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More days of either aerobic or strength exercise were associated with lower total cholesterol, LDL, HDL ratio and triglycerides, and higher HDL in both men and women. The association between exercise frequency and a positive blood lipid profile are in agreement with prior research . Interestingly, we did not observe a significant association between aerobic exercise frequency and total cholesterol in women, despite improvements in other blood lipids. This may be due to gender differences in lipid utilization during exercise , a physiological threshold to support reproductive function , or the concurrent rise in HDL, negating a net change in cholesterol.
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study
| 100.0 |
More days of either aerobic or strength exercise were associated with lower glucose and HbA1c in both men and women. Similarly, both physical activity and cardiorespiratory fitness have been associated with lower fasting glucose and lower HbA1c in prior research. Lower fasting glucose and HbA1c are indicative of better glucose regulation due to changes in beta cell functioning . The association of lower glucose and HbA1c with higher exercise frequency may be due to the insulin-independent mechanism for glucose uptake by muscle cells stimulated by muscle contraction during exercise .
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study
| 99.94 |
More days of either aerobic or strength exercise were associated with lower CRP in both men and women. Being an inflammatory factor produced by the liver that increases in response to infection or inflammation , CRP has been associated with chronic disease and sedentary lifestyle . Lower levels may suggest reduced systemic inflammation in more active individuals. Previous research has reported a similar association, where higher physical activity was associated with lower CRP . Lower CRP is believed to be part of the mechanism for the protective effects of physical activity against cardiovascular diseases through reduced coagulation .
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study
| 99.94 |
Associations between exercise frequency and total blood protein differed by mode and sex. In women, days of reported aerobic exercise participation were significantly associated with lower total serum protein, while days of reported strength exercise participation were significantly associated with higher total serum protein. In men, no association between days of aerobic exercise participation and total serum protein were observed. However, days of reported strength exercise participation were significantly associated with lower total serum protein in men. Although athletes have higher dietary protein requirements to support the increased needs for protein during recovery , it is unclear why mode of exercise and sex appear to affect total blood proteins differently. Observations may be explained by the sub-types of blood proteins, albumin, and globulin.
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study
| 99.94 |
More days of either aerobic or strength exercise were associated with higher levels of albumin in men and women, except for men who participated in strength training exercise, where levels were lower. Albumin is important for transporting substances in the blood such as bilirubin, calcium, and progesterone, and for maintaining osmotic balance . Increased levels in active individuals may be an adaptation to exercise training to expand plasma volume . Albumin is associated with protein status in the body , where strenuous exercise increases albumin excretion and low protein intake decreases rate of albumin synthesis . Men who strength train may thus have lower synthesis or higher excretion due to dietary intake or reduced stimulus for albumin production.
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study
| 99.94 |
The effects of exercise participation on blood globulin proteins showed a more consistent effect, where more days of either aerobic exercise were associated with lower levels of globulin protein in the blood for both men and women. Similarly, globulin levels have been shown previously to decrease with endurance exercise . As globulin proteins consist of a variety of proteins, it is plausible that reduced globulins with exercise participation is a physiological adaptation to increase the bioavailability of different compounds in the body as opposed to a reduction in immunoglobulins .
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study
| 100.0 |
With the exception of strength training participation in men, more days of either aerobic or strength exercise were associated with higher levels of bilirubin that were still within normal limits. Bilirubin is a metabolite of heme produced from normal red blood cell breakdown. In healthy athletes, elevated bilirubin may indicate an accelerated rate of red blood cell turnover , stimulated by exercise conditions such as muscle contraction, impact, and high oxygen.
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study
| 99.94 |
With the exception of strength training participation in men, more days of either aerobic or strength exercise were associated with higher levels of calcium. Prior research has shown that plasma calcium increases in response to exercise likely due to metabolic acidosis . Because 40% of circulating calcium is bound to albumin, the observed changes in calcium may be a direct result of the changes in albumin concentration.
|
study
| 100.0 |
More days of either aerobic or strength exercise were associated with higher levels of creatinine in both men and women. As creatinine is a metabolic product of creatine breakdown, active individuals and those with higher muscle mass would be expected to have higher creatine turnover resulting in higher serum creatinine levels. Prior research has similarly shown higher serum creatinine in athletic populations , particularly in sports involving strength and power . As our results and prior research have shown , reference intervals for creatinine for the general healthy population may not be appropriate for the active population.
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study
| 100.0 |
More days of either aerobic or strength exercise were associated with lower eGFR. eGFR is a measure of the rate that the kidneys are able to filter blood that is based on creatinine in the blood, along with age, race, and sex. While physical activity has been positively associated with kidney function eGFR may be higher in athletes following exercise because of higher creatine metabolism, especially for athletes with larger muscle mass . However, eGFR may be temporarily decreased in the day following exercise and has been shown to be lower in some endurance athletes and team sports athletes .
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study
| 99.9 |
More days of either aerobic or strength exercise were associated with higher levels of iron and percent saturation in both men and women. In addition to being important for the production of hemoglobin and new red blood cells, iron is an important constituent of myoglobin and various enzymes. Iron is also important to the metabolic processes involved in exercise and adaptations to exercise training . Athletes may lose iron 20% faster than non-athletes , as iron red blood cells are broken down during exercise by the mechanical stress of muscle contraction . Thus, the higher levels of iron and percent saturation in those with higher activity levels may be due to increased needs for iron during exercise .
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study
| 100.0 |
The effects of exercise frequency on TIBC differed by gender. In women, neither aerobic nor strength exercise participation were significantly associated with TIBC results. However, in men, both days of reported aerobic exercise participation and days of reported strength exercise training were significantly associated with lower TIBC. TIBC is a measure of the body’s ability to transport iron in the blood and is often elevated with iron-deficiency, lower work capacity, and fatigue in athletes . The lower levels of TIBC associated with higher levels of aerobic or strength exercise in men may be an adaptation to exercise training to allow greater iron transport to accommodate increased needs with higher exercise volumes. It is unclear why the same association was not evident in women. However, it may be due to the higher prevalence (32%) of iron deficiency or supplementation (50%) in female athletes.
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study
| 99.94 |
While days of reported aerobic exercise participation were significantly associated with lower ferritin in men only, days of reported strength exercise training were not associated with significant changes in ferritin levels in men or women. As ferritin is a protein that stores and transports iron, levels correlate to iron status in the blood. Previous research has shown that high-volume exercise training leads to decreased ferritin levels in male endurance athletes . Although type and duration of exercise determine iron metabolism and blood cell adaptations , it is unclear why aerobic exercise were not associated with ferritin levels in women.
