text
string | predicted_class
string | confidence
float16 |
|---|---|---|
The two sets of sequencing reads (454 and Illumina) from each sample were assembled using a hybrid de novo assembly strategy. Illumina reads were trimmed for base sequence quality using FASTQC (Andrews S: FastQC: A quality control tool for high throughput sequence data. [ http://www.bioinformatics.babraham.ac.uk/projects/fastqc/]). Per base sequence quality control (QC) cutoffs of 20% were used to trim illumina reads and then assembled into de novo contigs using VelvetOptimiser61, which is a wrapper that uses the Velvet denovo assembler and automatically estimates the optimal k-mer size that will produce the best possible assembly. The range of K-mer sizes specified were between 35 to 70. The best Illumina contigs obtained were then fragmented into shorter segments of ~400 bp, similar to the read length from 454. These 400 bp Illumina-fragmented contigs were then pooled with the reads generated from the 454 machine. A second de novo assembly using Newbler was then performed. The resulting de novo contigs were used for the downstream analysis mentioned below.
|
study
| 100.0 |
Contigs from 10 published genomes and the 33 projects in this study were annotated using the Prokka20 prokaryotic annotation pipeline. For pan-genome analysis, the complete predicted protein coding sequences from all 43 genomes were searched against themselves using BLASTP with an e-value cutoff of 1e-05 for significance. The best BLASTP scores were used for identifying orthologous groups using the OrthoMCL algorithm21. A panmatrix using all orthologous gene was created and imported into the R-package, micropan, to generate visualizations to describe the Legionella pan-genome. MUSCLE62 was used with default settings to align genes and proteins within ortholog groups; each of the multiple sequence alignments (MSA) was filtered by GBLOCKS63 to remove gaps and highly divergent regions. Core genes are defined as the protein-coding gene clusters that have genes present from all 43 Legionella serogroups and species. All core protein coding MSA’s were concatenated to generate a super alignment for protein-based Legionella phylogeny. The whole genome nucleotide alignment was also generated using progressive MAUVE by concatenating all nucleotide sequences of each of the core genes22. This MAUVE alignment was used as input alignment for generating the whole genome nucleotide phylogeny, ClonalFrame, fineSTRUCTURE and BAPS analyses (see below). We also generated 2 separate MAUVE alignments: Lp only (intra-specific alignment; 1,028,806 bp); and all Legionella species (interspecific alignment; 759,392 bp) for a second version of ClonalFrame analysis (see below). The single nucleotide polymorphisms (SNPs) were extracted from the MAUVE core alignment based on reference strain Lp1 strain Philidelphia, and the core SNP positions were combined to prepare the genome-wide haplotype data. For all accessory gene clusters with at least 3 Legionella genomes present, MUSCLE MSAs were trimmed by GBLOCKS to remove gaps.
|
study
| 100.0 |
The ML phylogenetic reconstruction was implemented using RAxML38. Nucleotide phylogenies were reconstructed using the GTR (General Time Reversible) nucleotide substitution model, while the core protein coding phylogeny was generated using Jones-Taylor-Thornton (JTT) amino acid substitution model. For both substitution models the rate of heterogeneity was estimated with 4 discrete rate categories. Internal branches of the phylogeny were estimated with 100 bootstraps.
|
study
| 100.0 |
The ChromoPainter algorithm was applied to the genome-wide haplotype data using the linkage model41 to elucidate the population structure of Legionella. A recombination map file was created by specifying a uniform recombination rate per-site per-generation using a Perl script called makeuniformrecfile.pl. a preprocessing tool provided in ChromoPainter (http://www.paintmychromosomes.com). The output from ChromoPainter analysis is a co-ancestry matrix that summarizes the recombination-derived DNA imports and their donors across the 43 Legionella genomes. The fineSTRUCTURE algorithm uses the ChromoPainter generated co-ancestry matrix and performs model-based clustering using the Bayesian MCMC approach to explore population structure41. FineSTRUCTURE was run at a total of 400,000 iterations; the first 200,000 iterations were discarded as MCMC burn in. The thin interval was specified as 100.
|
study
| 100.0 |
To further gain insights into the population structure of these species, we used the BAPS software to establish the genetically differentiated groups and determine the amount of admixture between these groups. We ran the BAPS clustering model using the hierarchical manner to identify substructures inside the main clusters64. To find the optimal clustering, we ran five independent iterations with the prior upper bound of the number of clusters set to 35; clustering was performed with 4 levels in the hierarchy. The first level gave 10 clusters whereas the fourth yielded 20 clusters, for which we conducted a mixture analysis. We ran this analysis considering the minimum number of individuals for a population as one using parameters described by Castillo-Ramirez S. et al.65.
|
study
| 100.0 |
To detect homologous intragenic recombination in the core gene clusters, we implemented the following three methods: (1) Pairwise Homoplasy Index (PHI); (2) Neighbor Similarity Score (NSS); and (3) Maximum2 using the PhiPack package66. For PHI, a window size of 50 nucleotides was used. For Maximum2, a fixed window size of two thirds of the number of polymorphic sites was used. P-values were estimated by employing 1,000 permutations for the three methods. Correction for multiple testing was performed using the Benjamini & Hochberg method implemented in the software Q-value67.
|
study
| 100.0 |
Genes under positive selection were identified using codeml as implemented in PAML, version 4.830. All gene clusters previously identified as having undergone recombination under any of the 3 intragenic recombination methods (described above) were removed for this analysis. We implemented the branch-site test268 to identify genes under positive selection in each of the clades compared to other Legionella clades. For each core gene, the likelihood of a model that does not allow positive selection (null model) was compared to a model that allows positive selection (alternative model) using a Likelihood Ratio Test (LRT)68. One degree of freedom was used to calculate p-values, and correction for multiple testing was performed using the Benjamini and Hochberg method at a significance level of 0.05 implemented in the software Q-value67.
|
study
| 100.0 |
To illustrate the distance-dependent decay of linkage disequilibrium, we adopted the method implemented by Shapiro et al.69. We used the core orthologs (1140 genes) that are present in one copy per genome in each of the 43 Legionella serogroups and species, and each unique allele was assigned a unique allele number. We then selected pairs of loci separated by increasing distance in the L. pneumophila reference genome. Neighboring loci on the same strand were excluded. Linkage disequilibrium between 2 pairs of loci was estimated using the D′A metric70, which provides a summary measure of linkage disequilibrium between those two loci.
|
study
| 100.0 |
ClonalFrame (version 1.2)23 was run at 40,000 iterations on the whole genome core nucleotide alignment identified by progressive MAUVE with all 43 genomes, and the initial half was discarded as Markov Chain Monte Carlo (MCMC) burn in. Good convergence and mixing properties were found between the four runs, making sure that they produced consistent estimates of the global parameters, clonal genealogy and location of recombination events. Additionally, for each reconstructed branch substitution event introduced by either mutation or recombination, the number of mutation events, and the number of recombination events were approximated. The relative effect of recombination and mutation on genetic change (r/m) and the relative rate of mutation and recombination (ρ/θ) were estimated. We also implemented two separate runs of ClonalFrame using the whole genome alignment of only the Lp serogroups (25 genomes) and non-Lp species (18 genomes) to obtain L. pneumophila specific recombination parameters.
|
study
| 100.0 |
We defined putative imports for each branch of the ClonalFrame tree as a genomic region for which the probability of recombination never goes below 80% and reaches 95% in at least one site. Such putative imported DNA segments were extracted from each of the genomes and, for each of them, we searched the GenBank nucleotide database for similarities with the highest normalized BLASTN score along with a percent identity (pcident) of at least 95% in the whole nucleotide BLAST database (updated February, 2016).
|
study
| 99.94 |
CRISPR sequences were identified using the online CRISPRs finding software (http://crispr.u-psud.fr/Server/). The software also searches the identified CRISPR sequences against the cas gene database. All spacer sequences were extracted and a sequence similarity clustering using dnaclust software was performed. BLASTN analysis against the NCBI nucleotide database as well as against the Legionella pan-genome proteome and the NCBI NR database were also performed.
|
study
| 100.0 |
The analysis for the history of gene gain and loss was done by a stochastic mapping method implemented using the gainLoss program32. The program takes the patterns of absence or presence of gene clusters and analyzes the evolution of such observed phyletic patterns within the likelihood framework using a probabilistic evolutionary model that assumes the gain and loss of genes along the phylogeny that follow a Markovian continuous process, and infers probabilities and expectations for all gain and loss events in a per site per branch manner. The core genome phylogeny was used as the reference tree. The probabilistic evolutionary model used here assumed that the gain/loss ratio varies among sites (variable gain/loss ratio (mixture)). The total number of gains/losses for each branch was calculated as the probability of gain/loss for each gene cluster, summed across all the genes. The probability cutoff implemented to call a gene gained/lost at a branch of the phylogenetic tree was >0.98.
