild response because of innate or acquired drug resistance during long-term treatment; therefore, resistant patients need alternative first-line or second-line therapies. Pharmacological resistance represents a big problem that counteracts the efficacy of treatment by reducing overall survival (OS) in mRCC patients. Investigating the molecular mechanisms underlying drug resistance is crucial to overcoming drug insensitivity and enhancing therapeutic outcomes. In this review, we emphasize the latest and most significant studies on the molecular mechanisms that drive drug resistance in ccRCC carcinoma. Particular attention is given to the key signaling pathways involved in resistance, including those mediated by HIF, p53, Akt-mTOR, MEK–ERK cascades, Wnt signaling, autophagy, membrane transporters, ferroptosis, and non-coding RNAs. Understanding these resistance mechanisms is essential for developing new therapeutic strategies aimed to enhancing overall OS and improving the quality of life for mRCC patients. This review also discusses recent clinical trial findings on the use of specific inhibitors able to circumvent drug resistance. The data presented here could be valuable for clinicians in understanding the mechanisms of drug resistance, ultimately aiding in the management of ccRCC patients.",20726694,ONCOLOGY
10.1007/s00432-025-06218-6,Thoracoscopy-guided thoracic paravertebral block using dexmedetomidine in combination with ropivacaine for postoperative analgesia after thoracoscopic radical resection of lung cancer: a randomized controlled trial,"Purpose The aim of this trial was to evaluate the analgesic effect of dexmedetomidine combined with ropivacaine for thoracoscopic-guided thoracic paravertebral block (TTPB) after thoracoscopic radical resection (TRR) of lung cancer. Methods A total of 60 patients were enrolled from our hospital who underwent elective TRR of lung cancer and randomized into either a control group (group C) or a dexmedetomidine group (group D). Prior to incisional suturing, group C received ropivacaine alone for TTPB, while group D received dexmedetomidine combined with ropivacaine for TTPB. The primary outcome was the time to the first analgesic request (TFAR). The secondary outcomes included heart rate (HR), mean arterial pressure (MAP), Ramsay sedation score, and Numerical Rating Scale (NRS) scores (both at rest and during coughing) at the following time points: before the TTPB operation (T0), 1 h postoperatively (T1), 2 h postoperatively (T2), 6 h postoperatively (T3), 12 h postoperatively (T4), 24 h postoperatively (T5), as well as 48 h postoperatively (T6). Additional secondary outcomes included the patient-controlled intravenous analgesia (PCIA) sufentanil dosage at 48 h postoperatively, the incidence of adverse reactions, and postoperative recovery. Results Compared to group C, group D showed a longer TFAR, lower total PCIA sufentanil dosage at 48 h postoperatively, and lower NRS scores at all time points; Group D also had lower MAP and HR, higher Ramsay sedation scores from T1 to T3 after surgery, a higher incidence of drowsiness, and better postoperative recovery. Conclusions As an adjuvant in combination with ropivacaine, dexmedetomidine enhanced the analgesic effect of TTPB, prolonged the duration of analgesia, and reduced the time to first ambulation and hospital stay. Clinical Trial Registration ChiCTR2400086347, Registered 28/06/2024.",14321335,ONCOLOGY
10.3389/feduc.2025.1596635,Financial literacy and educational level in Ecuadorian students: a structural analysis,"Background: Financial literacy has been recognized as a key competency for making in-formed economic decisions, particularly in contexts where access to financial products exceeds the population’s literacy level. However, in Ecuador, persistent gaps remain be-tween formal educational attainment and applied financial knowledge. In this context, the objective of this study was to analyze the relationship between educational level and financial literacy among Ecuadorian students.Methods: A quantitative approach was adopted, with a descriptive-correlational level, non-experimental type, and cross-sectional design. The sample consisted of 2,021 participants, selected through non-probabilistic convenience sampling. A structured questionnaire of 33 items was administered, distributed across four analytical dimensions. Statistical analysis was performed using SPSS and AMOS, including reliability testing, factorial validity, and structural model fit.Results: The results revealed that educational level has a significant effect on financial literacy. Individuals with higher education exhibited the highest levels, while those who completed only primary education showed the lowest. Four latent factors were validated: technical knowledge, socioeconomic impact of financial education, practical application of knowledge, and financial self-management.Conclusion: The correlations between these factors were strong and statistically significant, highlighting the pivotal role of educational level in shaping financial literacy. The proposed model presents a valid and consistent structure, effectively reflecting the relationships between the key variables. These findings emphasize the necessity for tailored and context-specific educational interventions that address the diverse needs of different population segments, thereby enhancing financial literacy across varying educational levels.",2504284X,EDUCATION
10.3390/educsci15050593,Everyone Is Reading and Playing! A Participatory Theatre Project to Promote Reading Competence,"This study explores the use of a theatre project to enhance reading competencies among students with special educational needs (SENs) in inclusive classrooms. The project, titled “Stop Bullying! A Theatre Project”, aimed to improve students’ reading skills through dramatised engagement with texts, with a particular focus on promoting literacy and social interaction. Employing a Design-Based Research (DBR) methodology, the study involved iterative cycles of implementation and data collection. Participants, including students with varying reading abilities, engaged in theatrical activities that incorporated reading strategies such as reading aloud, paired reading, and choral reading—each designed to support comprehension, fluency, and reading confidence. Findings from multiple cycles indicated improvements in students’ social dynamics, including stronger peer interactions and increased group cohesion. While quantitative reading assessment data showed only modest gains in reading performance, qualitative observations revealed significant improvements in reading skills and social interactions during collaborative performances. The study concludes that a theatre-based approach can effectively support reading development while fostering a more inclusive and supportive classroom environment.",22277102,EDUCATION
10.3390/educsci15050603,Developing Elite Strength and Conditioning Coaches’ Practice Through Facilitated Reflection,"Recent research has suggested that strength and conditioning (S&C) coach development should consider constructivist learning theories to promote coach development and learning of psychosocial coaching competencies. Reflective practice can encourage holistic learning through promoting an internal dialogue of the meaningfulness of an individual’s experiences. Our study aimed to examine the efficacy of a facilitated, guided, and longitudinal reflective process to promote coach learning of psychosocial coaching practice using Moon’s reflective framework. Over a four-week period, six elite S&C coaches engaged in a guided process reflection process with a facilitator. This included daily journaling in an e-diary with the facilitator providing feedback at the end of each week. At the end, each S&C coach participated in an exit interview. Data were analysed using interpretative phenomenological analysis. Findings revealed that there were potential benefits for the S&C coach’s process of reflection such as providing accountability through developing a close relationship with the facilitator, which enabled the S&C coaches to more critically link learning to behaviour change. Furthermore, S&C coaches’ learning resulted in developing awareness of self/athlete’s needs, increased flexibility, and enhanced confidence. This resulted in S&C coaches developing psychosocial coaching competencies that enabled them to change their practice to become more athlete centred.",22277102,EDUCATION
10.3389/feduc.2025.1574962,"Using website creation as a hub, promoted collaborative learning in teacher education","Introduction: The article presents a teaching design used in the first year of a teacher education in Norway. The teacher educators designed, taught and researched the project, evaluating it in collaboration with students. This is in line with a practitioner/action research approach and formative dialogue research. The teaching design was centered around the making of websites as a form of wiki learning. 143 students participated in the project. This article focuses on the student perspective and the data material was gathered through a survey and reflection papers.Results: The students pointed out the collaboration as the most important learning and how that prepared them for the future teacher profession. The student statements were classified into three categories of professional growth and discussed using the theory of professional capital. Using the students’ comments and the teacher educators’ experience, the teaching design is discussed up against earlier designs of wiki learning. The discussion elaborates on 6 possible success factors.",2504284X,EDUCATION
10.3389/feduc.2025.1600497,Academic writing strategies in university students from three disciplinary areas: design and validation of an instrument,"It is acknowledged that writing strategies are highly important not only for their usefulness in the process of text production but also for their value as a learning technique, as they involve the use of cognitive and metacognitive operations. Various international studies have validated scales to measure their use and have helped characterize expert and non-expert university writers. However, regarding specific strategies in Spanish as a mother tongue, further research is still needed in the context of higher education students. This study aimed to develop a standardized measurement instrument to identify university students' use of academic writing strategies according to disciplinary area. The sample consisted of 290 students from the Humanities and Social Sciences, Health Sciences, and Engineering from a regional university in Chile. A Likert-type scale was applied whose design was based on a thorough review of successful instruments from different parts of the world. The results indicate that the developed instrument is appropriate for higher education contexts and across different disciplinary areas.",2504284X,EDUCATION
10.3390/ejihpe15050086,Neuroscience Exposure as a Predictor of Teaching Self-Efficacy,"Teaching self-efficacy refers to a teacher’s confidence in their ability to engage students and foster learning, directly influencing their instructional planning, strategies, and student assessment practices. Neuroscience education for teachers has been shown to increase enthusiasm and support professional growth by introducing essential brain-related principles. This study investigated whether prior exposure to neuroscience predicts teaching self-efficacy among Brazilian basic education teachers. A total of 1120 teachers completed online surveys, providing sociodemographic information, educational background, teaching experience, and data regarding their previous neuroscience exposure. Participants’ neuroscience knowledge was assessed through a questionnaire designed to measure familiarity with fundamental neuroscience concepts, and teaching self-efficacy was evaluated using the Teacher Sense of Efficacy Scale (TSES). The results indicated that teachers with prior exposure to extracurricular neuroscience courses demonstrated significantly higher neuroscience knowledge. Additionally, those with previous neuroscience exposure exhibited a marginally significant increase in self-efficacy for instructional strategies and a significant increase in classroom management, while no significant differences were observed in student engagement. Regression analyses confirmed that neuroscience exposure significantly predicted self-efficacy in instructional strategies and classroom management. These findings reinforce the connection between neuroscience education and enhanced teaching self-efficacy, underscoring the importance of neuroeducation programs as valuable tools for supporting teachers’ professional development and well-being.",22549625,PSYCHOLOGY
10.3390/ai6050102,Classification of Exoplanetary Light Curves Using Artificial Intelligence,"In this article, we propose a robust star classification methodology leveraging light curves collected from 15 datasets within the Kepler field in the visible optical spectrum. By employing a Bagging neural network ensemble approach, specifically an Bagging-Performance Approach Neural Network (BAPANN), which integrates three supervised neural network architectures, we successfully classified 760 samples of curves which represent 9 type of stars. Our method demonstrated a high classification accuracy of up to 97% using light curve datasets containing 13, 20, 50, 150, and 450 points per star. The BAPANN achieved a minimum error rate of 0.1559 and exhibited efficient learning, requiring an average of 29 epochs. Additionally, nine types of stellar variability were classified through 45 conducted tests, taking into account error margins of 0, 5, and 10 for the light curve samples. These results highlight the BAPANN model’s robustness against uncertainty and ability to converge quickly in terms of iterations needed for learning, training, and validation.",26732688,AI
10.3389/frai.2025.1545607,Can chatbots teach us how to behave? Examining assumptions about user interactions with AI assistants and their social implications,"In this article we examine the issue of AI assistants, and the way they respond to insults and sexually explicit requests. Public concern over these responses, particularly because AI assistants are usually female-voiced, prompted tech companies to make them more assertive. Researchers have explored whether these female-voiced AI assistants could encourage abusive behavior and reinforce societal sexism. However, the extent and nature of the problem are unclear due to a lack of data on user interactions. By combining psychological and socio-cultural perspectives, we problematize these assumptions and outline a number of research questions for leveraging AI assistants to promote gender inclusivity more effectively.",26248212,AI
10.1007/s44196-025-00848-x,A Novel Human Action Recognition Model by Grad-CAM Visualization with Multi-level Feature Extraction Using Global Average Pooling with Sequence Modeling by Bidirectional Gated Recurrent Units,"Human action recognition is essential in many real-world scenarios, such as video surveillance, human–computer interaction, and behavior analysis. Despite the progress in deep learning, issues such as occlusion, distraction from the background, and motion pattern variability still exist, thus restricting the generalization ability of current models. Most methods are based only on spatial or temporal features and cannot efficiently capture both in one framework, causing lower accuracy in realistic situations. In response to these shortcomings, a multilevel feature extraction approach was proposed by integrating spatial and temporal features to improve the action recognition precision. The method captures RGB frames, optical flow, spatial saliency maps, and temporal saliency maps to enable an overall inspection of video streams. Efficient feature extraction was achieved by applying a pre-trained Inception V3 model and then bidirectional gated recurrent units (Bi-GRUs) to include sequential modeling. An attention mechanism was also included to boost the classification process by focusing on key temporal segments. UCF101 and HMDB51 benchmark datasets evaluated the efficiency of the strategy. The model’s accuracy was 98.13% on UCF101 and 81.45% on HMDB51, which validated the superior discrimination ability of the model in processing heterogeneous human actions. These results confirm that the provided framework is an efficient and discriminative action recognition approach, thus suitable for applications requiring extensive motion analysis and real-time deployment.",18756883,AI
10.3389/feduc.2025.1571711,Persistence patterns among secondary STEM teachers: a comparative study of Noyce scholar cohorts in face-to-face and blended learning environments amid the pandemic,"Noyce scholars were provided funding to compete teaching certification in STEM and earn a master’s degree. Then, they were required to teach for 2 years in a Title I school setting. All cohorts were impacted by the pandemic (e.g., university coursework, student teaching and/or teaching was converted to blended learning). This study highlights the differences in teaching persistence across the three cohorts of scholars (n = 24) regarding continuance in earning their degrees and completing their two-year teaching obligation. Descriptive case study methodology was used in this comparative study across three cohorts. The primary research question explored how different modalities of initial teaching experiences impact early persistence among secondary STEM teachers. The supplemental research question explored scholars’ intention to remain in the teaching profession. Results indicated that the cohort with blended first year teaching experiences had the lowest persistence rate. Generally, scholars intend on persisting in the profession for 6 years or more. Recommendations for practice include the need for more traditional, face-to-face initial teaching experiences and a cohort model for new teachers. Recommendations for research include continued evaluation of Noyce projects, longitudinal studies to track STEM teachers’ persistence, and a comprehensive analysis of teacher preparation programs’ effectiveness in promoting teacher retention.",2504284X,EDUCATION
10.1186/s40594-020-0202-3,Change theory and theory of change: what’s the difference anyway?,"This commentary focuses on the difference between a theory of change and change theory, as it relates to systemic change projects in STEM higher education. A theory of change is project-specific and related to evaluation. It makes the underlying rationale of a project explicit, which supports planning, implementation, and assessment of the project. In addition, a theory of change is often required by funding agencies as part of grant proposals. In contrast, change theories represent theoretical and empirically grounded knowledge about how change occurs that goes beyond any one project. Ideally, a theory of change is informed by change theories. This essay describes the connections between a theory of change and change theory and provides examples of how change theory can inform a project’s theory of change. Grounding projects in change theory allows change agents to draw on existing knowledge and to better contribute to our collective knowledge about how to achieve meaningful change in STEM higher education.",21967822,EDUCATION
10.1186/s40594-019-0200-5,Development and application of the Action Taxonomy for Learning Assistants (ATLAs),"Background: The success of the learning assistant (LA) model has largely been attributed to LA facilitation of active learning tasks. A deeper understanding of how LAs facilitate these tasks would inform LA training and support successful adoption of the LA model. Our investigation of LA actions during their interaction with students in the classroom contributes to that understanding. We present and discuss the development of the action taxonomy for learning assistants (ATLAs), as well as illustrate its applicability by presenting some analyses that were conducted on sample data. Results: The LAs carried out several different actions that we categorized broadly as LA-Directed Facilitation, LA-Guided Facilitation, Advice, Feedback, Course-Related Talk, and Non-Course-Related Talk. LA-Directed Facilitation and LA-Guided Facilitation were the most common types of actions observed. We found that LA actions varied by course. Conclusions: ATLAs is a tool that can be used to examine LA actions. In our sample data set, LAs undertook many different actions during interactions with students which indicates that LAs play several different roles in the classroom. These findings have practical implications not only for faculty seeking to implement a peer instruction model such as the LA model, but also for instructors wanting to utilize LAs in their courses more effectively. Understanding what the LAs are doing during interactions with students can provide us insight into the different roles that LAs undertake. Knowledge of these roles will guide effective training, feedback, and direction of LAs, particularly during the pedagogy course.",21967822,EDUCATION
10.3390/cancers12010244,Resistance to MET/VEGFR2 Inhibition by Cabozantinib Is Mediated by YAP/TBX5-Dependent Induction of FGFR1 in Castration-Resistant Prostate Cancer,"The overall goal of this study was to elucidate the role of FGFR1 induction in acquired resistance to MET and VEGFR2 inhibition by cabozantinib in prostate cancer (PCa) and leverage this understanding to improve therapy outcomes. The response to cabozantinib was examined in mice bearing patient-derived xenografts in which FGFR1 was overexpressed. Using a variety of cell models that reflect different PCa disease states, the mechanism underpinning FGFR1 signaling activation by cabozantinib was investigated. We performed parallel investigations in specimens from cabozantinib-treated patients to confirm our in vitro and in vivo data. FGFR1 overexpression was sufficient to confer resistance to cabozantinib. Our results demonstrate transcriptional activation of FGF/FGFR1 expression in cabozantinib-resistant models. Further analysis of molecular pathways identified a YAP/TBX5-driven mechanism of FGFR1 and FGF overexpression induced by MET inhibition. Importantly, knockdown of YAP and TBX5 led to decreased FGFR1 protein expression and decreased mRNA levels of FGFR1, FGF1, and FGF2. This association was confirmed in a cohort of hormone-naïve patients with PCa receiving androgen deprivation therapy and cabozantinib, further validating our findings. These findings reveal that the molecular basis of resistance to MET inhibition in PCa is FGFR1 activation through a YAP/TBX5-dependent mechanism. YAP and its downstream target TBX5 represent a crucial mediator in acquired resistance to MET inhibitors. Thus, our studies provide insight into the mechanism of acquired resistance and will guide future development of clinical trials with MET inhibitors.",20726694,ONCOLOGY
10.3389/frai.2019.00031,Analysis of Features Selected by a Deep Learning Model for Differential Treatment Selection in Depression,"Background: Deep learning has utility in predicting differential antidepressant treatment response among patients with major depressive disorder, yet there remains a paucity of research describing how to interpret deep learning models in a clinically or etiologically meaningful way. In this paper, we describe methods for analyzing deep learning models of clinical and demographic psychiatric data, using our recent work on a deep learning model of STAR*D and CO-MED remission prediction. Methods: Our deep learning analysis with STAR*D and CO-MED yielded four models that predicted response to the four treatments used across the two datasets. Here, we use classical statistics and simple data representations to improve interpretability of the features output by our deep learning model and provide finer grained understanding of their clinical and etiological significance. Specifically, we use representations derived from our model to yield features predicting both treatment non-response and differential treatment response to four standard antidepressants, and use linear regression and t-tests to address questions about the contribution of trauma, education, and somatic symptoms to our models. Results: Traditional statistics were able to probe the input features of our deep learning models, reproducing results from previous research, while providing novel insights into depression causes and treatments. We found that specific features were predictive of treatment response, and were able to break these down by treatment and non-response categories; that specific trauma indices were differentially predictive of baseline depression severity; that somatic symptoms were significantly different between males and females, and that education and low income proved important psycho-social stressors associated with depression. Conclusion: Traditional statistics can augment interpretation of deep learning models. Such interpretation can lend us new hypotheses about depression and contribute to building causal models of etiology and prognosis. We discuss dataset-specific effects and ideal clinical samples for machine learning analysis aimed at improving tools to assist in optimizing treatment.",26248212,AI
10.3389/fpsyg.2020.00139,Emotion Recognition and Aging. Comparing a Labeling Task With a Categorization Task Using Facial Representations,"Research suggests that aging comes with a decline in the ability to identify emotional expressions. In previous studies on emotion recognition and aging, participants were typically instructed to classify images of facial expressions using sets of lexical emotion labels. Yet, in daily life, when exposed to facial expressions by others, people match these with their conceptual knowledge of how emotions are visually presented (i.e., a smile for “happiness”), rather than recalling lexical labels (i.e., the word “happy”). By comparing performances of young adults and older adults on an emotion sorting task based on visual categorization and a traditional labeling task based on lexical categorization, this research aimed to explore a different way of studying emotion recognition abilities over the lifespan. In line with earlier research, results of the labeling task showed that our older participants (Mage = 71.9) were less accurate in labeling emotions than participants in a young age group (Mage = 23.8), especially for expressions of sadness, fear, anger and contempt. Outcomes of the categorization task suggest that older adults have difficulties separating distinctive meanings of emotions more than young adults do. Results of this study indeed shows a decline in emotion recognition using both tasks, and suggests future studies to examine possible changes in conceptual knowledge of emotions, rather than the inability to perceive certain facial cues.",16641078,PSYCHOLOGY
10.3389/fonc.2020.00121,Improved Prediction of Aqueous Solubility of Novel Compounds by Going Deeper With Deep Learning,"Aqueous solubility is an important physicochemical property of compounds in anti-cancer drug discovery. Artificial intelligence solubility prediction tools have scored impressive performances by employing regression, machine learning, and deep learning methods. The reported performances vary significantly partly because of the different datasets used. Solubility prediction on novel compounds needs to be improved, which may be achieved by going deeper with deep learning. We constructed deeper-net models of ~20-layer modified ResNet convolutional neural network architecture, which were trained and tested with 9,943 compounds encoded by molecular fingerprints. Retrospectively tested by 62 recently-published novel compounds, one deeper-net model outperformed four established tools, shallow-net models, and four human experts. Deeper-net models also outperformed others in predicting the solubility values of a series of novel compounds newly-synthesized for anti-cancer drug discovery. Solubility prediction may be improved by going deeper with deep learning. Our deeper-net models are accessible at",2234943X,ONCOLOGY
10.3390/cancers12020458,"Misregulation of ELK1, AP1, and E12 Transcription Factor Networks Is Associated with Melanoma Progression","Melanoma is among the most malignant cutaneous cancers and when metastasized results in dramatically high mortality. Despite advances in high-throughput gene expression profiling in cancer transcriptomic studies, our understanding of mechanisms driving melanoma progression is still limited. We present here an in-depth bioinformatic analysis of the melanoma RNAseq, chromatin immunoprecipitation (ChIP)seq, and single-cell (sc)RNA seq data to understand cancer progression. Specifically, we have performed a consensus network analysis of RNA-seq data from clinically re-grouped melanoma samples to identify gene co-expression networks that are conserved in early (stage 1) and late (stage 4/invasive) stage melanoma. Overlaying the fold-change information on co-expression networks revealed several coordinately up or down-regulated subnetworks that may play a critical role in melanoma progression. Furthermore, by incorporating histone lysine-27 acetylation information and highly expressed genes identified from the single-cell RNA data from melanoma patient samples, we present a comprehensive list of pathways, putative protein-protein interactions (PPIs) and transcription factor (TF) networks that are driving cancer progression. From this analysis, we have identified Elk1, AP1 and E12 TF networks that coordinately change expression in late melanoma when compared to early melanoma, implicating these TFs in melanoma progression. Additionally, the sumoylation-associated interactome is upregulated in invasive melanoma. Together, this bioinformatic analysis potentially implicates a combination of TF networks and PPIs in melanoma progression, which if confirmed in the experimental systems, could be used as targets for drug intervention in melanoma.",20726694,ONCOLOGY
10.1186/s40359-020-0384-y,Does physiological arousal lead to increased catastrophic misinterpretation? An experiment based on the concept of a fear memory,"Background: While there has been research on catastrophic misinterpretation of ambiguous situations and on the effects of the induction of physiological arousal, there has been no experimental research on the relationship between them. Based on the concept of a fear memory, we aimed to investigate if the induction of physiological arousal leads to catastrophic misinterpretations. Methods: Participants were shown either a suspenseful film clip to induce physiological arousal (EG, n = 43) or a calm film clip with no specific effect on arousal levels (CG, n = 40) before completing a measure of catastrophic misinterpretation (BSIQ-FR). To assess the specific predictive value of physiological arousal, measurements of other known predictors were included (BSI, BDI-II, ACQ, BSQ, STAI-T, ASI-3). Results: The film manipulation led to a significant increase in physiological arousal in the EG but not in the CG. The EG did not report more catastrophic misinterpretations than the CG – however, more participants in the EG reported at least one catastrophic misinterpretation. The increase in physiological arousal due to the film manipulation predicted catastrophic misinterpretation in the open response format in the EG, but not in the CG, even when controlling for other known predictors. Conclusions: Our study provides evidence that experimentally induced physiological arousal can predict catastrophic misinterpretation. The findings support the concept of a fear memory. With the BSIQ-FR, a German questionnaire measuring catastrophic misinterpretation was introduced. Further research on the relationship between physiological arousal and catastrophic misinterpretation with clinical samples is recommended.",20507283,PSYCHOLOGY
10.3390/cancers12040892,Integrated Analysis of RNA-Binding Proteins in Glioma,"RNA-binding proteins (RBPs) play important roles in many cancer types. However, RBPs have not been thoroughly and systematically studied in gliomas. Global analysis of the functional impact of RBPs will provide a better understanding of gliomagenesis and new insights into glioma therapy. In this study, we integrated a list of the human RBPs from six sources—Gerstberger, SONAR, Gene Ontology project, Poly(A) binding protein, CARIC, and XRNAX—which covered 4127 proteins with RNA-binding activity. The RNA sequencing data were downloaded from The Cancer Genome Atlas (TCGA) (n = 699) and Chinese Glioma Genome Atlas (CGGA) (n = 325 + 693). We examined the differentially expressed genes (DEGs) using the R package DESeq2, and constructed a weighted gene co-expression network analysis (WGCNA) of RBPs. Furthermore, survival analysis was also performed based on the univariate and multivariate Cox proportional hazards regression models. In the WGCNA analysis, we identified a key module involved in the overall survival (OS) of glioblastomas. Survival analysis revealed eight RBPs (PTRF, FNDC3B, SLC25A43, ZC3H12A, LRRFIP1, HSP90B1, HSPA5, and BNC2) are significantly associated with the survival of glioblastoma patients. Another 693 patients within the CGGA database were used to validate the findings. Additionally, 3564 RBPs were classified into canonical and non-canonical RBPs depending on the domains that they contain, and non-canonical RBPs account for the majority (72.95%). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that some non-canonical RBPs may have functions in glioma. Finally, we found that the knockdown of non-canonical RBPs, PTRF, or FNDC3B can alone significantly inhibit the proliferation of LN229 and U251 cells. Simultaneously, RNA Immunoprecipitation (RIP) analysis indicated that PTRF may regulate cell growth and death- related pathways to maintain tumor cell growth. In conclusion, our findings presented an integrated view to assess the potential death risks of glioblastoma at a molecular level, based on the expression of RBPs. More importantly, we identified non-canonical RNA-binding proteins PTRF and FNDC3B, showing them to be potential prognostic biomarkers for glioblastoma.",20726694,ONCOLOGY
10.3390/cancers12040896,Detection of Circulating Tumor Cells in the Diagnostic Leukapheresis Product of Non-Small-Cell Lung Cancer Patients Comparing CellSearch® and ISET,"Circulating tumor cells (CTCs) detected by CellSearch are prognostic in non-small-cell lung cancer (NSCLC), but rarely found. CTCs can be extracted from the blood together with mononuclear cell populations by diagnostic leukapheresis (DLA), therefore concentrating them. However, CellSearch can only process limited DLA volumes (≈2 mL). Therefore, we established a protocol to enumerate CTCs in DLA products with Isolation by SizE of Tumor cells (ISET), and compared CTC counts between CellSearch® and ISET. DLA was performed in NSCLC patients who started a new therapy. With an adapted protocol, ISET could process 10 mL of DLA. CellSearch detected CTCs in a volume equaling 2 × 108 leukocytes (mean 2 mL). CTC counts per mL were compared. Furthermore, the live cell protocol of ISET was tested in eight patients. ISET successfully processed all DLA products—16 with the fixed cell protocol and 8 with the live cell protocol. In total, 10–20 mL of DLA was processed. ISET detected CTCs in 88% (14/16), compared to 69% (11/16, p < 0.05) with CellSearch. ISET also detected higher number of CTCs (ISET median CTC/mL = 4, interquartile range [IQR] = 2–6, CellSearch median CTC/mL = 0.9, IQR = 0–1.8, p < 0.01). Cells positive for the epithelial cell adhesion molecule (EpCAM+) per mL were detected in similar counts by both methods. Eight patients were processed with the live cell protocol. All had EpCAM+, CD45−, CD235- cells isolated by fluorescence-activated cell sorting (FACS). Overall, ISET processed larger volumes and detected higher CTC counts compared to CellSearch. EpCAM+ CTCs were detected in comparable rates.",20726694,ONCOLOGY
10.3389/fonc.2020.00383,Resveratrol Sensitizes Colorectal Cancer Cells to Cetuximab by Connexin 43 Upregulation-Induced Akt Inhibition,"Cetuximab is a monoclonal antibody that acts as an anti-epidermal growth factor receptor (EGFR) agent. Cetuximab inhibits the phosphorylation and activation of EGFR and blocks downstream signal pathways of EGF/EGFR, including Ras-Raf-MAPK and PI3K-Akt pathways. Akt activation is an important factor in cetuximab resistance. It has been reported that resveratrol and connexin 43 regulate Akt in different ways based on tissue type. Since connexin 43 interacts with Akt, and resveratrol is known to upregulate connexin 43, we investigated whether resveratrol can sensitize colorectal cancer cells to cetuximab via connexin 43 upregulation. Our work confirmed that resveratrol increases the inhibition of growth by cetuximab in vitro and in vivo, upregulates connexin 43 expression and phosphorylation, increases gap junction function, and inhibits the activation of Akt and NFκB in parental or cetuximab-treated parental HCT116 and CT26 cells. Resveratrol did not exhibit these effects on connexin 43-shRNA transfected cells, so connexin 43 upregulation may contribute to Akt inhibition in these cells. Given these data, resveratrol may sensitize colorectal cancer cells to cetuximab via upregulating connexin 43 to inhibit the Akt pathway.",2234943X,ONCOLOGY