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study
| 99.94 |
With the exception of men who participate in aerobic exercise training, more days of strength or aerobic exercise were associated with higher AST. Additionally, with the exception of women who participate in strength exercise training, more days of strength or aerobic exercise were associated with lower ALT. AST and ALT are both aminotransferase enzymes found primarily in the liver and play a role in amino acid metabolism. Elevated levels of AST in active individuals are likely a result of increased amino acid metabolism and release from muscle . Prior research has shown that both AST and ALT increase after both aerobic and strength exercise where levels can be elevated for more than 7 days . As metabolic demands are increased in active individuals, it is not known why higher frequency of participation in aerobic exercise was associated with lower AST in men or why levels of ALT tended to be lower in active individuals; these associations may be due to lower amino acid metabolism in these individuals.
|
study
| 100.0 |
More days of aerobic or strength exercise participation were associated with lower GGT in men and women. Serum GGT is derived from the liver , serves as an indicator of general liver health, and is transported with albumin and lipoproteins in the blood . Prior research has shown that although GGT increases acutely after aerobic exercise , lower resting GGT is associated with higher physical activity . The role of GGT in exercise may be through counteracting oxidative stress by breaking down extracellular glutathione and making its component amino acids available to cells for repair . Serum levels of GGT are positively associated with body mass index, alcohol use, and total serum cholesterol .
|
study
| 99.94 |
With the exception of men who strength train, more days of aerobic or strength exercise participation were associated with lower ALP in men and women. ALP is an enzyme found primarily in bone and the liver that is involved in both removal of mineral phosphate from molecules and inflammatory conditions. Levels of ALP are related to bone activity . As levels of bone specific ALP increase during weight-bearing exercise , but return to baseline within 20-minutes following exercise, lower resting levels may be a consequence of the transient response to weight bearing exercises.
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study
| 100.0 |
Neither days of reported aerobic nor days of strength exercise participation were significantly associated with TSH in men or women. Thyroid hormones play an important role in metabolism, growth, tissue differentiation, fatty acid oxidation, and thermoregulation in response to exercise training [51–53]. Previous studies evaluating thyroid function in athletes have shown contradicting results . In elite soccer players, TSH levels have been shown to increase over a competitive season . However, in other studies, both power and aerobic athletes have been shown to have a lower serum TSH , indicating a possible increased sensitivity of the thyroid gland to TSH in athletes. Although, specific training plans may affect thyroid hormones in circulation, the present data does not support evidence of different levels of TSH in the active population compared to the more sedentary population.
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study
| 99.94 |
The effects of exercise frequency on uric acid differed by gender. In women, neither aerobic nor strength exercise participation were significantly associated with uric acid results. However, in men, reported days of both aerobic and strength exercise participation were significantly associated with lower uric acid. Lower uric acid may be an adaptation to training, as prior research has reported lower uric acid in male athletes compared to non-athletes . Uric acid increases after intense exercise that recruits fast-twitch muscle fibers , likely in order to increase serum antioxidant capacity and reduce oxidative stress during acute physical exercise . Despite its short term role in exercise responses, high resting uric acid has been associated with poor strength , vulnerability to tendon injury , and disease .
|
study
| 99.94 |
While this study reports new information on the relationship between exercise participation and common laboratory measures, findings should be interpreted within the context of the present study design. First, from a population level, assessment of exercise participation by frequency and mode alone is not able to capture the relationships or mechanisms with other exercise metrics such as intensity and duration. Further study is needed to evaluate the effects of exercise intensity and duration on these relationships. Additionally, in order to isolate and explore the different effects of strength vs. aerobic type exercise, predicted values were reported as 0 vs. 5+ days per week of exercise participation. While this may differ from some physical activity recommendations, it better allowed the distinct effects of each mode of exercise to be displayed. In addition, as exercise and health data were collected by questionnaire, the potential for recall and reporting bias may exist. Interpretation bias may also exist, as the questionnaire did not define aerobic or strength exercise. Furthermore, participants with reported medical conditions that may affect common laboratory tests were included in the study in order to represent a characteristic population. While the proportion of individuals without a reported health condition was higher for individuals reporting more days of strength or exercise participation, all individuals were included in the analytic sample due to broad health condition classifications, insufficient sample sizes by each reported condition to power subgroup analysis, and in order to represent a characteristic sample of the population. In regards to age, although younger age was associated with greater strength exercise participation, the restriction of our population to adults aged 18 to 34y and the less than 1 year difference found between groups was not considered clinically meaningful and supported the non-stratified analysis. Additionally, the sample may be biased toward working employees and not necessarily representative of the population. However as the goal of this study was to demonstrate the effects of exercise on biomarkers of health, the relationships may be applicable to a more broad population. Finally, this study was restricted to men and women aged 18 to 34 years of age in order to avoid the confounding influence of age. Accordingly, application of results would be most appropriate to populations with similar characteristics. Further study is needed to determine the influence of age on such relationships.
|
study
| 99.94 |
Physical exercise participation is related to clinical laboratory test results for a variety of common biomarker results. Laboratory test results should be interpreted within the context of each person and their unique set of circumstances. Reported relationships may help in the understanding and interpretation of common laboratory results for young, physically active adults and lead to defining appropriate reference intervals based on factors such as physical activity. Such data may help to interpret laboratory test results that may be a healthy adaptation to exercise training and to avoid misinterpretation of acceptable results.
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other
| 99.2 |
Bioclimatology or bioclimatics, which includes phenology, is an ancient science that investigates the relationship between living organisms and climates. According to historical records, China was the first country to conduct bioclimatic observation approximately 3,000 years ago. Bioclimatology is referred to as Wuhou (物候) in Chinese, a word that originated from the classic Ch’un-ch’iu Tso Chuan (春秋左傳). Western bioclimatology was established in approximately 1753 by Linnaeus, a Swedish botanist, who is known as the father of phenology. The term phenology was first introduced by the Belgian botanist Morren in 1853. One hundred years before the term was coined during Linnaeus’ time, phenology was focused on the seasonal and periodic phenomena that organisms exhibit and is referred to as classic or seasonal bioclimatology. In Japan, phenology is referred to as the study of seasons and organisms. Scientists have since identified that changes in living organisms follow periodic changes in climates. Thus, the scope and definition of phenology vary constantly as new bioclimatic findings are obtained. Consequently, the early definition of phenology has become inapplicable. Although numerous scientists have attempted to redefine phenology and create linguistically specific technical terms, many people prefer to use the established term phenology, which has been used continuously since it was coined. Bioclimatology, including phenology, now involves investigations of the correlations between climates and organisms (Chu and Wan 1999; Hopkins 1938; Hsieh and Chiou 2013; Lieth 1974; Schnelle 1955; Zou 1983). To avoid confusion caused by different definitions, this article defines all types of model that have both biological and climatic variables as bioclimatic models.
|
review
| 99.9 |
Despite its ancient origin, bioclimatology has long been disregarded because of problems, such as difficulty in funding long-term research in the past. In recent years, bioclimatology has received increasing attention and has become critical for investigating the effects of climate changes on organisms (Hänninen and Tanino 2011; Hsieh and Chiou 2013; Körner and Basler 2010; Lechowicz and Koike 1995). Initially, ancient people developed bioclimatology by recording the correlations between biological phenomena according to annual observations made during farming seasons and related experiences; in this way, lunar calendars and bioclimatic calendars were compiled. Thus, bioclimatic research development in ancient times was focused on agricultural phenomena and various biological indicators recorded in the bioclimatic calendars of different cultures were used as a disaster-prevention system for decision-making. Bioclimatology in the Western scientific field did not become a formal discipline until the mid-eighteenth century when Linnaeus established the first phenology observation networks in Sweden and emphasized the tasks and importance of phenological observations in his book Philosophia Botanica (Hsieh and Chiou 2013; Lieth 1974).