|
study
| 100.0 |
GO terms were identified using BLAST2GO analysis71. In short, a single representative nucleotide gene sequence from each of the 12,977 gene clusters was selected and BLASTX was performed locally against the NR database (last updated February 2016). The BLASTX output file in XML format (E-value < = 1e-05) was then used to map the GO terms using BLAST2GO under default settings71. GO term enrichment analysis was performed for all the clade-specific gene clusters, genes gained along the terminal and internal branches, genes under recombination and genes under positive selection. GO enrichment analysis was tested using the GOEAST tool72 assuming our experiment was a customized microarray platform. Because there was only one species placed in Clade 4, we could not compute enrichment for this clade for positive selection analysis. The p-value of GO ID enrichment was calculated as the hypergeometric probability of getting a sample of genes (example: number of genes gained/under recombination/selection) under the null hypothesis that they were selected randomly from the total pool of 12,977 genes. To control error rates for multiple hypothesis testing, the p-values were adjusted using the Benjamini Hochberg method implemented in the software Q-value67 where a false discovery rate (FDR)-adjusted p-value < 0.05 was considered significant.
|
study
| 100.0 |
All genes families with at least three members in each of Clades 1 to 3 were clustered using UPGMA. Each resulting tree was tested using the imonophyletic command of the R ape package42 and also using TOPD/FMTS (Version 3.3), where the former was implemented to determine if genes from the same clade formed monophyletic groups and the latter to check whether the topology of each of the accessory genes agrees with the topology of the Legionella species phylogenetic tree. For families that failed the screen, ML phylogenies were computed using RAxML38 and visually inspected for evidence of inter-clade gene movement.
|
study
| 100.0 |
Accession codes: The data generated in this study has been deposited in the NCBI SRA database under the bioproject accession number SRP070825. All scripts are on figShare (link: https://figshare.com/projects/Dynamics_of_genome_change_among_Legionella_species/14567).
|
other
| 99.94 |
Today multimodal monitoring is a part of the neurointensive care (NIC) management of patients suffering severe subarachnoid hemorrhage (SAH) (1). Microdialysis (MD) of the extracellular fluid may be used to monitor the metabolic state of the tissue in order to detect secondary injuries such as ischemia (2, 3). Cerebral ischemia is a feared complication which occurs in 20–30% of patients suffering from SAH and increases the morbidity and mortality (4). Monitoring cerebral metabolites and cerebral blood flow (CBF) provides vital information on tissue at risk of developing ischemia. However, MD is a focal technique that measures a small region of the brain tissue, and it is recommended that, if possible, the MD catheter should be placed in the vascular territory at risk (5). At our department, the MD catheter is routinely placed in right frontal lobe. This is based on the assumption that both the middle cerebral artery (MCA) and the anterior cerebral artery (ACA) territories will be monitored. Bedside Xenon-CT is used routinely in our NIC unit in order to assess the regional CBF in patients following SAH (6–8). In a previous Xenon-CT study including 64 SAH patients, we could not find any correlation between regional CBF and aneurysm location (7).
|
study
| 99.94 |
The objective of the current study, using bedside Xenon-CT, was to investigate if there is a difference in the association between the MD parameters and CBF measured around the MD catheter compared to global cortical CBF and to CBF in the vascular territories during the early acute phase of SAH.
|
study
| 100.0 |
The inclusion criteria were patients who underwent a Xenon-CT at day 0–3 after onset of SAH and received a MD catheter at admission. These patients needed to be mechanically ventilated for the Xenon-CT and in need of a ventriculostomy for simultaneous insertion of a MD catheter. Patients with a preexisting neurological deficit, an SAH resulting from trauma, or arteriovenous malformation were excluded. The SAH was verified by CT scanning and the aneurysm was visualized by a CT angiography and/or digital subtraction angiography (6).
|
study
| 99.9 |
The standardized protocol at our NIC unit, which is well described previously (6, 11), is based on intensive physiological monitoring and aggressive therapy of any derangement to avoid or minimize secondary brain injury. Unconscious patients are mechanically ventilated and receive a ventriculostomy. If ICP is above 20 mmHg, the drainage system is opened and cerebrospinal fluid drained against a pressure level of 15 mmHg. Hypotension is treated first with albumin 20% and crystalloid solutions, and with Dobutamine (Algol Pharma AB, Kista, Sweden) if needed. The goal is to keep CPP above 60 mmHg. Identified aneurysms are treated early by endovascular coiling or surgical clipping. All patients receive nimodipine (Nimotop®, Bayer AB, Solna, Sweden).
|
other
| 99.9 |
At our department, bedside Xenon-CT has been introduced as a routine and is performed on patients with SAH and mechanically ventilated at day 0–3, day 4–7 and after 7 days after admission as far as the necessary resources are available (6). This time point is used since delayed cerebral ischemia (DCI) is rarely seen before day 3 following onset of SAH (12, 13). The principal of CBF measurements using Xenon-CT has been previously described by Yonas et al. (14–16), and the procedure used at our department has also been previously described (6). Briefly, a concentration of 28% of stable Xenon is administered to the patients breathing circuit for about 4 min using the Enhancer 3000 and the specially developed computer software (Diversified Diagnostic Products Inc., Houston, TX, USA). During the Xenon inhalation, eight CT scans at four different levels with 10-mm spacing are obtained by the CereTom® (Neurologica, Boston, MA, USA). The first CT-scan is adjusted using the scout view in order to avoid inclusion of coil artifacts. The computer software synchronizes the Xenon delivery and the CT scans. The resulting radiologic tissue enhancement of the Xenon wash-in enables CBF (ml/100 g/min) to be calculated and plotted as colored maps.
|
study
| 100.0 |
Mean blood flow in each of 20 evenly distributed cortical regions (ROIs) was calculated for each level, and the global CBF is given as a mean of all four levels. The vascular territories were analyzed as following: ACA—ROI 1–2 (right) and 19–20 (left), MCA—ROI 3–8 (right) and 13–18 (left), and posterior cerebral artery (PCA)—ROI 9–10 (right) and 11–12 (left) (Figure 1). The tip of the MD catheter was identified on the structural CT scans and an ROI was drawn manually (diameter = 3 cm) for the corresponding area around the MD catheter on the CBF scans. Territories with CT-defined hematoma or artifacts were noted and excluded.
|
study
| 100.0 |
Xenon-CT scans at different levels obtained by bedside mobile CT-scanner. Conventional CT images are obtained for evaluation and identification of microdialysis (MD) catheter. Following Xenon delivery tissue enhancement of the Xenon wash-in enabled cerebral blood flow (CBF) (ml/100 g/min) to be calculated and plotted as colored maps. Scale of CBF is ml/100 g/min and is given to the right. Twenty cortical ROIs were used for CBF calculation and regional vascular territory was identified (anterior cerebral artery 1–2, 19–20, medial cerebral artery 3–8, 13–18, posterior cerebral artery 9–10, 11–12). CBF around the MD catheter was calculated by drawing an ROI manually around the catheter (circle in red). White arrow indicates EVD.
|
study
| 99.94 |
The cerebral MD technique in NIC has previously been extensively used and described (2, 9). The intracerebral MD catheter is placed in the right frontal lobe cortex through a separate burr hole, anterior to the ventricular drain. For intracerebral MD monitoring, a 70 brain MD catheter is used (M Dialysis AB, Stockholm, Sweden) with a membrane length of 10 mm and a membrane cutoff of 20,000 Da. The catheters are perfused with artificial CSF (NaCl 147 mmol/l, KCl 2.7 mmol/l, CaCl2 1.2 mmol/l, MgCl2 0.85 mmol/l) (perfusion fluid CNS; M Dialysis AB).
|
other
| 99.4 |
The perfusion rate was measured as 0.3 µl/min using a microinjection pump (CMA-106, M Dialysis AB). MD urea was monitored to validate catheter performance (17). The MD samples were collected on an hourly basis. For the correlation analysis, the MD sample was collected at the end of the Xenon-CT exanimation. Interstitial glucose, lactate, pyruvate, glutamate, glycerol, and urea were analyzed enzymatically using a CMA 600 analyzer or ISCUS Clinical Microdialysis Analyzer (M Dialysis AB).
|
study
| 99.94 |
All analyses were performed using SPSS Statistics for Macintosh, Version 23.0 (IBM®, Armonk, NY, USA). In order to assess the normality of the data set, the skewness and kurtosis of the distribution were analyzed. Since the parameters were not normally distributed, Spearman’s correlation was used. Bonferroni correction was performed for multiple comparisons. Results are expressed as mean ± SD and range within brackets. A p value <0.05 was considered statistically significant.
|
study
| 99.94 |
The Uppsala University Regional Ethics Review Board for clinical research granted permission to undertake the study. Written informed consent was obtained from all patients or their proxy for study participation. The study was also approved by the local Radiation Safety Authority.