10.3389/feduc.2020.00030,Place-Based Diminished Returns of Parental Educational Attainment on School Performance of Non-Hispanic White Youth,"Background: Youth educational outcomes are a function of a wide range of factors including parental education level. This effect, however, is shown to be smaller for African American, Hispanic, and Asian American youth, a pattern called Marginalization-related Diminished Returns (MDRs). It is, however, unknown if it is race/ethnicity or other conditions associated with race/ethnicity (e.g., poor neighborhood quality) which reduces the marginal returns of parental education for youth. Aim: To explore whether MDRs are only due to race/ethnicity or if they also remain for non-Hispanic Whites in poor neighborhoods, we compared the association between parental education level and adolescents’ school performance based on neighborhood quality in a nationally representative sample of non-Hispanic Whites in the United States. Methods: This cross-sectional study used wave 1 of the Add Health study, an ongoing nationally representative cohort, 1994–2019. Participants included 849 non-Hispanic White adolescents between the ages of 12 and 21 years and their parents. The independent variable was parental education level, which was treated as a continuous measure. Age, grade, gender, and parental marital status were the covariates. The dependent variable was school performance (sum of school grades in Math, English, History, and Science). Linear regression models were used for data analysis. Results: Overall, worse neighborhood quality was associated with worse school performance. Parental education level, however, was not directly associated with youth school performance. We found a statistically significant interaction between parental education level and neighborhood quality suggesting that the strength of the association between parental education and youth school performance weakens as neighborhood quality declines. Conclusion: Parental education level is a more salient determinant of youth educational outcomes in better neighborhoods. The result suggests that MDRs may not be solely due to race/ethnicity but contextual factors that commonly covary with marginalization and poverty. These contextual factors may include segregation, concentration of poverty, and social and physical neighborhood disorder.",2504284X,EDUCATION
10.1186/s40594-020-00212-9,Boundary crossing pedagogy in STEM education,"This commentary aims to discuss an overarching boundary crossing framework under which integrated STEM (Science, Technology, Engineering, Mathematics) pedagogy can be conceptualized. Four potential learning dialogical processes for boundary crossing are presented and used as the main theoretical construct for the discussion. A proposal of an interactive pedagogical framework is put forward accompanied by a provisional statement to relate the connective factors that are critical in the formation of a boundary crossing STEM pedagogy. These factors are situated learning, communities of practices, problem solving, learning dialogical processes, and boundary objects. A Hong Kong school STEM case is employed to illustrate the applicability of this framework. The commentary ends with a reflective remark on boundary crossing STEM pedagogy.",21967822,EDUCATION
10.3389/fonc.2020.00665,Results of Multilevel Containment Measures to Better Protect Lung Cancer Patients From COVID-19: The IEO Model,"A novel coronavirus causing severe acute respiratory syndrome (SARS), named SARS-CoV-2, was identified at the end of 2019. The spread of coronavirus disease 2019 (COVID-19) has progressively expanded from China, involving several countries throughout the world, leading to the classification of the disease as a pandemic by the World Health Organization (WHO). According to published reports, COVID-19 severity and mortality are higher in elderly patients and those with active comorbidities. In particular, lung cancer patients were reported to be at high risk of pulmonary complications related to SARS-CoV2 infection. Therefore, the management of cancer care during the COVID-19 pandemic is a crucial issue, to which national and international oncology organizations have replied with recommendations concerning patients receiving anticancer treatments, delaying follow-up visits and limiting caregiver admission to the hospitals. In this historical moment, medical oncologists are required to consider the possibility to delay active treatment administration based on a case-by-case risk/benefit evaluation. Potential risks associated with COVID-19 infection should be considered, considering tumor histology and natural course, disease setting, clinical conditions, and disease burden, together with the expected benefit, toxicities (e.g., myelosuppression or interstitial lung disease), and response obtained from the planned or ongoing treatment. In this study, we report the results of proactive measures including social media, telemedicine, and telephone triage for screening patients with lung cancer during the COVID-19 outbreak in the European Institute of Oncology (Milan, Italy). Proactive management and containment measures, applied in a structured and daily way, has significantly aided the identification of advance patients with suspected symptoms related to COVID-19, limiting their admission to our cancer center; we have thus been more able to protect other patients from possible contamination and at the same time guarantee to the suspected patients the immediate treatment and evaluation in referral hospitals for COVID-19.",2234943X,ONCOLOGY
10.3389/fonc.2020.00628,Precision Medicine and the Role of Biomarkers of Radiotherapy Response in Breast Cancer,"Radiotherapy remains an important treatment modality in nearly two thirds of all cancers, including the primary curative or palliative treatment of breast cancer. Unfortunately, largely due to tumor heterogeneity, tumor radiotherapy response rates can vary significantly, even between patients diagnosed with the same tumor type. Although in recent years significant technological advances have been made in the way radiation can be precisely delivered to tumors, it is proving more difficult to personalize radiotherapy regimens based on cancer biology. Biomarkers that provide prognostic or predictive information regarding a tumor's intrinsic radiosensitivity or its response to treatment could prove valuable in helping to personalize radiation dosing, enabling clinicians to make decisions between different treatment options whilst avoiding radiation-induced toxicity in patients unlikely to gain therapeutic benefit. Studies have investigated numerous ways in which both patient and tumor radiosensitivities can be assessed. Tumor molecular profiling has been used to develop radiosensitivity gene signatures, while the assessment of specific intracellular or secreted proteins, including circulating tumor cells, exosomes and DNA, has been performed to identify prognostic or predictive biomarkers of radiation response. Finally, the investigation of biomarkers related to radiation-induced toxicity could provide another means by which radiotherapy could become personalized. In this review, we discuss studies that have used these methods to identify or develop prognostic/predictive signatures of radiosensitivity, and how such assays could be used in the future as a means of providing personalized radiotherapy.",2234943X,ONCOLOGY
10.3389/fpsyg.2020.00728,Does the MRI/fMRI Procedure Itself Confound the Results of Meditation Research? An Evaluation of Subjective and Neurophysiological Measures of TM Practitioners in a Simulated MRI Environment,"Early research into meditation, including Transcendental Meditation (TM), relied exclusively on EEG to measure brain activity during meditation practice. Since the advent of neural imaging, MRI, and later fMRI, have dominated this field. Unfortunately, the use of this technology rests on the questionable assumption that lying down in a confining tube while exposed to very loud sounds would not interfere with the meditation practice. The present study was designed to assess the effects of the fMRI procedure on both the subjective and neurophysiological responses of short and long-term TM practitioners. Twenty-three TM practitioners volunteered to participate in this study: 11 short-term meditators, averaging 2.2 years practice, and 12 long-term meditators, averaging 34.8 years. The repeated-measures design included two activities for each participant, eyes-closed rest, and TM practice, in each of three conditions: sitting quietly in an upright position (normal TM practice); lying quietly in a supine position; and lying, with earplugs, inside a simulated fMRI tube (simMRI), while exposed to 110 dB recordings of an actual fMRI machine. Subjective experiences were collected after each activity in each condition. Physiological arousal was recorded using skin conductance levels. Scalp EEG was averaged into eight frequency bands within frontal and parietal leads; eLORETA software was used to explore the 3-D cortical distribution of EEG sources. During the simMRI condition, participants reported having more shallow meditation experiences, and greater agitation/distraction. Skin conductance levels paralleled self-reports, decreasing least during the simMRI condition. Frontal and parietal power decreased from sitting to simMRI in the alpha2 through gamma bands. Parietal power was higher during rest compared to TM in the alpha1 through beta2 bands. Frontal and parietal alpha1 coherence were highest during the simMRI condition. The eLORETA analysis revealed that the default mode network was more active during TM when sitting compared to the simMRI condition. The responses to the supine condition were generally between sitting and simMRI, with some significant exceptions. In conclusion, these data indicate that the fMRI procedure itself (high dB noise; lying down) strongly influences subjective and neurophysiological responses during meditation practice, and may therefore confound the interpretation of results from fMRI studies.",16641078,PSYCHOLOGY
10.3389/fpsyg.2020.00798,Do Customers Pay Attention to Motivations and Switching Costs When They Terminate Their Relationships?,"Research on some key boundary conditions and outcomes of consumers’ relationship termination in the online environment is scare. We examine how four categories (e.g., upkeep, time, benefits, and personal loss) of avoiding relationships affect customers’ relationship termination. We also consider both the motivation (hedonic vs. utilitarian) and switching costs when customers evaluate whether to exit from or stay in a relationship. Results show that time plays a significant role in customers’ relationship termination, but there appears to be an increase or decrease in customers’ relationship termination associated with the role of two moderators. More specifically, upkeep plays a significant role in affecting relationship termination for consumers motivated by hedonic interests (as opposed to those motivated by utilitarian interests). Meanwhile, personal loss plays a role in affecting relationship termination for utilitarian consumers (and not hedonic). Furthermore, we found that high switching costs facilitate a relationship termination if time and personal loss are involved. The findings indicate that the effect of high switching costs on customer loyalty is limited. We also found that when consumers consider time category, they are likely to have a greater intent to terminate a relationship regardless of the level of switching costs.",16641078,PSYCHOLOGY
10.1186/s40594-020-00218-3,Finding time for computer science in the elementary school day: a quasi-experimental study of a transdisciplinary problem-based learning approach,"Background: As the number of computer science (CS) jobs become increasingly available in this country and computing skills become essential tools for managing all aspects of our personal lives, CS is quickly becoming an essential element of K-12 education and recently, there has been increased attention to bringing computer science to the elementary grades. However, with a schedule that emphasizes literacy and mathematics, and other subjects competing for instructional time, creating opportunities for CS in the elementary school day is challenging. This study aimed to address this problem by investigating the use of problem-based transdisciplinary modules (i.e., “Time4CS” modules) that combined English language arts (ELA), science, and social studies lessons with theCode.org“Fundamentals” CS education program.Results: Results indicated that teachers who taught Time4CS modules completed more CS lessons than teachers who did not teach the modules. Further, across all classrooms, completing a higher percentage of non-grade level assignedCode.orgFundamentals lessons (i.e.,Code.orglessons above or below grade level that were available to teachers, but not required for their particular grade level) was positively associated with students’ achievement outcomes on state ELA and mathematics tests. Additionally, higher amounts of interdisciplinary teaching practices were associated with higher student achievement, specifically students’ state assessment ELA scores.Conclusions: This study demonstrated that transdisciplinary problem-based modules that integrate the teaching of CS with other subject areas are a feasible way to bring more CS opportunities to younger learners. Moreover, it showed that implementing such modules is linked to more positive student academic achievement outcomes. With attentive revision, the modules featured in this study may be useful tools for elementary schools. These findings have implications for researchers, school district administrators, and those individuals who are in-charge of public policy initiatives seeking ways to bring CS to all elementary school students. Specifically, they highlight that it is possible to make time in the elementary school day for CS, and that there are no negative consequences for core subjects (e.g., ELA and mathematics).",21967822,EDUCATION
10.1186/s40594-020-00221-8,Faculty persistence with research-based instructional strategies: a case study of participation in a faculty online learning community,"Background: Incorporating research-based instructional strategies (RBISs) into college classrooms is essential for improving learning outcomes. However, the rate of implementation of new strategies is quite low. The development and dissemination model of introducing faculty to new strategies has shown to be inadequate in encouraging uptake and consistent use of those strategies. This model lacks the ongoing support that has shown to be exceedingly important in the adoption and persistent use of new strategies. In addition, this model ignores the necessity of adaptation of RBISs due to differences in teaching situations including availability of particular resources or different student populations. Faculty online learning communities (FOLCs) are online collaborative faculty groups that provide continued support in order to fill this gap. This case study explores one FOLC member’s adoption of a research-based physical science curriculum as they reflect on their teaching experiences. We operationalize Rodgers’ cycle of reflection to make sense of these changes. Specifically, the study aims to understand how the focal faculty member’s participation in reflection in the context of the FOLC changes over time. Results: Analysis via Rodgers’ reflection framework revealed changes in the way Leslie participated in reflection within the context of the FOLC. The faculty participant optimized her teaching practice through iterative cycles of reflection with the FOLC cluster. As a result, she became more satisfied with the curriculum and her implementation over time. Conclusions: Faculty encounter challenges when adopting RBISs that must be addressed in real time. Reflection accompanied by ongoing community support via the Next Gen PET FOLC can provide support for changes in practice and increase faculty satisfaction with RBISs. The results contribute to evidence that community building and ongoing support in implementing new curricula is integral to the adaptation process, and FOLCs can provide that support to sustain long-term change.",21967822,EDUCATION
10.1186/s40594-020-00220-9,Development of the student course cognitive engagement instrument (SCCEI) for college engineering courses,"Background: Evidence shows that students who are actively engaged with learning materials demonstrate greater learning gains than those who are passively engaged. Indeed, cognitive engagement is often cited as a critical component of an educational experience. However, understanding how and in what ways cognitive engagement occurs remains a challenge for engineering educators. In particular, there exists a need to measure and evaluate engagement in ways that provide information for instructors to deploy concrete, actionable steps to foster students’ cognitive engagement. The present study reports the development and gathering of validation evidence for a quantitative instrument to measure students’ in-class cognitive engagement. The instrument was informed by Wylie and Chi’s ICAP (Interactive Constructive Active Passive) model of active learning, as well as contextual concerns within engineering courses. Results: The process followed the classical measurement model of scale development. We provide a detailed overview of the item development and scale validation processes, focusing on the creation of individual subscales to measure different modes of cognition within learning contexts. Multiple rounds of testing the student course cognitive engagement instrument (SCCEI) in college engineering courses provided evidence of validity. This indicated the reliable measurement of student cognitive engagement in the context of notetaking, processing material, and interacting with peers in the classroom. Results suggest differentiating modes of cognitive engagement is indeed applicable when considering students’ in-class notetaking and processing of material. Conclusions: Findings point towards the need for additional engagement scales that expand the instrument’s ability to distinguish between particular activities within a mode of engagement as defined by ICAP. The present study contributes to the growing body of literature on cognitive engagement of engineering students. Results address the development of measurement tools with evidence of validity for use in STEM education.",21967822,EDUCATION
10.1186/s40359-020-00421-5,Social media use disorder and loneliness: any association between the two? Results of a cross-sectional study among Lebanese adults,"Background: In Lebanon, it is already established that mental disorders are prevalent among the population. Lebanese people are active users of social media platforms. To date, no study has previously explored the relationship between mental health and social media use disorder in Lebanon. The present study aims to learn more about the link between social media use disorder and loneliness among Lebanese people. Methods: This cross-sectional study was carried out between January and December 2018. It enrolled 456 residents of the community randomly selected from Lebanon’s governorates in a proportionate rate. Results: The results showed that 107 (23.7%) participants were classified as having social media use disorder. The results of a stepwise linear regression, taking the loneliness score as the dependent variable, showed that female gender compared to males (Beta = 0.42), having a secondary level of education compared to illiteracy (Beta = 0.65), higher social media use disorder (Beta = 0.03) and higher insomnia (Beta = 0.02) and alexithymia (Beta = 0.02) were significantly associated with higher loneliness. Conclusion: The present study was able to contribute to the literature and showed the association between social media use disorder and loneliness. These findings can benefit psychologists and public health practitioners in their future prevention and intervention plans.",20507283,PSYCHOLOGY
10.3389/fonc.2020.549220,Survival Outcomes and Prognostic Analysis Following Greater Cytoreductive Radiotherapy in Patients With Metastatic Prostate Cancer,"Purpose: To assess the survival outcomes of patients with metastatic prostate cancer (mPCa) who undergo greater cytoreductive radiotherapy in a real-world clinical practice and determine their prognostic factors. Methods: We performed a retrospective study of 160 patients with mPCa who underwent cytoreductive radiotherapy between 2009 and 2018 at a single institution. The degree of the cytoreductive burden was calculated for each patient. Overall survival (OS) was calculated from the date of detection of metastases. Variables associated with prostate-specific antigen (PSA) response and OS were evaluated via univariate and multivariate analyses. Results: The median follow-up period was 47.2 months. The median OS was 42.3 months with a 5-year OS rate of 37.9%. The PSA levels of 90 patients (56.7%) decline by > 50% after radiotherapy. The 5-year OS rates of patients who underwent total, major, and minor cytoreductive radiotherapy were 53.4, 38.2, 17.6%, respectively; the corresponding median OS intervals were 62.5, 41.0, and 24.4 months, respectively (P < 0.001). A greater extent of cytoreduction (P < 0.05), lower PSA at radiotherapy initiation [hazard ratio 0.51, 95% confidence interval [CI] 0.33–0.78; P = 0.002] and better PSA response [hazard ratio 0.47, 95% CI 0.30–0.72; P < 0.001] were independent factors associated with superior OS. A high metastatic burden (as defined in the CHAARTED trial) was the only independent predictor of a poorer PSA response (odds ratio 0.36, 95% CI 0.19–0.69; P = 0.002). Grade 2 late gastrointestinal and genitourinary toxicities were observed in 3 and 2 patients, respectively, and only 1 patient had grade 3 late gastrointestinal toxicity. Conclusion: Cytoreductive radiotherapy is effective and safe in select patients with mPCa. Greater cytoreduction, together with lower PSA at radiotherapy initiation and improved PSA response are favorable prognostic factors. Further studies are needed to confirm our findings.",2234943X,ONCOLOGY
10.3389/feduc.2020.00146,OER4Schools: Outcomes of a Sustained Professional Development Intervention in Sub-Saharan Africa,"Sustaining educational initiatives beyond short-term pilot projects is highly challenging in low-income countries. We describe the outcomes and implications of our iterative Design-Based Implementation Research conducted in Zambia. This focused on a unique, school-based, peer-facilitated professional learning programme for primary teachers: OER4Schools integrates interactive pedagogy, open digital educational resources and mobile learning. Teacher interviews carried out 18 months after a year-long intervention showed that the programme became self-sustaining; earlier participants reported further development of their interactive teaching strategies and awareness of pupil progress; recent joiners developed similarly. Roles of teachers and pupils changed and a new classroom culture emerged. The study identifies the key mechanisms involved in sustainability, including culturally sensitive and participatory development and implementation, semi-structured multimedia materials, and supportive organisational structures for sustained professional learning. Our findings are hence framed by sociocultural influences as well as the wider policy context.",2504284X,EDUCATION
10.3389/fonc.2020.562189,Inhibitory Effect of a Microecological Preparation on Azoxymethane/Dextran Sodium Sulfate-Induced Inflammatory Colorectal Cancer in Mice,"This study aims to investigate the antitumor effect and the possible mechanism of a microecological preparation (JK5G) in mice. The mice treated with AOM/DSS were then randomly divided into the two model groups and the JK5G group, and the blank control group was included. Fecal samples were used for liquid chromatography–mass spectrometry and 16S rRNA gene sequencing analyses to reveal metabolic perturbations and gut flora disorders to demonstrate the effects of JK5G. Compared with the mice in the control group, the weight and food intake of mice after JK5G treatment were both upregulated. Moreover, JK5G could inhibit the growth of colon tumors and prolong the survival rate of mice, as well as inhibit the levels of cytokines in serum. The proportions of lymphocytes, T cells, CD3+CD4+ T cells, and CD3+CD8+ T cells in the spleen of the JK5G mice were all significantly increased compared to those in the control group (p < 0.05). Similarly, compared with the model group, the proportions of lymphocytes, B cells, T cells, natural killer T cells, CD3+CD4+ T cells, and CD3+CD8+ T cells in the intestinal tumors of the JK5G mice were significantly increased (p < 0.05). Furthermore, 16S rRNA high-throughput sequencing data revealed that Alloprevotella in the JK5G group was significantly upregulated, and Ruminiclostridium, Prevotellaceae_UCG_001, and Acetitomaculum were significantly downregulated. Fecal and serum metabolite analysis detected 939 metabolites, such as sildenafil and pyridoxamine, as well as 20 metabolites, including N-Palmitoyl tyrosine and dihydroergotamine, which were differentially expressed between the JK5G and model groups. Integrated analysis of 16s rRNA and metabolomics data showed that there were 19 functional relationship pairs, including 8 altered microbiota, such as Ruminiclostridium and Prevotellaceae_UCG_001, and 16 disturbed metabolites between the JK5G and model groups. This study revealed that JK5G treatment was involved in the growth of colorectal cancer, which may be associated with the role of JK5G in improving the nutritional status of mice and regulating the tumor microenvironment by regulating the changes of intestinal microbiota and metabolite bands on different pathways.",2234943X,ONCOLOGY
10.3389/fpsyg.2020.02180,"Prejudice, Does It Exist or Not? Consumer Price Discrimination in Minority Entrepreneurship","Many prior studies on minority entrepreneurship have found that some consumers display a strong bias against products from minority ventures. Not surprisingly, discrimination against products sold by minority-owned businesses increases the failure rate for such ventures. This paper seeks to verify the extent of consumer discrimination for minority products, and investigates whether it varies among different products. Building on insights from the theory of consumer discrimination, we conducted a comparative behavior experiment on 155 subjects for the expected pricing of two new products (common products and products with ethnic characteristics). Consistent with prior literature, we found that potential consumers held a bias against common products from minority ventures and offered a lower price. However, the theory of consumer discrimination could not be applied to the products with ethnic characteristics. Instead, potential consumers viewed ethnic characteristics products from minority ventures as being high quality and offered higher prices. This finding complements the theory of consumer discrimination and provides useful knowledge for minority entrepreneurs: minority entrepreneurs can employ price discrimination to strengthen the ethnic brand’s impression by integrating ethnic cultural features into new products.",16641078,PSYCHOLOGY
10.1186/s40594-020-00252-1,Gender gaps in the performance of Norwegian biology students: the roles of test anxiety and science confidence,"Background: Understanding student motivational factors such as test anxiety and science confidence is important for increasing retention in science, technology, engineering, and math (STEM), especially for underrepresented students, such as women. We investigated motivational metrics in over 400 introductory biology students in Norway, a country lauded for its gender equality. Specifically, we measured test anxiety and science confidence and combined students’ survey responses with their performance in the class. Results: We found that female students expressed more test anxiety than did their male counterparts, and the anxiety they experienced negatively predicted their performance in class. By contrast, the anxiety male students experienced did not predict their performance. Conversely, men had higher confidence than women, and confidence interacted with gender, so that the difference between its impact on men’s and women’s performance was marginally significant. Conclusions: Our findings have implications for STEM instructors, in Norway and beyond: specifically, to counter gender-based performance gaps in STEM courses, minimize the effects of test anxiety.",21967822,EDUCATION
10.3389/frai.2020.509354,Deep Active Inference and Scene Construction,"Adaptive agents must act in intrinsically uncertain environments with complex latent structure. Here, we elaborate a model of visual foraging—in a hierarchical context—wherein agents infer a higher-order visual pattern (a “scene”) by sequentially sampling ambiguous cues. Inspired by previous models of scene construction—that cast perception and action as consequences of approximate Bayesian inference—we use active inference to simulate decisions of agents categorizing a scene in a hierarchically-structured setting. Under active inference, agents develop probabilistic beliefs about their environment, while actively sampling it to maximize the evidence for their internal generative model. This approximate evidence maximization (i.e., self-evidencing) comprises drives to both maximize rewards and resolve uncertainty about hidden states. This is realized via minimization of a free energy functional of posterior beliefs about both the world as well as the actions used to sample or perturb it, corresponding to perception and action, respectively. We show that active inference, in the context of hierarchical scene construction, gives rise to many empirical evidence accumulation phenomena, such as noise-sensitive reaction times and epistemic saccades. We explain these behaviors in terms of the principled drives that constitute the expected free energy, the key quantity for evaluating policies under active inference. In addition, we report novel behaviors exhibited by these active inference agents that furnish new predictions for research on evidence accumulation and perceptual decision-making. We discuss the implications of this hierarchical active inference scheme for tasks that require planned sequences of information-gathering actions to infer compositional latent structure (such as visual scene construction and sentence comprehension). This work sets the stage for future experiments to investigate active inference in relation to other formulations of evidence accumulation (e.g., drift-diffusion models) in tasks that require planning in uncertain environments with higher-order structure.",26248212,AI
10.1007/s00432-020-03432-2,Experimental and clinical studies on radiation and curcumin in human glioma,"Purpose: There is progressing evidence for the anti-cancer potential of the natural compound and dietary spice curcumin. Curcumin has been ascribed to be cytotoxic for various tumour cell types, to inhibit cell proliferation and to interfere with the cellular oxidant status. The compound has been notified as a therapeutic agent with radiosensitizing potential in brain tumour therapy. We considered the rationale to combine curcumin with radiation in the treatment of human glioblastoma multiforme (GBM). Method: Determination of clonogenic cell survival following exposure of U251 human glioma cells to single dose (1–6 Gy) and fractionated irradiation (5 daily fractions of 2 Gy) without and with curcumin. Additional literature search focused on the interaction between curcumin and radiotherapy in experimental and clinical studies on human glioma. Results: No interaction was found on the survival of U251 human glioma cells after irradiation in combination with curcumin at clinically achievable concentrations. Experimental in vitro and in vivo data together with clinical bioavailability data from the literature do not give evidence for a radiosensitizing effect of curcumin. Reported GBM intratumoural curcumin concentrations are too low to either exert an own cytotoxic effect or to synergistically interact with radiation. Novel approaches are being explored to increase the bioavailability of curcumin and to facilitate transport over the blood–brain barrier, aimed to reach therapeutic curcumin levels at the tumour site. Conclusion: There is neither a biological nor clinical rationale for using curcumin as radiosensitizer in the therapy of GBM patients.",14321335,ONCOLOGY
10.3389/fpsyg.2020.566684,Unbiased Decisions Among Women’s Basketball Referees,"Decisions often reflect implicit biases. Ethnic, racial, and gender traits are associated with stereotypes that may influence the decision-making process. Previous research shows that referees’ decisions in men’s professional sports are often biased in favor of racial and nationalistic in-groups. This study examined if similar biases exist in women’s professional sports. Additionally, this study analyzed the potential influence of the gender composition of referee teams on rapid decisions. We gathered data on referee foul calls in women’s professional basketball in Spain, 2014–2019 and defined important decisions (fifth fouls) and stressful situations (one-possession matches). The main finding is that out-groups based on racial (i.e., Black players) and nationalistic (i.e., foreign players) criteria did not differ in number of foul calls received. In stressful situations, foreign players actually received fewer fouls than Spanish players. Similarly, there was no evidence of bias due to the gender composition of referee teams: foul calls did not differ between all-male and mixed teams. Implications for race and nationality as dynamic social constructs within ethnocentric and social identity theories are discussed.",16641078,PSYCHOLOGY
10.1186/s40594-020-00253-0,Variation in which key motivational and academic resources relate to academic performance disparities across introductory college courses,"Background: Differences in post-secondary academic outcomes along dimensions of gender, race/ethnicity, and socioeconomic status are a major concern. Few studies have considered differences in patterns of academic outcomes and underlying mechanisms driving disparities across different STEM disciplines. Using data from about 4000 undergraduates in introductory STEM courses at a large, urban university in the eastern United States, this study examines how differences in course grades by gender, race/ethnicity, and parent education vary in introductory chemistry, physics, and psychology courses. In addition, structural equation modeling techniques examine whether academic resources and discipline-specific motivational attitudes are important mediators of demographic differences in course grades.Results: This study finds that women have higher course grades than men on average in psychology, and men have marginally higher grades than women in physics. In addition, students whose race/ethnicity is represented or overrepresented in these courses (students who are White and or Asian) have higher course grades in chemistry and physics and marginally higher grades in psychology on average compared with underrepresented students (who are Black, Latinx, Native American, Pacific Islander, and or other racial/ethnic backgrounds). Further, first-generation college students have lower course grades in physics and psychology on average than students with a college-educated parent. The largest average differences in course performance are about half a full letter grade (e.g., the difference between a B and an A−). This study also finds that some demographic differences in physics and chemistry performance are linked to math resources whereas some disparities in psychology are more related to verbal resources. In addition, the results suggest discipline-specific self-efficacy is a motivational attitude associated with course performance in chemistry, physics, and psychology, while discipline-specific interest is only relevant in chemistry.Conclusions: Overall, the findings emphasize that there are demographic differences in post-secondary course performance on average, and academic resources and motivational attitudes help explain these differences. Importantly, the specific findings differ across chemistry, physics, and psychology. Understanding these pathways and how they are similar and different across disciplines within STEM is crucial for developing interventions aimed at attenuating disparities in post-secondary academic outcomes.",21967822,EDUCATION
10.3389/fpsyg.2020.570216,Psychological Pathways Linking Public Trust During the Coronavirus Pandemic to Mental and Physical Well-being,"The well-being of the public during the 2019 coronavirus (COVID-19) pandemic is deeply rooted in institutional trust in the government’s risk communication effort. The objective of this study was to examine the psychological pathway through which public trust in the government is associated with mental and physical well-being. We collected cross-sectional data from 501 participants aged ≥18 years using an online panel. Public trust in the government was assessed as our exposure variable. We screened for psychological distress by combining the Patient Health Questionnaire and the General Anxiety Disorder scale. Physical well-being was examined using self-rated health. We further assessed the roles of risk perceptions. The author conducted a one-way analysis of variance (ANOVA), Pearson’s correlations, multivariable regressions, and mediation analyses (using the Preachers and Hayes’ approach). Participants were 55.29% female, 67.86% Caucasian/white with a mean age of 32.44 ± 11.94 years. Public trust in the government regarding COVID-19 was negatively correlated with psychological distress (r = −0.20; p < 0.001) and positively associated with physical well-being (r = 0.13; p < 0.001). After adjusting for sociodemographic and socioeconomic factors, public trust remained negatively associated with psychological distress (β = −0.19; 95% confidence intervals, [CI] −0.30, −0.09) and positively associated with physical well-being (β = 0.26; 95% CI [0.16, −0.37]). Perceived self-efficacy to practice COVID-19 protective behavior partially mediated the relationship between public trust and psychological distress (13.07%); and physical well-being (28.02%). Perceived self-efficacy to protect self against COVID-19 infection can serve as a psychological pathway through which public trust may be associated with mental and physical health.",16641078,PSYCHOLOGY