|
review
| 99.75 |
Because the threat of climate change has recently attracted increasing attention, phenology network records have been developed into two complementary research systems; one is the concept of bioclimatic fingerprints, which was developed from phenology observation networks and is used for observing and monitoring the effects of climate changes on organisms, and the other is bioclimatic modeling based on long-term bioclimatic records and variations of the phenology observation networks for clarifying the correlation between climates and organisms and predicting the possible effects of climate changes on organisms. The results can be used as references in future disaster alert systems, disaster-prevention decision-making, and the assessment of disaster effects (Peñuelas and Filella 2001).
|
other
| 99.75 |
Although bioclimatic models are essential to researching climate change effects and despite the rapid international development and application of bioclimatic models, research and reports regarding the application and exploration of bioclimatic models remain scant in many undeveloped and developing countries, which are severely threatened by climate change. To improve the capability of people to address the threat of climate changes, we reviewed the factors that influence plant bioclimatology, the construction and development of bioclimatic models, and the application of bioclimatic models in disaster prevention and impact assessment. The sequential review of the development history and importance of bioclimatic models in climate change research provided in this study can be used as references by researchers studying climate changes.
|
review
| 99.9 |
Bioclimatic models represent the phenomena, processes, or mechanisms of the effect of climate factors on organisms. Thus, before understanding the modeling principles of bioclimatic models, basic knowledge regarding the environmental factors that affect plant bioclimatology must be acquired. The effects of environmental factors on plants vary with plant species, phenological phases, geographical environments, physiological statuses, and levels and types of ecological systems, yielding complex mechanisms. Among numerous environmental factors, temperature, water availability, and air flow (i.e., wind) are more closely related to climate changes and substantially affect plants.
|
review
| 99.7 |
The climatic conditions of different seasons and regions cause varying effects on the bioclimatology of different plants (Menzel et al. 2001). For example, the higher winter temperatures at middle latitudes cause most plants to blossom and sprout earlier (Sparkes et al. 1997). At middle and high latitudes, the end of growth periods and the beginning of dormant periods of most plants are primarily influenced by the shorter days and temperature conditions of late summer (Heide 1974; Wareing 1956). Subsequently, the low temperature of the following winter breaks plant dormancy (Fuchigami et al. 1982; Perry 1971; Vegis 1964). Fluctuating temperatures break plant dormancy more effectively than constant temperatures do (Campbell and Sugano 1975; Hänninen 1990; Murray et al. 1989). However for some plants, fluctuating and constant temperatures have the same effect (Myking 1997). Phenological variations during plant growth periods are primarily affected by accumulated temperature (Peñuelas and Filella 2001). However, selecting the initial temperature for calculating accumulated temperature has been a major difficulty in bioclimatology because it may differ substantially in plants of the same species when influenced by varying environmental factors (Heide 1993; Murray et al. 1989). This difference severely affects the precision and prediction accuracy in research regarding plant growth bioclimatology. Despite the differences, 5 °C is commonly used as the initial temperature for calculating the accumulated temperature of plants (Cannell and Smith 1986; Cannell et al. 1985; Kellomäki et al. 1995; Murray et al. 1989).
|
review
| 99.2 |
In addition to temperature, water availability critically affects plant bioclimatology and is highly relevant to climate changes. However, the effects of water availability vary with species and other environmental conditions. In particular, the photoperiods and temperature conditions in tropical zones are relatively stable and variation in water availability is often the main factor influencing plant bioclimatology (Tissue and Wright 1995). For example, when it rains in tropical arid or semiarid climates, various plants blossom simultaneously, exhibiting high phenological synchrony (de Lampe et al. 1992). The following rainfall continuance affects the fruits of plants. A majority of tropical plants bear fruit in rainy seasons and the fruiting period is shortened or prolonged based on the precipitation of the current season (Bawa and Hadley 1991). Water shortage causes growth arrest among numerous plants, resulting in eco-dormancy (Reich and Borchert 1984). In high mountains and middle- to high-latitude areas, water availability and temperature changes resulting from thawing snow are key to plant blossom and growth (Walker et al. 1995).
|
review
| 97.9 |
Airflow is also a critical climatic factor that affects plants. When daylight is sufficient, adequate airflow, such as a breeze or zephyr, facilitates the airflow exchange of leaves and promotes transpiration lowering the leaf and environmental temperatures. Airflow also assists the pollination of anemophilous plants; however, when the wind speed is excessively high, the photosynthesis of leaves is subdued; the stigmata of flowering plants dry up, which affects pollination and causes infertility; or soil drying and wind erosion are expedited, which results in exposed plant roots, fallen fruits, leaves, and flowers, and even severe mechanical injuries, such as broken and fallen stems. Consequently, trees are weakened because of malnutrition, diseases, pests, or infections, which cause alternate bearing, and eventually die from nutrition depletion (Campbell-Clause 1998; Duryea et al. 1996; Telewski 1995).
|
other
| 99.7 |
The effects of climatic factors on plants differ according to the various growth and development stages of plants. For example, climate conditions influence germination so that the germinating of seeds of different species and in various regions differs substantially. The seeds of plants that grow in temperate latitudes require low temperatures or fluctuating temperature conditions that last for a certain amount of time to break dormancy (Hsieh et al. 2004). However, numerous studies have shown that some temperate plant species can break seed dormancy through exposure to high temperatures and long photoperiod days (Isikawa 1954; Johnson and Irgens-Moller 1964; Stearns and Olson 1958). Some temperate species can break dormancy and sprout only after exposure to a period of low temperature following exposure to high temperature, such as Taxus sumatrana (Miq.) deLaub. (Chien et al. 1995) and peony seeds. The germination of seeds from numerous species also varies with environmental conditions, such as those for Tsuga canadensis L. The seeds of Tsuga canadensis L. break dormancy and germinate after exposure to 10 weeks of low temperature. However, the temperature required for germination of seeds that have not been exposed to low-temperature stratification increases with the length of photoperiod. For a general photoperiod of 8–12 h, the optimal germination temperature ranges from 17 to 22 °C, Whereas if the length of the photoperiod is 16 h, the optimal germination temperature increases to 27 °C (Stearns and Olson 1958). However, Pseudotsuga menziesii (Mirb.) Franco seeds that have not undergone low-temperature stratification can successfully germinate after a short-photoperiod below 25 °C (Johnson and Irgens-Moller 1964). The climate requirements and resistance may differ even among the various organs of a plant species. A survey exploring the freeze injuries of Pyrus koehnei C.K. Schneid. showed that 90 % of 6-year-old plants were frozen to death under −14 °C and 50 % of suckers were frozen to death under −12 °C, whereas only 28 % of stem surfaces exhibited freeze injury. The median lethal temperature of the different tissues ranged from −10 to −15 °C (Nee et al. 1995).