|
other
| 99.94 |
Thirty patients with severe SAH were included, 5 males and 25 females. Demographics and clinical data including the distribution of aneurysm location are given in Table 1. The physiological parameters were stable during CBF measurements, and baseline values are shown in Table 2.
|
study
| 100.0 |
AcomA, anterior communicating artery; ICA, internal carotid artery; PComA, posterior communicating artery; MCA, middle cerebral artery; AChA, anterior choroidal artery; PCA, posterior cerebral artery; BA, basilar artery; PICA, posterior inferior cerebellar artery.
|
other
| 99.94 |
Pyruvate showed a strong positive correlation with lactate which remained significant after Bonferroni correction (r = 0.738, p ≤ 0.001) and glucose (r = 0.496, p = 0.006), but the correlation with glucose did not pass the Bonferroni correction level. Glutamate showed the strongest correlation with lactate although not significant (r = 0.375, p = 0.049).
|
study
| 100.0 |
A significant negative correlation could be seen between lactate and CBF-MD (r = −0.468, p = 0.009). Lactate also negatively correlated with global CBF (r = −0.408, p = 0.025) but this did not remain significant following Bonferroni correction. There was a weak negative and non-significant correlation between L/P ratio and CBF-MD (r = −0.364, p = 0.048) and global CBF (r = −0.329, p = 0.075). No significant correlation could be found between CBF and glucose, pyruvate, glycerol, and glutamate.
|
study
| 100.0 |
The association between CBF in each vascular territory in the right hemisphere and MD parameters was investigated (Table 4). Lactate showed a significant negative correlation with CBF in ACA in the right hemisphere. This correlation was weaker and non-significant for CBF in PCA territory (Figure 3). After Bonferroni correction, only lactate correlated significantly with CBF in ACA territory.
|
study
| 100.0 |
The correlation between cerebral blood flow (CBF) in each vascular territory of the right hemisphere and microdialysis lactate/pyruvate ratio and lactate is shown. Lactate showed a significant correlation with CBF in anterior cerebral artery (ACA) territory in the right hemisphere.
|
study
| 99.94 |
In this study, we found that bedside monitoring of CBF using Xenon-CT in combination with MD in patients with SAH was feasible and safe. Placement of the MD catheter in the right frontal lobe following SAH showed a strong negative correlation between lactate and regional CBF in the anterior vascular territory but not in the middle and the posterior vascular territories. Few studies have combined CBF measurements with MD parameters in SAH patients (9, 10, 18). Using PET, Enblad et al. found that lactate, L/P ratio, and glutamate had the highest sensitivity for detecting ischemia in the area of the MD catheter (9). Also, Sarrafzadeh et al. found highest sensitivity for lactate and glutamate to detect ischemia using PET (10, 18).
|
study
| 99.94 |
High lactate levels have been reported to be associated with ischemia both in SAH patients and patients with head injury (19, 20). However, high lactate levels may also indicate hyperglycolysis (21, 22), explaining its rather low specificity as a biomarker of ischemia (9). Consequently, additional parameters such as L/P-ratio, pyruvate, and CBF should be evaluated to distinguish between ischemia, hyperglycolysis, and mitochondrial dysfunction (5, 23–25). In the current study, there was a significant negative correlation between CBF and lactate. However, the L/P ratio was not significantly correlated with CBF. We have recently reported on high lactate and low CBF during the acute phase following SAH in patients who later developed DCI (26). Different studies report on different levels of CBF thresholds for ischemia. Previous studies using Xenon-CT have reported on cortical CBF in awake normal subjects to be 52 ± 10 ml/100 g/min (27). In an additional study, comatose patients following head injury were compared to normal subjects and CBF threshold of 55.3 ml/100 g/min was defined as hyperemia (28). Our recent report on patients suffering severe SAH showed that patients who later develop DCI have initial low CBF levels of 23.7 ml/100 g/min compared to 37.5 ml/100 g/min in those who do not develop DCI (26). Current results are in line with previous findings and emphasize the important role of lactate in correlation with CBF in patients suffering SAH.
|
study
| 99.94 |
It is recommended that in patients suffering SAH, the MD catheter, if possible, should be placed in the vascular territory at risk (5). However, at our department, the MD catheter is placed in the right frontal lobe if there are no hematomas or infarction in conjunction to the ventriculostomy. This is based on the assumption that anterior brain a sensitive zone vascularized both by ACA and MCA, watershed areas, would offer an early warning signal of hypoperfusion and development of ischemia. In addition, this approach is logistically more feasible for the neurosurgeon on-call. In this study, we investigated how well the CBF in different vascular territories in the right hemisphere correlated with global CBF and if low CBF in different vascular territories was correlated to pathological findings from MD placed in right frontal lobe. We found a strong and significant correlation between global CBF and all three vascular territories in the right hemisphere. However, pathological values indicated by high lactate were correlated with ACA territory but not with MCA and PCA territories. This may be as expected since these territories are less covered by a catheter placed in the right frontal lobe.
|
study
| 100.0 |
The CBF measurements in this study were performed during day 0–3 following onset of SAH. Further studies are needed to evaluate the association between CBF and MD parameters at later time points after SAH with the catheter in right frontal lobe, given the increased risk of vasospasm and delayed focal cerebral ischemia. Another methodological limitation is the potential influence of artifacts from the EVD and MD catheter that may give inaccurately low CBF levels. This problem could not be avoided completely but is probably of minor magnitude. The artifacts were very small and comprised a minor proportion of the ROI volume analyzed.
|
study
| 100.0 |
A limitation of Xenon-CT CBF measurement compared to other methods such as PET is lower resolution and that only CBF can be quantified. However, PET is a complex and costly procedure with a need of cyclotron, while bedside Xenon-CT is more economical and accessible imaging technique with few adverse effects that can be used in the routine NIC to measure CBF.
|
review
| 89.94 |
In conclusion, the results of this study, using bedside Xenon-CT day 0–3 after SAH with simultaneous MD monitoring, show correspondence between high lactate levels and low regional CBF in the territory of right ACA but not in the middle and posterior vascular territories, when the MD catheter is placed in the right frontal lobe.
|
study
| 100.0 |
The Uppsala University Regional Ethics Review Board for clinical research granted permission to undertake the study. Written informed consent was obtained from all patients or their proxy for study participation. The study was also approved by the local Radiation Safety Authority.
|
other
| 99.94 |
ER: design, data acquisition, analysis, and manuscript preparation. HE: Xenon-CT performance and manuscript preparation. TH, ER-E, and AL: data acquisition. PN: manuscript preparation. LH: data acquisition and manuscript preparation. PE: design and manuscript preparation.
|
other
| 99.94 |
In spite of efforts by public agencies to monitor the types of food sold in school settings or regulate food advertising aimed at young people, their exposure to energy-dense foods (those with a high caloric concentration per bite) at and away from school remains high . A recent study on the consumption of fast food in 36 developed and developing countries showed that more than 50% of adolescents consume fast food frequently or very frequently . In Latin America, the Global School-based Health Survey (GSHS) showed that two-thirds of adolescents (13–17 years old) in Argentina, Chile and Uruguay reported daily intake of sugar-sweetened beverages . In the early 2010s, among European 15-year-old, daily soft drink consumption was more than 40% in England, the Netherlands, Belgium, Slovakia and Slovenia .
|
study
| 99.9 |
Evidence is available on the role of Western-type diets (WD) in limiting cognitive abilities in critical brain maturation periods (i.e., infancy and childhood) . Animal models show that exposure to a high-fat, high-sugar (HFS) diet in adolescence is related to impairment in hippocampal learning and memory processes, regardless of weight status . One important mechanism that is proposed to underlie HFS-induced impaired hippocampal function is the reduced synthesis, secretion, and action of the brain-derived neurotrophic factor (BDNF). BDNF facilitates synaptic efficacy by converting changes in electrical activity to long-lasting changes in synaptic function, which is a suggested key process for memory formation . Reduced levels of BDNF in association with impaired memory function has been well documented in the literature .
|
review
| 99.7 |
Impairment of memory consolidation and memory performance is a risk factor for learning difficulties and poor academic progress . Thus, a diet of poor nutritional value may compromise students’ ability to perform well in school. Longitudinal and cross-sectional studies, mostly conducted in developed countries, have examined the relationship between diet and school grades , as well as the relationship between diet and performance on standardized academic tests . Results collectively suggest that better educational outcomes are associated with regular consumption of nutritious breakfasts, lower intake of energy-dense, nutrient-poor foods, and maintaining a healthy diet .
|
review
| 99.4 |
The effect of WDs on academic results can be used to strengthen health promotion strategies. While the connection between unhealthy diet and poor academic performance (as measured by school grades and standardized test scores) in elementary and middle schoolers has been well described, less is known about the relationship between dietary habits and postsecondary educational aspirations—that is, the intention to pursue higher education after secondary school. The increasing number of HS graduates seeking entrance to higher education institutions, including in non-industrialized nations, has made this a particularly important topic for students, families and policymakers.