10.3389/frai.2020.544972,AI for Improving Children’s Health: A Community Case Study,"The Indian health care system lacks the infrastructure to meet the health care demands of the country. Physician and nurse availability is 30 and 50% below WHO recommendations, respectively, and has led to a steep imbalance between the demand for health care and the infrastructure available to support it. Among other concerns, India still struggles with challenges like undernutrition, with 38% of children under the age of five being underweight. Despite these challenges, technological advancements, mobile phone ubiquity and rising patient awareness offers a huge opportunity for artificial intelligence to enable efficient healthcare delivery, by improved targeting of constrained resources. The Saathealth mobile app provides low-middle income parents of young children nflwith interactive children’s health, nutrition and development content in the form of an entertaining video series, a gamified quiz journey and targeted notifications. The app iteratively evolves the user journey based on dynamic data and predictive algorithms, empowering a shift from reactive to proactive care. Saathealth users have registered over 500,000 sessions and over 200 million seconds on-app engagement over a year, comparing favorably with engagement on other digital health interventions in underserved communities. We have used valuable app analytics data and insights from our 45,000 users to build scalable, predictive models that were validated for specific use cases. Using the Random Forest model with heterogeneous data allowed us to predict user churn with a 93% accuracy. Predicting user lifetimes on the mobile app for preliminary insights gave us an RMSE of 25.09 days and an R2 value of 0.91, reflecting closely correlated predictions. These predictive algorithms allow us to incentivize users with optimized offers and omni-channel nudges, to increase engagement with content as well as other targeted online and offline behaviors. The algorithms also optimize the effectiveness of our intervention by augmenting personalized experiences and directing limited health resources toward populations that are most resistant to digital first interventions. These and similar AI powered algorithms will allow us to lengthen and deepen the lifetime relationship with our health consumers, making more of them effective, proactive participants in improving children’s health, nutrition and early cognitive development.",26248212,AI
10.3389/fpsyg.2020.621065,University Students’ Motives-for-Physical-Activity Profiles: Why They Practise and What They Get in Terms of Psychological Need Satisfaction,"Physical activity (PA) is an important habit for overall health and quality of life, but it tends to recede as young adults transition from high school into university. The present study sought to understand, in the case of university students that still practice PA, their motives for PA and their relationships with psychological need satisfaction (PNS) and characteristics of practice regularity (frequency, duration, team, competitive, coach, league, federation, and type of day of the week for PA). Participants were 423 university students who reported to practice PA (203 identified as men, 191 as women, 29 did not report gender), with ages ranging from 18 to 30 years old (M = 19.91, SD = 1.97). Measures assessing motives for PA, PNS, and PA characteristics were completed. Hierarchical, followed by iterative, cluster analysis was used and four naturally occurring groupings of university students were identified based on their motives for PA: one extrinsic-motives cluster (with both extrinsic motives—fitness and appearance—above the mean), one all-motives cluster (with all five motives above the mean), one intrinsic-motives cluster (with all three intrinsic motives—enjoyment, competence, social—above the mean), and one low-motives cluster (with all motives below the mean). Groupings were compared in terms of the characteristics of their practice regularity (frequency, duration, competition, team, coach, league, federation, type of day of the week used for PA) and their levels of PNS (of the needs for autonomy, competence, and relatedness in PA). Significant between-group differences were observed in the duration of single principal PA sessions, minutes per week practicing main PA, total PA minutes per week, and type of day of the week used for PA. The number of days per week devoted to the principal PA and the number of total PAs practiced were similar across all four clusters. With regard to between-group differences in psychological need satisfaction in PA by cluster, these analyses showed the existence of four clearly distinguishable naturally occurring groupings based on motives for PA, which gives researchers and practitioners the possibility to analyze and implement tailored interventions aimed at promoting PA among university students.",16641078,PSYCHOLOGY
10.3389/fpsyg.2021.610817,The Effects of Viewing Cute Pictures on Performance During a Basketball Free-Throw Task,"Previous studies have shown that viewing cute pictures leads to performance improvement in a subsequent fine motor task. We examined the beneficial effects of viewing cute pictures in a more complex sporting skill (i.e., basketball free throws) by comparing three conditions (viewing baby animal pictures, adult animal pictures, and no pictures) and two tests (no-pressure and pressure). The participants, all of whom were college basketball players, performed 16 free throws in each condition. In the no-pressure test, male participants improved performance after viewing pictures of baby animals but not after adult animals and no pictures. In the pressure test, no significant improvement was observed. For female participants, the cuteness-viewing effect was not observed in both tests. The results suggest that viewing cute pictures may improve performance during basketball free throws in a low-pressure situation by narrowing the breadth of attentional focus and inducing approach motivation and caregiving behaviors.",16641078,PSYCHOLOGY
10.3389/frai.2021.654154,Dissemination Dynamics of Receding Words: A Diachronic Case Study of Whom,"We explore the relationship between word dissemination and frequency change for a rapidly receding feature, the relativizer whom. The success of newly emerging words has been shown to correlate with high dissemination scores. However, the reverse—a correlation of lower dissemination scores with receding features—has not been investigated. Based on two established and two newly developed measures of word dissemination—across texts, linguistic environments, registers, and topics—we show that a general correlation between dissemination and frequency does not obtain in the case of whom. Different dissemination measures diverge from each other and show internally variable developments. These can, however, be explained with reference to the specific sociolinguistic history of whom over the past 300 years. Our findings suggest that the relationship between dissemination and word success is not static, but needs to be contextualized against different stages in individual words’ life-cycles. Our study demonstrates the applicability of large-scale, quantitative measures to qualitatively informed sociolinguistic research.",26248212,AI
10.1007/s44196-023-00263-0,Thermal Error Modeling of Numerical Control Machine Based on Beetle Antennae Search Back-propagation Neural Networks,"Thermal errors are one key impact factor on the processing accuracy of numerical control machine. This study targeted at a certain vertical processing center presents a new algorithm for predictive modeling of thermal errors in numerical control machine. This algorithm is founded on back-propagation neural networks (BPNNs) and adopts beetle antennae search (BAS) to find the best weights and thresholds of BPNNs. It avoids the local minimization due to local extremums faced by traditional BPNNs. The intermingling rate and arithmetic computation efficiency of neural network algorithms are further improved. Then, a BAS-BP thermal error prediction model is built with the machine temperature changes and thermal errors as the input data. Compared with conventional BPNNs, the BPNN after particle swarm optimization suggests the convergence rate of BAS-BP is improved by 85%, the leftover mistakes between the genuine information and the anticipated information are under 1 um, and the overall prediction precision is above 90%. Thus, the new model has high precision, high anti-disturbance ability and strong robustness.",18756883,AI
10.3390/educsci13050530,Digital Literacy and Digital Self-Efficacy of Australian Technology Teachers,"Agriculture is being increasingly transformed into a technological industry and calls for a greater need for digitally literate employees. To ensure school students are best placed for this requirement, the development of teacher digital literacy, self-efficacy, and the awareness of agricultural technology is essential. The current study explores the digital literacy and self-efficacy of Australian Technology Mandatory teachers who were participants in a one-day workshop (n = 185). The workshop introduced participants to the GPS Cows module, a complete teaching resource specifically designed to cover agricultural aspects of the Technology Mandatory syllabus. Data were collected by way of classroom ‘clickers’ during the workshop and by a post-workshop survey. Teachers were found to have reasonable basic digital literacy but lacked the confidence to conduct more detailed analytics. There was also some evidence that a teacher’s own digital literacy may also impact their perception of their students’ skills. Professional development workshops, such as the GPS Cows workshop, can improve teacher digital literacy and self-efficacy through hands-on learning in a collaborative, team environment.",22277102,EDUCATION
10.1007/s00432-023-04941-6,Nodal frozen section + elective neck dissection as an alternative to sentinel lymph node biopsy for the management of cT1-2N0 oral squamous cell carcinoma patients: a viability and accuracy study,"Purpose: Oral Squamous Cell Carcinoma (OSCC) is characterized by a high aggressiveness and a tendency to metastasize. The management of the neck in cT1-2N0 patients c follows three strategies: watchful waiting, elective neck dissection (END) or sentinel lymph node biopsy (SLNB). The aim was to assess the viability of intraoperative frozen sections of the nodes of cT1-2N0 to spot occult metastases as an alternative to SLNB, performing a modified radical neck dissection (MRND) in intraoperatively positive patients. Methods: The patients were treated at the Maxillo-Facial Surgery Unit of Policlinico San Marco of Catania between 2020 and 2022. END was performed in all patients, including frozen section examination of at least one clinically suspicious node per level. In case of positivity after frozen section examination, neck dissection was extended to levels IV and V. Results: All frozen sections were compared with a definitive test after paraffin inclusion. During surgery, 70 END were performed, and 210 nodes were analyzed with frozen sections. Among the 70 END, 52 were negative after frozen Sects. (156 negative nodes), and surgery was ended. Five of the 52 negative ENDs resulted in pN + after paraffin inclusion (9.6%), which underwent postoperative adjuvant treatment. The sensibility of our END + frozen section method was 75%, while the specificity of our test was 94%. The negative predictive value was 90,4%. Conclusions: Elective neck dissection + intraoperative frozen section could be an alternative to SLNB to spot occult nodal metastases in cT1-2N0 OSCC due to the opportunity to perform a one-step diagnostic/therapeutic procedure.",14321335,ONCOLOGY
10.1007/s00432-023-04936-3,Should I call psycho-oncology? Training nurses on psycho-oncological screening reduces uncertainties,"Purpose: Psycho-oncological screening is required to identify distressed patients and direct them to psycho-oncological care. In practice, screening procedure and related communication are still insufficient due to various barriers on the side of the medical team. The aim of this study is to evaluate the specifically developed training (OptiScreen training) on screening from nurses’ perspective. Methods: N = 72 nurses from visceral–oncological care at Hanover Medical School received the 6-h training, which consisted of three modules and targeted topics around screening, psycho-oncology and communication. The training was evaluated using a pre- and post-questionnaire assessing screening knowledge, uncertainties and further satisfaction outcomes. Results: Personal uncertainties were significantly reduced by the training (t(63) = − 13.32, p < .001, d = 1.67). General satisfaction with the training was achieved (62.0–98.6% satisfied with the training elements). Feasibility (69%) and general acceptance (94.3%) for the training were rated positively. Conclusion: The nurses rated the training as useful to reduce personal uncertainties regarding the screening process. Acceptability, feasibility and satisfaction with the training from the nursing perspective were achieved. The training contributes to minimizing barriers to inform about psycho-oncology and to recommend appropriate support services to patients.",14321335,ONCOLOGY
10.3390/educsci13070648,"Constructing a Novel E-Learning Course, Educational Computational Chemistry through Instructional Design Approach in the TPASK Framework","The educational scenario after the COVID-19 confinement presents new challenges for teachers. Technological advances require teachers to be prepared for instruction through technology, and with this, the need for e-learning courses arose to strengthen this knowledge. This article aims to describe an innovative e-learning course in Educational Computational Chemistry (ECC) for in-service chemistry teachers through an Instructional Design (ID) that allows the development of the constructs associated with the Technological Pedagogical Science Knowledge (TPASK) framework. From the literature overview, relevant findings were raised concerning ID and its potential technological support. The results indicate that an effective ID must present general elements, such as the organisation and generation of content, progress monitoring, and feedback instances. However, the stages of engagement, flexibility, and positioning are relevant elements. These design elements are linked to emerging technological tools, such as artificial intelligence for generating audiovisual material, interactive content development, and event logs. In addition, positive results are evident from the teachers who participated in the ECC e-learning course, who project the knowledge, computer skills, and learning acquired into their professional work as chemistry teachers. Based on the above, a course design for ECC is proposed with general guidelines that contribute to the continuous training of in-service chemistry teachers.",22277102,EDUCATION
10.1186/s40594-023-00439-2,Exploring senior engineering students’ engineering identity: the impact of practice-oriented learning experiences,"Background: Engineering identity reflects students' acceptance and recognition of engineering, which has a great influence on their willingness to enter and stay in the engineering field. Existing studies have shown that curricular and co-curricular practice-oriented experiences may be helpful for developing students’ engineering identity. However, the actual impact of various practice-oriented learning experiences remained to be further examined. This quantitative study aims to explore the impact of three types of practice-oriented learning experiences (capstone experiences, technological innovation and entrepreneurship competitions, and engineering-related internships) in the development of engineering talents' engineering identity. A theoretical framework of engineering identity, which consists of three dimensions, that is, Interest, Performance/Competence and Recognition, was adopted to guide the research. Results: Through responses from 160 senior engineering students at a leading research intensive Chinese university, the study explored the relationships between engagement in practice-oriented learning experiences and engineering identity. Senior capstone design was found to be associated positively with students' development of engineering identity and recognition by others. Participating in two or more technological innovation and entrepreneurship competitions associated positively with students' development of engineering identity, performance/competence and recognition. Meanwhile, internships did not show any statistically significant effect on engineering identity. Moreover, by analyzing the potential mediating effect, we found that recognition played a complete intermediary role between senior capstone design and engineering identity. In addition, recognition and performance/competence mediated the relationship between twice or more technological innovation and entrepreneurship competitions and engineering identity. Conclusions: These findings add to our current understanding about the role of different practice-oriented learning activities on students’ development of engineering identity. These findings point to the importance of learning activities, including technological innovation and entrepreneurship competitions and senior capstone design, on the development of engineering identity. Moreover, the results highlighted the important role of students’ engagement in multiple authentic engineering projects throughout the curriculum and their gaining recognitions through these project experiences. Based on these findings, practical suggestions are proposed to help nurture students’ engineering identity. In addition, future qualitative investigations about the underlying mechanisms are recommended to facilitate the understanding of students’ development of engineering identity.",21967822,EDUCATION
10.3390/ejihpe13070091,The Effect of STEAM Activities Based on Experiential Learning on Ninth Graders’ Mental Motivation,"The impact of STEAM (Science, Technology, Engineering, Arts, and Math) on pupils’ learning has been increasingly highlighted recently. This study aims to shed light on the effect of STEAM activities based on experiential learning on ninth graders’ mental motivation and learning. The present research adopted a mixed methodology (quantitative and qualitative). The study sample consisted of 90 students divided into three groups. The tools utilized in conducting the study included California Measurement Mental Motivation, and semi-structured interviews with (10) participants. The tools’ validity and reliability were verified. After data were analyzed, the findings showed statically significant differences between students’ post average scores regarding mental motivation due to teaching method, and in favor of the experimental groups (face-to-face STEAM activities, online STEAM activities). This provides tangible proof for the need to include STEAM activities in school curricula to enhance learners’ curiosity, problem-solving skills and self-confidence through learning, as well as their task accomplishment ability.",22549625,PSYCHOLOGY
10.3390/cancers15143683,Xpert Bladder Cancer Monitor for the Early Detection of Non-Muscle Invasive Bladder Cancer Recurrences: Could Cystoscopy Be Substituted?,"XBM was prospectively assessed in spontaneous urine collected just before flexible cystoscopy and washing cytology carried out within the first 2 years follow-up of 337 patients with NMIBC. Recurrences were pathologically confirmed in 49 patients (14.5%), 22 of them being high-risk (6.5%). The XBM sensitivity for detecting any type of recurrence was 69.4% and 63.6% in the cases of high-risk NMIBC. Negative predictive value (NPV) for XBM was 93% for all recurrences and 96.2% for high-risk recurrences. XBM could have avoided 213 invasive controls but missed the detection of 15 recurrences (30.6%)–8 of them of high-risk (36.4%). XBM false positive elevations were detected in 90 patients (26.7%), whereas 10 patients with the invasive method had a false positive result (3%), p <0.001. However, early detection of recurrences during the first year’s follow-up after an XBM false positive result was observed in 18 patients (20%). On the other hand, 19 recurrences were detected during this period among the rest of the patients (7.7%)—p = 0.003, and odds ratio (OR) 3.0 (95% CI 1.5–6.0). Regarding one-year follow-up recurrences, 10% were high-risk recurrences in the XBM false positive group and 3.2% in the rest of the patients—p = 0.021, and OR 3.3 (95% CI 1.2–8.9). Additionally, 11.3% of the patients without false positive results developed a recurrence, p = 0.897, for any recurrence, being 10% and 5.2%, respectively, and high-risk and low-risk recurrences, p = 0.506. After searching for the best XBM cutoff for detecting the 38 high-risk initial recurrences and the early high-risk recurrences after a one-year follow-up, a linear discriminant analysis (LDA) of 0.13 could have avoided 11.3% of cystoscopies and bladder wash cytologies, as this cutoff missed only 1 high-risk recurrence (2.6%). More extensive and well-designed studies will confirm if XBM can improve the surveillance of NMIBC.",20726694,ONCOLOGY
10.3390/cancers15153796,"Modelling the Tumour Microenvironment, but What Exactly Do We Mean by “Model”?","The Oxford English Dictionary includes 17 definitions for the word “model” as a noun and another 11 as a verb. Therefore, context is necessary to understand the meaning of the word model. For instance, “model railways” refer to replicas of railways and trains at a smaller scale and a “model student” refers to an exemplary individual. In some cases, a specific context, like cancer research, may not be sufficient to provide one specific meaning for model. Even if the context is narrowed, specifically, to research related to the tumour microenvironment, “model” can be understood in a wide variety of ways, from an animal model to a mathematical expression. This paper presents a review of different “models” of the tumour microenvironment, as grouped by different definitions of the word into four categories: model organisms, in vitro models, mathematical models and computational models. Then, the frequencies of different meanings of the word “model” related to the tumour microenvironment are measured from numbers of entries in the MEDLINE database of the United States National Library of Medicine at the National Institutes of Health. The frequencies of the main components of the microenvironment and the organ-related cancers modelled are also assessed quantitatively with specific keywords. Whilst animal models, particularly xenografts and mouse models, are the most commonly used “models”, the number of these entries has been slowly decreasing. Mathematical models, as well as prognostic and risk models, follow in frequency, and these have been growing in use.",20726694,ONCOLOGY
10.3390/educsci13080774,Adapted Education for Gifted Students in Norway: A Mixed Methods Study,"In this article, we describe the mixed methods research (i.e., quantitative survey and qualitative interviews) we conducted to investigate adapted education for gifted students in Norway. The survey results showed that the teachers (n = 132) used differentiation strategies and agreed that gifted students need an adapted education that extends beyond the regular curriculum. We identified three themes related to adapted education based on an analysis of the student interview data (n = 17, aged 12–15) and four themes based on an analysis of the teachers’ responses to the open-ended survey question regarding adapted education. We also investigated similarities and differences between teacher and student themes: both groups reported similar enrichment strategies applied within adapted education and similar barriers and systematic challenges to its facilitation.",22277102,EDUCATION
10.3390/cancers15153917,Novel Discovery of the Somatostatin Receptor (SSTR2) in Pleomorphic Adenomas via Immunohistochemical Analysis of Tumors of the Salivary Glands,"Reliable preoperative diagnosis between salivary gland tumor entities is difficult. In this monocentric retrospective study, we examined the somatostatin receptor 2 (SSTR2) status of salivary gland tumors after salivary gland tumor resection via immunohistochemistry (IHC), and stains were compared in analogy to the HER2 mamma scale. A total of 42.3% of all pleomorphic adenoma (PA) tumors (42 of 99, 95% confidence interval 32.5–52.8%) demonstrated ≥20% of cells displaying the SSTR2 as compared to just 1% of all other tumors (1/160, 95% CI 0.02–3.4%). The other tumor was a neuroendocrine carcinoma. PA had a higher intensity of SSTR2 staining, with 90.9% staining ≥ an intensity of 2 (moderate). Tumors with an intensity of SSTR2 expression equal to or greater than 2 had an 89.9% likelihood of being a PA (95% CI: 82.2–95.0%, AUC: 0.928). Only one Warthin tumor demonstrated a ‘strong’ SSTR2 staining intensity. No Warthin tumor showed a percentage of cells staining for SSTR2 above ≥20%. This result demonstrates consistent and strong expression of SSTR2 in PAs as compared to Warthin tumors, which may allow physicians to utilize radioligand-somatostatin analog PET CT/MR imaging to diagnose the PA. SSTR2 positivity, if shown to be clinically relevant, may allow peptide receptor radionuclide therapy in the future.",20726694,ONCOLOGY
10.3390/ejihpe13090135,Association of Outdoor Physical Activity and Sports with Life Satisfaction among Women of Reproductive Age According to a European Representative Sample—A Longitudinal Analysis,"(1) Background: Low life satisfaction (LS) is associated with impaired mental and physical health. Outdoor physical activity (PA) has diverse somatic and psychological benefits. This study aimed to analyse the associations between sports settings and LS in women of reproductive age. (2) Methods: Special Eurobarometer on Sport and Physical Activity (2022, 2018, 2013) data on regularity and settings of sports/PA, LS and sociodemographic variables were analysed. The representative sample consisted of 18,489 women (34.60 ± 9.36 years). Pearson χ2 test and multivariate logistic regression analysis were conducted, using IBM SPSS version 28.0 according to the STROBE guidelines. The significance level was set at p < 0.05. (3) There was a significant difference in LS based on sports settings (χ2 = 409.696, p < 0.001). In the outdoor group, a 21.4% higher probability of being “very satisfied” compared to the non-outdoor, 30.0% higher compared to the inactive group, was found (R2N = 0.151). Dividing the sample by age, a significant effect remained in middle adulthood (35–44 years p = 0.002 and 45–49 years p = 0.033). (4) Conclusions: Our results underline the importance of the promotion of outdoor, green exercise and the development of special interventions to maintain or improve the psychological well-being of women in reproductive age.",22549625,PSYCHOLOGY
10.3390/cancers15184598,Predicting Long-Term Care Service Demands for Cancer Patients: A Machine Learning Approach,"Background: Long-term care (LTC) service demands among cancer patients are significantly understudied, leading to gaps in healthcare resource allocation and policymaking. Objective: This study aimed to predict LTC service demands for cancer patients and identify the crucial factors. Methods: 3333 cases of cancers were included. We further developed two specialized prediction models: a Unified Prediction Model (UPM) and a Category-Specific Prediction Model (CSPM). The UPM offered generalized forecasts by treating all services as identical, while the CSPM built individual predictive models for each specific service type. Sensitivity analysis was also conducted to find optimal usage cutoff points for determining the usage and non-usage cases. Results: Service usage differences in lung, liver, brain, and pancreatic cancers were significant. For the UPM, the top 20 performance model cutoff points were adopted, such as through Logistic Regression (LR), Quadratic Discriminant Analysis (QDA), and XGBoost (XGB), achieving an AUROC range of 0.707 to 0.728. The CSPM demonstrated performance with an AUROC ranging from 0.777 to 0.837 for the top five most frequently used services. The most critical predictive factors were the types of cancer, patients’ age and female caregivers, and specific health needs. Conclusion: The results of our study provide valuable information for healthcare decisions, resource allocation optimization, and personalized long-term care usage for cancer patients.",20726694,ONCOLOGY
10.3390/educsci13090942,How Has the Pandemic Affected Access and the Feeling of Belonging in Portuguese Higher Education?,"This study is based on an in-depth analysis of the Portuguese reality. The main question addressed concerns the effects of the pandemic on the social profile and conditions of participation, and higher education students’ sense of belonging in Portugal. The changes resulting from the pandemic will also be considered in light of the policies that have been pursued and implemented at the national level with the aim of increasing and enhancing students’ integration within the higher education community. The application of a longitudinal approach was made possible through institutional data and data produced by the EUROSTUDENT project. The results obtained clarify some of the immediate effects that the pandemic has had on higher education and on the social and academic conditions and contexts of students in Portugal. On a more structural level, these results also emphasise the importance of political choices in the process of democratisation and extending the system to new segments of the population.",22277102,EDUCATION
10.3390/educsci13100971,Empowering Novice Teachers: The Design and Validation of a Competence Model to Manage Verbal Aggressive Behaviour in the Classroom,"(1) Background: Dealing with students’ maladaptive behaviour in the classroom, such as verbal aggressive behaviour, is challenging, particularly for novice teachers. They often encounter limited opportunities for training and practice in handling such incidents during their pre-service education, rendering them ill-equipped and uncertain when confronted with instances of verbal aggression during their initial teaching experiences. This article reports on the design and validation of a verbal aggression management competence model to guide and substantiate novice teachers’ immediate reactions. (2) Methods: The model’s construction and validation processes were informed by a dual-pronged approach, encompassing a literature analysis to explore theoretical concepts and semi-structured interviews involving 32 educational experts to validate its practical applicability. (3) Results: The design and validation processes resulted in a comprehensive competence model consisting of concrete steps to be taken during or immediately following an incident and overarching attitudes to be adopted throughout the incident managing process. (4) Conclusions: This study contributes a structured framework to empower novice teachers, offering tools to address verbal aggressive behaviour within the classroom environment. Furthermore, it highlights the potential of incorporating this model into teacher education programs, facilitating the competence development of future teachers, and fostering conducive learning environments.",22277102,EDUCATION
10.1186/s40594-023-00438-3,"How are primary school computer science curricular reforms contributing to equity? Impact on student learning, perception of the discipline, and gender gaps","Background: Early exposure to Computer Science (CS) and Computational Thinking (CT) for all is critical to broaden participation and promote equity in the field. But how does the introduction of CS and CT into primary school curricula impact learning, perception, and gaps between groups of students? Methodology: We investigate a CS-curricular reform and teacher Professional Development (PD) programme from an equity standpoint by applying hierarchical regression and structural equation modelling on student learning and perception data from three studies with, respectively, 1384, 2433 and 1644 grade 3–6 students (ages 7–11) and their 83, 142 and 95 teachers. Results: Regarding learning, exposure to CS instruction appears to contribute to closing the performance gap between low-achieving and high-achieving students, as well as pre-existing gender gaps. Despite a lack of direct influence of what was taught on student learning, there is no impact of teachers’ demographics or motivation on student learning, with teachers’ perception of the CS-PD positively influencing learning. Regarding perception, students perceive CS and its teaching tools (robotics, tablets) positively, and even more so when they perceive a role model close to them as doing CS. Nonetheless, gender differences exist all around with boys perceiving CS more positively than girls despite access to CS education. However, access to CS-education affects boys and girls differently: larger gender gaps are closing (namely those related to robotics), while smaller gaps are increasing (namely those related to CS and tablets). Conclusion: This article highlights how a CS curricular reform impacts learning, perception, and equity and supports the importance of (i) early introductions to CS for all; (ii) preparing teachers to teach CS all the while removing the influence of teacher demographics and motivation on student outcomes; and (iii) having developmentally appropriate activities that signal to all groups of students.",21967822,EDUCATION
10.1186/s40359-023-01368-z,Psychometric properties of the Persian Gaming Disorder Test and relationships with psychological distress and insomnia in adolescents,"Background: Gaming Disorder (GD) was recently included by the World Health Organization (WHO) as a psychiatric condition in the eleventh revision of the International Classification of Diseases (ICD-11) and is a concern worldwide, including in Iran. Thus, based on the ICD-11 criteria, a Persian version of the Gaming Disorder Test (GDT) was developed to facilitate assessment of GD. Methods: The present study used classical test theory and Rasch analysis to examine the psychometric properties of the Persian GDT. Iranian adolescents (n = 3837; 2171 [56.6%] males; mean [SD] age = 16.02 [1.4] years) completed the GDT and other instruments assessing disordered gaming, psychological distress, and insomnia. Results: Overall, the psychometric properties of the Persian GDT were satisfactory based on classical test theory (i.e., confirmatory factor analysis corroborated the unidimensional structure of GDT) and Rasch analysis (i.e., fit statistics suggested that all items were embedded in the concept of GD). Moreover, the Persian GDT was found to be sex-invariant, displaying no items with substantial differential item functioning across sexes. Additionally, it was found that GD mediated associations between time spent gaming and measures of psychological distress and insomnia. Conclusion: The Persian GDT is a convenient and short instrument for assessing GD among Iranian adolescents. The mediating roles of GD in the associations between time spent gaming and psychological distress and between time spent gaming and insomnia suggest that targeting features of GD may reduce psychological distress and improve sleep for Iranian adolescents.",20507283,PSYCHOLOGY
10.1186/s40359-023-01356-3,"A Lenz into the predictive power of language teacher emotion regulation and self-evaluation on L2 grit, teaching style preferences, and work engagement: a case of Chinese EFL instructors","An individual’s capacity to successfully control their emotional experiences and react to them requires them to engage in a number of processes, including those that are physiological, behavioral, and cognitive. When educators engage in self-evaluation, they investigate and assess the quality of their professional work. These two teacher-related conceptions have the potential to open up valuable perspectives in the course of the professional pursuits of teachers. Even though earlier research has shown their significance, the potential implications of these factors on the resiliency and teaching style preferences of language instructors have not been emphasized. As a result, the purpose of this study was to determine the extent to which a language teacher’s ability to regulate their emotions while carrying out self-evaluation procedures may accurately predict their level of resilience as well as their preferred method of instruction. To accomplish this, 399 English as a foreign language (EFL) teachers were asked to reflect on their experiences by responding to the following related questionnaires: The Language Teacher Emotion Regulation Inventory (LTERI), The Core of Self-evaluation Questionnaire (CSEQ), the L2-teacher Grit Scale (L2TGS), Grasha Teaching Style Inventory (TSI) and the Engaged Teacher Scale (ETS). The results demonstrated that those EFL teachers who maintained healthy emotional control were grittier and more engaged. They also tended to teach in a manner focused on the students. The pedagogical implications of this research are discussed further in depth.",20507283,PSYCHOLOGY
10.3390/educsci13101054,‘Something Better than a Cure’ in Times of Mental Health Crisis,"In this paper, I turn to Adam Phillips’ recent discussion of the vexed nature of cure in psychoanalysis to consider the structural differences between mental and physical health. I examine how psychoanalytic thinking raises questions for naturalistic ways of thinking about mental health and for broader crisis narratives that are becoming prevalent in Western modernity. In the latter half of this paper, I draw a comparison between thinking about matters of health and ways of thinking in the philosophy of education. I suggest that the lure of cure can be detected in statements of universalist aims and ends for education (which themselves have come to invoke conceptions of wellbeing and mental health in modern times). I also explore Phillps’ account of psychoanalysis as ‘something better than a cure’ and consider its implications for future thinking in the philosophy of education.",22277102,EDUCATION
10.3390/ejihpe13100162,Prisoners’ Educational Experiences in Five Different Prison Sports Programmes: A Research Note,"Organized sports programmes offer manifold opportunities for learning and personal development. Prisoners in organized sports programmes could profit from these educational opportunities, which could eventually support their process of reintegration into society. However, research on the educational experiences of imprisoned individuals during organized sports activities is scarce. Using quantitative survey data (N = 568 adult male prisoners) collected within the scope of the Hessian Prison Sports Study in Hesse, Germany, the present study examines educational experiences that are instigated through participation in five different prison sports programmes (fitness, racket, and team sports, running groups, and strength training). The results show that participants reported few educational experiences. The most common experiences reported were learning to exert effort and acquiring health-related knowledge. The findings reveal distinct patterns for specific sports programmes. For instance, team sports more frequently address cooperation skills and fairness. This paper advocates for more attention to the educational potential of sports in prison settings, where sports outcomes should be better aligned with the desired educational outcomes.",22549625,PSYCHOLOGY