|
review
| 99.8 |
Climate changes may exert differing effects on the same species of plant in different areas with identical climatic conditions. For example, in certain areas of the former Soviet Union where the climatic conditions are identical, walnuts trees are frozen to death in autumn in certain locations but survive autumn in other places. A subsequent finding indicated that the difference is caused by varying photoperiods. In certain areas, the photoperiods shorten before the autumn frost, resulting in the early dormancy of walnuts. In other areas, the photoperiods are not short enough to induce bud dormancy. Therefore, with the same temperature during autumn frost, walnuts may be frozen to death in some areas but survive the frost in other areas (Haldane 1947). Photoperiods also influence the blossoming of strawberry flowers. Temperatures and photoperiods jointly regulate the differentiation of flower buds. Generally, long photoperiods imply that flower bud induction requires long durations at low temperatures whereas short photoperiods imply that flower bud induction requires short durations at low temperatures. Thus, in areas with the same temperature conditions, varying photoperiods may affect whether strawberry flowers blossom. The condition of the plant itself may also have an influence; for example, during flower bud induction, a decreased number of old leaves easily induces flower bud differentiation (Darnell and Hancock 1996).
|
study
| 99.94 |
Distinct microtopographies and microclimates influence precipitation; even a slight variation in rainfall may substantially affect plant growth. For example, at high altitudes, the fruiting amount of Actinidia is inversely proportional to the degree of overlap of flowering periods and the East Asian rainy season. A high degree of overlap implies low fruiting rates for a certain year, whereas a low degree of overlap increases the fruiting rate. Certain species lack fruit every year because the East Asian rainy season overlaps the flowering period. This severely affects the reproduction and growth of Actinidia. and damages economic growth related to the plants (Nee 1994). Moreover, plant species respond differently to climate changes. For example, if plants, such as Acer saccharum Marsh. and eastern hemlock, which originate from different regions, are planted at one location, the plants from the north areas or high altitudes stop growing early in the autumn (Nienstaedt and Olson 1961; Robak and Magnesen 1970). Altitudes also affect the temperature requirements and responses of plants. For example, the seeds and buds of Actinidia have different dormancy conditions at different altitudes. The higher the altitude, the higher the chilling requirement to break seed and bud dormancy (Fan and Nee 2007). By contrast, peach and cherry trees have lower chilling requirements at high altitudes (Huang 2011; Ou et al. 2000).
|
study
| 99.94 |
Based on the aforementioned research cases, we identified that understanding the physiological mechanisms through which climates affect plants is crucial to climate change research. The influence of climate changes on plants varies substantially with differences in species, region, and other influential factors. Therefore, if the physiological and ecological conditions of plants are not specifically controlled, constructing an appropriate bioclimatic model for climates with similar variable conditions and accurately evaluating and explaining the resulting influence of climate changes can be difficult.
|
study
| 99.06 |
The origin of plant bioclimatic modeling is earlier than the formal establishment of bioclimatology. Such models can be traced back to 1735, when Reaumur proposed that the bioclimatic events of organisms and the dates of occurrence differ with regions, species, and altitude because the temperature required for each organism to grow and develop varies and accumulates differently according to region. This is the earliest degree-day summation concept, and for hundreds of years, this concept has been a fundamental basis for constructing bioclimatic models, such as the spring index model (Schwartz 1997; Schwartz and Marotz 1986, 1988), thermal time model (Cannell and Smith 1983; Robertson 1968), and spring warming model (Hunter and Lechowicz 1992).
|
review
| 99.6 |
After Reaumur, three types of bioclimatic models were developed in response to different research needs, methods, and objectives. Scientists refer to the three model types as theoretical, statistical, and mechanistic models. The theoretical model is also called the analytical model because it emphasizes the equilibrium between the productivity and the energy and nutrition absorption of leaves. Thus, because the model focuses on growth and development, it is suitable for research regarding the evolution of the survival strategies of species. The statistical model encompasses a wide and complex research scope. The primary objective of this model is to conduct statistical modeling, such as polynomial regression and general linear models, based on bioclimatic observation to directly connect climatic factors and biological events. Therefore, this model is also referred to as the empirical model. The mechanistic model focuses on the causal relationship between bioclimatic events and environmental factors to explain the effects of environmental factors on plant physiology. Because rigorous physiological and ecological theories and experimental bases support this model, its results are accepted relatively easily by a majority of scholars. The mechanistic model has been the standard of bioclimatic model research for a long period (Zhao et al. 2013). Except for the few bioclimatic models that use simple calculations, difficulties have typically been encountered during the early development of other bioclimatic models. These models were not developed and widely used until computer software and hardware became more easily accessible and a concomitant increase in the availability of data to parameterize such models (e.g., freely available gridded climate products) resulted in a stronger emphasis on global climate changes.
|
review
| 99.9 |
Each bioclimatic model has specific application restrictions and advantages and disadvantages. Scientists use the thermal time model most often because this model considers only the accumulated temperature, threshold temperature, and mean daily temperature of bioclimatic events as the parameters, facilitating model application. The model is shown as follows:1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$S_{f} = \sum\limits_{{t_{0} }}^{y} {R_{f} (X_{t} ) = F^{*} }$$\end{document}Sf=∑t0yRf(Xt)=F∗ where Sf represents the accumulated units required to promote growth that satisfies bioclimatic event occurrence; \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$y$$\end{document}y represents the date of the bioclimatic event occurrence; \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$t_{0}$$\end{document}t0 represents the initial time for calculating the accumulated temperature; \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$X_{t}$$\end{document}Xt represents the mean daily temperature; and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{f} (X_{t} )$$\end{document}Rf(Xt) represents the calculation function of effective accumulated temperature. This function is calculated using the following equation:2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{f} (X_{t} ) = \left\{ {\begin{array}{*{20}l} {\begin{array}{*{20}l} 0 & \quad{\rm if} & {x_{t} \le T_{b1} } \\ \end{array} } \\ {\begin{array}{*{20}l} {x_{t} - T_{b1} } & \quad{\rm if} & x \\ \end{array} > T_{b1} } \\ \end{array} } \right.$$\end{document}Rf(Xt)=0ifxt≤Tb1xt-Tb1ifx>Tb1 where \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{b1}$$\end{document}Tb1 represents the initial temperature for calculating the accumulated temperature. In this model, when the temperature is below the threshold growth temperature of a plant, the temperature does not influence phenological events. Only when the temperature exceeds the threshold growth temperature of a plant does the accumulated temperature affect phenological events. The higher the temperature, the greater the degree of influence is. However, this model is only applicable to the optimal temperature of plant growth. When the plant encounters extreme temperatures that exceed the optimal temperature of growth during the calculation of plant-accumulated temperature, the prediction errors of the model increase. Thus, several scientists have established the following formula to calculate the effective accumulated temperature based on the curves of plant growth development in response to temperatures.3\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{f} (x_{t} ) = \left\{ \begin{array}{ll} 0 & \quad {\rm if} \,\,\, {x_{t} < 0} \\ {\frac{a}{{1 + e^{{b(x_{t} - c)}} }}} & \quad {\rm if}\,\,\,{x_{t} \ge 0} \end{array}\right.$$\end{document}Rf(xt)=0ifxt<0a1+eb(xt-c)ifxt≥0 where c represents the optimal temperature for plant growth, b represents the parameter of plant sensitivity to variations in effective accumulated temperature, and a represents the upper limit of effective accumulated temperatures when bioclimatic events occur. This formula categorizes temperatures below 0 °C as noninfluential on bioclimatic events and involves only temperature accumulation above 0 °C.