|
other
| 99.9 |
Since the question of how WD foods may compromise students’ intention to pursue higher education is also of interest to non-academic audiences, we used a translational-research approach to provide evidence that can be translated from research and applied to practice and policy. Thus, we examined the relationship of nutritional quality of snacks with academic outcomes using functional cognition measures like grade point average (GPA), high school (HS) completion, and college entrance examination participation rates. Our decision to concentrate on snacks rather than overall diet or meals such as breakfast, lunch or supper was based on wanting to focus on food choices made by adolescents rather than consumption of foods over which they may have little volition. We hypothesized that students habitually eating unhealthy snacks would have lower grades and be less likely to complete HS and take college admission exams.
|
study
| 99.94 |
We studied 16–17-year-old adolescents living in Santiago, Chile, from low-to-middle socioeconomic status (SES), who were part of an infancy cohort. Participants were recruited at 4 months from public healthcare facilities in the southeast area of Santiago (n = 1791). They were born at term of uncomplicated vaginal births, weighed >3.0 kg, and were free of acute or chronic health problems. At 6 months, infants free of iron deficiency anemia (n = 1657) were randomly assigned to receive iron supplementation or no added iron (ages 6–12 months). They were assessed for developmental outcomes in infancy, and at 5, 10 and 15 years . At 16–17 years, those with complete data in each wave (n = 678) were also assessed for obesity risk and the presence of cardiovascular risk factors in a half-day evaluation that included assessment of dietary habits and nutritional content of food intake. Ethical approval was obtained by the institutional review boards of the University of Michigan, Institute of Nutrition and Food Technology (INTA), University of Chile, and the University of California, San Diego. Participants and their primary caregiver provided informed and written consent, according to the norms for Human Experimentation, Code of Ethics of the World Medical Association (Declaration of Helsinki, 1995).
|
study
| 99.94 |
Nutritional quality of in-school and at-home snacking was measured considering the amount of saturated fat, fiber, sugar and salt in the food. Assessment was performed with a food frequency questionnaire, validated using three 24 h recalls to include weekends . A section of this questionnaire was specially designed to assess the usual diet during the snack time at school and at home, by asking about the frequency of food consumption within the past three months. A list of 50 foods and beverages was used. The frequency of food consumption was assessed by a multiple response grid; respondents were asked to estimate how often a particular food or beverage was consumed. Categories ranged from ”never” to ”five or more times a week”. The electronic version of the Chilean Food Composition Tables/Database was used to assess the quality of snacks composition . Food items were classified as unhealthy (poor nutritional value items, high in fat, sugar, salt and calories), unhealthy-to-fair (highly processed items although low in fat) and healthy (nutrient rich foods). We assigned adjustment weights to each food item conditioned to its nutritional quality. A score ranging from 0–10 was computed by adjusting the frequency of food consumption to the nutritional quality of foods consumed during the snack time. For each snacking type (in-school or at-home), participants had a continuous score, with higher scores representing healthier snacking habits. We applied quartile cutoffs for the Chilean adolescent population (comprising students of high-, middle- and low-SES) to classify the nutritional quality of in-home and at-school snacking of participants into three groups: unhealthy (≤4.3 or ≤25th percentile), unhealthy-to-fair (from 4.4 to 5.9 or >25th percentile and <75th percentile) and healthy (≥6.0 or ≥75th percentile) .
|
study
| 100.0 |
The academic outcomes measured were HS GPA, the likelihood of HS completion, and the likelihood of taking college entrance exams. Data on GPA and high school completion were obtained from publicly available records at the Academic Assessment Unit of the Ministry of Education of Chile. Following the Ministry of Education criteria, GPA (on a scale of 1–7) was transformed into standardized scores (ranging from 210–825), and adjusted by type of secondary education (academic, vocational or adult school). Data on college examination rates were derived from publicly available information from the Assessment and Measurement Department of the University of Chile, which administers the tests for college entrance on behalf of the Ministry of Education. Although the exams for college admission are non-mandatory for HS graduates (only for those aiming at enrolling in higher education), more than 85% of Chilean HS graduates take the tests and, thus, have plans for future schooling .
|
study
| 99.9 |
A research physician used standardized procedures to measure the adolescent’s height (cm) and weight (kg) in duplicate. Body mass index (BMI = kg/m2) at age 16 was evaluated and z-scores were estimated according to the World Health Organization (WHO) 2007 references . Weight status was defined as follows: underweight (BMI-z < −1 SD), normal weight (BMI-z from −1 SD to 1 SD), overweight (BMI-z from 1 SD to <2 SD) and obesity (BMI-z ≥ 2 SD).
|
study
| 99.94 |
Physical activity has been found to be associated with academic achievement in studies conducted in Chile ; therefore, it could be a relevant confounder for the association between diet and academic results. We approached physical activity habits with scheduled, repetitive and planned exercise, accounting for the number of weekly hours devoted to Physical Education (PE), and extracurricular sports. To measure this, we used a questionnaire that was validated in a previous study using accelerometry-based activity monitors in both elementary and high school children . The questionnaire was administered by a researcher to all students at the time they attended the anthropometric examination. Participants were asked: (1) On average, over the past week, how often did you engage in PE? (2) On average, over the past week, how often did you engage in extracurricular sports, either school- or non-school-organized? (3) On those days, on average, how long did you engage in such activities? With this information, we estimated the average hours per week of scheduled physical activity. Participants having ≤90 min of weekly scheduled physical activity, which is the mandatory time for school-based PE, were considered to be physically inactive.
|
study
| 100.0 |
Parental educational attainment is an important measure of human capital level among populations and, also, is an important predictor of children’s educational outcomes . In infancy, participant’s mother and father were asked to report the highest schooling level they have been enrolled in, as well as the highest grade they completed at that level. In our analysis, five standard hierarchic levels were defined according to the 2011 International Standard Classification of Education: (1) no education completed; (2) first level (primary school or 1st–8th); (3) secondary level (first phase or 9th–10th); (4) secondary level (second phase or 11th–12th); and (5) post-secondary non-tertiary educations or short-cycle tertiary education . Then, we merged these categories into two: incomplete secondary education (1 + 2 + 3), and complete secondary education or higher (4 + 5). In health research, parental education has been often used as proxy for socioeconomic background . Also, because the literature describes correlations between children’s educational outcomes and family structure , we include a variable denoting whether the participant was raised in a fatherless family. This information was reported by the participant’s parents or guardian. Finally, to control potential design biases, we used a categorical variable denoting whether the participant had received iron supplementation or no added iron at 6–12 months.
|
study
| 100.0 |
Data were processed using Stata SE for Windows 12.0 (Lakeway Drive College Station, TX, USA). All categorical data were expressed as absolute and relative frequencies, while continuous data were expressed as means and standard deviations. Statistical analysis included χ2 for categorical variables, and analysis of variance (ANOVA) with Bonferroni correction for comparison of means. We tested for effect measure modification (interaction) by weight status and physical activity, in the association between quality of snacking and academic outcomes using two-way ANOVA. The interaction of quality of snacking with weight status and physical activity was non-significant at p < 0.05 and, therefore, we did not stratify the analysis. Unadjusted logistic models were used to explore cross-sectional patterns of variation in academic behavior across snack categories (unhealthy and unhealthy-to-fair vs. healthy). Next, the models were adjusted for sex, weight status, physical activity, familial background and a variable to control potential design biases. Odds ratios are presented in the tables with 95% CI to evaluate the strength and precision of the associations. Analysis of covariance (ANCOVA) was used to determine whether high school GPA differed by nutritional quality of snacking, accounting for the same potential confounders. Because GPA scores do not have an intrinsic meaning, the effect size for difference was estimated using Cohen’s d coefficients. A p < 0.05 denoted statistical significance.
|
study
| 100.0 |
As shown in Table 1, our sample was composed of 16.8-year-old (0.3 SD) adolescents (47% males). Eighty-four percent completed HS (n = 571) and were allowed to take the exams for college admission. Of them, 68% (n = 388) took the college entrance exam. High school GPA ranged from 269–795 points, and mean value was 481.1 (92.3 SD) points. Mean value of BMI-z was 0.65 (1.2 SD). Of the participants, 25% and 14% were overweight and obese, respectively. In the sample, 60% were physically inactive.
|
study
| 100.0 |
The share of students completing the secondary education significantly increased with better nutritional quality of at-school (χ2 = 6.73, p < 0.05) and in-home (χ2 = 7.19, p < 0.05) snacking (Figure 1). Likewise, the proportion of students taking the exams for higher education was significantly higher among participants having healthy in-home (χ2 = 12.40, p < 0.01) and at-school (χ2 = 11.66, p < 0.01) snacking (Figure 2).