10.3390/cancers15215133,The Association between Proton Pump Inhibitors and the Effectiveness of CDK Inhibitors in HR+/HER- Advanced Breast Cancer Patients: A Systematic Review and Meta-Analysis,"There have been many clinical questions regarding whether the use of proton pump inhibitors (PPIs) could deteriorate the effects of cyclin-dependent kinase inhibitors (CDKIs) in HR+/HER2- advanced breast cancer patients. We performed a systematic review and meta-analysis of this clinical question, including studies enrolling HR+/HER2- metastatic breast cancer patients treated with CDKIs (Palbociclib or Ribociclib) and reporting at least one comparative survival outcome, either overall survival (OS) or progression-free survival (PFS), between concomitant PPI users and non-users. Eight studies met the eligibility criteria, with a total of 2584 patients included (PPI users: 830, PPI non-users: 1754), demonstrating that concomitant PPI use was associated with significantly higher risks of all-cause mortality (HR = 2.03; 95% CI, 1.49 to 2.77; I2 = 0%) and disease progression (HR = 1.75; 95% CI, 1.26 to 2.43; I2 = 59%) in breast cancer patients taking Palbociclib. In contrast, there were no significant survival impacts of PPIs on Ribociclib (HR = 1.46; 95% CI, 0.91 to 2.34; I2 = 36%). Additionally, there was no significant difference in the risk associated with CDKI dose reduction due to drug toxicity (RR = 1.12; 95% CI, 0.97 to 1.29). Therefore, when HR+/HER2- advanced breast cancer patients require the use of PPIs, it may be reasonable to consider using Ribociclib.",20726694,ONCOLOGY
10.3390/educsci13111081,Effects of COVID-19 on First-Year Undergraduate Research in Physical Geography,"Having confirmed that including research in first-year undergraduate teaching can actually help students understand the research process, link research with concepts, and improve both their academic and professional skills, we intended to evaluate how this experiential learning component fared during the COVID-19 challenge. For a first-year three-credit physical geography class, we have included a First Year Research Experience (FYRE) project for six iterations. A cluster analysis grouped students’ perceptions obtained from survey questions into five categories, from high to low. The results showed an overall improvement in perception of the FYRE during the pandemic, driven primarily by soft-skill development related to time management and self-motivation. Students were also able to better connect the research project with the theoretical content of the course. Components of the FYRE that suffered during the pandemic include engaging with course instructors and completing the oral presentation phase of the research. Soft-skill development continued through the second year of the pandemic, although students’ dissatisfaction with continued restrictions on in-person contact was evident.",22277102,EDUCATION
10.3390/ejihpe13110167,"A Moderated Mediation Model of the Influence of Cynical Distrust, Medical Mistrust, and Anger on Vaccination Hesitancy in Nursing Staff","During the pandemic, nurses experienced anger that stemmed from a sense of threat, frustration, or even a sense of injustice. The purpose of this study was to examine the relationship between vaccination hesitancy, anger, cynicism, and medical mistrust among nurses, as there are no relevant studies in the literature. This study was conducted online by completing self-report questionnaires. The Dimensions of Anger Reactions-5, the 8-item “Cynical Distrust” scale, and the Medical Mistrust Multiformat Scale were used. For vaccination hesitancy, two questions with a 5-point scale were used: one question examining hesitancy to get vaccinated with the COVID-19 vaccine, and another question examining hesitancy to get vaccinated with the influenza vaccine. In total, 387 nurses (66 men and 321 women) participated in this study. Nurses showed statistically greater hesitancy toward the COVID-19 vaccine compared to hesitancy toward the influenza vaccine. The variation in vaccine hesitancy was explained by the scores in the Medical Mistrust Multiformat Scale, the Dimensions of Anger Reactions, and the Cynical Distrust Scale. The Medical Mistrust Multiformat Scale mediated the relationship between the Cynical Distrust Scale and total vaccine hesitancy. The Dimensions of Anger Reactions Scale significantly moderated the indirect effect of the Cynical Distrust Scale on total vaccine hesitancy through the Medical Mistrust Multiformat Scale. In conclusion, it is highly likely that anger is involved in reported vaccine hesitancy both by activating schemas of distrust in others and by adopting anti-systemic views of mistrust in the medical system.",22549625,PSYCHOLOGY
10.3390/ejihpe13110174,Antecedents and Mediators of Academic Satisfaction in Virtual Vocational Training,"At a time when distance vocational training is on the rise, it seems logical to investigate the variables that can affect the quality of such teaching. The usability of the virtual environment, as well as the behaviour and disposition of the teaching staff, emerge as key factors that influence burnout, engagement, and academic satisfaction. Using a cross-sectional sample of 208 distance vocational training students, the mediating role of burnout and academic engagement in the relationships established between the usability of the virtual environment, teacher support, and academic satisfaction was analysed. On the other hand, multiple regression analyses were carried out in order to investigate the relationships between the challenges and obstacles faced by distance vocational training students and their level of burnout or engagement. Our results confirm the mediating role of academic burnout and engagement in students’ academic satisfaction. Regression analyses suggest that the obstacles faced by distance vocational education and training (D-VET) students influence their level of academic burnout or engagement. Our findings are consistent with the current understanding of the role that certain variables play in the well-being of students and which, in turn, influence the quality of teaching.",22549625,PSYCHOLOGY
10.1186/s40594-023-00456-1,"Correction: How are primary school computer science curricular reforms contributing to equity? Impact on student learning, perception of the discipline, and gender gaps",,21967822,EDUCATION
10.3390/cancers15215303,An Interpretable Radiomics Model Based on Two-Dimensional Shear Wave Elastography for Predicting Symptomatic Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma,"Objective: The aim of this study was to develop and validate an interpretable radiomics model based on two-dimensional shear wave elastography (2D-SWE) for symptomatic post-hepatectomy liver failure (PHLF) prediction in patients undergoing liver resection for hepatocellular carcinoma (HCC). Methods: A total of 345 consecutive patients were enrolled. A five-fold cross-validation was performed during training, and the models were evaluated in the independent test cohort. A multi-patch radiomics model was established based on the 2D-SWE images for predicting symptomatic PHLF. Clinical features were incorporated into the models to train the clinical–radiomics model. The radiomics model and the clinical–radiomics model were compared with the clinical model comprising clinical variables and other clinical predictive indices, including the model for end-stage liver disease (MELD) score and albumin–bilirubin (ALBI) score. Shapley Additive exPlanations (SHAP) was used for post hoc interpretability of the radiomics model. Results: The clinical–radiomics model achieved an AUC of 0.867 (95% CI 0.787–0.947) in the five-fold cross-validation, and this score was higher than that of the clinical model (AUC: 0.809; 95% CI: 0.715–0.902) and the radiomics model (AUC: 0.746; 95% CI: 0.681–0.811). The clinical–radiomics model showed an AUC of 0.822 in the test cohort, higher than that of the clinical model (AUC: 0.684, p = 0.007), radiomics model (AUC: 0.784, p = 0.415), MELD score (AUC: 0.529, p < 0.001), and ALBI score (AUC: 0.644, p = 0.016). The SHAP analysis showed that the first-order radiomics features, including first-order maximum 64 × 64, first-order 90th percentile 64 × 64, and first-order 10th percentile 32 × 32, were the most important features for PHLF prediction. Conclusion: An interpretable clinical–radiomics model based on 2D-SWE and clinical variables can help in predicting symptomatic PHLF in HCC.",20726694,ONCOLOGY
10.1007/s44196-023-00352-0,Unmanned Vehicle Fusion Positioning Technology Based on “5G + Beidou” and 3D Point Cloud Image,"Unmanned vehicles need to know their location and direction information accurately to plan and navigate their paths. However, the positioning system is susceptible to interference from a variety of factors, which leads to increased positioning errors, thereby affecting the accuracy of unmanned vehicle positioning. An unmanned vehicle fusion positioning technology based on the ""5G + Beidou"" integrated positioning system was proposed. While using the ""5G + Beidou"" base station for positioning, the 3D point cloud image was fused, and the high-precision real-time positioning was carried out through the vehicle's autonomous navigation algorithm. This paper first analyzed the current situation and characteristics of GNSS technology and studied the key technologies and principles of the ""5G + Beidou"" integrated positioning system. Then, aiming at the difficulty of 5G base station deployment, the GNSS system parameter optimization scheme based on a multidimensional fusion structure was designed. Finally, in the experiment, it was verified that the fusion system could achieve higher precision positioning results compared with traditional single-dimensional GNSS and multi-dimensional GNSS. The technical advantages of ""5G + Beidou"" were used for data fusion processing of unmanned vehicles, and a positioning method based on the combination of 3D point cloud image and high-precision map was proposed. Through some experiments, it was concluded that the fusion location method could control the error below 0.1, which showed the accuracy of the fusion location.",18756883,AI
10.3390/cancers15225323,The Potential of Lifestyle Medicine: Strategies to Optimize Health and Well-Being in Oncology Care with Dr. Amy Comander,"The field of lifestyle medicine in cancer care and survivorship is undergoing significant transformation, presenting both challenges and opportunities. This collection of insights and reflections by an esteemed speaker aims to address critical facets of this evolving landscape and the intersection of healthcare, lifestyle, and cancer. With a focus on optimizing the health of cancer survivors, the speaker emphasizes the correlation between general population health and strategies for mitigating cancer risk. Evidence-based resources have a key role in their comprehensive insights into lifestyle changes’ role in cancer prevention and survivorship. Lifestyle interventions also have a promising role in mitigating the late effects in the pediatric context. Therefore, encouraging the early adoption of healthy practices in childhood cancer survivors emerges as a pivotal strategy. Furthermore, challenges in enhancing education and access to lifestyle medicine are addressed. This highlights the importance of patient-centered communication, motivational interviewing, and personalized guidance in facilitating lifestyle changes with patients. Finally, the role of nutritionists in advising breast cancer patients to consider calorie restriction to lower IGF-1 levels is explored. This collection underscores the multifaceted nature of lifestyle medicine in cancer care, highlighting challenges, opportunities, and the transformative power of passion and curiosity in shaping healthcare careers.",20726694,ONCOLOGY
10.3390/ejihpe13110182,The Perth Empathy Scale: Psychometric Properties of the Polish Version and Its Mental Health Correlates,"The Perth Empathy Scale (PES) is a 20-item self-report questionnaire that assesses people’s ability to recognize emotions in others (i.e., cognitive empathy) and vicariously experience other’s emotions (i.e., affective empathy), across positive and negative emotions. Originally developed in English, the aim of our study was to introduce the first Polish version of the PES and test its psychometric performance. Our sample was 318 people (184 females, 134 males) with ages ranging from 18 to 77. The factor structure was verified with confirmatory factor analysis. Reliability was tested in terms of internal consistency and test–retest reliability. To explore convergent, divergent, and discriminant validity, we examined relationships between the PES and measures of depression, anxiety, and emotional intelligence. It was shown that the scale was characterized by the intended four-factor solution, thus supporting factorial validity. The internal consistency reliability was also good and test–retest reliability was moderate. The convergent, divergent, and discriminant validity were strong. The clinical importance of assessing affective empathy across both positive and negative emotions was supported. Overall, our results therefore suggest that the Polish version of the PES has strong psychometric performance and clinical relevance as a measure of the multidimensional empathy construct.",22549625,PSYCHOLOGY
10.3390/ejihpe13110185,Evaluation of Linguistics Students’ Learning Outcomes in Peer Teaching Courses: The Effect of Altruistic and Egoistic Behaviors,"In the current study, we evaluated the students’ foreign language lexical and grammatical skills in the course based on the peer teaching methodology and analyzed the effect of their altruistic and egoistic behaviors on learning results. This experiment was conducted in a groups of senior students majoring in linguistics. The total number of participants accounted for 197 students (101 students in reference groups and 96 in exposure groups); the difference between the reference and exposure groups was that the undergraduates in the latter were to prepare a fragment of a lesson, create exercises, and act in the capacity of a teacher during the course. To evaluate students’ foreign language lexical and grammatical skills, the diagnostic test was conducted at the beginning and at the end of the experiment. Apart from comparing the diagnostic and final tests, we also circulated a questionnaire which checked the students’ egoistic and altruistic tendencies. The data appeared to be quite noisy; therefore, we processed them with a tool which proves effective when it comes to solving such problems, i.e., neural networks. According to the results on learning outcomes, students improved their English proficiency in the exposure groups to a greater extent than in the reference groups. At the same time, the results of the psychological tests revealed that the higher the students’ training level, the less altruistic they are. Also, it was detected that the more altruistic learners’ progress in outcomes was higher than those of the more selfish students, regardless of the way in which the learning process was organized. Moreover, the statistical data proved the efficiency of the peer teaching methodology for students’ majoring in linguistics, despite their psychological characteristics.",22549625,PSYCHOLOGY
10.3390/educsci13111150,Promoting Interdisciplinary Research Collaboration among Mathematics and Special Education Researchers,"This manuscript provides a theoretical framing of a collaborative research design effort among mathematics education and special education researchers. To gain insight into the current state of research on mathematics learning, we drew on how researchers in mathematics education and special education have defined and operationalized the term ‘mathematical concept’ related to the learning of fractions. Using this information, we designed a future study that focuses on and connects prior research in mathematics and special education. We conclude by discussing the implications of such collaborative research efforts.",22277102,EDUCATION
10.3390/ejihpe13120193,Trends in Suicidal Mortality and Motives among Working-Ages Individuals in Japan during 2007–2022,"Suicides in Japan consistently decreased from 2009–2019, but increased during the COVID-19 pandemic. To identify causes of increasing suicides, age-dependent and temporal fluctuations of suicide mortality rate per 100,000 (SMRP) in working-age generations (20–59 years) disaggregated by suicidal motives (7-categories; 52-subcategories) and sex from 2007 to 2022, were analyzed by analysis of variance and joinpoint regression, respectively, using the government suicide database “Suicide Statistics”. The SMRP of 20–29 year-old males and 20–49 year-old females began to increase in the late 2010s. SMRPs of these high-risk groups for suicides caused by depression (the leading suicidal motive for all groups) began increasing in the late 2010s. Economic-related, employment-related, and romance-related problems contributed to the increasing SMRPs in 20–29 males in the late 2010s. Romance-related and family-related problems contributed to the increasing SMRPs of 20–29 females in the late 2010s. Increasing SMRPs caused by child-raising stress in 20–39 year-old females from the late 2010s was a remarkable finding. In contrast, SMRPs of 30–59 year-old males consistently decreased until 2021; however, in these groups, SMRPs for suicides caused by various motives sharply increased in 2022. The consistent increase in SMRPs of high-risk groups from the late 2010s to the pandemic suggest recent socioeconomic and psychosocial problems in Japan possibly contributed to the increasing SMRPs in these high-risk groups independently of pandemic-associated factors, whereas the SMRPs of males of 30–59 years were probably associated with the ending of the pandemic rather than pandemic-associated factors.",22549625,PSYCHOLOGY
10.3390/cancers15235617,Extracellular Vesicles: Biological Packages That Modulate Tumor Cell Invasion,"Tumor progression, from early-stage invasion to the formation of distal metastases, relies on the capacity of tumor cells to modify the extracellular matrix (ECM) and communicate with the surrounding stroma. Extracellular vesicles (EVs) provide an important means to regulate cell invasion due to the selective inclusion of cargoes such as proteases and matrix proteins into EVs that can degrade or modify the ECM. EVs have also been shown to facilitate intercellular communication in the tumor microenvironment through paracrine signaling, which can impact ECM invasion by cancer cells. Here, we describe the current knowledge of EVs as facilitators of tumor invasion by virtue of their effects on proteolytic degradation and modification of the ECM, their ability to educate the stromal cells in the tumor microenvironment, and their role as mediators of long-range communication aiding in cell invasion and matrix remodeling at secondary sites.",20726694,ONCOLOGY
10.1186/s40594-023-00449-0,Using intensive longitudinal methods to quantify the sources of variability for situational engagement in science learning environments,"Background: Situational engagement in science is often described as context-sensitive and varying over time due to the impact of situational factors. But this type of engagement is often studied using data that are collected and analyzed in ways that do not readily permit an understanding of the situational nature of engagement. The purpose of this study is to understand—and quantify—the sources of variability for learners’ situational engagement in science, to better set the stage for future work that measures situational factors and accounts for these factors in models. Results: We examined how learners' situational cognitive, behavioral, and affective engagement varies at the situational, individual learner, and classroom levels in three science learning environments (classrooms and an out-of-school program). Through the analysis of 12,244 self-reports of engagement collected using intensive longitudinal methods from 1173 youths, we found that the greatest source of variation in situational engagement was attributable to individual learners, with less being attributable to—in order—situational and classroom sources. Cognitive engagement varied relatively more between individuals, and affective engagement varied more between situations. Conclusions: Given the observed variability of situational engagement across learners and contexts, it is vital for studies targeting dynamic psychological and social constructs in science learning settings to appropriately account for situational fluctuations when collecting and analyzing data.",21967822,EDUCATION
10.3390/ejihpe13120197,Subjective Well-Being and Self-Assessed Health of Adolescents: A Longitudinal Cohort Study,"Background: The aim of this study was to investigate the stability and predictors of subjective well-being and self-perceived health in adolescents over a two-year period, focusing on the importance of mental health in overall well-being. Methods: Participants in this longitudinal cohort study were surveyed at the ages of 15 (n = 441) and 17 (n = 354) through questionnaires. The data were analyzed using both descriptive and inferential statistical methods. Hierarchical regression was employed to investigate significant predictors of subjective well-being. The subjective well-being and self-perceived health dimensions showed a consistent level of stability throughout the two-year period of secondary education. Additionally, there was a significant correlation between well-being at the beginning and end of this education period. Furthermore, self-perceived health dimensions, particularly general health, vitality, and mental health, were positively associated with well-being at the end of secondary education, highlighting their role in overall subjective well-being. The regression analysis revealed that self-perceived health factors, notably “General health” and “Mental health”, significantly predicted overall subjective well-being, enhancing the model’s explanatory power beyond gender and economic status. Nevertheless, baseline subjective well-being has the strongest predictive effect on final well-being. Conclusions: This study highlights the importance of psychological and health factors, particularly mental health, that affect the overall well-being of adolescents and emphasizes the need to focus on and improve these factors in order to improve subjective well-being.",22549625,PSYCHOLOGY
10.1186/s40359-023-01477-9,The development of the fear of earthquake scale: validity and reliability study in Türkiye after the 2023 earthquake,"Background: In 2023, Türkiye experienced a significant earthquake disaster that profoundly impacted 11 provinces. The enduring consequences of these earthquakes on daily life triggered widespread fears and anxieties in society, leading to scholarly investigations in this field. Objective: The primary objective of this study was to create and evaluate the psychometric properties of the Fear of Earthquake Scale (FES), a modified adaptation of the Fear of COVID-19 Scale (FCV-19 S), tailored to measure earthquake-related experiences in Türkiye. Methods: A total of 315 Turkish adult participants (106 men, 209 women), with a mean age of 37.71 years, completed the FES, along with the Brief Psychological Resilience Scale (BPRS). Psychometric analyses included confirmatory factor analysis as well as the evaluation of alternative factor structures, internal consistency, convergent validity, and criterion validity with respect to resilience. Results: The findings indicate that the Turkish version of the Fear of Earthquake Scale has strong psychometric properties in terms of validity and reliability. After assessing various factor structures, it was observed that the two-factor model which represents the emotional and somatic response to fear, exhibited the best-fit values The Cronbach’s alpha coefficients were calculated as 0.89 for the overall FES, 0.84 for the emotional subscale and 0.86 for the somatic subscale, indicating high internal consistency. Additionally, the negative correlation between resilience and the FES supports the criterion validity of the scale, and multi-group confirmatory factor analyses proved that measurement invariance held across genders and whether they experienced an earthquake or not for all groups. Furthermore, the results of the study revealed that women and individuals with prior earthquake experience reported higher levels of fear of earthquakes. Conclusions: The FES emerged as a reliable and valid tool for assessing earthquake-related fears among the Turkish population.",20507283,PSYCHOLOGY
10.3390/educsci13121238,Let’s Get Digital: ICT Training Needs in Pre-Service Language Teaching,"During the last five years, language teaching in Europe has been heavily influenced by two major occurrences. On the one hand, the outbreak of COVID-19 forced teachers to extensively adapt many of their teaching practices to the digital world; this major paradigm shift is likely to have continued repercussions post-pandemic in terms of methodology and use of resources. At the same time, the publication of an updated version of the Common European Framework, commonly known as the Companion Volume focuses our attention on the real-life communicative needs of language users. The Companion Volume emphasizes digital and online communication processes throughout the development of language skills, and this focus inevitably translates into changes in national and regional curricula for language education. The present study investigates the degree to which future teachers are prepared for this new reality and explores emerging digital training needs among pre-service teachers. The investigation obtains quantitative and qualitative data from 30 pre-service teachers who have completed postgraduate studies in language education, which included a stage of school-based teaching practice. Results indicate that while pre-service language teachers have a positive view of ICT and moderate levels of general digital competence, they feel additional specific and in-depth preparation is required within their initial training.",22277102,EDUCATION
10.3390/ejihpe14010001,The Impact of a School Dog on Children’s Social Inclusion and Social Climate in a School Class,"Animal-assisted pedagogy is well known in classroom practice, but scientific evidence of its impact on teaching and learning conditions is still lacking. At the same time, the biggest challenge in education systems worldwide is the social inclusion of students. In a pre–post design, 30 heterogeneous students (16 f/14 m) from four different school classes (grades 5–8) of two secondary schools and one grammar school were interviewed (in a problem-centered interview) about their social inclusion and their social climate in class before and after being taught selected subjects with a school dog for one school term. At the second measurement point, participants were also asked about their perception of animal-assisted pedagogy. The qualitative data analysis (Kuckartz) showed that the presence of a dog leads to an improved social climate, more social integration and to a change in social roles; therefore, we discussed our findings in the context of role theory (Krappmann). In addition, we found that the mutual perception of the other students and the teacher changes to a more positive and friendlier image. Through animal-assisted pedagogy, a new social role is added to the classroom, where caring and bonding are prioritized. Social interaction and norms are influenced and stereotypical and individual roles can be changed. Therefore, animal-assisted pedagogy can be key to promoting social inclusion in the school environment.",22549625,PSYCHOLOGY
10.3390/educsci14010007,Do Cases Always Deliver What They Promise? A Quality Analysis of Business Cases in Higher Education,"Although the usage of case studies is very common in teaching worldwide, there has been inadequate discussion concerning the quality with respect to teaching and learning. The focus of this article is to assess the pedagogic aspect of business case studies in academic teaching. On the basis of a specific tool to detect the pedagogical quality of business cases and related teaching notes, a total of nine award-winning case studies delivered by a well-known publishing house were analysed. The findings indicate that the pedagogical quality varies from case to case. There are deficits concerning the focus on problem orientation and the complexity of the cases. Further weaknesses have been identified in some case studies regarding the learner’s autonomy and prior knowledge, while with respect to real-life orientation, most case studies have a high level of accordance with a pedagogic optimum.",22277102,EDUCATION
10.3390/ai5010005,Application of YOLOv8 and Detectron2 for Bullet Hole Detection and Score Calculation from Shooting Cards,"Scoring targets in shooting sports is a crucial and time-consuming task that relies on manually counting bullet holes. This paper introduces an automatic score detection model using object detection techniques. The study contributes to the field of computer vision by comparing the performance of seven models (belonging to two different architectural setups) and by making the dataset publicly available. Another value-added aspect is the inclusion of three variants of the object detection model, YOLOv8, recently released in 2023 (at the time of writing). Five of the used models are single-shot detectors, while two belong to the two-shot detectors category. The dataset was manually captured from the shooting range and expanded by generating more versatile data using Python code. Before the dataset was trained to develop models, it was resized (640 × 640) and augmented using Roboflow API. The trained models were then assessed on the test dataset, and their performance was compared using matrices like mAP50, mAP50-90, precision, and recall. The results showed that YOLOv8 models can detect multiple objects with good confidence scores. Among these models, YOLOv8m performed the best, with the highest mAP50 value of 96.7%, followed by the performance of YOLOv8s with the mAP50 value of 96.5%. It is suggested that if the system is to be implemented in a real-time environment, YOLOv8s is a better choice since it took significantly less inference time (2.3 ms) than YOLOv8m (5.7 ms) and yet generated a competitive mAP50 of 96.5%.",26732688,AI
10.3390/ai5010008,Statistically Significant Differences in AI Support Levels for Project Management between SMEs and Large Enterprises,"Background: This article delves into an in-depth analysis of the statistically significant differences in AI support levels for project management between SMEs and large enterprises. The research was conducted based on a comprehensive survey encompassing a sample of 473 SMEs and large Slovenian enterprises. Methods: To validate the observed differences, statistical analysis, specifically the Mann–Whitney U test, was employed. Results: The results confirm the presence of statistically significant differences between SMEs and large enterprises across multiple dimensions of AI support in project management. Large enterprises exhibit on average a higher level of AI adoption across all five AI utilization dimensions. Specifically, large enterprises scored significantly higher (p < 0.05) in AI adopting strategies and in adopting AI technologies for project tasks and team creation. This study’s findings also underscored the significant differences (p < 0.05) between SMEs and large enterprises in their adoption and utilization of AI technologies for project management purposes. While large enterprises scored above 4 for several dimensions, with the highest average score assessed (mean value 4.46 on 1 to 5 scale) for the usage of predictive Analytics Tools to improve the work on the project, SMEs’ average levels, on the other hand, were all below 4. SMEs in particular may lag in incorporating AI into various project activities due to several factors such as resource constraints, limited access to AI expertise, or risk aversion. Conclusions: The results underscore the need for targeted strategies to enhance AI adoption in SMEs and leverage its benefits for successful project implementation and strengthen the company’s competitiveness.",26732688,AI
10.3390/ejihpe14010014,Climate Change Perception and Mental Health. Results from a Systematic Review of the Literature,"Climate change is one of the main global challenges and influences various aspects of human health. Numerous studies have indeed demonstrated an association between extreme climate-related events and physical and mental health outcomes, but little is still known about the association between the perception/awareness of climate change and mental health. In accordance with the PRISMA 2020 guidelines, a search was conducted on PubMed and Scopus. The protocol was registered on PROSPERO. The included studies were original observational studies published in English, reporting the association between the perception/awareness of climate change and mental health. A total of 3018 articles were identified. A total of 10 observational studies were included. The period covered in the included studies ranged between 2012 and 2022. Climate change perception is consistently associated with adverse mental health effects across different types of estimates. In particular, the studies identified an association between a higher level of perception/awareness of climate change and depression, anxiety, eco-anxiety, stress, adjustment disorder, substance use, dysphoria, and even thoughts of suicide. Qualitative data underscore the impact on daily activities, contributing to feelings of loss and suicidal ideation. Moreover, climate change perception correlates with lower well-being and resilience. The association between awareness of climate change and mental health is a complex and still poorly explored phenomenon. The main limitations are the high heterogeneity in terms of exposure assessment and data reporting, which hinders quantitative analysis. These results show that climate change perception impacts mental health. Better understanding the phenomenon represents an opportunity to inform public health interventions that promote mental well-being.",22549625,PSYCHOLOGY
10.3390/cancers16020343,Bacterial Lipopolysaccharide Induces PD-L1 Expression and an Invasive Phenotype of Oral Squamous Cell Carcinoma Cells,"Background: Expression of programmed death ligand-1 (PD-L1) is related to the prognosis of many solid malignancies, including oral squamous cell carcinoma (OSCC), but the mechanism of PD-L1 induction remains obscure. In this study, we examined the expression of PD-L1 and partial epithelial–mesenchymal transition (pEMT) induced by bacterial lipopolysaccharide (LPS) in OSCC. Methods: The expression of Toll-like receptor 4 (TLR4) recognizing LPS in OSCC cell lines was analyzed. Moreover, the induction of PD-L1 expression by Porphyromonas gingivalis (P.g) or Escherichia coli (E. coli) LPS and EMT was analyzed by western blotting and RT-PCR. Morphology, proliferation, migration, and invasion capacities were examined upon addition of LPS. PD-L1 within EXOs was examined. Results: PD-L1 expression and pEMT induced by LPS of P.g or E. coli in TLR4-expressing OSCC cell lines were observed. Addition of LPS did not change migration, proliferation, or cell morphology, but increased invasive ability. Moreover, higher expression of PD-L1 was observed in OSCC EXOs with LPS. Conclusion: Oral bacterial LPS is involved in enhanced invasive potential in OSCC cells, causing PD-L1 expression and induction of pEMT. The enhancement of PD-L1 expression after addition of LPS may be mediated by EXOs.",20726694,ONCOLOGY
10.1186/s40359-024-01526-x,Evaluation of the psychometric properties of the family adaptability and cohesion scale (FACES III) through item response theory models in students from Chile and Colombia,"Background: A psychometric study of the Family Adaptability and Cohesion Scale (FACES III) has been conducted in Spanish-speaking countries from the perspective of the classical test theory. However, this approach has limitations that affect the psychometric understanding of this scale. Objective: Accordingly, this study used the item response theory to investigate the psychometric performance of the items. Furthermore, it evaluated the differential performance of the items for Colombia and Chile. Method: For this purpose, 518 health science students from both countries participated. Confirmatory Factor Analysis was used. Results: The study results revealed that the cohesion and adaptability items presented adequate discrimination and difficulty indices. In addition, items 5, 8, 13, 17, and 19 of cohesion indicated differential functioning between students from both countries, with Chilean students exhibiting a greater discriminatory power. Further, the Colombian group exhibited a greater discriminatory power for item 18 of adaptability. Conclusions: The study concluded that the items of FACES III indicated adequate psychometric performance in terms of their discriminative capacity and difficulty in Chile and Colombia.",20507283,PSYCHOLOGY
10.3390/cancers16020404,Intramedullary Spinal Cord Tumors: Whole-Genome Sequencing to Assist Management and Prognosis,"Intramedullary spinal cord tumors (IMSCTs) harbor unique genetic mutations which may play a role in prognostication and management. To this end, we present the largest cohort of IMSCTs with genetic characterization in the literature from our multi-site institutional registry. A total of 93 IMSCT patient records were reviewed from the years 1999 to 2020. Out of these, 61 complied with all inclusion criteria, 14 of these patients had undergone genetic studies with 8 undergoing whole-genomic sequencing. Univariate analyses were used to assess any factors associated with progression-free survival (PFS) using the Cox proportional hazards model. Firth’s penalized likelihood approach was used to account for the low event rates. Fisher’s exact test was performed to compare whole-genome analyses and specific gene mutations with progression. PFS (months) was given as a hazard ratio. Only the absence of copy neutral loss of heterozygosity (LOH) was shown to be significant (0.05, p = 0.008). Additionally, higher risk of recurrence/progression was associated with LOH (p = 0.0179). Our results suggest LOH as a genetic predictor of shorter progression-free survival, particularly within ependymoma and glioblastoma tumor types. Further genomic research with larger multi-institutional datasets should focus on these mutations as possible prognostic factors.",20726694,ONCOLOGY