|
study
| 89.8 |
The review of previous models shows that early thermal time models considered only the forcing units of growth, rather than the chilling requirements. In addition, during dormancy, plants are completely quiescent; thus, the phenological phase during dormancy is difficult to observe and define. However, a high number of physiological experiments in later stages have shown that low temperatures are necessary in winter for temperate plants to blossom and sprout. Bioclimatic models that neglect chilling requirements cannot effectively predict the flowering and sprouting of temperate plants. Therefore, scientists have developed numerous mechanistic models based on differing physiological plant types and have integrated chilling requirements into various models. Among these models, the most well-known are the sequential model (Hänninen 1987, 1990; Sanders 1975; Sarvas 1974), parallel model (Landsberg 1974; Sarvas 1974), alternating model (Cannell and Smith 1983; Kramer 1994; Murray et al. 1989), deepening rest model (Kobayashi et al. 1982), and four phase model (Hänninen 1990; Vegis 1964).
|
review
| 99.9 |
The differences between these bioclimatic models are as follows: The sequential model emphasizes that forcing temperature is effective only after chilling requirements are met, presenting a sequential order. Landsberg (1974) proposed the parallel model for identifying the dormancy characteristics of apple buds, indicating that regardless of temperatures, the phenological expression of plants is affected. The alternating model emphasizes that the forcing units and chilling units possess a negative indicative correlation. Thus, the two requirements alternatively influence phenological expression based on different weighting degrees with variations in the dormancy stages of plants. Kobayashi et al. (1982) proposed the deepening rest model in their study regarding the bud dormancy characteristics of Cornus sericea L. This model emphasizes that chilling requirements occur only during the deep rest stage, and that calculations of chilling requirements are not necessary for other dormancy stages. The four phase model emphasizes that plants have four sub-phenological phases during dormancy, which are the prerest, true-rest, postrest, and quiescence phases. The critical temperature-forced growth increases continuously during the prerest phase, but decreases during the postrest phase. In the true-rest phase, plants do not respond to any forcing growth temperature. The critical plant growth temperature decreases to the lower limit of initial temperatures for plant development in the postrest phase. When the external temperature remains below the lower limit temperature, plants enter the quiescence phase, the length of which is determined by the physiological conditions of the plant and the temperature increase in the following spring.
|
study
| 99.94 |
Regarding the measurement of the chilling requirements of plants in thermal time models, two common calculation methods exist:4\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{c} (x_{t} ) = \left\{ {\begin{array}{ll} 1 & \quad {\rm if} \,\,\, {x_{t} < T_{b2} } \\ 0 & \quad {\rm if} \,\,\, {x_{t} \ge T_{b2}}\end{array}} \right.$$\end{document}Rc(xt)=1ifxt<Tb20ifxt≥Tb2 where \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{f}$$\end{document}Rf becomes \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{c}$$\end{document}Rc, indicating that the growth accumulated temperature is replaced by the accumulated low temperature of chilling requirements, and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{b2}$$\end{document}Tb2 represents the upper limit of the critical temperature of effective low temperatures. Temperatures higher than \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{b2}$$\end{document}Tb2 have no effect on the temperature accumulation of chilling requirements. Only temperatures lower than \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{b2}$$\end{document}Tb2 affect the temperature accumulation of plant chilling requirements. Binary coding is adopted to calculate the effective accumulated temperature. In other words, regardless of temperature values lower than the critical temperature, one effective chilling unit is counted. Even if the temperature is −50 °C, which freezes plants to death, an effective chilling unit is counted. This formula obviously contradicts empirical experience. Therefore, subsequent scientists have developed another formula for calculating the effective chilling unit:5\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{c} (x_{t} ) = \left\{ \begin{array}{ll} 0 & \quad {\rm if}\,\,\, x_{t} \le T_{m}\,\,\,{\rm or}\,\,\,x_{t} \ge T_{M}\\ {\frac{{x_{t} - T_{m} }}{{T_{0} - T_{m} }}} & \quad {\rm if}\,\,\, T_{0} > x_{t} > T_{m}\\ {\frac{{x_{t} - T_{M} }}{{T_{0} - T_{M} }}} & \quad {\rm if}\,\,\, T_{0} < x_{t} < T_{M} \end{array}\right.$$\end{document}Rc(xt)=0ifxt≤Tmorxt≥TMxt-TmT0-TmifT0>xt>Tmxt-TMT0-TMifT0<xt<TM where \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{m}$$\end{document}Tm and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{M}$$\end{document}TM represent the upper and lower limits of the effective low temperatures of plants, respectively. When the external temperature is lower or higher than the upper and lower limits, the accumulated temperatures for plant chilling requirements are not effective. The term \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{0}$$\end{document}T0 refers to the most effective chilling requirement temperature of plants. Clearly, this formula meets the actual situation more accurately than formula (4) does.
|
other
| 96.25 |
Different plant bioclimatic models combined with various plant physiological types must be calculated using different methods. For example, when thermal time models are used to predict plant flowering on the sequential model, the plant chilling requirements must be calculated and satisfied before the growth-accumulated temperature of plants is calculated. If parallel models are used, chilling accumulated temperature and forcing accumulated temperature must also be calculated to predict bioclimatic events. Hence, dozens of model combinations for predicting plant flowering or sprouting by using the thermal time model are available. The high degree of plant bioclimatic and physiological diversity contributes to the complex development of bioclimatic models. The complexity of bioclimatic model development, to a certain degree, effectively increases the accuracy of bioclimatic prediction; however, such complexity also impedes the promotion and application of the models. To simplify the application of bioclimatic models, Chuine (2000) combined numerous major mechanistic models and developed a set of unified bioclimatic model calculation methods, which comprises two formulas to calculate the forcing and chilling requirements of plants. Through the adjustment of various parameters in the model, Chuine fitted the plant differences resulting from physiological responses, phenological phases, regions, and latitudes. Subsequently, Chuine and Beaubien (2001) further argued that the distribution of woody plants is primarily determined by the degree of fitness of the plant bioclimatology to the local climates. Thus, they integrated other models, such as those of freeze injury and fruit ripening, to develop a bioclimatic model based on biological processes, which they referred to as the PHENOFIT model. The model uses bioclimatic observation data for parameter fitting of bioclimatic models and meteorological variable map layers provided by Environment Canada, Climate Archives, the National Climatic Data Center, and the World Radiation Center to determine species distribution according to the fitting degree of the species bioclimatology to the local climates. Because the PHENOFIT model combines multiple bioclimatic models, the calculation formula is complex. Nevertheless, the PHENOFIT model requires the input of only five variables to obtain 12 variables that explain the effects of climates on species. These resulting variables altogether can determine the distribution appropriateness of species. The PHENOFIT model uses climatic data from various geographic regions to infer the distribution of numerous temperate perennial woody plants. The results indicated that the outcomes inferred using the model highly corresponded to the actual distribution of the target species.