|
study
| 100.0 |
Table 2 shows the estimated cross-sectional association between graduating HS and the nutritional quality of in-home and at-school snacking. After adjusting for sex, weight status, physical activity, parental education, family structure and iron supplementation in infancy, unhealthy snacking significantly reduced the odds of completing the secondary education. For instance, students having unhealthy in-home snacks were 53% (odds ratio (OR): 0.47, 95% CI: 0.25–0.88) less likely to complete HS than students having healthy in-home snacks. Odds were lower but non-significant among students eating foods of unhealthy-to-fair nutritional quality at home compared to those eating healthy snacks at home. When school snacking was the exposure, we also found a positive significant association of nutritional quality of snacks with the likelihood of getting the HS diploma (aOR: 0.49, 95% CI: 0.27–0.89). In all these models, sex and physical activity were also related to the chances of HS graduation.
|
study
| 100.0 |
Similarly, among students who completed HS, the odds of taking the college entrance exam were significantly lower for those having unhealthy in-home snacks compared to those having healthy in-home snacks (Table 3). After controlling other influences, students who reported consumption of unhealthy in-home snacks were 47% less likely (aOR: 0.53; 95% CI: 0.31–0.88) to take the college entrance exam, compared to students eating healthy snack items. In addition, students eating in-home snacks of unhealthy-to-fair nutritional quality had lower odds of taking the college entrance exam, compared to those with healthier habits, though the association was non-significant. When school snacking was the exposure, the odds of taking the examination for college were also lower in students eating unhealthy snacks (aOR: 0.57; 95% CI: 0.35–0.90) compared to those eating healthy at-school snacks. In all these models, the odds of taking the college entrance exam were significantly associated with sex, maternal education and family structure.
|
study
| 100.0 |
The nutritional quality of snacking was also significantly related with students’ final GPA as shown in Figure 3. After accounting for the effect of sex, weight status, physical activity, parental education, family structure and iron supplementation in infancy (Table 4), the group snacking on unhealthy foods at home had a final GPA of 490.0 points, on average, whereas participants having healthy snacks at home had a final GPA of 530.1 points (GPA mean difference = −40.1 points; 95% CI: −59.2; −16.9, d = 0.43). When comparing those having unhealthy-to-fair snacks vs. those having healthy snacks at home the GPA mean difference was −27.9 points (95% CI: −43.5; −8.2, d = 0.30). It is worth noting that Cohen’s d coefficients around 0.20 are considered of interest in educational research when they are based on measures of academic achievement . Lastly, the same pattern was observed when the main exposure was the nutritional quality of at-school snacking.
|
study
| 100.0 |
This study explored whether the nutritional quality of in-home and at-school snacking among high school students in Santiago, Chile, was cross-sectionally associated with secondary school academic achievement and the intention to enroll in higher education. Although numerous studies have approached the effects of short-term exposure to a WD on academic outcomes , very few have focused on foods consumed during snack times. We found that unhealthy snacking was correlated with lower high school GPA and rate of graduation, as well as a reduced likelihood of taking college admission exams. When controls for sex and other potentially confounding variables (e.g., weight status, physical activity, familial background, etc.) were entered into the models, unhealthy snacking continued to be associated with worse academic results.
|
study
| 100.0 |
Our findings are consistent with previous research that found evidence of a relationship between a healthy diet and academic achievement. The results of a population-based study of 4th and 8th grade Chilean school children—students from subsidized, partially subsidized, and private schools—showed a positive cross-sectional association between performance in language and mathematics as measured by Chile’s standardized System for the Assessment of Educational Quality test and the nutritional quality of school snacking, regardless of sex, SES, and other educational influences . Similarly, in a subset (n = 395) of the current sample, Correa et al. observed that, among students taking college entrance exams, unhealthy dietary habits of 16-year-old were associated with lower performance on college examination tests when compared to the performance of students with healthy dietary habits.
|
study
| 99.94 |
Cross-sectional studies conducted in adolescents from other countries also found that participants having healthy dietary habits performed better at school compared to those having unhealthy dietary habits. For instance, the native and foreign language attainment among 14- and 15-year-old Icelandic students, as well as their mathematics achievement, were negatively influenced by poor dietary habits . Norwegian 9th and 10th graders with a high intake of sugar-sweetened soft drinks, candies, chocolate, chips, pizza, hot dogs, and hamburgers were up to 6 times more likely to manifest learning difficulties in mathematics. Conversely, a diet of fresh fruits at least once daily reduced the chances of difficulties in these areas . Also in 15- to 17-year-old Norwegian adolescents, high academic achievement was associated with a high intake of fruits and berries, and a low intake of sugar-sweetened beverages . Unfavorable academic performance, as measured by a standardized test, was positively associated with unhealthy dietary patterns in 6- to 13-year-old Taiwanese students. The likelihood of underperforming on the test was 1.63 times higher for students with greater consumption of low-quality foods (e.g., sweets and fried foods) than it was for students with low intake of such items. Fu et al. also showed that students with poor academic performance were less likely to regularly eat foods that are rich in protein, vitamins and minerals .
|
study
| 99.94 |
Diet is also an important influence on other determinants of academic success. Among adolescent students from Iceland, having an optimal diet was cross-sectionally associated with decreased odds of behavioral problems in the classroom . Likewise, in 15- and 16-year-old male students from Oslo (Norway), intake of >4 glasses/day of sugar-sweetened soft drinks more than doubled the probability of having behavioral problems at school, compared to students drinking <1 glass of sugary drinks per day . Among female students in Oslo with excessive intake of sugar-sweetened soft drinks, the chances of conduct problems at school were 4.1 times higher compared to the reference group. In males, soft drink consumption was also related to hyperactivity and higher levels of mental distress, both of which are associated with academic difficulties .
|
study
| 99.94 |
It is likely that the effect on academic results of excessive consumption of foods high in saturated fats and simple sugars is mediated by the effect of these macronutrients on brain health and cognitive function. In developmental stages such as adolescence, the brain is particularly vulnerable to the effects of excessive intake of saturated fats and simple carbohydrates . Diet-induced impairment in learning and hippocampus-dependent memory processes have been widely documented . In addition to reducing production of neurotrophins such as BDNF, other WD-induced effects have been reported on this brain structure, including overexpression of proinflammatory cytokines, mitochondrial damage due to oxidative stress, and altered blood–brain barrier permeability . Also, insulin resistance and hyperleptinemia have been linked to impaired hippocampal synaptic plasticity and poor cognitive functioning . Furthermore, evidence suggests that juvenile exposure to a WD may be more harmful than such exposure in adulthood. A 3-week juvenile WD regimen induced similar weight gain and metabolic alterations as did a 12-week adult WD regimen. Juvenile exposure, however, also affected memory consolidation and flexible memory expression while promoting exaggerated pro-inflammatory cytokine expression in the hippocampus after an immune challenge, and it diminished hippocampal neurogenesis .
|
review
| 99.44 |
While the cross-sectional design of our study prevents definitive conclusions about causality and the direction of the associations depicted here, it is worth noting that research conducted in both animals and humans described short-term effects of Western-type dietary habits on hippocampal-dependent learning and memory. In animals, it is well established that a WD causes rapid impairments of hippocampal-based tasks, with diet-related cognitive effects observed after only 72 h . Studies in humans are limited but they confirm that a WD impacts hippocampal memory tasks following a relatively short exposure. Healthy 20-year-old college students from Australia consuming a HFS breakfast (30% saturated fats plus 18% refined sugars), over four consecutive days, showed significantly poorer memory recall compared to control students consuming a healthier breakfast of similar palatability and food types, but significantly lower in saturated fats and refined sugars (5% saturated fats plus 10% sugars). Since these changes in memory performance were linked to shifts in blood glucose across breakfast, authors suggest that this could be one potential mechanism by which a WD affects hippocampal function . In a similar manner, in sedentary men aged 25–45 years, Edwards et al. found decreased power of attention and increased simple reaction time after seven days of consuming a diet comprising 74% kcal. from fat . It is less clear for how long the cognitive effects of a WD will remain and, thus, further investigations should address that question. Although experimental studies in humans show that improvements in memory can occur following reductions in energy intake and fat , or shift to a diet low in saturated fats and refined sugars , observational longitudinal studies conducted in Anglo-Saxon countries suggest that unhealthy dietary practices in developmental periods have a lasting association with cognitive and educational outcomes that seem to persist over time, regardless of later changes in diet .
|
study
| 79.0 |
Our results also showed that a significant share (73%) of participants in the sample ate snacks of intermediate or poor nutritional value. This is consistent with population surveys conducted nationally and internationally. In Chile, adolescents (aged 14 years to 18 years) ranked first in the consumption of refined sugar (121 g/day) and second in the consumption of saturated fats (12.7 mL-g/day) compared to other age groups. In this age group, the consumption of sugar-sweetened soft drinks was 254 mL/day, according to the latest National Food Consumption Survey . This survey also reported that 97% of children and adolescents aged 6 years to 18 years need to improve the quality of their diets. The World Health Organization’s Health Behaviour in School-aged Children (HBSC) survey found that in Scotland, 35% of adolescents eat sweets or chocolate every day, and 18% eat chips every day. In addition, 20% of Scottish female adolescents and 27% of their male counterparts consume sugary soft drinks daily . Among US high schoolers, 22% of males and 17% of females report consumption of sugar-sweetened soft drinks ≥2 times per day .