10.3389/fonc.2023.1296948,T-cell receptor determinants of response to chemoradiation in locally-advanced HPV16-driven malignancies,"Background: The effect of chemoradiation on the anti-cancer immune response is being increasingly acknowledged; however, its clinical implications in treatment responses are yet to be fully understood. Human papillomavirus (HPV)-driven malignancies express viral oncogenic proteins which may serve as tumor-specific antigens and represent ideal candidates for monitoring the peripheral T-cell receptor (TCR) changes secondary to chemoradiotherapy (CRT).Methods: We performed intra-tumoral and pre- and post-treatment peripheral TCR sequencing in a cohort of patients with locally-advanced HPV16-positive cancers treated with CRT. An in silico computational pipeline was used to cluster TCR repertoire based on epitope-specificity and to predict affinity between these clusters and HPV16-derived epitopes.Results: Intra-tumoral repertoire diversity, intra-tumoral and post-treatment peripheral CDR3β similarity clustering were predictive of response. In responders, CRT triggered an increase peripheral TCR clonality and clonal relatedness. Post-treatment expansion of baseline peripheral dominant TCRs was associated with response. Responders showed more baseline clustered structures of TCRs maintained post-treatment and displayed significantly more maintained clustered structures. When applying clustering by TCR-specificity methods, responders displayed a higher proportion of intra-tumoral TCRs predicted to recognise HPV16 peptides.Conclusions: Baseline TCR characteristics and changes in the peripheral T-cell clones triggered by CRT are associated with treatment outcome. Maintenance and boosting of pre-existing clonotypes are key elements of an effective anti-cancer immune response driven by CRT, supporting a paradigm in which the immune system plays a central role in the success of CRT in current standard-of-care protocols.",2234943X,ONCOLOGY
10.3390/ejihpe14020018,Academic Motivation of Students Experiencing Person-Environment Misfit in Social Work Educational Settings: The Role of Social Dominance Orientation,"Interweaving social dominance, person-environment fit, and self-determination theories, the present study sought to understand whether the attrition between students’ levels of social dominance orientation and the hierarchy-attenuating function of the social work faculty in which they study may influence students’ academic motivational pathways. A total of 221 undergraduate social work students participated in the study and completed a self-report questionnaire. Participants’ social dominance orientation, person-environment misfit, and academic intrinsic and extrinsic motivation were measured. Results indicated that students’ social dominance orientation was associated with an external rather than an internal regulation of their academic motivation, mediated by their perceived person-environment misfit. For those students who personally support group-based inequalities, exposure to hierarchy-attenuating contexts would lead to regulating their academic behavior toward the pursuit of extrinsic (vs. intrinsic) goals, that is, studying to gain financial benefits and social prestige, in accordance with the pursuit of their beliefs of social dominance.",22549625,PSYCHOLOGY
10.3390/cancers16030605,Lung Resection for Non-Small Cell Lung Cancer following Bronchoscopic Lung Volume Reduction for Heterogenous Emphysema,"Bronchoscopic lung volume reduction (BLVR) is a minimally invasive treatment for emphysema. Lung cancer may be associated with emphysema due to common risk factors. Thus, a growing number of patients undergoing BLVR may develop lung cancer. Herein, we evaluated the effects of lung resection for non-small cell lung cancer in patients undergoing BLVR. The clinical data of patients undergoing BLVR followed by lung resection for NSCLC were retrospectively reviewed. For each patient, surgical and oncological outcomes were recorded to define the effects of this strategy. Eight patients were included in our series. In all cases but one, emphysema was localized within upper lobes; the tumor was detected during routine follow-up following BLVR and it did not involve the treated lobe. The comparison of pre- and post-BLVR data showed a significant improvement in FEV1 (29.7 ± 4.9 vs. 33.7 ± 6.7, p = 0.01); in FVC (28.5 ± 6.6 vs. 32.4 ± 6.1, p = 0.01); in DLCO (31.5 ± 4.9 vs. 38.7 ± 5.7, p = 0.02); in 6MWT (237 ± 14 m vs. 271 ± 15 m, p = 0.01); and a reduction in RV (198 ± 11 vs. 143 ± 9.8, p = 0.01). Surgical resection of lung cancer included wedge resection (n = 6); lobectomy (n = 1); and segmentectomy (n = 1). No major complications were observed and the comparison of pre- and post-operative data showed no significant reduction in FEV1% (33.7 ± 6.7 vs. 31.5 ± 5.3; p = 0.15) and in DLCO (38.7 ± 5.7 vs. 36.1 ± 5.4; p = 0.15). Median survival was 35 months and no cancer relapses were observed. The improved lung function obtained with BLVR allowed nonsurgical candidates to undergo lung resection for lung cancer.",20726694,ONCOLOGY
10.3389/fonc.2023.1225116,FI-CEUS: a solution to improve the diagnostic accuracy in MRI LI-RADS-indeterminate (LR-3/4) FLLs at risk for HCC,"ObjectiveTo evaluate the diagnostic accuracy of fusion imaging contrast-enhanced ultrasound (FI-CEUS) of magnetic resonance imaging (MRI) LI-RADS-indeterminate (LR-3/4) and conventional ultrasound undetected focal liver lesions (FLLs) in patients at risk for hepatocellular carcinoma (HCC).MethodsBetween February 2020 and July 2021, 71 FLLs in 63 patients were registered for diagnostic performance evaluation respectively for ultrasound-guided thermal ablation evaluation in this retrospective study. Diagnostic performance regarding FLLs was compared between FI-CEUS and contrast-enhanced MRI (CE-MRI).ResultsFor diagnostic performance evaluation, among 71 lesions in 63 patients, the diagnostic efficacy of FI-CEUS with LI-RADS was significantly higher than that of CE-MRI (P < 0.05) in both overall and hierarchical comparison (except for the group with lesion diameter ≥2 cm). For malignant lesions, the proportion of arterial phase hyperenhancement (APHE) and washout on FI-CEUS was higher than that on CE-MRI (P < 0.05).ConclusionFI-CEUS has a high value in the precise qualitative diagnosis of small FLLs (<2 cm) of MRI LI-RADS-indeterminate diagnosis (LR-3/4) that are undetected by conventional ultrasound in patients at risk for HCC and can be a good supplementary CE-MRI diagnostic method for thermal ablation evaluation.",2234943X,ONCOLOGY
10.1186/s40594-023-00461-4,Can training and apprentice programs in STEM increase worker life satisfaction and optimism?,"Background: Despite the significant relationship between life satisfaction and education, less is known about the connection between life satisfaction and informal learning in the context of training and apprenticeship programs. This paper examines the influence of the LaunchCode program, a novel training and apprentice program in STEM, on participant’s life satisfaction and optimism. We also explore mediating roles of STEM employment and earnings, as well as moderating role of participants’ educational attainment levels. Results: We find high life satisfaction and optimism among those who completed both the training course and the apprenticeship component. In addition, we find a significant mediation effect of STEM employment on the relationships between program participation and current life satisfaction, as well as optimism, among the apprenticeship completers. Finally, we find a significant moderation effect of one’s education level on the relationship between program completion and finding a STEM job, such that participants with a college degree are more likely to secure STEM employment through coursework alone. Conclusions: Our findings highlight the significance of apprenticeships in increasing life satisfaction and optimism, as well as the importance of STEM employment in explaining the significant effect of apprenticeships on life satisfaction and optimism. These findings suggest that what people do for a living is more important than how much they earn. However, while apprenticeships may offer an alternative route to the labor market, education may still facilitate connections to STEM employment in the absence of an apprenticeship.",21967822,EDUCATION
10.3389/fonc.2024.1320766,Antibody-mediated targeting of Claudins in cancer,"Tight junctions (TJs) are large intercellular adhesion complexes that maintain cell polarity in normal epithelia and endothelia. Claudins are critical components of TJs, forming homo- and heteromeric interaction between adjacent cells, which have emerged as key functional modulators of carcinogenesis and metastasis. Numerous epithelial-derived cancers display altered claudin expression patterns, and these aberrantly expressed claudins have been shown to regulate cancer cell proliferation/growth, metabolism, metastasis and cell stemness. Certain claudins can now be used as biomarkers to predict patient prognosis in a variety of solid cancers. Our understanding of the distinct roles played by claudins during the cancer progression has progressed significantly over the last decade and claudins are now being investigated as possible diagnostic markers and therapeutic targets. In this review, we will summarize recent progress in the use of antibody-based or related strategies for targeting claudins in cancer treatment. We first describe pre-clinical studies that have facilitated the development of neutralizing antibodies and antibody-drug-conjugates targeting Claudins (Claudins-1, -3, -4, -6 and 18.2). Next, we summarize clinical trials assessing the efficacy of antibodies targeting Claudin-6 or Claudin-18.2. Finally, emerging strategies for targeting Claudins, including Chimeric Antigen Receptor (CAR)-T cell therapy and Bi-specific T cell engagers (BiTEs), are also discussed.",2234943X,ONCOLOGY
10.1007/s00432-023-05603-3,A subregion-based RadioFusionOmics model discriminates between grade 4 astrocytoma and glioblastoma on multisequence MRI,"Purpose: To explore a subregion-based RadioFusionOmics (RFO) model for discrimination between adult-type grade 4 astrocytoma and glioblastoma according to the 2021 WHO CNS5 classification. Methods: 329 patients (40 grade 4 astrocytomas and 289 glioblastomas) with histologic diagnosis was retrospectively collected from our local institution and The Cancer Imaging Archive (TCIA). The volumes of interests (VOIs) were obtained from four multiparametric MRI sequences (T1WI, T1WI + C, T2WI, T2-FLAIR) using (1) manual segmentation of the non-enhanced tumor (nET), enhanced tumor (ET), and peritumoral edema (pTE), and (2) K-means clustering of four habitats (H1: high T1WI + C, high T2-FLAIR; (2) H2: high T1WI + C, low T2-FLAIR; (3) H3: low T1WI + C, high T2-FLAIR; and (4) H4: low T1WI + C, low T2-FLAIR). The optimal VOI and best MRI sequence combination were determined. The performance of the RFO model was evaluated using the area under the precision-recall curve (AUPRC) and the best signatures were identified. Results: The two best VOIs were manual VOI3 (putative peritumoral edema) and clustering H34 (low T1WI + C, high T2-FLAIR (H3) combined with low T1WI + C and low T2-FLAIR (H4)). Features fused from four MRI sequences ( $${F}_{seq}^{\mathrm{1,2},\mathrm{3,4}}$$ F seq 1 , 2 , 3 , 4 achieved the AUPRC of 0.972 (VOI3) and 0.976 (H34) in the primary cohort (p = 0.905), and 0.971 (VOI3) and 0.974 (H34) in the testing cohort (p = 0.402). Conclusion: The performance of subregions defined by clustering was comparable to that of subregions that were manually defined. Fusion of features from the edematous subregions of multiple MRI sequences by the RFO model resulted in differentiation between grade 4 astrocytoma and glioblastoma.",14321335,ONCOLOGY
10.3389/fpsyg.2024.1349353,"Starting fresh: a mixed method study of follower job satisfaction, trust, and views of their leader’s behavior","Introduction The leadership literature has been dominated by the study of broad styles rather than the identification of specific key behaviors. To address this deficiency, a mixed method approach was utilized to explore how follower behavioral descriptions of their leaders would relate to potential outcomes of trust in that leader and job satisfaction. Methods Data were collected from 273 hospital direct reports of 44 managers. They were asked to first describe the leadership approach of their managers in their own words, and then complete quantitative measures of the two potential outcomes. Results The qualitative responses were coded into nine leadership behavior themes listed here in order from most to least often mentioned: Kindness, Supportive, Open to Input, Allow Autonomy, Engage with Team, Transparency, Fairness, Professionalism, Hold Accountable. All behavior themes related significantly to trust of the leader, with three themes relating significantly to job satisfaction (Transparency, Fairness, and Professionalism). Discussion These results provide a more specific view of leader behavior than does the typical style approach.",16641078,PSYCHOLOGY
10.3390/educsci14030220,Challenges Faced by Students with Special Needs in Primary Education during Online Teaching,"This study investigates the psychological, educational, and technological difficulties faced by primary education students with special needs during online teaching. An interpretative phenomenological analysis was used for the qualitative analysis of data obtained through semi-structured interviews with twenty-two (22) teachers in primary education at a European country. The results revealed that their students showed negative emotions and behaviour. Those diagnosed with autism and learning disabilities had difficulty concentrating in class, while those with sensory disabilities had epileptic instances. Students with mild mental retardation in particular found it difficult to use digital tools. Many problems, however, are due to the lack of infrastructure and digital skills, as well as proper preparation of teachers for online teaching. Therefore, students and teachers should be equipped with the necessary digital skills, specialised digital tools and accessible open educational resources (OER) in order to effectively participate in online education.",22277102,EDUCATION
10.1186/s40359-024-01597-w,The effect of working memory training on test anxiety symptoms and attentional control in adolescents,"Objective: The percentage of adolescents with test anxiety is increasing rapidly. Working memory (WM) training has been demonstrated to reduce anxiety levels and enhance attentional control in individuals. Therefore, we investigated whether adaptive dual n-back WM training could lower test anxiety level and improve attentional control in adolescents. Methods: Forty adolescents were allocated to either adaptive dual n-back WM training (n = 21) or non-adaptive dual 1-back WM training (n = 19) for 10 days. The Test Anxiety Scale was applied to measure individuals’ test anxiety symptoms. The Attentional Control Scale (ACS), the flanker task, and the Go/Nogo task were used to measure attentional control. Results: Compared with the control group, the training group reported significantly relief of test anxiety symptoms; however, there were no significant differences between the two groups in pre-to-post changes in ACS scores or performance on the flanker task and Go/Nogo task. Conclusion: In sum, adaptive dual n-back WM training effectively reduced adolescents’ level of test anxiety but did not improve their attentional control.",20507283,PSYCHOLOGY
10.3389/fpsyg.2024.1269954,Why teachers do (or do not) implement recommended teaching practices? An application of the theory of planned behavior,"Introduction In Luxembourg, competency-based practices (CBP), differentiated instruction (DI), and formative assessment (FA) have been imposed by the 2009 school law. Referring to the Theory of Planned Behavior (TPB), this study examined factors influencing the implementation of these practices in classrooms. Methods Teachers participated in an online survey assessing their attitudes, subjective norm, perception of behavioral control, intention, and pedagogical practices regarding CBP, DI, or FA. Measurement models were used in structural equation models testing the TPB. Results If the main relationships postulated by the theory were confirmed, some inconstancies were observed depending on the targeted practices. Structural equation TPB models controlling for gender, experience, teaching level, and socio-economic level of the school population explained between 20 and 45% of the variance in teachers’ practices, and between 65 and 75% of the variance in teachers’ intention to use these practices. Discussion The relevance of the TPB for studying teaching practices and implications for professional training are discussed.",16641078,PSYCHOLOGY
10.1007/s00432-024-05648-y,Psoralen: a narrative review of current and future therapeutic uses,"Psoralen is a family of naturally occurring photoactive compounds found in plants that acquire potential cytotoxicity when activated by specific frequencies of electromagnetic waves. Psoralens penetrate the phospholipid cellular membranes and insert themselves between the pyrimidines of deoxyribonucleic acid (DNA). Psoralens are initially biologically inert and acquire photoreactivity when exposed to certain classes of electromagnetic radiation, such as ultraviolet light. Once activated, psoralens form mono- and di-adducts with DNA, leading to marked cell apoptosis. This apoptotic effect is more pronounced in tumor cells due to their high rate of cell division. Moreover, photoactivated psoralen can inhibit tyrosine kinase signaling and influence the immunogenic properties of cells. Thus, the cytotoxicity of photoactivated psoralen holds promising clinical applications from its immunogenic properties to potential anti-cancer treatments. This narrative review aims to provide an overview of the current understanding and research on psoralen and to explore its potential future pharmacotherapeutic benefits in specific diseases.",14321335,ONCOLOGY
10.1007/s44196-024-00433-8,Applying a Genetic Algorithm to Implement the Fuzzy-MACBETH Method in Decision-Making Processes,"This paper describes the development of an evolutionary algorithm for building cardinal scales based on the Fuzzy-MACBETH method. This method uses a triangular fuzzy numbers scale in the MACBETH method to incorporate the subjectivity of a semantic scale into mathematical modeling, which enables circumventing the cardinal inconsistency problem of the classical method, facilitating its application in complex contexts. A genetic algorithm is used in the fuzzy system developed here to build the basic fuzzy scale in a cardinally inconsistent decision matrix. The proposed technique is inspired by crossover and mutation genetic operations to explore potential solutions and obtain a cardinal scale aligned with the decision maker’s preferences. Finally, an illustrative example of the application of the proposed decision support system is presented. The results confirm that the FGA-MACBETH method aligns with the classical method. This study’s primary contribution is that circumventing the problem of cardinal inconsistency in a semantically consistent decision matrix enabled obtaining a cardinal scale without requiring the decision maker to redo his/her initial assessments.",18756883,AI
10.1007/s00432-024-05690-w,Retraction Note: The role of lymph node dissection in the surgical treatment of endometrial cancer patients (retrospective analysis),,14321335,ONCOLOGY
10.1007/s44196-024-00475-y,Retraction Note to: A Multilevel Fuzzy Evaluation of Cross-Border E-Commerce Profitability Model,,18756883,AI
10.3390/cancers16071333,Real-World Outcome and Prognostic Factors in MDS Patients Treated with Azacitidine—A Retrospective Analysis,"Azacitidine (AZA) is recognized as a vital drug used in the therapy of myelodysplastic syndromes (MDS) due to its beneficial effect on survival and quality of life. Nevertheless, many patients fail to respond to AZA treatment, as prognostic factors still are not identified. The present retrospective analysis included 79 patients with MDS treated with AZA as first-line therapy in a real-life setting. The percentage of patients with good, intermediate, and poor cytogenetics was 46.8%, 11.4%, and 34.2%, respectively. The overall response rate (complete remission [CR], partial remission [PR], and hematological improvement [HI]) was 24%. The CR, PR, and HI rates were 13.9%, 2.5%, and 7.6%, respectively. Stable disease (SD) was documented in 40.5% of patients. The median overall survival (OS) and progression-free survival (PFS) were 17.6 and 14.96 months, respectively. Patients with ORR and SD had a significantly longer median OS (23.8 vs. 5.7 months, p = 0.0005) and PFS (19.8 vs. 3.5 months, p < 0.001) compared to patients who did not respond to AZA. In univariate analysis, only an unfavorable cytogenetic group was a prognostic factor of a lower response rate (p = 0.03). In a multivariate model, older age (p = 0.047), higher IPSS (International Prognostic Scoring System) risk (p = 0.014), and higher IPSS-R cytogenetic risk (p = 0.004) were independent factors of shorter OS. Independent prognostic factors for shorter PFS were age (p = 0.001), IPSS risk (p = 0.02), IPSS cytogenetic risk (p = 0.002), and serum ferritin level (p = 0.008). The safety profile of AZA was predictable and consistent with previous studies. In conclusion, our study confirms the efficacy and safety of AZA in a real-world population and identifies potential biomarkers for response and survival.",20726694,ONCOLOGY
10.1186/s40594-024-00479-2,"Beyond performance, competence, and recognition: forging a science researcher identity in the context of research training","Background: Studying science identity has been useful for understanding students’ continuation in science-related education and career paths. Yet knowledge and theory related to science identity among students on the path to becoming a professional science researcher, such as students engaged in research at the undergraduate, postbaccalaureate, and graduate level, is still developing. It is not yet clear from existing science identity theory how particular science contexts, such as research training experiences, influence students’ science identities. Here we leverage existing science identity and professional identity theories to investigate how research training shapes science identity. We conducted a qualitative investigation of 30 early career researchers—undergraduates, postbaccalaureates, and doctoral students in a variety of natural science fields—to characterize how they recognized themselves as science researchers. Results: Early career researchers (ECRs) recognized themselves as either science students or science researchers, which they distinguished from being a career researcher. ECRs made judgments, which we refer to as “science identity assessments”, in the context of interconnected work-learning and identity-learning cycles. Work-learning cycles referred to ECRs’ conceptions of the work they did in their research training experience. ECRs weighed the extent to which they perceived the work they did in their research training to show authenticity, offer room for autonomy, and afford opportunities for epistemic involvement. Identity-learning cycles encompassed ECRs’ conceptions of science researchers. ECRs considered the roles they fill in their research training experiences and if these roles aligned with their perceptions of the tasks and traits of perceived researchers. ECRs’ identity-learning cycles were further shaped by recognition from others. ECRs spoke of how recognition from others embedded within their research training experiences and from others removed from their research training experiences influenced how they see themselves as science researchers. Conclusions: We synthesized our findings to form a revised conceptual model of science researcher identity, which offers enhanced theoretical precision to study science identity in the future. We hypothesize relationships among constructs related to science identity and professional identity development that can be tested in further research. Our results also offer practical implications to foster the science researcher identity of ECRs.",21967822,EDUCATION
10.3390/ejihpe14040058,Emotional Regulation Mechanisms of University Students in Group Work Situations,"Universities are active agents of social change through knowledge, providing citizens with the necessary abilities to face professional challenges. This work aims to evaluate and analyse the adaptation of emotional regulation in learning situations of group work in virtual and hybrid (virtual and presential) environments, of a group of students of Physical Activity and Sport Sciences belonging to a Chilean university and a Spanish university. Method: A total of 107 students from a Chilean university and a Spanish university, all of them enrolled in the degree in Physical Activity and Sport Sciences, participated in the study. The instrument used was the Adaptative Instrument for Regulation of Emotions questionnaire. Results: The analysis of the data shows that there are some significant differences (p ≤ 0.05), between the groups of students who worked virtually and those who worked in hybrid situations, in the aspects related to personal motivations (learn from my classmates, not to disappoint my working group, and enjoying the experience of working in a group). The students who worked online resolved conflicts mainly through individual regulation mechanisms with significant differences in relation to the students who worked in hybrid mode. No significant differences were found in the socioemotional challenges or in the balance of the metacognitive experience. Conclusion: The group that worked in hybrid learning valued group purposes over personal purposes and used the social regulation mechanism over individual regulation in conflict resolution. On the other hand, the group that worked virtually valued group and personal purposes equally and used the mechanism of individual regulation and social regulation to solve difficulties. Differences between students who worked in virtual and hybrid environments may be due to greater social interaction and group dynamics in hybrid environments, as well as differences in culture and access to resources and technology.",22549625,PSYCHOLOGY
10.1186/s40594-024-00481-8,Science teacher identity research: a scoping literature review,"Science teacher identity significantly influences teacher professional development, practices, and attitudes, which in turn impacts student learning outcomes. With an increased number of studies on science teacher identity over the past two decades, there is a need for a scoping literature review that holistically maps the current state of science teacher identity research and identifies future research directions. This scoping literature review identified 48 empirical articles on science teacher identity, published from 2000 to 2023, in peer-reviewed journals and examined the studies’ (a) characteristics; (b) theoretical frameworks on identity; (c) definitions of science teacher identity; and (d) major findings. Specifically, there is a need for precise conceptualizations and definitions of science teacher identity; this clarity will facilitate valid, reliable, and fair instruments to capture the relatively stable facets of science teacher identity at a given moment in a given context in order to longitudinally track science teacher identity development. This scoping review identifies both progress and gaps in the current literature and future directions for synergistic, cross-cultural international research on science teacher identity.",21967822,EDUCATION
10.3390/ejihpe14040061,Assessing We-Disease Appraisals of Health Problems: Development and Validation of the We-Disease Questionnaire,"In couples dealing with health problems, we-disease appraisals can influence dyadic coping strategies to alleviate distress. This study describes the development and validation of a self-report scale to assess we-disease appraisals of health problems. The newly developed We-Disease Questionnaire (WDQ) was administered in three samples: parents of children with type 1 diabetes (n = 240) or cancer (n = 125) and individuals with visual impairment and their partners (n = 216). Reliability was measured by coefficient omega. To assess construct validity, correlations with other measures of individual and dyadic adjustment were examined. Descriptive statistics across all samples were compared. A 4-item version of the WDQ demonstrated good reliability and validity and showed meaningful associations with established scales. We-disease appraisals were highest among parents of children with cancer and lowest among couples with visual impairment. The WDQ is a reliable and valid measure that can be used across different health problems.",22549625,PSYCHOLOGY
10.3389/fonc.2024.1373127,Comparison of chemotherapy and chidamide combined with chemotherapy in patients with untreated angioimmunoblastic T-cell lymphoma,"Background Angioimmunoblastic T-cell lymphoma (AITL) is characterized by high recurrence rates and poor prognosis, and effective first-line treatment is lacking. Recently, histone deacetylase inhibitors (HDACi), such as chidamide, have been found to induce durable remissions in AITL patients. Methods Patients with untreated AITL from March 2015 to March 2023 were retrospectively collected and divided into chemotherapy (ChT) group and chidamide combined with chemotherapy (C-ChT) group based on the first-line treatment received. The comparison of efficacy and safety between the two groups was conducted. Results 86 patients with newly diagnosed AITL were enrolled, in which 35 patients were in the ChT group and 51 in the C-ChT group. The objective response rate (ORR) of C-ChT group was significantly higher than that of ChT group (84.3% vs. 60%, P= 0.011), and had superior progression-free survival (PFS) (27 months vs. 12 months, P= 0.025). However, no significant difference in overall survival (OS) was observed between the two groups (P= 0.225). In addition, the responding patients who received autologous stem cell transplantation (ASCT) had superior PFS compared to those who did not (P= 0.015). Conclusions Compared with ChT regimen, C-ChT regimen was well tolerated and had superior ORR and PFS in patients with untreated AITL. ASCT may contribute to longer PFS in remission patients.",2234943X,ONCOLOGY
10.1007/s44196-024-00453-4,Leveraging Model Scaling and Butterfly Network in the Bone Scan Image Segmentation,"As we all know, cancer is one of the leading causes of death worldwide and the second leading cause of death overall. This is why regular screenings or health checks are necessary to detect cancer lesions early. Since bone scan images have become the primary means of detecting the emergence of cancer lesions on bone, high segmentation accuracy is essential for establishing the model of some predefined regions in bone scan images where cancer metastasis was predicted to appear. Consequently, robust localization and identification of the specific region in bone scan images are required for automated metastasis detection. To this end, we propose Efficient-BtrflyNet, a new deep learning-based architecture for skeleton segmentation of whole-body bone scan images. The proposed architecture exploits the benefits of EfficientNet’s model scaling and the encoder–decoder design of butterfly-type networks. We added EfficientNetB7 to the encoder section to obtain more specific features. The proposed architecture simultaneously processes anterior and posterior whole-body bone scan images. Using 37 bone scan images, we evaluated the performance of our proposed skeleton segmentation system using the Dice score. Efficient-BtrflyNet achieves superior segmentation performance compared to the existing representative method.",18756883,AI
10.3390/ai5020028,Artificial Intelligence in Healthcare: ChatGPT and Beyond,"Artificial intelligence (AI), the simulation of human intelligence processes by machines, is having a growing impact on healthcare",26732688,AI
10.3390/ai5020029,Development of an Attention Mechanism for Task-Adaptive Heterogeneous Robot Teaming,"The allure of team scale and functional diversity has led to the promising adoption of heterogeneous multi-robot systems (HMRS) in complex, large-scale operations such as disaster search and rescue, site surveillance, and social security. These systems, which coordinate multiple robots of varying functions and quantities, face the significant challenge of accurately assembling robot teams that meet the dynamic needs of tasks with respect to size and functionality, all while maintaining minimal resource expenditure. This paper introduces a pioneering adaptive cooperation method named inner attention (innerATT), crafted to dynamically configure teams of heterogeneous robots in response to evolving task types and environmental conditions. The innerATT method is articulated through the integration of an innovative attention mechanism within a multi-agent actor–critic reinforcement learning framework, enabling the strategic analysis of robot capabilities to efficiently form teams that fulfill specific task demands. To demonstrate the efficacy of innerATT in facilitating cooperation, experimental scenarios encompassing variations in task type (“Single Task”, “Double Task”, and “Mixed Task”) and robot availability are constructed under the themes of “task variety” and “robot availability variety.” The findings affirm that innerATT significantly enhances flexible cooperation, diminishes resource usage, and bolsters robustness in task fulfillment.",26732688,AI
10.1007/s44196-024-00502-y,Alzheimer’s Disease Detection via Multiscale Feature Modelling Using Improved Spatial Attention Guided Depth Separable CNN,"Early detection of Alzheimer's disease (AD) is critical due to its rising prevalence. AI-aided AD diagnosis has grown for decades. Most of these systems use deep learning using CNN. However, a few concerns must be addressed to identify AD: a. there is a lack of attention paid to spatial features; b. there is a lack of scale-invariant feature modelling; and c. the convolutional spatial attention block (C-SAB) mechanism is available in the literature, but it exploits limited feature sets from its input features to obtain a spatial attention map, which needs to be enhanced. The suggested model addresses these issues in two ways: through a backbone of multilayers of depth-separable CNN. Firstly, we propose an improved spatial convolution attention block (I-SAB) to generate an enhanced spatial attention map for the multilayer features of the backbone. The I-SAB, a modified version of the C-SAB, generates a spatial attention map by combining multiple cues from input feature maps. Such a map is forwarded to a multilayer of depth-separable CNN for further feature extraction and employs a skip connection to produce an enhanced spatial attention map. Second, we combine multilayer spatial attention features to make scale-invariant spatial attention features that can fix scale issues in MRI images. We demonstrate extensive experimentation and ablation studies using two open-source datasets, OASIS and AD-Dataset. The recommended model outperforms existing best practices with 99.75% and 96.20% accuracy on OASIS and AD-Dataset. This paper also performed a domain adaptation test on the OASIS dataset, which obtained 83.25% accuracy.",18756883,AI