|
review
| 99.8 |
The temperature, light, water availability, and airflow changes caused by climate changes influence the transpiration rate of leaves, which is determined by numerous factors, such as the net radiation balance of leaves, water supply conditions, leaf shapes, environmental wind speed, and the reaction of the stomata to transpiration sensitivity (Gates 1968; Raschke 1960). The model is as follows:6\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$S_{t} (1 - \alpha_{l} ) + L_{d} - \varepsilon \sigma T_{a}^{4} = \frac{{\rho C_{p} (T_{l} - T_{a} )}}{{r_{a} }} + \frac{{\rho C_{p} }}{{\gamma^{*} }}\frac{{(e_{o} - e_{a} )}}{{r_{s} + r_{a} }}$$\end{document}St(1-αl)+Ld-εσTa4=ρCp(Tl-Ta)ra+ρCpγ∗(eo-ea)rs+ra where \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$S_{t}$$\end{document}St represents the incoming solar radiation ( Wm−2); \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha_{l}$$\end{document}αl is the albedo of the leaf; \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_{d}$$\end{document}Ld is the incoming longwave radiation (Wm−2); \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varepsilon \sigma T^{4}$$\end{document}εσT4 is the long-wave radiation emitted by the leaf at the leaf temperature (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{l}$$\end{document}Tl); \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho$$\end{document}ρ is the environmental air density around the leaf (kgm−3); \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$C_{p}$$\end{document}Cp is the specific heat of air (kPa); \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{a}$$\end{document}Ta is the air temperature (°C); \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$r_{a}$$\end{document}ra is the aerodynamic conductance to heat transfer (sm−1); \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma^{ * }$$\end{document}γ∗ is the psychrometric constant (kPa °C−1); \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$e_{0}$$\end{document}e0 is the saturated vapor pressure (kPa) at the current leaf temperature; \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$e_{a}$$\end{document}ea is the actual vapor pressure (kPa); and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$r_{s}$$\end{document}rs represents the stomatal conductance (sm−1). Formula (6) shows that a slight change in the temperature affects multiple factors simultaneously. When the air temperature increases, the long-wave radiation absorption of leaves is affected, increasing the thermal load of leaves and changing the saturated vapor pressure in the atmosphere. Consequently, the actual vapor pressure is insufficient and causes the water transpiration rate of the leaf to increase along with water consumption. Thus, the model can effectively evaluate the effects of temperature, light, water availability, and airflow changes on plants according to climate changes. Moreover, stomatal conductance differs with the sensitivity of plant species and strains to climate changes (Hofstra and Hesketh 1969).
|
study
| 99.8 |
Because of article length limitations, we introduced only three major types of plant bioclimatic models. In addition to the models introduced in this study, other bioclimatic models are of importance in separate fields of development. Basically, the diversity of relationships between organisms and climates leads to diversity among statistical (empirical) models, such as the thermal time, degree-days, heat sums, growing degree-days, physiological time, and spring warming models. The physiological and genetic diversity of organisms contributes to the diversity of mechanistic models, such as the parallel, sequential, deepening rest, four phases, Utah (Richardson et al. 1974), positive chill (Linsley-Noakes et al. 1995), and North Carolina models (Gilreath and Buchanan 1981). The diversity of biological and statistical theories contributes to the diversity of theoretical models, such as the models based on carbon equilibrium, the interaction of hormones, survival and reproductive adaptation, ecological niches, genetic behaviors, biological processes, and remote sensing. Naturally, some of the models involve a certain degree of correlation, which occasionally enables their mutual and complementary combination.
|
review
| 98.56 |
By reviewing the development of early bioclimatic models, we identified the following tendencies: (a) The number of studies regarding the bioclimatic models for perennial species substantially exceeds that of those for annual plants. (b) The number of bioclimatic model studies on temperate plants is considerably higher than that of those on tropical and subtropical plants. (c) The number of bioclimatic model studies on woody plants is substantially higher than that of those on herbal plants. (d) The number of observational bioclimatic model studies is substantially higher than that of experimental studies. (e) The number of bioclimatic model studies on plants that sprout and blossom in spring is considerably higher than that of those on plants with different growth and development stages. (f) The number of bioclimatic model studies on crops greatly exceeds that of those on forest plants. The majority of the bioclimatic model research conducted after 1753 has focused on the flowering and sprouting models of temperate plants. Regarding other bioclimatic models, only a few model studies on fruit ripening bioclimatology were found (Piper et al. 1996; Song and Ou 1997). Moreover, research on the bioclimatic model of leaf colouring periods is scant (Chuine and Beaubien 2001).
|
review
| 99.9 |
Plant bioclimatic models have been applied and developed in different fields, such as for predicting and evaluating the influence of climate changes on plant bioclimatology (Hänninen and Tanino 2011; Hänninen et al. 2007; Hao et al. 2001; Morin et al. 2009), improving the primary productivity of ecosystem (Kramer and Mohren 1996; Watsona et al. 2013), helping patients with pollinosis predict the time when pollen will occur in the air (Frenguelli and Bricchi 1998), assisting in crop or forest management and disaster-risk decision assessment, diagnosing the effects of climate on crop growth and development, predicting or assessing the correlations between species and their survival or adaptive strategy evolution (Chuine and Beaubien 2001; Morin et al. 2008), rebuilding regional climate environments in the past (Maurer et al. 2011; Menzel 2005; Yiou et al. 2012), forecasting the flowering time of cherry blossoms for developing the tourisy industry (Allen et al. 2014), and diagnosing the growth and development conditions of organisms as well as diseases and pests (Villalta et al. 2007). Unsurprisingly, these applications are correlated with one other to a certain degree. In recent years, plant bioclimatic models have been continuously applied to climate change research to evaluate the effects of climate changes on organisms. This implies that the importance of applying plant models in climate change-related research has constantly increased (Peñuelas and Filella 2001). Thus, this study introduced the application of bioclimatic models in assessing the influence of climate changes and in disaster prevention.
|
study
| 99.2 |
Initially, scientists focused on how plant sprouting and leaf expansion in the spring are correlated with freeze and cold injuries in the spring. Thus, statistical and mechanistic models regarding plant sprouting were the first models used to evaluate the effects of climate changes on plants. These models are often used to evaluate plants’ ability to resist freezing or frost injuries (Cannell 1985; Cannell and Smith 1986; Hänninen 1991) or the competition for light that occurs among different species after climate changes (Cesaraccio et al. 2004). As bioclimatic model research progresses, theoretical models such as the DORMPHOT model, which is based on theoretical processes, are frequently used to assess the effects and risks of extremely low temperatures and freezing and cold injuries on forests. Theoretical models are also used to assess the risks of native species being affected by climate changes (Kramer 1995; Kramer et al. 1996; O’Neill et al. 2010). Based on an empirical experiment, the DORMPHOT model was more accurate than traditional models in assessing tree sprouting (Caffarra et al. 2011; Zottele et al. 2011).
|
review
| 99.7 |
Regarding the assessment of the effects of climate changes on plant bioclimatology, productivity, vegetation structures, vegetation dynamics, and forest landscapes, forest gap models that contain climate variables are often used to explain the effects of climate changes on forest succession, growth, landscapes, and the structural variations of plant communities (Bugmann 2001; Keane et al. 2001; Prentice et al. 1993). Additionally, because of the differing sensitivities of the models, the response degree of forest primary productivity models varies with the model adopted (Leinonen and Kramer 2002; Vitasse et al. 2011). Common instances are the effects of energy and carbon dioxide flows on leaf expansion and falling leaf bioclimatology, and the model for assessing the relationship between leaf area index and seasonal evolution (Chase et al. 1996). In addition, empirical (statistical) degree-day growing models are frequently used in investigating the bioclimatic changes and carbon sequestration cycles in land surface models (Arora and Boer 2005; Baldocchi et al. 2005; Delpierre et al. 2009; Vitasse et al. 2011). Similarly, regarding the effects of climate changes on the carbon sequestration ability of vegetation, the large-scale biological sphere model based on forest ecological system processes, BIOME-BGC, includes information on leaf growth and falling dates as parameters and applies the information to three types of vegetation research (Running and Hunt 1993).