|
study
| 99.94 |
Our results are of interest for a number of reasons. Translating research knowledge to practice and policy is much needed in the field of health promotion . The idea of testing the connection between diet and cognition using functional cognitive measures such as GPA, graduation rates, and rates of taking college entrance exams was aimed at bridging the gap between research and policymaking. Although evidence on the consequences of unhealthy diets on learning and cognition is growing, the failure to implement effective interventions persists. A more informed approach to this connection can influence healthcare practitioners, educators and parents.
|
other
| 62.66 |
In addition, lower academic results have been associated with several health-risk behaviors in youths. In US adolescent populations, over the past three decades, cross-sectional and longitudinal studies demonstrate links connecting poor academic performance with sedentary lifestyle, alcohol/tobacco abuse, sexually risky behaviors, and violence . All of these risk behaviors have been regarded as important contributors to poor health status in adulthood and multiple social problems. Since the influence of academic performance on future health is known , the relationship of diet and academic results may be an important public health tool. It is also important to identify the nutrients and dietary patterns that most influence cognitive health and academic performance.
|
review
| 99.7 |
The fact that adolescents struggle to make healthy dietary choices is not new information. Youthful anomalous health decision-making has been attributed to an aversion to forced choices; the inclination to rely on taste, brands, and convenience as primary drivers of food decisions; and the tendency to discount the value of delayed rewards or penalties . Also, sufficient nutrition knowledge does not necessarily correspond to responsible dietary behavior . Thus, associating healthy dietary choices with school performance can perhaps enhance the value of healthy eating and boost motivation. After all, academic achievement, academic behavior, and academic performance are closely linked to expectations of better postsecondary opportunities and subsequent job status .
|
other
| 99.9 |
Our results that show an association between a healthy diet and improved cognitive and educational outcomes should be a matter of interest to support nutrition interventions designed for adolescents. To date, the majority of interventions that emphasize the relationship between diet type and cognition and academics have been designed for infants and young children , who are less independent in their food choices. For health promotion purposes, unhealthy dietary habits during adolescence are usually said to be related to early onset of cardiometabolic disorders, including high blood pressure, type-2 diabetes and coronary heart disease, while arguments based on the potential cognitive impact of diet are still lacking. We have seen that adolescents are also exposed to the detrimental cognitive effects of a diet high in saturated fats and refined sugars. Moreover, adolescence is a transitional period with subcortical regions associated with reward-seeking and emotion developing earlier than prefrontal control regions . Greater emotional reactivity and sensitivity may in part explain unhealthy dietary habits among teenagers. Sociocultural changes, the need to fit in, food availability and the quest for independent decision-making also contribute to unhealthy food choices that are common during adolescence , making this period one of tremendous importance in terms of cognitive development.
|
study
| 99.9 |
A further implication of these findings is that they can potentially play a major role in health promotion by educational agencies and schools. Dietary habits that comport with food guidelines might help pave the way for students on the path to higher education. Chilean high school students perform far below the Organization for Economic Co-operation and Development (OECD) average in mathematics, reading and science, with less than 2% of 15-year-old scoring in the group of top performers . Evidence shows that students who fail to reach baseline levels of performance in these areas have difficulties with academic readiness, persistence and higher education completion . Nonetheless, 80% of Chilean parents expect their children to obtain a college degree .
|
other
| 99.9 |
This research provides results that support a connection between nutritious dietary intake and higher academic achievement. Given that most studies have been conducted in the developed world, one strength of this study is that it provides evidence that may be useful for countries undergoing nutritional and epidemiological transitions. Second, the use of a translational research approach to explore the diet–learning–cognition connection and provide applicable results is a positive contribution. Further, to our best knowledge, this is the first study to investigate the association of nutrition and academic achievement on HS students’ postsecondary education intentions.
|
study
| 99.94 |
Despite these strengths, several limitations persist that should be considered when interpreting these results. Our sample is not representative of the Chilean adolescent population, as it consisted of adolescents from low and middle SES families. However, data from these socioeconomic groups may be especially important: population-based surveys conducted in Chile show that the prevalence of unhealthy dietary habits, physical inactivity, and excess weight is higher in adolescents from low and middle SES families compared to adolescents from high SES families . This means that students from low and middle SES families are more exposed to risk factors for difficulties related to progressing from high school to higher education. Encouraging healthy dietary habits and, in particular, intake of healthy snacks, might smooth the pathway to college. Second, although we accounted for the effect of important confounders (including parental education and family structure), we were not able to consider other key influences, such as family support-related variables, general motivational factors (e.g., achievement motivation), and students’ interests in specific subject areas, which may also impact their academic functioning. A third limitation is the cross-sectional nature of the study. Since data on snack quality for each participant was recorded only once, it would be difficult to infer the temporal association between this exposure and the academic outcomes. Thus, only association, and not causation, can be inferred from our study. While our results may be useful to inform new hypotheses, a more complex investigation, such as a longitudinal study or crossover intervention trial, should be conducted to test the temporality of these associations, i.e., that the exposure to Western-type food items precede academic difficulties. Finally, future studies should replicate and extend this analysis in other young populations.
|
study
| 100.0 |
Poor nutritional quality snacking at school and at home was associated with poor secondary school academic achievement and lower intention to enroll in higher education. Both types of snacking showed similar associations with these educational outcomes. These results may have important implications for the promotion of healthy lifestyles by educational agencies and schools. Also, associating healthy snacking with educational outcomes can perhaps enhance the value of having responsible health behaviors and boost motivation for a healthy way of life.
|
study
| 99.8 |
Glioblastoma (GBM), the most commonly diagnosed malignant brain tumor in adults , has a poor prognosis, with a median survival of only 12-15 months and a high rate of recurrence . Poor prognosis and overall survival (OS) is attributable to the marked inter- and intra-tumoral genetic heterogeneity of GBM tumors [3–6]. Magnetic resonance imaging (MRI) holds great potential for characterizing the phenotypic heterogeneity of GBMs by inferring this from textural information and intensity variations in radiological images. Common techniques such as gadolinium contrast-enhanced T1-weighted imaging highlight perfusion variations in tumor images and advanced image-texture analysis may be able to characterize signal intensity variations within tumors. Texture analysis has many applications in medical image processing and provides one approach to quantify the distribution of gray-level patterns such as homogeneity, entropy, etc., within a set of imaging data . Multiple methods for assessing imaging features and characterizing pixel intensity distributions by quantifying gray levels have been described [8–11]. These methods allow for rigorous and reproducible derivation of detailed, pertinent information, and have been used to analyze MRI features, such as apparent diffusion coefficient, 2-dimensional (2D) spatial habitats , and texture features. These characteristics correlate with the grade of disease, patient survival, response to chemotherapy, and genetic and epigenetic status [12–18]. With recent advances in radiomics and radiogenomics (or imaging-genomcis), molecular and genetic heterogeneity can be inferred from MRI features by correlating imaging datasets with corresponding molecular and clinical information.
|
review
| 99.9 |
Several studies have correlated specific features seen in MRI of GBM with patient survival and molecular subtype. However, these investigations have been restricted to 1 or 2 particular MRI sequences and typically considered only features from a single 2D slice [12, 16, 17]. In contrast to these single-sequence, slice-by-slice analyses, radiologists review all acquired MRI sequences in their assessments. Additional research is needed to develop methods for extracting computational radiological features from full multiparametric MR imaging sets. To this end, this study focuses on using four MR sequences to understand the heterogeneity of a tumor region.
|
study
| 99.94 |
We hypothesized that by performing a 3D volumetric analysis of commonly available MRI sequences, we could identify particular imaging habitats correlated with both patient overall survival status and identify key genetic pathways associated with such habitats in GBM. Comprehensive analysis of imaging data could improve the predictive power of this approach and provide novel insights to aid clinical decision-making.
|
study
| 100.0 |
Eighty-five patients with GBM identified in the Cancer Genome Atlas who had imaging, clinical, and genomic data available were included in this study. Table 1 shows the patient and respective tumor characteristics within 85 TCGA-GBM cases. Four pre-operative MR scans were obtained for each case: Pre-contrast T1-weighted (T1) image, post-gadolinium T1 (T1c) image, T2-weighted (T2) image, and T2 fluid-attenuated inversion recovery (FLAIR) image. Following skull stripping, rigid registration, and automated segmentation using Brain Tumor Image Analysis (BraTumIA) software , we grouped tumor voxels into high and low signal bins for each of the 4 MRI sequences (FLAIR, T1, T1c, and T2) via Kmeans clustering. Across these 4 MR sequences, this leads to the identification of 16 imaging habitats (i.e 24 combinations) based on unique combinations of these high and low signals. The habitats were assigned labels from 0 to 15, with “0” being low-intensity in all 4 acquisition modalities (i.e., FLAIR=0, T1=0, T1c = 0, T2 = 0) and “15” being high-intensity in all 4 (i.e., FLAIR=1, T1=1, T1c = 1, T2 = 1). For instance, habitat 2 represents low intensity in FLAIR, T1, and T2 with high intensity in T1c. Figure 1 describes the process for obtaining these 16 imaging habitats.