10.1007/s00432-024-05767-6,Construction of a prognostic model for extensive-stage small cell lung cancer patients undergoing immune therapy in northernmost China and prediction of treatment efficacy based on response status at different time points,"Background and purpose: Recently, the emergence of immune checkpoint inhibitors has significantly improved the survival of patients with extensive-stage small cell lung cancer. However, not all patients can benefit from immunotherapy; therefore, there is an urgent need for precise predictive markers to screen the population for the benefit of immunotherapy. However, single markers have limited predictive accuracy, so a comprehensive predictive model is needed to better enable precision immunotherapy. The aim of this study was to establish a prognostic model for immunotherapy in ES-SCLC patients using basic clinical characteristics and peripheral hematological indices of the patients, which would provide a strategy for the clinical realization of precision immunotherapy and improve the prognosis of small cell lung cancer patients. Methods: This research retrospectively collected data from ES-SCLC patients treated with PD-1/PD-L1 inhibitors between March 1, 2019, and October 31, 2022, at Harbin Medical University Cancer Hospital. The study data was randomly split into training and validation sets in a 7:3 ratio. Variables associated with patients’ overall survival were screened and modeled by univariate and multivariate Cox regression analyses. Models were presented visually via Nomogram plots. Model discrimination was evaluated by Harrell’s C index, tROC, and tAUC. The calibration of the model was assessed by calibration curves. In addition, the clinical utility of the model was assessed using a DCA curve. After calculating the total risk score of patients in the training set, patients were stratified by risk using percentile partitioning. The Kaplan–Meier method was used to plot OS and PFS survival curves for different risk groups and response statuses at different milestone time points. Differences in survival time groups were compared using the chi-square test. Statistical analysis software included R 4.1.2 and SPSS 26. Results: This study included a total of 113 ES-SCLC patients who received immunotherapy, including 79 in the training set and 34 in the validation set. Six variables associated with poorer OS in patients were screened by Cox regression analysis: liver metastasis (P = 0.001), bone metastasis (P = 0.013), NLR < 2.14 (P = 0.005), LIPI assessed as poor (P < 0.001), PNI < 51.03 (P = 0.002), and LDH ≥ 146.5 (P = 0.037). A prognostic model for immunotherapy in ES-SCLC patients was constructed based on the above variables. The Harrell’s C-index in the training and validation sets of the model was 0.85 (95% CI 0.76–0.93) and 0.88 (95% CI 0.76–0.99), respectively; the AUC values corresponding to 12, 18, and 24 months in the tROC curves of the training set were 0.745, 0.848, and 0.819 in the training set and 0.858, 0.904 and 0.828 in the validation set; the tAUC curves show that the overall tAUC is > 0.7 and does not fluctuate much over time in both the training and validation sets. The calibration plot demonstrated the good calibration of the model, and the DCA curve indicated that the model had practical clinical applications. Patients in the training set were categorized into low, intermediate, and high risk groups based on their predicted risk scores in the Nomogram graphs. In the training set, 52 patients (66%) died with a median OS of 15.0 months and a median PFS of 7.8 months. Compared with the high-risk group (median OS: 12.3 months), the median OS was significantly longer in the intermediate-risk group (median OS: 24.5 months, HR = 0.47, P = 0.038) and the low-risk group (median OS not reached, HR = 0.14, P = 0.007). And, the median PFS was also significantly prolonged in the intermediate-risk group (median PFS: 12.7 months, HR = 0.45, P = 0.026) and low-risk group (median PFS not reached, HR = 0.12, P = 0.004) compared with the high-risk group (median PFS: 6.2 months). Similar results were obtained in the validation set. In addition, we observed that in real-world ES-SCLC patients, at 6 weeks after immunotherapy, the median OS was significantly longer in responders than in non-responders (median OS: 19.5 months vs. 11.9 months, P = 0.033). Similar results were obtained at 12 weeks (median OS: 20.7 months vs 11.9 months, P = 0.044) and 20 weeks (median OS: 20.7 months vs 11.7 months, P = 0.015). Finally, we found that in the real world, ES-SCLC patients without liver metastasis (P = 0.002), bone metastasis (P = 0.001) and a total number of metastatic organs < 2 (P = 0.002) are more likely to become long-term survivors after receiving immunotherapy. Conclusion: This study constructed a new prognostic model based on basic patient clinical characteristics and peripheral blood indices, which can be a good predictor of the prognosis of immunotherapy in ES-SCLC patients; in the real world, the response status at milestone time points (6, 12, and 20 weeks) can be a good indicator of long-term survival in ES-SCLC patients receiving immunotherapy.",14321335,ONCOLOGY
10.1186/s40594-024-00476-5,The impact of changing engineering perceptions on women’s attitudes and behavioral intentions towards engineering pursuits,"Background: Women are underrepresented in the field of engineering within academic and professional settings. Based upon premises outlined by social role theory and goal congruity theory, a key factor that contributes to this underrepresentation is a gendered societal belief that there is a disconnect between engineering (seen as more agentic, or self-oriented) and women’s values and abilities (which are believed to be more communal, or other-oriented). While there is evidence that this perceived disconnect influences women’s pursuit of engineering, the extent to which an intervention could realistically counter these perceptions at key points along the engineering pathway has not been explored. Across two studies, we examine the impact of a communal-based intervention (in which we frame engineering majors and careers in more, though not exclusively, communally oriented ways) on women’s engineering-related attitudes and behavioral intentions at two points along the academic-employment pathway: women’s major selection and women’s job selection. Results: Study 1 found that women with undeclared majors had more positive attitudes (confidence and interest) towards engineering majors when engineering major descriptions were framed as more communal versus more agentic. However, there was no impact on their behavioral intentions to pursue the major. Study 2 found that women with engineering majors were more confident in their ability to be successful in a job role and were more likely to apply when the job role was framed as more communal as compared to more agentic. However, they did not indicate greater interest in the job role. Conclusions: Testing this intervention on relevant populations advances the literature by providing greater evidence for the potential of such an intervention to meaningfully address women’s underrepresentation at multiple points along the engineering pathway. Furthermore, this study provides evidence that a messaging-based intervention is impactful with a realistic representation of engineering as both an agentic and communally oriented field, which ensures that the retention of those attracted to the field is not negatively impacted by idealistic messaging. While addressing women’s pursuit of engineering is important, work must continue to seek ways to always improve women’s experience in engineering contexts as well.",21967822,EDUCATION
10.3389/fpsyg.2024.1389935,Beauty ideals and body positivity: a qualitative investigation of young women’s perspectives on social media content in China,"Much of the existing knowledge regarding the impact of beauty ideals and body positive social media content on women’s body image is based on the Western cultural context. This limits our understanding of the issue in other cultures, such as China, among others. Therefore, to address this gap, this study examined young Chinese women’s perspectives on beauty ideals and body positivity in social media through a qualitative investigation. Female university students in China (N = 24) participated in individual interviews. A thematic analysis revealed four primary themes: (1) characteristics of mainstream beauty ideals in Chinese social media; (2) impact of beauty ideals on young women; (3) perspectives on the content and roles of body positivity; (4) influences of body positive social media content on young women. These findings indicate that young Chinese women are aware of the beauty ideals in social media and their negative impact on their body image. Furthermore, young Chinese women generally expressed a favorable outlook on body positivity but noted its limitations.",16641078,PSYCHOLOGY
10.1007/s00432-024-05859-3,FERMT1 suppression induces anti-tumor effects and reduces stemness in glioma cancer cells,"Objective: Glioma is a leading cause of mortality worldwide, its recurrence poses a major challenge in achieving effective treatment outcomes. Cancer stem cells (CSCs) have emerged as key contributors to tumor relapse and chemotherapy resistance, making them attractive targets for glioma cancer therapy. This study investigated the potential of FERMT1 as a prognostic biomarker and its role in regulating stemness through cell cycle in glioma. Methods: Using data from TCGA-GBM, GSE4290, GSE50161 and GSE147352 for analysis of FERMT1 expression in glioma tissues. Then, the effects of FERMT1 knockdown on cell cycle, proliferation, sphere formation ability, invasion and migration were investigated. The influences of FERMT1 on expression of glycolysis-related proteins and levels of ATP, glucose, lactate and G6PDH were also explored. Furthermore, the effects of FERMT1 knockdown on cellular metabolism were evidenced. Results: Significant upregulation of FERMT1 in glioma tissues was observed. Silencing FERMT1 not only affected the cell cycle but also led to a notable reduction in proliferation, invasion and migration. The expression of glycolysis-associated proteins including GLUT1, GLUT3, GLUT4, and SCO2 were reduced by FERMT1 knockdown, resulted in increased ATP and glucose as well as decreased lactic acid and G6PDH levels. FERMT1 knockdown also inhibited cellular metabolism. Moreover, FERMT1 knockdown significantly reduced sphere diameter, along with inhibiting the expression of transcription factors associated with stemness in glioma cells. Conclusion: These findings demonstrated that FERMT1 could be an ideal target for the advancement of innovative strategies against glioma treatment via modulating cellular process involved in stemness regulation and metabolism.",14321335,ONCOLOGY
10.1186/s40594-024-00488-1,A microgenetic analysis of teachers’ learning through teaching,"Background: What and how teachers learn through teaching without external guidance has long been of interest to researchers. Yet limited research has been conducted to investigate how learning through teaching occurs. The microgenetic approach (Siegler and Crowley, American Psychologist 46:606–620, 1991) has been useful in identifying the process of student learning. Using this approach, we investigated the development of teacher knowledge through teaching as well as which factors hinder or promote such development. Results: Our findings suggest that teachers developed various components of teacher knowledge through teaching without external professional guidance. Further, we found that the extent to which teachers gained content-free or content-specific knowledge through teaching depended on their robust understanding of the concept being taught (i.e., content knowledge), the cognitive demand of the tasks used in teaching, and the lesson structure chosen (i.e., student centered vs. teacher centered). Conclusions: In this study, we explored teacher learning through teaching and identified the sources leading to such learning. Our findings underscore the importance of teachers’ robust understanding of the content being taught, the tasks used in teaching, and a lesson structure that promotes teachers’ learning through teaching on their own.",21967822,EDUCATION
10.3389/feduc.2024.1347052,Enhancing doctoral learning through virtual communities of practice: an autoethnographic perspective,"This article explores the role of virtual communities of practice in enhancing the doctoral experience, particularly in the contemporary digital era. The author emphasizes the multifaceted benefits, including elevating academic networking, optimizing knowledge management, and supporting the mental well-being of remote learners. The establishment of clear shared objectives, dynamic leadership, and a conducive environment for collaborative innovation are identified as key prerequisites for building successful virtual communities of practice. As remote doctoral education becomes more prevalent, virtual communities of practice not only facilitate academic engagement but also foster mutual support and advocacy among doctoral students. The researcher, as a final year PhD student employed autoethnography as a research method to offer an intimate and reflective exploration of her personal experiences within virtual communities of practice. This unique insider perspective adds depth to the discussion on elevating academic networking, optimizing knowledge management, and supporting the mental well-being of remote learners. Furthermore, her ongoing doctoral research focuses on the socialization process and the development of a sense of belonging among doctoral students. Motivated by her research topics, she commenced her doctoral studies during the epidemic and cultivated the practice of consistently maintaining a researcher’s reflection diary. This perspective article examines her diary, elucidating her experiences, opinions, and feelings. The researcher utilized a thematic approach to thoroughly analyze the author’s research diaries covering the period from December 2020 to August 2023. The article concludes by calling for further research into the professional identity development of doctoral students within virtual learning communities, exploring potential challenges and effective coping mechanisms to achieve inclusive practices in the complex and diverse digital era of academia.",2504284X,EDUCATION
10.3389/feduc.2024.1404076,Investigating how early academic performance and parental socio-economic status predict and explain successful completion of secondary education in Germany,"In educational sociology, it is of greatest interest to explain why some students are more successful than others and obtain higher educational qualifications or receive better grades, which can have long-lasting consequences. The present study compares the influence of early academic performance, which can be regarded as a proxy of overall intelligence, to the socio-economic status (SES) of the family, which measures how much a family can invest in the education of their offspring. Using large-scale German NEPS panel data (N = 5,208), the analyses test statistically how much variance of two outcome variables (acquisition of higher education eligibility and final grade) are explained by academic performance and SES; both measured approximately 9 years earlier at the beginning of secondary education. Dominance analyses reveal that performance has a larger influence (ca. 14% for both outcomes) than SES (ca. 8% for eligibility and ca. 4% for grades). Regression analyses show that high performance can better compensate for low SES than vice versa. These results indicate that performance is probably more relevant for academic success than the SES of one’s own family.",2504284X,EDUCATION
10.3390/educsci14080809,Teaching Experience as a Key Factor in Dealing with Digital Teaching Stress,"Digital pandemic stress among university faculty has become a key issue in the contemporary era, marked by the rapid transition to online teaching. This study conducts a quantitative investigation into the teaching experience as a key explanatory variable in explaining the levels of such stress. For this purpose, a validated instrument has been used, which has been answered by a sample of 1240 university professors. The results show that, although the participating professors do not express high self-concepts of their digital competence or professional aspects, they do not express high levels of digital stress due to the pandemic. However, strong divergences have been identified between the levels of digital pandemic stress of more experienced professors and those of younger professors. Specifically, more experienced professors report lower levels of stress than younger professors, although there are no significant differences in their respective digital competencies. Consequently, the results suggest that teaching experience mitigates teaching digital stress, even when this greater experience does not concur with greater digital competence. It has also been found that the evolution of ratings with teaching experience depends on whether the professor is a specialist in scientific–technical or humanistic–social areas. Specifically, professors in scientific–technical areas with 15 to 25 years of experience are those who suffer more digital stress. Moreover, the digital stress of professors in scientific–technical areas increases between 10 and 25 years of experience, while it decreases among professors with less than 10 years of experience. In contrast, among professors in humanistic–social areas, the trend in the evolution of digital stress is the opposite: it increases among those with less than 10 years of experience and decreases among those with more than 10 years of experience.",22277102,EDUCATION
10.1007/s44196-024-00607-4,MLAWSMOTE: Oversampling in Imbalanced Multi-label Classification with Missing Labels by Learning Label Correlation Matrix,"Missing labels in multi-label datasets are a common problem, especially for minority classes, which are more likely to occur. This limitation hinders the performance of classifiers in identifying and extracting information from minority classes. Oversampling is an effective method for addressing imbalanced multi-label problems by generating synthetic instances to create a class-balanced dataset. However, the existing oversampling algorithms mainly focus on the location of the generated data, and there is a lack of design on how to complete the labels of the synthetic data. To address this issue, we propose MLAWSMOTE, a synthetic data generation algorithm based on matrix factorization weights. We introduce a weak supervised learning method in the oversampling method, optimize the weights of features and labels by using label correlation, and iteratively learn the ideal label weights. The mapping relationship between features and labels is learned from the dataset and the label correlation matrix. The oversampling ratio is defined based on the discrepancy between observed labels and the ideal label of synthetic instances. It mitigates the impact of missing minority labels on the model’s predictions. The labeling of synthetic instances is performed based on label prediction, and the potential labeling distribution is complemented. Experimental results on multiple multi-label datasets under different label missing ratios demonstrate the effectiveness of the proposed method in terms of ACC, Hamming loss, MacroF1 and MicroF1. In the validation of the four classifiers, MacroF1 decreased by 24.78%, 17.81%, 3.8% and 19.56%, respectively, with the increase of label loss rate. After applying MLAWSMOTE only decreased by 15.79%, 13.63%, 3.78% and 15.21%.",18756883,AI
10.3389/feduc.2024.1433184,“It actually helped”: students’ perceptions of feedback helpfulness prior to and following a teacher professional learning intervention,"This study investigated the effects of a teacher professional learning intervention, underpinned by a student-centred model of feedback, on student perceptions of feedback helpfulness. The study was conducted in the context of primary education English writing in Queensland, Australia. No overall differences in feedback perceptions of students in 13 intervention and 9 comparison schools were identified following the intervention. However, more detailed analyses revealed significantly greater increases in perceived helpfulness among intervention group students for six feedback strategies. This suggests the intervention changed teachers’ feedback practices, enhancing student perceptions of feedback helpfulness. Student focus group data provided valuable qualitative insights into student feedback perceptions. Overall findings highlight the interrelatedness between feedback strategies across the feedback cycle for enhancing student learning.",2504284X,EDUCATION
10.1007/s44196-024-00608-3,Construction of Risk Prediction Models for Enterprise Finance Sharing Operations Using K-Means and C4.5 Algorithms,"The evaluation of financial sharing centres in enterprises typically relies on outdated financial data, lacks comprehensive assessment, and presents risks such as employee misconduct. To address these challenges, we propose a risk prediction model for enterprise financial sharing operations based on the K-means clustering algorithm for performance evaluation and the C4.5 algorithm for managing employee risks. Our approach enhances the accuracy and objectivity of performance evaluation while improving the efficiency of personnel risk management. Results indicate that the K-means algorithm classifies employee performance into five levels, facilitating comprehensive performance evaluation. Furthermore, through risk management optimisation, accuracy and recall rates increase to 0.905 and 0.890, respectively. The proposed risk prediction model achieves high accuracy rates of 90.5% and 92.4% in the training and test sets, respectively. Practical application of our methodology and model in A Group's financial sharing centre demonstrates their effectiveness and potential for enhancing the operation and management of enterprise financial sharing centres.",18756883,AI
10.3389/frai.2024.1424924,"A methodology for planning, implementation and evaluation of skills intelligence management – results of a design science project in technology organisations","Introduction: The evolving labour market requirements amidst digital transformation necessitate robust skills intelligence for informed decision-making and adaptability. Novel technologies such as Big Data, Machine Learning, and Artificial Intelligence have significant potential for enhancing skills intelligence.Methods: This study bridges the gap between theory and practice by designing a novel software artefact for skills intelligence management. With its systematic framework for identifying skills intelligence elements, an assessment instrument, and an implementation methodology, the artefact ensures a thorough approach to skills intelligence management.Results: The artefact was demonstrated in 11 organisations. Feedback collected from interviews, focus group sessions, and observations (N = 19) indicated that the artefact is a feasible starting point for implementing or systematising skills intelligence management. Participants suggested improvements but concurred that the systematic approach enhances skills intelligence data collection and quality.Discussion: The study shows that the artefact facilitates the application of advanced technologies in skills intelligence management. Additionally, it contributes a set of principles for effective skills intelligence management, fostering a broader conversation on this critical topic. Participants’ feedback underscores the artefact’s potential and provides a basis for further refinement and application in diverse organisational contexts.",26248212,AI
10.3390/cancers16162816,Analysis by TeloView® Technology Predicts the Response of Hodgkin’s Lymphoma to First-Line ABVD Therapy,"Classic Hodgkin’s lymphoma (cHL) is a curable cancer with a disease-free survival rate of over 10 years. Over 80% of diagnosed patients respond favorably to first-line chemotherapy, but few biomarkers exist that can predict the 15–20% of patients who experience refractory or early relapsed disease. To date, the identification of patients who will not respond to first-line therapy based on disease staging and traditional clinical risk factor analysis is still not possible. Three-dimensional (3D) telomere analysis using the TeloView® software platform has been shown to be a reliable tool to quantify genomic instability and to inform on disease progression and patients’ response to therapy in several cancers. It also demonstrated telomere dysfunction in cHL elucidating biological mechanisms related to disease progression. Here, we report 3D telomere analysis on a multicenter cohort of 156 cHL patients. We used the cohort data as a training data set and identified significant 3D telomere parameters suitable to predict individual patient outcomes at the point of diagnosis. Multivariate analysis using logistic regression procedures allowed for developing a predictive scoring model using four 3D telomere parameters as predictors, including the proportion of t-stumps (very short telomeres), which has been a prominent predictor for cHL patient outcome in a previously published study using TeloView® analysis. The percentage of t-stumps was by far the most prominent predictor to identify refractory/relapsing (RR) cHL prior to initiation of adriamycin, bleomycin, vinblastine, and dacarbazine (ABVD) therapy. The model characteristics include an AUC of 0.83 in ROC analysis and a sensitivity and specificity of 0.82 and 0.78 respectively.",20726694,ONCOLOGY
10.1186/s40359-024-01926-z,The moderating effect of altruism on the relationship between occupational stress and turnover intentions: a cross-sectional study of community rehabilitation workers in China,"Background: In China, community rehabilitation workers are facing a growing challenge related to heavy occupational stress, which is having an impact on employment turnover. Previous studies have explored the effect of the public service motivation of workers in “helping” jobs on occupational stress or turnover intention, but there is a lack of clarification of the impact of altruism on turnover intention in the case of complex pathways involving various factors. Methods: A stratified sampling method was used, and a total of 82 community rehabilitation workers who assist disabled people from 34 community health centres in Jiangmen city were included in the study from August to October 2022. The turnover intention, occupational stress, burnout, quality of life, altruism, and certain sociodemographic information of community rehabilitation workers were measured using a structured questionnaire. The partial least squares method was employed to construct and test the structural equation model. Results: Although altruism had no direct impact on occupational stress or turnover intention, altruism moderated the effect of occupational stress on burnout (βMod = −0.208) and quality of life (βMod = 0.230) and weakened the mediation of burnout and quality of life between occupational stress and turnover intention. Conclusions: This study proposes to address the dilemma of “strong function” and “weak specialty” in community rehabilitation services and to conduct positive psychological interventions for community rehabilitation workers through the guidance of altruistic values.",20507283,PSYCHOLOGY
10.3389/frai.2024.1431156,"Person-based design and evaluation of MIA, a digital medical interview assistant for radiology","Introduction: Radiologists frequently lack direct patient contact due to time constraints. Digital medical interview assistants aim to facilitate the collection of health information. In this paper, we propose leveraging conversational agents to realize a medical interview assistant to facilitate medical history taking, while at the same time offering patients the opportunity to ask questions on the examination.Methods: MIA, the digital medical interview assistant, was developed using a person-based design approach, involving patient opinions and expert knowledge during the design and development with a specific use case in collecting information before a mammography examination. MIA consists of two modules: the interview module and the question answering module (Q&A). To ensure interoperability with clinical information systems, we use HL7 FHIR to store and exchange the results collected by MIA during the patient interaction. The system was evaluated according to an existing evaluation framework that covers a broad range of aspects related to the technical quality of a conversational agent including usability, but also accessibility and security.Results: Thirty-six patients recruited from two Swiss hospitals (Lindenhof group and Inselspital, Bern) and two patient organizations conducted the usability test. MIA was favorably received by the participants, who particularly noted the clarity of communication. However, there is room for improvement in the perceived quality of the conversation, the information provided, and the protection of privacy. The Q&A module achieved a precision of 0.51, a recall of 0.87 and an F-Score of 0.64 based on 114 questions asked by the participants. Security and accessibility also require improvements.Conclusion: The applied person-based process described in this paper can provide best practices for future development of medical interview assistants. The application of a standardized evaluation framework helped in saving time and ensures comparability of results.",26248212,AI
10.3389/frai.2024.1384709,Deep learning models for the early detection of maize streak virus and maize lethal necrosis diseases in Tanzania,"Agriculture is considered the backbone of Tanzania’s economy, with more than 60% of the residents depending on it for survival. Maize is the country’s dominant and primary food crop, accounting for 45% of all farmland production. However, its productivity is challenged by the limitation to detect maize diseases early enough. Maize streak virus (MSV) and maize lethal necrosis virus (MLN) are common diseases often detected too late by farmers. This has led to the need to develop a method for the early detection of these diseases so that they can be treated on time. This study investigated the potential of developing deep-learning models for the early detection of maize diseases in Tanzania. The regions where data was collected are Arusha, Kilimanjaro, and Manyara. Data was collected through observation by a plant. The study proposed convolutional neural network (CNN) and vision transformer (ViT) models. Four classes of imagery data were used to train both models: MLN, Healthy, MSV, and WRONG. The results revealed that the ViT model surpassed the CNN model, with 93.1 and 90.96% accuracies, respectively. Further studies should focus on mobile app development and deployment of the model with greater precision for early detection of the diseases mentioned above in real life.",26248212,AI
10.3389/fonc.2024.1452559,Fibrosis to carcinogenesis: unveiling the causal dynamics between pulmonary fibrosis and lung cancer,"Background: Previous clinical evidence has shown a correlation between pulmonary fibrosis (PF) and lung cancer (LC), but their causal relationship remains unknown.Methods: This study utilized a bidirectional two-sample Mendelian randomization (MR) approach to explore the causal relationship between PF and LC, including its subtypes. Genetic data were obtained from the IEU and FinnGen Genome-Wide Association Studies (GWAS). SNPs with genome-wide significance were selected, and analyses were conducted using Inverse-Variance Weighted (IVW), MR Egger, and Weighted Median methods. The IVW results for various subtypes of lung cancer and PF were used in a meta-analysis to investigate the overall causal effect between PF and lung cancer. Sensitivity analysis was used for both MR and meta-analysis to investigate the robustness of the results.Results: The bidirectional MR analysis showed no significant causal relationship between PF and overall, LC or its subtypes, except for SCLC, which had a significant positive association (OR = 1.29, 95% CI 1.07-1.57, p = 0.009). The meta-analysis results indicated no overall causal effect (OR = 1.067, 95% CI: 0.952-1.195, P = 0.265, I² = 57.3%). In the reverse MR analysis, NSCLC and LUSC showed significant associations with PF (OR = 1.12, 95% CI 1.01-1.23, p = 0.028 and OR = 1.04, 95% CI 1.01-1.08, p = 0.012, respectively), while the meta-analysis results indicated no significant causal effect (OR = 1.006, 95% CI: 0.973-1.040, P = 0.734, I² = 55.9%). Sensitivity analyses indicated no evidence of horizontal pleiotropy or significant heterogeneity.Conclusion: This study suggests a potential causal relationship between PF and SCLC, as well as between NSCLC and LUSC with PF. However, the overall causal relationship between PF and LC was not statistically significant, possibly due to individual variability and other influencing factors. Further research using data from diverse populations is needed to validate these findings.",2234943X,ONCOLOGY
10.3389/feduc.2024.1408275,The significance of school bullying prevention program: a narrative inquiry from the perspective of a school police officer at a Youth Police Academy in Korea,"The need for effective school bullying prevention programs is more pronounced than ever. To address school bullying, Korea has operated the Youth Police Academy (YPA) since 2014. Although the School Police Officers (SPOs) in charge at YPA can provide valuable insights into the significance of school bullying prevention programs, there has been limited research in this area. The purpose of this study is to explore the relevance of school bullying prevention programs and delineate the role of YPA in preventing school bullying, based on the professional experiences and perspectives of YPA’s SPOs. We employed narrative analysis based on interviews with SPOs. The findings revealed that while the majority of SPOs experienced career crises, they overcame these challenges and developed professional perspectives on the YPA program and anti-bullying program. SPOs perceive that school bullying prevention program should focus on “resolving relationships,” “collaborative care,” and “teaching coping behaviors.” Accordingly, YPA can function as a “place of reconciliation,” “place helping students understand others’ perspectives through experiential and case-based educational approaches,” “hub for school bullying prevention education grounded in collaboration with relevant institutions and local experts,” “provider of coping information,” and an “active protector of victims.”",2504284X,EDUCATION
10.3389/feduc.2024.1360848,Task-irrelevant visual distractions and mindful self-regulated learning in a low-stakes computer-based assessment,"Introduction: There is a growing concern about the threat of distractions in online learning environments. It has been suggested that mindfulness may attenuate the effects of distraction. The extent to which this translates to academic performance is under investigation. We aimed to investigate the relationship between task-irrelevant visual distraction, time pressure, and mindful self-regulated learning in the context of a low-stake computer-based assessment.Methods: The study sampled 712 registered users of Prolific.co who were prescreened, current undergraduate university students. After data quality screening, 609 were retained for analyses. A 2 × 2 between-subjects design was used. Participants were randomly assigned to the following groups: (1) a control condition, (2) a distract condition, (3) a time pressure condition, or (4) a distract and time pressure condition. All participants completed reading comprehension questions, demographic questions, and the Mindful Self-Regulated Learning Scale.Results: Presenting a visual distraction increased self-reported distraction and having a clock present increased self-reported time pressure. The distraction did not have a statistically significant effect on test performance. Mindfulness was negatively correlated with test performance, self-reported distraction, and self-reported time pressure.Discussion: Continuous task-irrelevant visual distractions may not be distracting enough to influence low-stakes testing performance, but they do influence self-perceptions.",2504284X,EDUCATION
10.3389/feduc.2024.1352959,Sustainability in undergraduate course curricula at Andalusian (Spain) universities: a critical analysis,"Education is one of the main tools used to implement sustainable development goals (SDGs). Higher education institutions (HEIs) have a major social responsibility regarding sustainability given the relevance and impact of their educational work and the creation of knowledge through their research. Sustainability is promoted and linked to values, teaching-learning methodologies, and studying of global–local problems. Within this framework, the objective of our research is to determine the presence and means by which sustainability appears in the course curricula of university bachelor’s degrees of the public universities of Andalusia (Spain). The study used quantitative methodology. As in other studies, major deficiencies have been revealed in terms of the inclusion of sustainability in the universities, determining a limited presence of local problems to address sustainability. Thus, Andalusian universities distance themselves from the society and community in which they exist. This may also limit student knowledge of sustainability issues in which they could potentially be relevant participants.",2504284X,EDUCATION
10.3390/ai5030074,"Understanding Physics-Informed Neural Networks: Techniques, Applications, Trends, and Challenges","Physics-informed neural networks (PINNs) represent a significant advancement at the intersection of machine learning and physical sciences, offering a powerful framework for solving complex problems governed by physical laws. This survey provides a comprehensive review of the current state of research on PINNs, highlighting their unique methodologies, applications, challenges, and future directions. We begin by introducing the fundamental concepts underlying neural networks and the motivation for integrating physics-based constraints. We then explore various PINN architectures and techniques for incorporating physical laws into neural network training, including approaches to solving partial differential equations (PDEs) and ordinary differential equations (ODEs). Additionally, we discuss the primary challenges faced in developing and applying PINNs, such as computational complexity, data scarcity, and the integration of complex physical laws. Finally, we identify promising future research directions. Overall, this survey seeks to provide a foundational understanding of PINNs within this rapidly evolving field.",26732688,AI
10.3389/feduc.2024.1438721,Exploring the assessment of musical praxis through ICT in the academic context,"The evaluation of musical praxis involves a nuanced assessment of performer competencies within the intricate dynamics of musical elements, often hindered by subjective influences and the transient nature of performance. This study investigates the integration of Information and Communication Technology (ICT) tools to enhance instrumental praxis evaluation, focusing on French horn applicants to the University of Valencia Philharmonic Orchestra (OFUV). Employing a descriptive observational methodology and utilizing the MAXQDA application for analysis, the study examines key aspects of interpretation through individual recordings. Results demonstrate that ICT applications facilitate transparent and precise evaluation of performance aspects, underscoring the importance of incorporating these tools in performative education. In this regard, 89% of participants found the feedback to be very useful. Leveraging audio-video recordings offers a promising avenue for comprehensive analysis, providing clearer feedback and advocating for their integration by educational authorities and instructors to foster objective evaluation and enhance musical pedagogy.",2504284X,EDUCATION