|
review
| 99.8 |
The prediction results of bioclimatic modeling or the models themselves can be integrated with other models with various purposes to conduct research on the effects of climate changes (Halofsky et al. 2013). For example, Bonan (1998) used the monthly leaf area indices predicted using the land surface model of the National Center for Atmospheric Research as model parameters and applied the parameters to the grids of the Community Climate Model to facilitate global climate change research. Kaduk and Heimann (1996) determined the precautionary and mechanical structures that identify bioclimatology phases in environmental conditions and applied the structure to land carbon cyclic model research. Botta et al. (2000) used remote sensing data to estimate leaf sprouting time and developed empirical prediction formulas to predict leaf bioclimatology dynamics and propose a global bioclimatology precautionary structure. In addition, other professional bioclimatic models of climate change for large-scale structures based on biospheres or ecological systems exist, such as the Frankfurt biosphere model established based on the carbon equilibrium structure; the Lund-Potsdam-Jena dynamic global vegetation model, which assesses ecological system dynamics, plant geography, and land field carbon cycles (Sitch et al. 2003); the Canadian Centre for Climate Modeling and Analysis integrated biosphere simulator model, which predicts leaf bioclimatology based on light and temperature functions (Foley et al. 1996); and the forest carbon model based on photosynthesis and transpiration (Chiang and Brown 2007). These models have been widely applied in large-scale climate change research in recent years.
|
review
| 99.9 |
Recently, ecologists have focused on the effects of climate changes on species distribution, the resulting habitat fragmentation, and relevant species conservation arguments (Channell and Lomolino 2000; Crimmins et al. 2013; Fan et al. 2013; Gavin et al. 2014; Pauli et al. 2014; Pimm et al. 2014; Renton et al. 2013). Thus, numerous species distribution models developed on the based of the climate ecological niche theory of bioclimatic models have been applied in research on the effects of climate changes on species distribution and habitats. A major portion of these models are also referred to as climate envelope models (CEMs) (Hijmans and Graham 2006), such as the maximum entropy models (Phillips et al. 2004), machine-learning-based artificial neural network models, and integrated species distribution models (e.g., BIOMOD) (Coetzee et al. 2009; Thuiller 2003). However, not all species distribution models are categorized as CEMs. For example, although the PHENOFIT model was developed on the basis of biological processes and many physiologically based SDMs (Kearney and Porter 2009) are used to evaluate the effects of climate changes on species distribution, they are not CEMs.
|
review
| 99.9 |
The mapped atmosphere-plant-soil system model (Lenihan et al. 2003, 2008) can be used to assess the effects of climate changes on vegetation distribution, ecological system productivity, or forest fires. Remote-sensing time sequential data can be used to measure and assess land field surface phenology for assessing the vegetation responses after fires (van Leeuwen et al. 2010). In addition, regarding large-scale biological effect research, the BIOME-BGC, CLASS, Interannual Flux Tower Upscaling Sensitivity Experiment, third generation Coupled Global Climate Model, I/O buffer information specification, Lund-Potsdam-Jena, National Center for Atmospheric Research Land Surface Model, and remote-sensing-based NDVI/NDWI models can be used for assessing the effects of climate changes on large areas of vegetation (Bonan 1998; Desai 2010; Foley et al. 1996; Sitch et al. 2003). These models are convenient for use in large plain areas; thus, they have been widely adopted by studies in numerous temperate continental countries in recent years.
|
review
| 99.25 |
The types, application methods, and purposes of bioclimatic models are numerous, and the predictive accuracy of the models is determined by (a) the quality and quantity of data, (b) whether the user selects and uses the most appropriate model, and (c) the accuracy in forecasting climate changes. Because scientists mostly focus on (a) and (b), this paper does not discuss item (c), which requires the expertise of meteorologists. In particular, the situation described in (a) is inevitable when any model is used. However, because various models require different levels of data sensitivity, the requirements for data quality and quantity also differ. The requirements for data quality and accuracy are strict and are often based on bioclimatic models driven by data, such as the maximum entropy model, CEMs, and machine-learning models used for species distribution modeling. Thus, the preparation and compilation works of data are critical in these types of model. Two conditions are used to determine whether a user has selected and used the appropriate model. The first condition is the user’s understanding of the target organisms’ physiology, ecology, behavior, or biology. For example, if the constrain conditions of the distribution of a species is not a climatic factor, using CEMs and current species distribution data to assess the effects of climate changes on species distribution may lead to considerable errors. Therefore, to use bioclimatic models to assess the effects of climate changes on organisms, is necessary to identify the period in the target organisms’ life cycle that is most sensitive to climate changes. Subsequently, based on the period, a suitable model should be selected for conducing assessment to maximize the effectiveness of the model. Choosing an inappropriate model to conduct assessment typically results in errors (Coetzee et al. 2009).
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review
| 99.7 |
All applications of bioclimatic models in assessing the effects of climate changes have advantages and disadvantages (Elith et al. 2006; Hijmans and Graham 2006). For example, statistical models are the most widely used and are user-friendly and users are not required to consider biological processes, genetics, and physiology; however, they lack explanatory power for the research results and have a limited scopes of applications. Statistical models generally can not be applied to research on the effects on large areas of vegetation variations. Mechanistic models yield the highest explanatory power for the effects of climate changes, and thus have optimal assessment effectiveness. However, uncertainty of species’ physiological mechanisms is a constraining factor of using such models. For instance, users may be uncertain regarding what model to use to assess the effects of climate changes on the dormancy of Sassafras randaiense Hay. Rehder because the bud dormancy and physiology of the plant species have not yet been thoroughly investigated. Regarding the research on bioclimatic models for exploring the effects of climate changes, the successful application of models is determined by the user’s understanding of each model. Only by selecting suitable models can reliable assessment on the effects of climate changes be conducted and accurate results be attained.
|
review
| 99.9 |
In our previous review of climate change research on plants (Hsieh and Chiou 2013), we found that phenological gardens and phenological observation networks are used to record the effects of past climate changes on organisms in climate change research and monitor the direct influence of climate changes on organisms. Bioclimatic models are used to assess the possible effects of future climate changes and assist in making disaster-prevention decisions. Bioclimatic models and phenological observation networks are complementary in assessing the effects of climate changes; neither can be neglected. Without the historical records of phenological observation networks, bioclimatic models lack modeling data; without bioclimatic models, phenological observation networks lack the function of risk assessment and cannot assist in disaster-prevention decision-making. Thus, phenological fingerprints and models have been developed rapidly for applications in international climate change research. The use of regional phenological fingerprints, which was once a tool for small- to medium-scale spaces, has been expanded to continental and global scales through the establishment of global bioclimatic monitoring plans (Bruns et al. 2003; Parmesan and Yohe 2003; Root et al. 2003). Regarding the application of models, although the global bioclimatic models developed on the basis of remote sensing data have been widely applied in studies in temperate continental countries in Europe and North America, small- to medium-scale phenological fingerprints and models are more suitable for Taiwan because of its small terrain.