|
study
| 100.0 |
Based on 4 MR sequences (multi-parametric MRI scans), classify each voxel within the tumor volume into high and low categories via kmeans clustering. With 16 (24) signal combinations across the 4 sequences (i.e. 0000-1111), every voxel in the tumor volume can be identified uniquely. The resultant habitat map shows the spatial heterogeneity within tumor.
|
study
| 99.94 |
Random survival forest modeling and Cox proportional hazards regression analysis determined imaging habitats 2,7, and 10 to be both important (+ve variable importance) and significant (p-value < 0.05) for determining OS after adjustment for covariates of age, Karnofsky performance score, tumor volume, and IDH1 mutation status (P < 0.05, Supplementary Table 1). These three habitats were thus designated as “relevant” habitats. The process of acquiring these relevant habitats is described in Figure 2. They represent distinct tumor sub-regions of clinical relevance to outcome in GBM, after adjusting for clinical covariates. Their relevance, coupled with the availability of matched genomic data for these patients, enables us to study the molecular mechanisms (pathway activities) associated with the presence of these habitats in GBM.
|
study
| 100.0 |
After adjusting for clinical covariates (age, Karnofsky performance score, tumor volume, and IDH1 mutation status), we identified important habitats (positive variable importance) via Random Forest survival analysis. Those habitats were then assessed for significance via Cox Proportional Hazards Regression to determine overall survival (OS). Only habitat 2,7, and 10 are both important and significant (i.e “relevant”) in determining OS.
|
study
| 100.0 |
We used the pair-wise Spearman rank test to correlate the amount of each relevant habitat in the tumor with the amount of necrotic, enhancing, non-enhancing, and edema regions within the tumor (Table 2). In particular, habitat 2 was also associated with necrosis (p = 0.0172). For habitat 7 and 10, there was no specific association with canonical tumor sub-volumes, suggesting the need for deeper examination of their physiology and molecular context.
|
study
| 100.0 |
To study the relationships between relevant habitat proportions and molecular pathway data , we performed Dirichlet regression analysis. Table 3 lists the key genetic pathways that are most strongly correlated with the relevant habitats. In particular, habitat 2 was positively associated with positive regulation of NFκB transcription-factor activity; while negatively associated with dendrite morphogenesis. Habitat 7 is correlated positively with DNA damage response signal transduction resulting in induction of apoptosis and macrophage activation. Further, habitat 7 was correlated negatively with immune cell activity (monocyte differentiation). Habitat 10 shows positive association with activity of signal transducers and activators of transcription-1 (STAT-1) and Natural killer cell activation, while showing negative correlated with ion channel activity (potassium channel inhibitor activity and voltage gated calcium channel activity).
|
study
| 100.0 |
Through analysis of multi-parametric MR imaging, we have identified tumor sub-regions with unique combinations of gray-level intensities from each of the four MR modalities included in this study. From these 16 habitats, relevant (i.e. important and significant) habitats were identified based on association with OS status, and further, correlated with morphological and pathological characteristics of tumor, such as leading edge, infiltrating tumor into normal brain, edema, and enhancement around lesion edge. For example, habitat 10 was associated with canonical tumor sub-volumes like edema, peripheral tumor tissue, and enhancement around lesion edge.
|
study
| 100.0 |
Our analysis reveals that the intratumoral abundance of these habitats are associated with outcome. Delineating the extent and location of these aggressive habitats can have implications for delivery of radiotherapy (boosting RT to aggressive habitat areas), surgical resection (an aggressive habitat not impinging on an eloquent area is amenable for possibly complete resection). Additionally, tracking/monitoring the growth of aggressive habitat subvolumes can provide a deeper understanding of disease evolution/recurrence instead of just gross tumor volume. The utility of defining heterogeneity in glioblastoma thus is closely related with prognosis and overall survival of patients [1–4]. Hence, defining such phenotypic heterogeneity is directly relevant for treatment planning, surgical intervention, disease monitoring, and prognosis estimation in the clinic.
|
study
| 99.94 |
Dirichlet regression implicated each relevant habitat with pathway alterations due to unique upstream transcriptional regulators and signaling activity. Imaging-derived habitats also showed some common cellular processes and pathway activity, such as natural killer cell and STAT-1 signaling. These findings are consistent with hallmarks of cancer [21, 22], such as avoiding cell death (natural killer cell) and inducing angiogenesis (tyrosine phosphorylation of STAT-1).
|
study
| 100.0 |
Recent literature supports the relationships inferred between clinical pathologies for habitats (Table 4) and pathway alterations (Table 3). For instance, it is reported that that overexpression of inflammatory cytokines is linked with the leading edge of the gliomas. This is consistent with our findings (positive association of cytokine production) in habitat 2, which is associated with the leading edge of the tumor . Furthermore, it is well known that glioblastoma is infiltrated by diverse immune cells including macrophages , which might explain the positive association of macrophage activation and habitat 7. It is also reported that potassium channel inhibitor activity plays a critical role in cell proliferation and cell swelling in neuroblastoma and gliomas . Further, Sforna et al. reported that calcium ions channels play a role in swelling in GBM. These reports are consistent with our clinical pathology interpretation, edema, for habitat 10.
|
study
| 99.94 |
Our study has some potential limitations. This retrospective study relied on publicly available imaging data acquired across multiple clinical sites. Thus there were some variations in imaging acquisition/sequence parameters (e.g., Relaxation Time and Echo Time) and hardware (e.g., magnetic field strength and receiver coil geometry). In order to mitigate these effects, and in accordance with standard practice, intensity normalization and registration were applied to each image prior to habitat analysis. However, any remaining intensity variations could have potentially affected initial tumor segmentation. A systematic study with standardized image acquisition protocols is needed in order to validate the robustness of these imaging-derived habitat characteristics. Another aspect of uncertainty in this study is derived from the patient outcome data. Because these patients were treated at different institutions, aspects of their treatment regimens may not have been fully standardized, which could potentially affect patient OS duration. Additionally, an inherent challenge with all genomic information derived from tumor specimens is the inability to account for spatial heterogeneity of genomic alterations and tumor cell clones. As with the quality of the imaging data described above, the robustness of the genomic data is also subject to similar uncertainties that can influence the overall generalizability of our conclusions. Also, the presented relationships between habitats and genetic pathway alterations are inferred based on statistical regression methods. These findings could potentially form the basis for targeted perturbation experiments in-vivo to illuminate the mechanistic or causative nature of the relationships between habitats and pathway activity. While outside the scope of this study, research efforts in this direction [27, 28] are essential before these associations can be exploited therapeutically. However, the process of habitat inference and its association mining for prognostic intent can be done quite readily in the current clinical scenario since these 4 MR sequences (T1, T1c, T2, FLAIR) are used routinely.
|
study
| 99.94 |
One hundred patients with primary GBM were identified from The Cancer Genome Atlas (TCGA). Patient image data and corresponding clinical data were extracted from The Cancer Imaging Archive . All patients had undergone routine MRI prior to surgery and treatment. Pre-contrast T1-weighted (T1) images, post-gadolinium T1 (T1c) images, T2-weighted (T2) images, and T2 fluid-attenuated inversion recovery (FLAIR) images were acquired. Patient genomic and molecular data were obtained from cBioPortal and included data on genetic pathway activation (PARADIGM scores ). This study abided by the TCGA data use agreement and was Institutional Review Board-exempt.
|
study
| 100.0 |
Of the initial 100 GBM patients identified, 85 patients had a complete set of imaging, clinical, and genomic data available. These patients were separated into 2 survival groups: OS (OS) ≥ 12 months and OS < 12 months. The acquisition parameters for the four MRI sequences used in this study are as follows – T1 (echo time: 15-8.5 ms, relaxation time: 642-400 ms), T1 post contrast (echo time: 15-8.5 ms, relaxation time: 700-400 ms), T2 (echo time: 120-30 ms, relaxation time: 6000-2140 ms) and FLAIR (echo time: 150-90 ms, relaxation time: 11000-6000 ms).
|
study
| 100.0 |
For our study, Brain Tumor Image Analysis (BraTumIA) software was used to perform image preprocessing steps (skull stripping and rigid registration), followed by automated segmentation of normal structures (cerebrospinal fluid, gray matter, and white matter) and diseased tissue (necrosis, edema, non-enhancing tissue, and enhancing tissue) .