10.3390/cancers16183178,Clinical Characteristics and Outcomes of Tympanomastoid Paragangliomas: A Report from Slovenia,"(1) Background: Head and neck paragangliomas are neuroendocrine tumors that typically originate from the parasympathetic nervous system and are predominantly non-secretory. Their clinical manifestations result from their mass effect on the surrounding tissues. The approach to treating these tumors depends on factors such as their location, size, impact on adjacent structures, and the patient’s overall health and preferences. (2) Methods: A retrospective analysis of the management of temporal bone paraganglioma classes A and B (according to the modified Fisch classification) was performed at the University Medical Centre, Ljubljana, between 2011 and 2023. (3) Results: We analyzed 23 cases, 19 of which underwent surgery; complete tumor removal was achieved in 18 of them. Four patients were irradiated due to tumor progression to class C. Three of these four patients initially refused surgery and were treated with radiotherapy (RT) 7, 13, and 18 years after diagnosis. In the fourth patient, complete surgical resection was not achieved and she was treated with RT four years after surgery, due to the growth of the tumor to class C. The average follow-up time from diagnosis was 8.9 years (median 6 years; range 1–26 years). (4) Conclusions: The surgical treatment of patients with class A and B paragangliomas is effective and safe. In cases where surgery is refused but the tumor continues to grow to class C, RT is an alternative and efficient method of controlling tumor growth.",20726694,ONCOLOGY
10.1007/s00432-024-05953-6,A prospective study to compare the diagnostic accuracy of 99mTc-CNDG SPECT/CT and contrast-enhanced CT in staging of non-small cell lung cancer,"Objective To explore the value of 99mTc-isonitrile deoxyglucosamine (CNDG) SPECT/CT in the staging and resectability diagnosis of non-small cell lung cancer (NSCLC) compared with contrast-enhanced CT (CECT). Methods This research was approved by the hospital ethics review committee. Sixty-three patients with NSCLC received 99mTc-CNDG SPECT/CT, CECT and initial TNM staging before treatment. Thirty-three patients who underwent radical surgery underwent postoperative pathological TNM staging as the reference standard. Another thirty patients underwent radiochemotherapy; among them, the reference standard of 7 patients of N staging and 5 patients of M staging was based on biopsy pathology, and the diagnosis of the remaining lesions was confirmed by at least one different image or clinical imaging follow-up for more than 3 months. The McNemar test and receiver operating characteristic (ROC) curve analysis were used to compare the diagnostic accuracy of staging and resectability of 99mTc-CNDG SPECT/CT and CECT in NSCLC, respectively. Results For all patients and surgical patients, the accuracies of 99mTc-CNDG SPECT/CT in diagnosing the T stage and N stage were higher than those of CECT (all patients: 90.5%, 88.9% vs. 79.4%, 60.3%; surgical patients: 81.8%, 78.8% vs. 60.6%, 51.5%), and the differences were statistically significant (all patients: T stage, P = 0.016; N stage, P = 0.000; surgical patients: T stage, P = 0.016; N stage, P = 0.004). For all patients, the accuracy of 99mTc-CNDG SPECT/CT in diagnosing the M stage was higher than that of CECT (96.8% vs. 90.5%), but the difference was not statistically significant (P = 0.289). ROC curve analysis showed that the accuracy of 99mTc-CNDG SPECT/CT in diagnosing the potential resectability of NSCLC was significantly better than that of CECT (P = 0.046). Conclusion This preliminary clinical study shows that 99mTc-CNDG SPECT/CT is of great value for accurate clinical staging of NSCLC compared with CECT and can significantly improve the accuracy of resectability diagnosis.",14321335,ONCOLOGY
10.1007/s44196-024-00651-0,An Energy-Efficient Bio-Inspired Mobility-Aware Cluster p-WOA Algorithm for Intelligent Whale Optimization and Fuzzy-Logic-Based Zonal Clustering Algorithm in FANET,"The newest research topic is flight ad hoc network (FANET). The primary obstacles faced by unmanned aerial vehicles (UAVs) are their limited flight duration and inefficient routes resulting from their great mobility and low battery power. Compared to MANETs or VANETs, FANETS routing is thought to be more difficult because of these topological restrictions. Artificial intelligence (AI)-based clustering techniques can be applied to resolve intricate routing issues in situations when both static and dynamic routing are ineffective. To overcome these path difficulties, clustering techniques based on evolutionary algorithms, including intelligent, probabilistic, bio-inspired whale optimization algorithms (p-WOAs), we suggest fuzzy-logic-based zonal clustering-based routing algorithms in this study to be used in FANET to build clusters. In addition to requiring fewer cluster heads (CHs) for routing, p-WOA offers good coverage and low energy consumption. The stochastic whale optimization technique, which draws inspiration from nature, is utilized in this paper to build networks and deploy nodes. The next step is to choose cluster heads using a region clustering technique based on fuzzy logic. By selecting the right cluster head, you can decrease routing traffic and increase cluster longevity. Routing overhead is also decreased. The data are then sent to the best path using a reference point group mobility model. The proposed p-WOA was used to test fuzzy integral and fuzzy logic ant optimization, fuzzy integral and neural network interference system, fuzzy integral and whale optimization algorithm (ANFIS-WOA), and fuzzy integral and FL-ALO. An array of indicators, such as cluster count, longevity, cluster configuration time, cluster head consistency, and energy usage, are employed to assess the effectiveness of the suggested methodology. The suggested algorithm works better than the most advanced techniques available today, as demonstrated by the experimental findings presented in this paper.",18756883,AI
10.3389/feduc.2024.1389592,Unskilled and unaware? Differences in metacognitive awareness between high and low-ability students in STEM,"Introduction: Metacognition, or the ability to monitor and control one's cognitive processes, is critical for learning in self-regulated contexts, particularly in introductory STEM courses. The ability to accurately make predictions about one's ability and performance can determine the effectiveness in which students effectively prepare for exams and employ good study strategies. The Dunning-Kruger pattern, where low-performing individuals are more overconfident and less accurate at the ability to predict their performance than high-performing individuals, is robustly found in studies examining metacognitive monitoring. The extent to which the Dunning-Kruger pattern can be explained by the lack of metacognitive awareness is not yet established in the literature. In other words, it is unclear from prior work whether low-performing students are “unskilled and unaware” or simply “unskilled but subjectively aware.” In addition, arguments about whether this pattern is a psychological phenomenon or a statistical artifact of the measurement of metacognition can be found in the literature.Methods: Students enrolled in three different physics courses made predictions about their exam scores immediately before and after taking each of the three exams in the course. Student predictions were compared to their exam scores to exam metacognitive accuracy. A new method for examining the cause of the Dunning-Kruger effect was tested by examining how students adjust their metacognitive predictions after taking exams.Results: In all contexts low-performing students were more overconfident and less accurate at making metacognitive predictions than high-performing students. In addition, these students were less able to efficiently adjust their metacognitive predictions after taking an exam.Discussion: The results of the study provide evidence for the Dunning-Kruger effect being a psychological phenomenon. In addition, findings from this study align with the position that the skills needed to accurately monitor one's performance are the same as those needed for accurate performance in the first place, thus providing support for the “unskilled and unaware” hypothesis.",2504284X,EDUCATION
10.1186/s40359-024-02073-1,Factors affecting the quality of work life for industrial labour force: empirical evidence from a developing country,"The success of any organization requires a skilled, competent, and satisfied workforce. If the workforce can be provided with the necessary components to ensure a high quality of working life, they will become permanent assets. Various factors undoubtedly affect the quality of workers' work lives. This study aims to investigate the drivers of the quality of work life in industrial labour force in a developing country, Bangladesh. It enumerated the elements that have an impact on industrial labour force’s quality of work life (QWL). A structured questionnaire was administered to 420 Bangladeshi workers across diverse industries, yielding a commendable response rate of 93.33%. The collected data underwent analysis employing the partial least squares structural equation modeling (PLS-SEM) technique. Representative industries and respondents were chosen by random selection. The results revealed that work environment, organizational culture and climate, relationships and cooperation, compensation and rewards, adequacy of resources, autonomy of work, job satisfaction, and security are directly related to the QWL. Training and development, and facilities do not significantly affect QWL. The research results can be used to improve the quality of work life for those working in the industrial sector. An industry may accomplish long-term and short-term goals by maintaining a pleasant workforce. The study's findings will provide policymakers and regulatory authorities of Bangladesh's industrial sector with strategic references and strategies to boost industrial productivity and economic growth for sustainable development by ensuring industrial employees' quality of work life that can serve as a template for Bangladesh.",20507283,PSYCHOLOGY
10.3389/frai.2024.1447171,Political ideology shapes support for the use of AI in policy-making,"In a world grappling with technological advancements, the concept of Artificial Intelligence (AI) in governance is becoming increasingly realistic. While some may find this possibility incredibly alluring, others may see it as dystopian. Society must account for these varied opinions when implementing new technologies or regulating and limiting them. This study (N = 703) explored Leftists’ (liberals) and Rightists’ (conservatives) support for using AI in governance decision-making amidst an unprecedented political crisis that washed through Israel shortly after the proclamation of the government’s intentions to initiate reform. Results indicate that Leftists are more favorable toward AI in governance. While legitimacy is tied to support for using AI in governance among both, Rightists’ acceptance is also tied to perceived norms, whereas Leftists’ approval is linked to perceived utility, political efficacy, and warmth. Understanding these ideological differences is crucial, both theoretically and for practical policy formulation regarding AI’s integration into governance.",26248212,AI
10.3389/feduc.2024.1380295,Data based individualization in early writing: the importance and measurement of implementation fidelity,"In this paper we describe the process of monitoring fidelity of implementation for a teacher-implemented early writing intervention. As part of a large, federally funded project, teachers who worked with students in grades 1 through 3 in schools across two states in the US were recruited and then randomly assigned to implementation and control conditions. Using Data-Based Individualization (DBI) as a framework for best practice in assessment and intervention, teachers in the implementation group received professional development on early writing intervention and assessment and then implemented these practices with their students who had significant writing challenges. Coaches, who were part of the research project, supported teachers and also observed teachers in both the implementation and control conditions at least twice during the course of the 20-week study. This paper focuses on the results of the fidelity measures that were administered throughout the project. An overview of the importance of fidelity checks is followed by a description of the fidelity tools used, as well as data from those tools. Areas of strength and challenge for teachers when implementing early writing assessment and intervention and engaging in data-based decision making with fidelity are discussed, along with recommendations regarding the practical and research importance of fidelity checks.",2504284X,EDUCATION
10.1007/s44196-024-00675-6,Application and Empirical Analysis of Fuzzy Neural Networks in Mining Social Media Users’ Behavioral Characteristics and Formulating Accurate Online Marketing Strategies,"In the current digital social environment, social media platforms have become an important position for user behavior insights and precision marketing. User behavioral data on social media contain rich information, but they are often fuzzy, uncertain and highly complex. Fuzzy neural network (FNN), as an advanced model combining fuzzy logic and neural network theory, provides a powerful tool for processing and analyzing social media user behavioral features. This study is dedicated to exploring the application of fuzzy neural networks in social media user behavior analysis and their key role in the design of accurate online marketing strategies. We construct and optimize a fuzzy neural network model by meticulously classifying and quantifying user behavioral features, including behavioral frequency features, content topic features, social interaction features, and time series features, as well as applying fuzzy set theory to deal with fuzzy features such as emotional states. Through empirical analysis, we will show how fuzzy neural networks can reveal the intrinsic laws behind user behaviors, and how these insights can be used to design and implement precise online marketing strategies to improve advertising effectiveness, user engagement, and brand loyalty.",18756883,AI
10.3390/cancers16223762,The Impact of Bone Marrow Involvement on Prognosis in Diffuse Large B-Cell Lymphoma: An 18F-FDG PET/CT Volumetric Segmentation Study,"Background: This study assessed the prognostic value of tumor burden in bone marrow (BM) and total disease (TD), as depicted on 18F-FDG PET/CT in 140 DLBCL patients, for complete remission after first-line systemic treatment (iCR) and 3- and 5-year overall survival (OS3 and OS5). Methods: Baseline 18F-FDG PET/CT scans of 140 DLBCL patients were segmented to quantify metabolic tumor volume (MTV), total lesion glycolysis (TLG), and SUVmax in BMI, findings elsewhere (XL), and TD. Results: Bone marrow involvement (BMI) presented in 35 (25%) patients. Median follow-up time was 47 months; 79 patients (56%) achieved iCR. iCR was significantly associated with TD MTV, XL MTV, BM PET positivity, and International Prognostic Index (IPI). OS3 was significantly worse with TD MTV, XL MTV, IPI, and age. OS5 was significantly associated with IPI, but not with MTVs and TLGs. Univariate factors predicting OS3 were XL MTV (hazard ratio [HR] = 1.29), BMI SUVmax (HR = 0.56), and IPI (HR = 1.92). By multivariate analysis, higher IPI (HR = 2.26) and BMI SUVmax (HR = 0.91) were significant independent predictors for OS3. BMI SUVmax resulted in a negative coefficient and hence indicated a protective effect. Conclusions: Baseline 18F-FDG PET/CT MTV is significantly associated with survival. BMI identified on 18F-FDG PET/CT allows appropriate treatment that may improve survival.",20726694,ONCOLOGY
10.3389/feduc.2024.1420048,Toward a “pluriversal” international relations studies in Indonesia,"What are the grounds of International Relations (IR) studies? Scholars have pointed out the strong connection between IR and Western knowledge, philosophies, and histories (Barasuol & da Silva, 2016;Blaney, 2002;Blaney & Tickner, 2017a, 2017b;Liu, 2016). Highlighting a Western-centered discipline, recent scholarship in IR has concluded the lack of plurality in IR theorizing, with the call to adopt more diverse means of understanding how the world works in a political sense (Acharya, 2014(Acharya, , 2016)). The consequence of a Western-centered discipline has been that the voices from the Global South are underrepresented and excluded from IR knowledge formation. In addition, the recent exploration of critical theories in IR (Critical Theory, Feminism, Marxism, etc.) has not been perceived as sufficient to eliminate biases in the field, as many have argued about the 'epistemic violence' encountered by scholars in the Global South (Ala et al., 2021;Odoom & Andrews, 2017). With the presence of biases in IR knowledge, this opinion article calls for re-evaluating the pedagogy of IR studies, especially in parts of the globe that do not share a common perspective with the Global North.The historical, cultural, and political contexts of the Global North (Western states) differ from the Global South (Small and Middle powers, primarily located in Africa, Latin America, and Asia). In Latin American, African, and Asian countries, perceptions of how the world works and what matters in global politics contrast with the common literature produced in IR. However, a general belief, predominantly adopted in the Global North, is that IR theories are ""…universally applicable, irrespective of the local context, culture, and society"" (Ala et al., 2021, p.38). The universal applicability of IR studies impacts the teaching and learning processes in the Global South, as there is a lack of convergence between what is taught and the socio-political realities in their countries. The problem associated with the tendency to universalize this Western-based knowledge is multiplied when higher education curriculums are geared to adopt Western-based perspectives, epistemologies, and ontologies in IR without exploring more diverse perspectives in the field. The core of Western-based knowledge includes IR grand theories, including realism, liberalism, constructivism, and the assessment of empirical investigations from the West to support the claims of those theories.In brief, this opinion article extends the applicability of the 'global pluriversal IR' echoed in Ala, Inoue, and Valencia's 2021 study. It argues that Indonesia, as a country of the Global South, has similarities to Brazil and South Africa regarding the prospects and challenges of diversifying the IR curriculum in the country. Eventually, this article echoes the importance of revealing the potential of Indonesian philosophies as an alternative means to understanding IR theories, transcending the dominant western-centrist IR studies currently adopted in Indonesia. It is further argued that knowledge and ontologies can benefit from plurality through Indonesia's IR worldviews, leading to a higher connection to the social realities in the Global South. The focus is on five prominent undergraduate IR programs, including those under Universitas Hasanuddin, Universitas Padjajaran, Binus University, Universitas Airlangga, and Universitas Indonesia. The study programs are hosted by universities consistently ranked in the top 15 among Indonesian Universities according to the world university rankings of Quacquarelli Symonds and Times Higher Education (QS, 2024;THE, 2024).The argument put forward is as follows. First, the dominance of Western-centered IR theories and sub-areas of IR and the seclusion of Global South perspectives. Second, this article provides some suggestions on measures that can be taken by Indonesian higher education institutions to achieve a 'pluriversal' IR in Indonesia. This includes bridging local Indonesian values to interpret regional Southeast Asian affairs, and as the basis to establish alternative interpretations to world affairs.IR students have been exposed to this Western-centered IR since the early years of their undergraduate studies. Students are expected to be introduced to the Great Debate among IR scholars in the twentieth century, connected to European and US history, Western Powers, and how the Global North perceives the other parts of the globe. Following this, sub-areas of IR are primarily dominated by the American academy, focused on foreign policy, political economy, and international security (Acharya & Buzan, 2010;Baylis et al., 2019;Griffiths, 2020;Putra, 2023a). Consequently, if not left out, local knowledge, such as the norms and contexts that influence Indonesia's foreign policies, has become a minor theme in the IR curriculum. In addition, this article also identifies the problem that IR theories introduced in the early years of an IR student are focused on those Western IR theories, thus shaping the foundations of an IR student's understanding of IR studies. , 2024). These courses form the foundation of how Indonesian IR students think about the study, including the types of theories that would be utilized as analytical tools in assessing cases in the following years.However, the substantive would predominantly be Western-centered, leading to the perception that what matters in the study are the variables highlighted by realism, liberalism, and constructivism. Paradigms of the Global South, for example, decolonization materials or how non-Western states perceive IR, tend to occupy a minor aspect in the foundational stages of IR teaching. Indonesian IR study programs are members of the Association of International Relations Indonesia (AIHII), which facilitates benchmarking curriculums from leading IR programs in the state. It is thus viable to conclude that the curriculum structure adopted in those five IR...",2504284X,EDUCATION
10.3390/ai5040120,A Novel Multi-Objective Hybrid Evolutionary-Based Approach for Tuning Machine Learning Models in Short-Term Power Consumption Forecasting,"Accurately forecasting power consumption is crucial important for efficient energy management. Machine learning (ML) models are often employed for this purpose. However, tuning their hyperparameters is a complex and time-consuming task. The article presents a novel multi-objective (MO) hybrid evolutionary-based approach, GA-SHADE-MO, for tuning ML models aimed at solving the complex problem of forecasting power consumption. The proposed algorithm simultaneously optimizes both hyperparameters and feature sets across six different ML models, ensuring enhanced accuracy and efficiency. The study focuses on predicting household power consumption at hourly and daily levels. The hybrid MO evolutionary algorithm integrates elements of genetic algorithms and self-adapted differential evolution. By incorporating MO optimization, GA-SHADE-MO balances the trade-offs between model complexity (the number of used features) and prediction accuracy, ensuring robust performance across various forecasting scenarios. Experimental numerical results show the superiority of the proposed method compared to traditional tuning techniques, and random search, showcasing significant improvements in predictive accuracy and computational efficiency. The findings suggest that the proposed GA-SHADE-MO approach offers a powerful tool for optimizing ML models in the context of energy consumption forecasting, with potential applications in other domains requiring precise predictive modeling. The study contributes to the advancement of ML optimization techniques, providing a framework that can be adapted and extended for various predictive analytics tasks.",26732688,AI
10.3389/fonc.2024.1491167,A real−world pharmacovigilance study of FDA Adverse Event Reporting System events for pralsetinib,"Background: Pralsetinib, a selective oral inhibitor of rearranged during transfection (RET) fusion proteins and oncogenic RET mutants, has shown significant efficacy in treating RET fusion-positive non-small cell lung cancer and thyroid cancer. However, since pralsetinib was approved in the United States in September 2020, there have been limited reports of post-marketing adverse events (AEs). In this study, we aimed to analyze the AE signals with pralsetinib on the basis of the United States Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) to provide instructions in clinical practice.Methods: All AE reports were obtained from the FAERS database from the first quarter (Q3) of 2020 to the second quarter (Q2) of 2024. Various signal quantification techniques were used for analysis, including reporting odds ratios, proportional reporting ratios, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker (MGPS)-based empirical Bayesian geometric mean.Results: Out of 8,341,673 case reports in the FAERS database, 1,064 reports of pralsetinib as the “primary suspected (PS)” AEs were recorded, covering 26 system organ classes and 256 preferred terms. Of the reports, 62.5% were from consumers rather than healthcare professionals. The most common systems were general disorders and administration site conditions (n = 704), investigations (n = 516), and gastrointestinal disorders (n = 405). A total of 95 significant disproportionality preferred terms (PTs) conformed to the four algorithms simultaneously. AEs that ranked the top three at the PT level were hypertension (n = 80), asthenia (n = 79), and anemia (n = 65). Of the 95 PTs with significant disproportionation, unexpected significant AEs such as increased blood calcitonin, increased myocardial necrosis marker, and bacterial cystitis were observed, which were not mentioned in the drug’s instructions. The median onset time of pralsetinib-associated AEs was 41 days [interquartile range (IQR) 14–86 days]. The majority of the AEs occurred in 30 days (42.86%).Conclusion: Our pharmacovigilance analysis of real-world data from the FEARS database revealed the safety signals and potential risks of pralsetinib usage. These results can provide valuable evidence for further clinical application of pralsetinib and are important in enhancing clinical medication safety.",2234943X,ONCOLOGY
10.3389/feduc.2024.1288723,Generative AI and education: dynamic personalization of pupils’ school learning material with ChatGPT,"The widespread use of generative AI tools like ChatGPT has seen significant growth. This rise prompted discussions on integrating these technologies into school education. However, the practical implementation, testing, and assessment of generative AI in primary and secondary education remained largely unexplored. This article examines the application of ChatGPT-3.5 and 4 in primary school education. A study involving 110 students aged 8–14 across grades 4–6 in two Uruguayan schools was conducted. The focus was on using generative AI for dynamic personalization of educational content during classroom lessons. In these sessions, instructional content followed the curriculum goals, and text, illustrations, and exercises were generated and dynamically adjusted based on generative AI. The findings indicate that generative AI effectively tailors school materials to match varying pupil knowledge levels. Real-time adjustments during lessons cater to individual learning needs, enhancing cognitive ergonomics. This approach not only boosts pupil motivation but also improves their performance, facilitating more effective achievement of the curriculum’s learning objectives. These results suggest a promising avenue for leveraging generative AI to personalize and optimize primary school education.",2504284X,EDUCATION
10.3389/fonc.2024.1513956,Corrigendum: Exogenous let-7a-5p induces A549 lung cancer cell death through BCL2L1-mediated PI3Kγ signaling pathway,"In the published article, there were errors in Figure 3B-C, Figure 4E-F, and Figure 7A-B as published. During the transwell assay and scratch test procedures, we used the equipment's default image naming system for batch exports, which led to difficulties in distinguishing between intervention groups during image selection and resulted in incorrect image placement. Given that a significant amount of time has elapsed since the publication, the original data associated with these results are no longer available, we therefore carried out independent repeat experiments and achieved consistent outcomes with the initial findings. As a result, the relevant images and their quantitative data in Figure 3B-E The corrected Figure 7 and its caption appear below.",2234943X,ONCOLOGY
10.3389/frai.2024.1476950,What is in a food store name? Leveraging large language models to enhance food environment data,"Introduction: It is not uncommon to repurpose administrative food data to create food environment datasets in the health department and research settings; however, the available administrative data are rarely categorized in a way that supports meaningful insight or action, and ground-truthing or manually reviewing an entire city or neighborhood is rate-limiting to essential operations and analysis. We show that such categorizations should be viewed as a classification problem well addressed by recent advances in natural language processing and deep learning—with the advent of large language models (LLMs).Methods: To demonstrate how to automate the process of categorizing food stores, we use the foundation model BERT to give a first approximation to such categorizations: a best guess by store name. First, 10 food retail classes were developed to comprehensively categorize food store types from a public health perspective.Results: Based on this rubric, the model was tuned and evaluated (F1micro = 0.710, F1macro = 0.709) on an extensive storefront directory of New York City. Second, the model was applied to infer insights from a large, unlabeled dataset using store names alone, aiming to replicate known temporospatial patterns. Finally, a complimentary application of the model as a data quality enhancement tool was demonstrated on a secondary, pre-labeled restaurant dataset.Discussion: This novel application of an LLM to the enumeration of the food environment allowed for marked gains in efficiency compared to manual, in-person methods, addressing a known challenge to research and operations in a local health department.",26248212,AI
10.3389/frai.2024.1385522,Frugal innovation in the business environment: a literature review and future perspectives,"Introduction: This research aims to explore the growing field of frugal innovation within the business environment, particularly its intersection with sustainability and artificial intelligence.Methods: Through a comprehensive literature review, the study analyzes key research trends and methodologies from 420 scholarly articles published between 2012 and August 2024. A bibliometric review traces the evolution of frugal innovation, while a content analysis provides insights into its practical applications across various industries, especially in resource-constrained settings.Results: The findings highlight the significant role of frugal innovation in addressing global challenges, such as reducing environmental impact and promoting social inclusion, especially through the adoption of cleaner technologies and socially responsible business practices. The study also emphasizes the transformative potential of AI in enhancing the scalability and efficiency of frugal solutions.Discussion: This research contributes to the ongoing conversation on sustainable development by identifying knowledge gaps and proposing future strategies for leveraging frugal innovation to drive inclusive growth. The implications of this research are valuable for academics, practitioners, and policymakers aiming to foster sustainable innovation in diverse socio-economic contexts.",26248212,AI
10.3389/fpsyg.2024.1514482,Research on the driving mechanism of tourists’ ecological protection behavior in intangible cultural heritage sites,"Despite the increasing focus on intangible cultural heritage tourism, there is a lack of research on the ecological protection behaviors of tourists in these contexts. With UNESCO’s continuous refinement of the World Heritage system, intangible cultural heritage has gradually become a focal point for tourism development and protection. While such tourism can promote the preservation and transmission of heritage, it also introduces ecological environmental issues that need to be addressed. Therefore, exploring the driving mechanisms of tourists’ ecological protection behavior holds significant practical value. Based on the Theory of Planned Behavior (TPB), this study constructs a driving model of tourists’ ecological protection behavior. It examines the influence of behavioral attitude, subjective norms, perceived behavioral control, and personal norms on tourists’ willingness to engage in ecological protection. By distributing questionnaires both offline and online, we analyzed data from 312 valid responses. The results indicate that all four factors have a significant positive impact on tourists’ willingness to engage in ecological protection behavior. Among these factors, personal norms and behavioral attitude have a relatively larger influence. The findings provide valuable references for intangible cultural heritage sites in China and regions with similar cultural and tourism dynamics.",16641078,PSYCHOLOGY
10.3389/fpsyg.2024.1433171,"Empowering young athletes: the influence of autonomy-supportive coaching on resilience, optimism, and development","Introduction: The present study investigates how autonomy-supportive coaching style influences youth athlete development through psychological resilience and dispositional optimism. Despite growing interest in factors that contribute to athlete development, gaps remain in understanding how coaching approaches interact with psychological traits to foster youth athletes’ growth. This study addresses these gaps by proposing a serial mediation model in which autonomy-supportive coaching indirectly enhances athlete development through resilience and optimism.Methods: Data were collected from 325 youth athletes and their coaches across training facilities and schools in China, and analyzed using structural equation modeling in SmartPLS.Results: Results indicate that autonomy-supportive coaching style significantly increases psychological resilience, which in turn boosts dispositional optimism, positively impacting athlete development. Both resilience and optimism serially mediate the link between coaching style and athlete growth.Discussion: These findings emphasize the importance of autonomy-supportive coaching in creating psychologically supportive environments that foster resilience, optimism, and developmental pathways in youth sports.",16641078,PSYCHOLOGY
10.1007/s44196-024-00726-y,A Novel Conflict Deduction Algorithm Based on Contradiction Separation Inference Rule,"Automated reasoning, a significant field within artificial intelligence, has attracted increased attention in recent years due to the rising demand for trustworthy AI. Binary resolution, among other inference rules, is crucial in automated reasoning of first-order logic, including the new conflict resolution method. Conflict resolution processes only two clauses in each deduction step and eliminates a complementary pairs of literals from input clauses. This paper proposes a contradiction separation conflict deduction (CSCD) method based on the contradiction separation rule to address these limitations. This novel resolution methodology, together with its automated reasoning theory and method, handles several clauses in each deduction step to seek for conflicts and generates learnt clauses through synergized deduction. Thus, the approach improves deduction by detecting conflicts more effectively, especially with lengthier input clauses. CSCD and conflict resolution are analyzed in detail, then how to create a practical CSCD algorithm and its implementation is summarized. We tested the CSCD algorithm to solve the CASC-26 problems and also applied it to the current leading ATP system (Eprover). Experimental results show that the CSCD deduction approach improves reasoning capability of conflict deduction method. Additionally, the Eprover with the proposed CSCD algorithm improves its performance and has solved various problems with a rating of 1 from the benchmark database TPTP.",18756883,AI
10.3389/feduc.2024.1380942,The attractiveness of the teaching profession: a integrative literature review,"The widespread shortage of teachers highlights the urgent need to examine the factors influencing the attractiveness of the teaching profession. This issue is driven by high rates of early-career attrition, an ageing workforce, and a decline in candidates entering teacher education programs. Understanding the factors that make the profession appealing—or unappealing—has become essential for ensuring educational quality and equity. An integrative literature review was conducted to identify the key themes related to the attractiveness of the teaching profession, synthesizing evidence from multiple studies and highlighting research gaps. Findings reveal that teaching still attracts candidates driven by intrinsic motivations and social utility. However, external factors such as low salaries, challenging working conditions, and limited career progression remain significant deterrents. The social image of teaching, shaped by media and community perceptions, also influences career choices. The intersection of demographic shifts and educational policy changes highlights the complexity of addressing teacher shortages. Despite increased attention from policymakers, significant gaps remain, particularly in relation to interventions that reduce early-career attrition and support teacher retention. Future research should explore targeted strategies to support early-career teachers and examine the socio-economic factors that influence career decisions. Addressing these issues is critical to developing sustainable policies that enhance the attractiveness of the teaching profession and promote educational equity.",2504284X,EDUCATION