|
study
| 100.0 |
Patient images and the BraTumIA-derived segmentation masks were loaded into MATLAB for habitat analysis. For habitat analysis, we used only the regions of the MR image associated with tumor (i.e. necrosis, edema, non-enhancing tissue, and enhancing tissue). These BraTumIA segmentation labels were combined to create one binary mask of the tumor region for each patient. The masks were applied to each scan to extract intensity values from the tumor. The tumor intensity values were first scaled relative to gray matter and white matter intensity and then subsequently, linearized (scaled from 0 to 1) based on the maximum and minimum in each image. Following Zhou et.al K-means clustering was applied to each MR sequence type (FLAIR, T1, T1c, and T2) across all patients to derive sequence-specific, intensity thresholds that separate high-intensity pixel values from low-intensity pixel values. Each sequence image for each patient was then dichotomized into sub-regions of high or low enhancement (1 or 0, respectively). The combinations of high and low enhancement for each patient resulted in 16 possible imaging habitats, where habitat 0 is represents regions with low-intensity (FLAIR = 0, T1 = 0, T1+C = 0, T2 = 0), habitat 3 represents regions with characteristics (FLAIR = 0, T1 = 0, T1+C = 1, T2 = 1), and habitat 15 represents regions having high-intensity in all acquisitions (FLAIR = 1, T1 = 1, T1+C = 1, T2 = 1). A 3D spatial representation of the imaging habitats was created using these labels. Subsequently, habitat proportions, the fraction of tumor pixels belonging to each imaging habitat, were calculated for each patient. The process of obtaining 16 habitats is described in Figure 1.
|
study
| 100.0 |
Statistical analysis was performed using R statistical software (R Foundation, Vienna, Austria) with the “survival” (v 2.38-2), “randomForestSRC” (v 2.0.5), and “DirichletReg” (v 0.6-3) packages. Random survival forest (RSF) regression was applied to the imaging habitat proportions to determine if any habitats were associated with OS [16, 38, 39]. The random forest regression identified a subset of habitats that were deemed “important.” Cox proportional hazard regression analysis was then used to determine the association of these (RSF-derived) important habitats with OS (p-values less than 0.05) [40–42], after adjusting for clinical covariates (age, volume, karnofsky score: KPS, IDH1 mutation). Image habitats that were deemed important based on random survival forest regression, and significant from the Cox proportional hazard regression were designated “relevant”. The process of obtaining relevant habitats is depicted in Figure 2. These relevant habitats were then correlated with BraTumIA-derived tumor volume segmentations (edema, necrosis, enhancing regions, and non-enhancing regions) via pair-wise Spearman rank correlation tests. In addition, Dirichlet regression was applied to each relevant habitat to determine if that habitat was associated with pathway activation (PARADIGM) scores. This analysis generated molecular signatures associated with each relevant imaging habitat. The significance of the Dirichlet regression for each pathway was determined by calculating a Bonferroni-adjusted P value, and the strength of association was determined from the absolute value of the Dirichlet regression coefficient.
|
study
| 100.0 |
This study has elucidated a nuanced relationship between imaging habitats derived from MR images, clinical characteristics, and molecular data in a cohort of GBM patients. The present study implemented an automated methodology that parallels the traditional practice of a neuroradiologist by considering the totality of 3D imaging data (i.e. across multiple MR sequences) from each patient. This technique represents an advance in imaging-genomics. Whereas previous studies derived associated imaging features and genomic data from 2D imaging datasets [12, 29, 30], this study adopted a 3D approach, which is consistent with the progress of the field towards studying 3D image features [10, 31–34] for imaging-genomic analysis. Our approach utilized a multi-parametric representation of 3D image features derived from different imaging sequences overlaid upon each other to generate an imaging phenotype that predicts OS duration, after adjusting for clinical covariates.
|
study
| 99.94 |
This work revealed associations between MRI-derived habitats and oncogenic molecular mechanisms in patients with GBM. The analytical framework and workflow demonstrated in this study are inherently scalable to any number of MR sequences. The four MRI sequences used, FLAIR, T1, T1+C, and T2, are readily available on most modern scanners and used routinely in clinical practice. More advanced sequences such as susceptibility-weighted imaging, diffusion-weighted imaging, or MRI spectroscopy could be incorporated into this framework in a fairly linear manner (with ‘k’ MR sequences, you have 2k habitats). Furthermore, with appropriate imaging and tumor segmentation, this workflow could accommodate data from other tumor types and/or other anatomical sites.
|
study
| 100.0 |
Pathway analysis of the molecular data associated with each habitat showed significantly altered molecular pathways, supporting the hypothesis that each radiographically-distinct tumor habitat is associated with distinct molecular characteristics. Some of these altered pathways pertain to angiogenesis, while others correlate with signaling pathways known to be co-opted by tumor cells to facilitate their avoidance of cell death. The relationships elucidated by this study between imaging habitats and underlying biology may offer additional information regarding the patient's disease state, complementing inference based on genomics alone. Future work will extend this analysis by considering tumor location, extent of resection, methylguanine-DNA methyltransferase (MGMT) promoter methylation status, as well as extending this work to other tumor types and anatomical sites. A systematic assessment of the impact of acquisition parameter variability on robustness of imaging habitats will also need to be performed before clinical adoption. These results also lay the groundwork for investigations of targeted hypotheses from MRI-guided biopsies [27, 28] in GBM with corresponding genomic analyses to confirm and validate these phenotypic-genomic relationships.
|
study
| 99.94 |
Different treatments which are employed to improve cognitive performance in children with ADHD have certain pros and cons . Although pharmacological treatments are easily applicable and usually useful for treating ADHD, their long-term health effects are still under question [4, 5]. They are also associated with certain side effects such as sleep disturbance, loss of appetite, and growth suppression. Furthermore, psychosocial treatments including training parents and behavioral therapy are effective interventions but results are not maintained in long term [4, 6]. Regarding the limitations of available treatments, new treatment options are needed for ADHD.
|
review
| 99.9 |
Neurofeedback (NF) has been introduced to treat ADHD recently and is able to improve the attention level and alleviate the hyperactivity symptoms [7–12]. The process provides a mechanism by which the patient can normalize the cortical activity profile through decreasing slow wave activity and increasing fast wave activity. It is expected that compensation of the dysfunctional electroencephalogram (EEG) enhances concentration and attention and increases the arousal level [13–17]. In fact, patients will learn how to enhance the desirable EEG frequencies associated with relaxed attention and how to reduce the undesirable frequencies which are associated with under- or overarousal .
|
review
| 99.8 |
Despite therapeutic advantages of NF for patients with ADHD [10, 11, 19], the results of various studies are not conclusive. The reason for dissimilar results of available reports might be the different treatment techniques or protocols used for this purpose. In other words, since NF is almost a new treatment approach, a variety of treatment protocols is being examined. Different variations over different bands of cortical activity in various parts of the cortex have been applied, and each one has been accompanied by different clinical efficiencies. The most common treatment protocol for improving various symptoms of ADHD involves suppressing theta wave and enhancing beta wave . Alpha activity might be an interesting target of treatment as it is associated with different types of cognitive processes, memory performance, perceptual performance, and intelligence. Klimesch et al. and Escolano et al. report effectiveness of upper alpha power in improving cognitive performance in ADHD. However results are not conclusive about the best protocol for ADHD. Increased alpha reference power is associated with large event-related desynchronization, better memory, and perceptual performance [23, 24]. High-frequency alpha band would improve the memory function in patients with ADHD and previous reports suggest targeting theta and alpha activity in NF protocols .
|
review
| 99.9 |
According to previous findings, this study aims to compare the efficacy of two NF protocols including theta suppression/beta enhancement and theta suppression/high-frequency alpha enhancement regarding their effect on cognitive functioning of children with ADHD.
|
study
| 99.94 |
Sixty children with ADHD were randomly selected from patients who were referred to the specialized psychiatric clinics in Tabriz, northwest of Iran. This study was verified by the Scientific and Ethics Committee of Tabriz University of Medical Sciences as a doctoral thesis . The protocol is registered in Iranian Registry of Clinical Trials (IRCT201404122660N4, http://en.search.irct.ir/view/17747). After a thorough explanation of the study purpose, caregivers of participants signed the consent form for participating in the study.
|
study
| 99.4 |
All of drug naïve children and adolescents who meet the DSM-5 diagnostic criteria (American Psychiatric Association, 2013) for combined ADHD were eligible. The diagnosis was made through a semistructured diagnostic interview with parents using SADS-K-PL by a child and adolescent psychiatrist. Exclusion criteria were history of severe head injury, neurological disorders, genetic disorders, psychiatric disorders other than ADHD, and intellectual disability. Children who had received psychotherapy within the past one year were also excluded. After enrolment by the evaluating psychiatrist, selected children were randomly divided into two groups by a schedule generated by RandList (Figure 1) by a nonevaluator coauthor. Recruitment started in April and ended in December 2014.
|
study
| 99.94 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.