10.3389/frai.2024.1473837,Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm,"Background: The Department of Rehabilitation Medicine is key to improving patients’ quality of life. Driven by chronic diseases and an aging population, there is a need to enhance the efficiency and resource allocation of outpatient facilities. This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models. The goal is to improve patient visit efficiency and optimize resource allocation through these predictive models.Methods: Data were collected from 38 Chinese institutions, including 4,244 patients visiting outpatient rehabilitation clinics. Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. The steps included handling missing values, data normalization, and encoding conversion. The data were divided into 80% training and 20% test sets using the Scikit-learn library to ensure model independence and prevent overfitting. Performance comparisons among XGBoost, random forest, and logistic regression were conducted using metrics, including accuracy and receiver operating characteristic (ROC) curves. The imbalanced learning library’s SMOTE technique was used to address the sample imbalance during model training. The model was optimized using a confusion matrix and feature importance analysis, and partial dependence plots (PDP) were used to analyze the key influencing factors.Results: XGBoost achieved the highest overall accuracy of 80.21% with high precision and recall in Category 1. random forest showed a similar overall accuracy. Logistic Regression had a significantly lower accuracy, indicating difficulties with nonlinear data. The key influencing factors identified include distance to medical institutions, arrival time, length of hospital stay, and specific diseases, such as cardiovascular, pulmonary, oncological, and orthopedic conditions. The tiered diagnosis and treatment tool effectively helped doctors assess patients’ conditions and recommend suitable medical institutions based on rehabilitation grading.Conclusion: This study confirmed that ensemble learning methods, particularly XGBoost, outperform single models in classification tasks involving complex datasets. Addressing class imbalance and enhancing feature engineering can further improve model performance. Understanding patient preferences and the factors influencing medical institution selection can guide healthcare policies to optimize resource allocation, improve service quality, and enhance patient satisfaction. Tiered diagnosis and treatment tools play a crucial role in helping doctors evaluate patient conditions and make informed recommendations for appropriate medical care.",26248212,AI
10.3389/fonc.2024.1474105,Application value of 18F-FDG PET/CT in soft tissue metastasis of intrahepatic cholangiocarcinoma: a case report and literature review,"Intrahepatic cholangiocarcinoma (ICC)originates from the epithelial cells of the intrahepatic bile ducts, with insidious onset and strong invasiveness, and most of the cases are found in the advanced stage, with extremely poor prognosis. In advanced stages, distant metastases to the lungs, bones, and brain are common, but distant soft tissue (subcutaneous and skeletal muscle) and breast metastases are rare, and simultaneous metastases to all three rare sites had not been reported. We report a 69-year-old woman with right upper abdominal pain who underwent a plain and enhanced CT scan of the upper abdomen, which revealed an intrahepatic space-occupying lesion, as well as subcutaneous and peritoneal nodules in the abdomen. To further evaluate the presence of other metastases, an 18F-FDG PET/CT scan was performed, which showed abnormal FDG uptake in the liver, peritoneum, left upper femur, right breast, subcutaneous tissues of the thoracic and abdominal regions, and skeletal muscle, while the corresponding CT densities of part of the skeletal muscle and the left upper femur did not show any significant abnormality. Pathologic confirmation of ICC with multiple metastases was obtained by puncture biopsy of the liver and subcutaneous nodes. This case demonstrates the advantages of 18F-FDG PET/CT in comprehensively evaluating systemic metastasis of ICC and detecting occult metastases, which is of great significance in its clinical diagnosis and staging.",2234943X,ONCOLOGY
10.1186/s40359-025-02377-w,The effects of physical activity on social physique anxiety in college students—the mediating and moderating role of mental toughness and negative physical self,"To examine the effects of physical activity on college students' social physique anxiety and the mediating and moderating roles of negative physical self and mental toughness in it, and to provide empirical evidence that physical activity improves college students' social physique anxiety. Stratified whole cluster convenience sampling was used to survey 1177 university students, 53.8% male and 46.2% female, with a mean age of (19.12 ± 1.21) years. Mediated and moderated effects were analysed using SPSS 26.0 and AMOS 28.0. (1) Physical activity negatively predicted social physique anxiety (2) Negative physical self and mental toughness (individual power) played a significant partial mediating role between physical activity and social physique anxiety, with mediating effects accounting for 40.09% and 27.11% of the total effect, respectively; (3) The R2 change in the interaction term of physical activity and family support in mental toughness (supporting force) reached a significant level, and family support played a significant negative moderating role between physical activity and social physique anxiety, whereas the interaction term of interpersonal assistance and physical activity was not significant and could not moderate the interrelationship between physical activity and social physique anxiety. Physical activity affects college students' levels of social physique anxiety through negative physical self and mental toughness (individual power); the effect of physical activity on social physique anxiety is negatively moderated by the family support dimension of mental toughness (supporting force).",20507283,PSYCHOLOGY
10.3389/feduc.2025.1431793,Supporting a state in developing a working theory of improvement for promoting equity in science education,"Introduction: This study was undertaken to explore the potential of developing a working theory of improvement for creating a more equitable system of science education at the level of a US state. We ask: How can tools from a long-term research-practice partnership support a state team in initiating improvement research toward promoting a more equitable system of science education?Methods: This design study took place in winter 2024 in a single state. External partners supported leaders of a single state in the US Northeast to support a process of articulating aims, specifying primary and secondary drivers, and identifying change strategies to promote a more equitable system of science education in the state, grounded in the vision of A Framework for K-12 Science Education (National Research Council, 2012). In this paper, we rely on descriptive analyses of joint meetings and a focus group with state leaders describe the tools supporting the process of development, the team’s use of the tools to generate an early draft of the Driver Diagram, and issues surfaced while developing it with a team of interest holders in the state.Results: Two meanings of equity emerged as significant within the series of meetings: that of the importance of universal access to professional learning and the importance of students having opportunities to experience culturally relevant instruction. The issues surfaced highlighted the need for infrastructures for professional learning to reach a diverse group of interest holders in science, including teachers, school leaders, and district leaders across the state. They also saw curriculum materials that connect to students’ everyday lives and community priorities as key drivers for equitable change in the system, around which professional learning activities should be organized. The team also surfaced several policy changes needed to implement change strategies, only some of which team members felt they had some authority.Discussion: Where past researchers have observed that equity can disappear as a focus during implementation of reforms, this study found that developing an aim statement and driver diagram helped energize and refocus a team’s implementation efforts geared toward a vision for science teaching and learning that is focused on ensuring all students can engage in meaningful science learning that is culturally and locally relevant to them.",2504284X,EDUCATION
10.1007/s00432-025-06130-z,Retraction Note: A prospective diagnostic model for breast cancer utilizing machine learning to examine the molecular immune infiltrate in HSPB6,,14321335,ONCOLOGY
10.3389/feduc.2025.1546448,Factors influencing the implementation of a teacher professional development program to improve teaching quality,"In this study, we examined why a Teacher Professional Development (TPD) program, designed to support teachers in using students’ perceptions of teaching quality (SPTQ) data, faced significant implementation challenges in 17 secondary schools in Chile. Despite voluntary participation and initial interest, 15 of the 17 schools dropped out within 2–3 months of starting the program. Through 12 semi-structured interviews with professional learning community coordinators from nine schools, we investigated four key attributes of the TPD program to understand implementation challenges: its added value, compatibility, clarity, and tolerance. While coordinators valued several aspects of the program (including its structured manual, evidence-based teaching strategies, and integration of SPTQ data) significant implementation barriers emerged. Time constraints, lack of technological infrastructure, and insufficient organizational routines made the implementation of the TPD program too burdensome for most schools. We discuss how compatibility between TPD programs and schools’ existing structures and routines acts as a critical bottleneck that can prevent successful implementation, even when participants see value in the program. This study provides important insights into the conditions necessary for successful TPD implementation in a global south country.",2504284X,EDUCATION
10.1186/s40594-025-00535-5,"A more positive mindset context is associated with better student outcomes in STEM, particularly for traditional-age students","Students' beliefs about their ability to grow in STEM disciplines have been linked to better course outcomes. However, such mindset beliefs are subject to the environmental cues projected by the instructor in the classroom, which we refer to as the mindset context. Recent meta-analyses indicated heterogeneity in the benefits of student mindset interventions, which the classroom environment may shape. In this work, we use structural equation modeling (SEM) to investigate the mindset context and its impact on students’ affect and performance in STEM courses, particularly for students from marginalized groups who may be disproportionately affected by these factors. We collected student perceptions of their instructors’ universality beliefs about student abilities (all people or only some people can reach excellence in STEM), students’ growth beliefs, sense of belonging (as measured by peer support, faculty support, and classroom comfort) and course grades. The sample was collected from courses in a STEM college within a demographically diverse, moderately selective institution in the Southern United States (N = 625). We found that student perceptions of the mindset context did not directly predict course grades, but ACT scores did (standardized exams used for college entry in the USA). However, SEM analysis revealed that when students perceived instructors to believe only some students can succeed in STEM (endorse more non-universal beliefs), they reported fewer growth beliefs about their abilities in STEM. This led to less classroom comfort in contributing to class discussions, ultimately lowering STEM grades. Multigroup moderation analysis showed no differences in paths based on race, gender, and generational status. However, the mindset context impacted traditional students’ (age of 18–22) growth beliefs to a greater extent than non-traditional students (> 22 years old). Additionally, classroom comfort significantly predicted grades for traditional students but not for non-traditional students. Our finding suggests that when students perceive the mindset context more positively, their outcomes improve, especially for traditional students who may be more sensitive to classroom cues. Thus, mindset interventions for faculty (coupled with student interventions) may also be beneficial to supporting student success. Additionally, we recommend improving student content preparation to enhance foundational knowledge, considering that indicators of prior preparation (ACT scores) play a more direct role in predicting student grades.",21967822,EDUCATION
10.1186/s40594-025-00538-2,Analysis of two pedagogical approaches to foster discipline integrations in an educational data mining class using communities of practice,"This paper describes research into two pedagogical approaches to foster transdisciplinarity in a graduate engineering course that involves education and computer science. Leveraging the Communities of Practice framework, we examine how students majoring in computer science can integrate new knowledge from education and computer science to engage in an educational data mining project. The first course iteration sought to connect students from education and computer science disciplines through a blend of problem-based learning and traditional lectures. The second course iteration involved computer science students only, but included two instructors, one from computer science and the other from education. To evaluate these approaches, we conducted multiple student interviews and classroom observations. We found that pursuing interdisciplinary through student brokers had a localized student impact on discipline integration without creating an entire class transdisciplinary environment, proving particularly effective for students with backgrounds outside of computer science. However, it fell short of achieving an overarching integration of education knowledge across the entire class. In contrast, the co-teaching approach influenced class dynamics significantly as instructors honed their brokerage skills and introduced crucial components to the multidisciplinary toolkit. Students reinterpreted these elements within the context of their projects, leading to a deeper integration of education and computer science disciplines. However, while students did acquire more knowledge from both disciplines, they did not always achieve a comprehensive practical understanding of the class outcomes. Findings suggest that differences in instructional design can significantly impact how interdisciplinary integration forms within a class. Using CoP, we identified various models to foster disciplinary integration. The two pedagogical approaches used—student brokers and co-instructors—achieved some disciplinary integration, highlighting multidisciplinary, interdisciplinary, and transdisciplinary integration. Engaging in projects with multidisciplinary teams allows students to interact one-on-one while working on real projects, enabling them to negotiate their participation with peers and resulting in a deeper integration of the involved disciplines. This paper discusses the merits and the drawbacks of employing both approaches to build an interdisciplinary class.",21967822,EDUCATION
10.1007/s44196-025-00771-1,Advanced Hybrid Machine Learning Model for Accurate Detection of Cardiovascular Disease,"Cardiovascular disease (CVD) is one of the foremost reasons behind the death of people worldwide. Prevention and early diagnosis are the only ways to control its progression and onset. Thus, there is an urgent need for a detection model comprising intelligent technologies, including Machine Learning (ML) and deep learning, to predict the future state of an individual suffering from cardiovascular disease by effectively analyzing patient data. This study aims to propose a hybrid model that provides a deep insight into the data under consideration to enhance model accuracy for effectively detecting cardiovascular disease. This current research proposes a hybrid model comprising four stages. In the first stage of the proposed hybrid model, the data imbalance problem is solved using a hybrid sampling technique named Synthetic Minority Oversampling Technique-Edited Nearest Neighbors Rule. In the second stage, the Chi-square is applied as a feature selection method to select the highly relevant features from the records of 1190 with 11 clinical features, curated by combining the 5 most popular datasets, including Long Beach VA, Hungarian, Switzerland, and Statlog (Heart). In the third stage, the preprocessed dataset is passed to a stacking ensemble model comprising three base learners: Random Forest Tree (RFT), K-Nearest Neighbor (K-NN), and AdaBoost classifier and one meta-learner: Logistic Regression (LR), optimized with Grid Search Cross-Validation (GSCV) optimization approach, whose performance is evaluated against individual classifier. In the fourth stage, the performance is evaluated in terms of accuracy, sensitivity, specificity, F1 score, and ROC_AUC score.. The comparative results prove that the proposed hybrid model scored the highest accuracy of 97.8%, 96.15% sensitivity, and 96.75% specificity and 98.6% ROC_AUC score when compared with the existing techniques and models after applying the SMOTE–ENN (for data balancing) and Chi-square (for feature selection) methods for the efficient detection of cardiovascular disease. The implementation results demonstrate that the suggested hybrid model may accurately identify cardiovascular disease among patients. It facilitates the application of robust clinical treatment strategies.",18756883,AI
10.3389/frai.2025.1496109,Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease,"Background: The diagnostic power of exercise stress electrocardiography (ExECG) remains limited. We aimed to construct an artificial intelligence (AI)-based method to enhance ExECG performance to identify patients with significant coronary artery disease (CAD).Methods: We retrospectively collected 818 patients who underwent both ExECG and coronary angiography (CAG) within 6 months. The mean age was 57.0 ± 10.1 years, and 614 (75%) were male patients. Significant coronary artery disease was seen in 369 (43.8%) CAG reports. We also included 197 individuals with normal ExECG and low risk of CAD. A convolutional recurrent neural network algorithm, integrating electrocardiographic (ECG) signals and features from ExECG reports, was developed to predict the risk of significant CAD. We also investigated the optimal number of inputted ECG signal slices and features and the weighting of features for model performance.Results: Using the data of patients undergoing CAG for training and test sets, our algorithm had an area under the curve, sensitivity, and specificity of 0.74, 0.86, and 0.47, respectively, which increased to 0.83, 0.89, and 0.60, respectively, after enrolling 197 subjects with low risk of CAD. Three ECG signal slices and 12 features yielded optimal performance metrics. The principal predictive feature variables were sex, maximum heart rate, and ST/HR index. Our model generated results within one minute after completing ExECG.Conclusion: The multimodal AI algorithm, leveraging deep learning techniques, efficiently and accurately identifies patients with significant CAD using ExECG data, aiding clinical screening in both symptomatic and asymptomatic patients. Nevertheless, the specificity remains moderate (0.60), suggesting a potential for false positives and highlighting the need for further investigation.",26248212,AI
10.3390/ejihpe15040045,Relations Between Medical Students’ Motivational Persistence Skills and Their Acceptance of Specific Blended Learning Tools,"The concept of blended education, which refers to the intensive integration of digital resources into the teaching process and its mixed online and on-site delivery, combining as much as possible the advantages of both methods in an optimal way, is becoming increasingly popular among teaching tools. There is no universal recipe for designing a successful blended course; the success of such courses is measured entirely through their degree of acceptance among students, defined by their emotional motivation to learn and the obtained practical results. Our study aimed to evaluate the motivational persistence degree (MPS) of medical students in connection with the students’ acceptance of different didactic tools involved in blended-learning approaches. Materials and Method: We investigated a sample comprising 523 students in Dental Medicine or General Medicine, belonging to all years of study, from four main Universities in Romania; we classified them according to their motivational persistence profile (using k-means data clustering) and we comparatively investigated the main relevant features of students in each cluster—gender, age group, opinions about the general usefulness of multimedia resources in the learning process, and their degree of acceptance of specific types of instructional materials involved in blended learning. Results: We found that the students who mostly enjoy the traditional learning style have average motivational persistence skills; they are perseverant and competitive, but they are not so good at planning their daily tasks. They enjoy external directions, set by teachers. The students who most enjoy PowerPoint presentations and those who enjoy instructional videos show similar behavior, both belonging to the cluster with the highest MPS score. They have the best motivational persistence skills amongst all categories; they are particularly excellent at planning and fulfilling daily tasks, as well as following their goals in the long term. The students who mostly enjoy online documentary sources belong also to a cluster with above average MPS score; they excel in fulfilling daily tasks, but exhibit weaker performance in recalling unachieved goals. These results are similar to those already reported in the literature; the strength of our study is in that it provides much more specific evaluations oriented to the motivational persistence degree, which is highly significant in the case of medical students, because it is a measure of their commitment in fulfilling certain tasks. Conclusions: Our results have the potential to highlight reasons for academic success or failure according to a student’ s profile, and will prove helpful in selecting the most appropriate didactic tools.",22549625,PSYCHOLOGY
10.3389/fonc.2025.1489169,"The relationship of depression and quality of life with mediating role of death anxiety, silver lining and religious coping among women cancer patients in Pakistan","Objective: Pakistani women are among those most likely to be diagnosed with cancer. Cancer patients experience significant changes that impact their mental and physical health, primarily due to the increased burden of the disease. This study aims to explore the relationship between depression and quality of life (QOL) in cancer patients, as well as how religious coping (RC), silver lining (SL), and death anxiety (DA) influence this connection.Materials and methods: A total of 450 individuals diagnosed with cancer were recruited from outpatient departments of various hospitals in Islamabad. Out of these, 421 patients who met the inclusion criteria were included in the study. Three types of cancer were considered for data collection there was 132 (31.4%) breast cancer, 154 (36.6%) blood cancer and 135 (32.1%) lung cancer patients Participants were assessed using the following measurement tools: the Demographic Form, The Short Muslim Religious Practice and Religious Belief, the Patient Health Questionnaire (PHQ-9, 2011), the Death Anxiety Scale, the Silver Lining Questionnaire, and the WHOQOL-BREF Questionnaire.Results: The findings of the current study revealed a negative association between depression and quality of life (QOL). Additionally, death anxiety (DA) was positively correlated with both depression and QOL. Conversely, silver lining (SL) and religious coping (RC) were negatively associated with depression and positively associated with QOL. Path analysis indicated that DA, SL, and RC served as mediators in the relationship between depression and QOL among cancer patients.Conclusion: The study concluded that cancer patients can better manage their depression and enhance their quality of life by strengthening their silver lining (SL) and religious coping (RC). These findings should be considered when developing strategies to manage depression and other psychological issues in cancer patients, thereby providing more effective treatments for this population",2234943X,ONCOLOGY
10.3390/educsci15040430,Boosting Active Learning Through a Gamified Flipped Classroom: A Retrospective Case Study in Higher Engineering Education,"Active learning and associated techniques such as flipped classes have been demonstrated to have positive impacts on student learning and performance. Active learning faces several challenges when learners apply weak learning styles. Weak learning might happen when a student is not motivated to carry out any pre-class content activity, actively participate in the class activity, or reflect and reinforce the learned content during and after the class. This study explores how a gamified flipped classroom affects active learning performance and learning outcomes. The case is related to a technical course in the Maintenance Engineering Field, which is well known for a high rate of misunderstanding and low learning outcomes. It is found that sequential game-boosting activities in the flipped classroom have managed to level up students’ learning outcomes by explaining almost all concepts with low levels of misconceptions.",22277102,EDUCATION
10.1186/s40594-025-00542-6,Investigating the emotion regulation of STEM teachers: a scoping review,"A significant tension exists between the necessity for teachers to regulate their emotions and the tendency to overlook these emotions in STEM education. Teachers’ emotion regulation is inherently context-sensitive and discipline-specific. Therefore, it is crucial for researchers to explore the particularities of teachers’ emotion regulation in the context of STEM education. This study presents a scoping review of existing research on STEM teachers’ emotion regulation, focusing on theoretical underpinnings, methodological approaches, and research foci. Following scoping review guidelines, a corpus of 23 studies published between 2004 and 2023 was collected and analyzed. Emotional intelligence emerged as the most frequently employed theoretical underpinning for conceptualizing STEM teachers’ emotion regulation, followed by emotional labor and emotion regulation. Among the four research approaches—quantitative, qualitative, mixed, and conceptual—the majority of studies adopted quantitative and qualitative methods to investigate the nature and the relational model of teachers’ emotion regulation in STEM education. The findings indicate that research on STEM teachers’ emotion regulation exhibits imbalances in theoretical and methodological approaches. Although various contexts, antecedents, and outcomes of STEM teachers’ emotion regulation have been identified, the scope and depth of these investigations remain limited. Research on STEM teachers’ emotion regulation is still in its early stages for several reasons: the paucity of studies in this area, a reliance on broad emotional constructs rather than specific emotion regulation perspectives, and the lack of tailored theoretical frameworks addressing STEM teachers’ emotion regulation. This scoping review maps existing knowledge on teachers’ emotion regulation in STEM education, elucidates the underlying philosophical standpoints of prior research, and offers recommendations for future research directions.",21967822,EDUCATION
10.3389/fonc.2025.1587069,Safety and efficacy of apatinib in combination treatment versus apatinib as second-line treatment for advanced gastric cancer,"Background: Apatinib is a systemic therapeutic agent for advanced gastric adenocarcinoma (GAC) and gastroesophageal junction adenocarcinoma (GEJA). Its efficacy can be enhanced by applying it as a combination therapy, but the evidence supporting its combination application as a second-line treatment is not well documented. In the current study, we aimed to assess the efficacy and safety profile of apatinib, both as a monotherapy and in combination regimens, for second-line treatment of GAC and GEJA in real-world settings.Methods: In this retrospective cohort analysis, we analyzed clinical data from 96 patients with advanced GAC or GEJA who received second-line apatinib monotherapy or combination therapy. Cox regression analysis was performed to identify prognostic factors influencing clinical outcomes of different treatment approaches (apatinib combination with other drugs).Results: The results indicated that the overall objective response rate (ORR) and disease control rate (DCR) for second-line apatinib therapy were 19.8% and 31.3%, respectively. The median progression-free survival (mPFS) was 4.8 months (95% CI: 4.3-6.2m), while the median overall survival (mOS) was 10.3 months (95% CI: 8.9-12.4m). Multivariable Cox regression analysis identified gender, liver metastasis, and peritoneal metastasis as independent predictors of inferior PFS and OS outcomes. In terms of safety, the primary adverse reactions included myelosuppression, elevated AST and ALT levels, hypertension, hand-foot syndrome, hyperbilirubinemia, proteinuria, fatigue, and vomiting, with a low incidence of grade 3–4 toxicities.Conclusions: Apatinib-based combination therapy significantly enhances both progression-free survival and overall survival in patients with advanced gastric cancer when compared to monotherapy, while also demonstrating a safe and reliable profile.",2234943X,ONCOLOGY
10.1007/s00432-025-06202-0,Increased expression of DNAJC7 promotes the progression of hepatocellular carcinoma by influencing the cell cycle and immune microenvironment,"Background Hepatocellular carcinoma (HCC) is the leading cause of cancer-related mortality worldwide owing to the lack of effective and early diagnostic tools and therapeutic approaches. DNAJC7, a member of the DnaJ heat shock family, is crucial in protein folding and stability; however, its specific functions and mechanisms in HCC remain unclear. Objective This study aimed to explore the role of DNAJC7 in HCC progression and evaluate its potential clinical significance as a prognostic marker. Methods Public databases (TCGA, ICGC, GEO, and TIMER) were used to assess DNAJC7 expression, correlations with clinical parameters, and related signaling pathways. Proliferation, migration, invasion, and cell cycle assays were performed to evaluate the function of DNAJC7 in HCC. Immune infiltration and associations with checkpoint proteins were analyzed using TIMER, and a Gene Set Enrichment Analysis (GSEA) was used to explore enriched pathways. Results DNAJC7 expression was higher in HCC tissues than in adjacent normal tissues and was associated with advanced malignancy and poor prognosis, including a lower overall survival, progression-free survival, and disease-free survival. DNAJC7 knockdown resulted in reduced malignant behavior of HCC cells, leading to S-phase cell cycle arrest. Increased DNAJC7 expression was associated with immune cell infiltration and the presence of immunological checkpoint molecules, including CTLA4 and PD-1. GSEA highlighted the activation of key pathways, including WNT signaling and cell cycle regulation. Conclusion DNAJC7 regulates tumor cell proliferation, migration, invasion, and immune evasion by acting as an oncogene in HCC. It can serve as a diagnostic and prognostic biomarker and potential treatment target for HCC.",14321335,ONCOLOGY
10.3390/ai6050097,"FASTSeg3D: A Fast, Efficient, and Adaptive Ground Filtering Algorithm for 3D Point Clouds in Mobile Sensing Applications","Background: Accurate ground segmentation in 3D point clouds is critical for robotic perception, enabling robust navigation, object detection, and environmental mapping. However, existing methods struggle with over-segmentation, under-segmentation, and computational inefficiency, particularly in dynamic or complex environments. Methods: This study proposes FASTSeg3D, a novel two-stage algorithm for real-time ground filtering. First, Range Elevation Estimation (REE) organizes point clouds efficiently while filtering outliers. Second, adaptive Window-Based Model Fitting (WBMF) addresses over-segmentation by dynamically adjusting to local geometric features. The method was rigorously evaluated in four challenging scenarios: large objects (vehicles), pedestrians, small debris/vegetation, and rainy conditions across day/night cycles. Results: FASTSeg3D achieved state-of-the-art performance, with a mean error of <7%, error sensitivity < 10%, and IoU scores > 90% in all scenarios except extreme cases (rainy/night small-object conditions). It maintained a processing speed 10× faster than comparable methods, enabling real-time operation. The algorithm also outperformed benchmarks in F1 score (avg. 94.2%) and kappa coefficient (avg. 0.91), demonstrating superior robustness. Conclusions: FASTSeg3D addresses critical limitations in ground segmentation by balancing speed and accuracy, making it ideal for real-time robotic applications in diverse environments. Its computational efficiency and adaptability to edge cases represent a significant advancement for autonomous systems.",26732688,AI
10.3389/feduc.2025.1552760,Exploring teachers’ pedagogical reasoning in mathematics education using the TPACK framework,"Effective integration of technology in mathematics education requires teachers to blend content knowledge, pedagogical strategies, and digital tools. The Technological Pedagogical Content Knowledge (TPACK) framework offers a lens for understanding teachers’ pedagogical reasoning when designing technology-enhanced lessons. However, the ways in which TPACK informs instructional planning and the challenges educators face remain under - synthesized. A systematic review following PRISMA guidelines was conducted using Scopus (2015–2024). Search terms included “pedagogical reasoning,” “instructional reasoning,” “TPACK,” and “math*.” From 118 records retrieved, title/abstract screening and full - text eligibility assessments yielded eight empirical studies examining TPACK and pedagogical reasoning in mathematics contexts. The included studies employed predominantly qualitative case studies and mixed - methods designs to capture teachers’ decision - making processes. Findings indicate that educators leverage TPACK to enhance conceptual understanding and student engagement via dynamic visualizations, interactive simulations, and scaffolded digital tasks. Common obstacles include limited subject - specific professional development, resource constraints, and heterogeneity in teachers’ TPACK proficiency. Evidence also highlights TPACK’s capacity to foster inquiry - based learning and develop teachers’ adaptive expertise. Sustained, targeted professional development and equitable access to technology are essential for deepening TPACK enactment. Implications for practice include designing PD programs that integrate subject - specific technology applications and creating institutional support structures. Future research should investigate longitudinal impacts of TPACK on teachers’ reflective practices and student outcomes, and develop standardized assessment tools tailored to mathematics instruction.",2504284X,EDUCATION
10.3389/frai.2025.1431003,Co-Learning: code learning for multi-agent reinforcement collaborative framework with conversational natural language interfaces,"Online question-and-answer (Q&A) systems based on the Large Language Model (LLM) have progressively diverged from recreational to professional use. However, beginners in programming often struggle to correct code errors independently, limiting their learning efficiency. This paper proposed a Multi-Agent framework with environmentally reinforcement learning (E-RL) for code correction called Code Learning (Co-Learning) community, assisting beginners to correct code errors independently. It evaluates the performance of multiple LLMs from an original dataset with 702 error codes, uses it as a reward or punishment criterion for E-RL; Analyzes input error codes by the current agent; selects the appropriate LLM-based agent to achieve optimal error correction accuracy and reduce correction time. Experiment results showed that 3% improvement in Precision score and 15% improvement in time cost as compared with no E-RL method respectively. The results indicate that integrating E-RL with a multi-agent selection strategy can effectively enhance both the accuracy and efficiency of LLM-based code correction systems, making them more practical for educational and professional programming support scenarios.",26248212,AI
10.3389/feduc.2025.1555167,Problem-solving: development and validation of a short instrument for higher education,"Problem-solving is becoming more and more seen as an important skill for college students to learn to build metacognitive skills, critical thought, and the ability to learn on their own. Even though this skill is very important, there aren’t many approved tools that can be used to test it in schools, especially in Peru. The goal of this study is to fill in that gap by creating and testing a short problem-solving scale based on the Rational Problem-Solving Style, which stresses taking a planned and organized approach to problems. 733 Peruvian college students (mean age: 21.56 years, standard deviation: 4.15 years; 59.89% female) took part. A 15-item Problem-Solving Questionnaire and used experimental (EFA) and confirmatory factor analysis (CFA) to test it. The scale’s validity and reliability were checked, along with its link to academic self-efficacy. There were four parts to the Problem-Solving Questionnaire: Solution Analysis and Planning, Critical Evaluation of Solutions, Generation and Evaluation of Alternatives, and Prioritization and Review of Alternatives. Fit scores from CFA (like CFI = 0.98 and RMSEA = 0.062) and reliability coefficients (ω = 0.73–0.90) showed that it was a reliable educational tool. There was proof of concept validity in the form of correlations with academic self-efficacy (r = 0.36–0.80). The scale is a validity and effective way to test the problem-solving skills of university students in Peru. Due to its brevity and emphasis on logical methods, it is suitable for use in both education and research, aligning with global goals for quality education.",2504284X,EDUCATION