|
review
| 99.9 |
The effects of global climate changes have increased in recent years. Numerous cities in Europe, the United States, China, and Japan were measured to have had high temperatures exceeding 40 °C for several consecutive days throughout the summer of 2013. Torrential rain has caused disasters in numerous regions and weather stations all over the planet measured atmospheric carbon dioxide concentrations exceeding 400 ppm, the highest in millions of years. Moreover, climate changes have exerted increasingly severe effects on plants and wildlife (Anderegg et al. 2012; Harley 2011; Ibáñez et al. 2008; Inouye 2008; Kaschner et al. 2011; Moritz et al. 2008; Rode et al. 2010; van Mantgem et al. 2009). These disasters indicate that the threats of climate change are ubiquitous. Because of the global impacts of disasters, we suggest that all countries’ government and relevant research units immediately establish international phenology gardens and network systems, develop phenological fingerprint observation technologies, improve the ability to monitor the effects of climate changes on global organisms, and employ long-term bioclimatic observation records to develop bioclimatic models that are suitable for local climates and disaster prevention. Consequently, the capacity for assessing the effects of climate changes and predicting and preventing disasters can be prepared, and measures and strategies can be prepared in response to disasters caused by climate changes.
|
review
| 99.44 |
Identification and authentication of pharmaceuticals can be confidently achieved by mass spectrometry, which provides plentiful molecular information to probe the chemical nativity of all types of samples. Owing to the complexity of the tablet composition, targeted analytes must be separated from matrices before detection by mass spectrometry. The separation methods include HPLC , GC , CE , lab-on-chip system [4, 5], etc. These methods need laborious and time-consuming sample preparation. In 2004, Cooks et al. demonstrated that analyte ions can be produced using desorption electrospray ionization (DESI) in an open-air environment without separating the matrix of real-world samples. From then on, more than 30 ionization methods have been reported for direct creation of analyte ions in ambient conditions such as direct analysis in real time (DART) , low temperature plasma (LTP) , extractive electrospray ionization (EESI) , and desorption atmospheric pressure chemical ionization (DAPCI) . By using DESI and other ambient ionization techniques, throughput of mass spectrometry analysis was dramatically improved because no/minimal sample pretreatment was required [11–14].
|
review
| 99.8 |
To date, ambient ionization methods usually provide protonated/deprotonated analyte molecules for mass detection with a positive/negative ion detection mode, which simplifies the datum interpretation and improves the readability of the mass spectrum. Since the matrix is not removed in ambient mass spectrometry, multiple stage mass spectrometry experiments are normally required to obtain characteristic fragments of each analyte to exclude any potential false positive signals. Consequently, either a mass spectrometry instrument with extremely high resolution for exact mass measurement [15, 16] or tandem mass spectrometry capability (MSn, n ≥ 2) is required to obtain confident results. At present, advanced instruments required to achieve either high mass resolution or multiple stage mass spectrometry experiments impose high cost, large size, and heavy weight on the mass spectrometers.
|
review
| 98.06 |
Apparently, these instruments are not suitable for in situ analysis, which limits the application of ambient mass spectrometry in many important fields such as chemical industry, process monitoring, drug discovery, and pharmaceutical screening. On the other hand, simple mass spectrometers have been constructed for onsite analysis [18–20]. More recently, miniature mass spectrometers installed with ambient ionization sources such as DESI [21, 22] and LTP have been reported, showing increasing interest to develop inexpensive mass spectrometers with high analytical throughput for in situ applications.
|
review
| 99.7 |
Microwave plasma torch (MPT) has been used as the excitation source for atomic emission spectrophotometry (AES) for decades. Traditionally, the capability of MPT to produce ions has not been considered in AES. In fact, MPT combines many merits such as relatively high temperature, high electron density, and high positive charge density . These make MPT a suitable ionization source for desorption ionization of solid samples. Recently, protonated analytes in liquid samples were also produced by MPT . Theoretically, the high temperature of MPT allows the observation of ambient thermal dissociation of the analyte ions produced by MPT sources. In such a case, the total amount of the energy transferred to the analyte ion can be manipulated by changing the experimental conditions and, thus, the extent of fragmentation can be tuned without applying collision-induced dissociation (CID) experiments. Obviously, it is highly desirable to couple MPT with a simple mass spectrometer for rapid qualitative analysis of real-world samples. In this work, a novel, facile strategy is proposed to tune the mass spectral pattern by combining desorption and ionization process in a miniaturized MPT source. Because fast screening counterfeit drugs is of sustainable interest, MPTDI-MS was applied to rapid detection of ions of the active ingredients in drug preparations. The results showed installation of MPTDI-MS is cost-effective in potential screening of counterfeit drugs.
|
study
| 99.94 |
Ten kinds of tablets, including ribavirin (100 mg ribavirin/piece), azithromycin dispersible (250 mg azithromycin/piece), oxytetracycline (250 mg oxytetracycline/piece), metronidazole (200 mg metronidazole/piece), isoniazid (100 mg isoniazid/piece), compound paracetamol (126 mg paracetamol/piece), salbutamol sulfate (2 mg salbutamol/piece), acyclovir (100 mg acyclovir/piece), theophylline sustained-release (100 mg theophylline/piece), and amantadine hydrochloride (100 mg amantadine hydrochloride/piece) were purchased from local pharmacies. High-purity argon (99.999%) was obtained from Juyang Gas Co., Ltd. (Changchun, China). Ultrapure water (resistivity 18.2 MΩ cm−1) was produced by a Milli-Q device (Thermo Scientific, San Jose, CA, USA).
|
other
| 99.9 |
Analysis was conducted with a time-of-flight mass spectrometer (TOF-MS 5000; Hexin Mass Spectrometry, Guangzhou, China) equipped with a MPT source with standard voltage, pressure, distance, and angling capability (Changchun Jilin University Little Swan Instrument, Jilin, China). The MPT ion source mainly consists of microwave plasma torch tube and microwave power source. Argon was used as plasma gas. The MPTDI-MS system is shown in Figure 1. LTQ-XL mass spectrometer (Thermo Scientific) was used for validation purpose in this study.Figure 1Schematic of MPT ion source coupled with a TOF MS. * Distance from MS inlet to plasma torch is fixed at 17 mm. The height of tablet surface to plasma torch is desorption distance h
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study
| 100.0 |
The instrument parameters were optimized. The configurations and operation of the MPT ion source were stated in detail in our previous work . Microwave power was set to 50 watt, and the reflected power was reduced to almost 0 watt by adjusting the tuning piston of the microwave plasma torch tube. Stable argon plasma could be obtained when the flow rate of working gas (Ar) was 0.4 L/min and flow rate of carrier gas (Ar) was 1.2 L/min. In order to reduce the measurement error caused by the uneven distribution of active ingredient in tablets, the contact area of about 0.5 cm2 between plasma torch and the sample was controlled by adjusting the angle and distance of desorption (h).
|
study
| 100.0 |
The TOF-MS 5000 is a simple mass spectrometer with a relatively narrow mass range (m/z 50–800), a reduced size (70 cm length × 65 cm width × 75 cm height), and lighter weight (85 kg), and thus no tandem mass spectrometry experiment could be implemented in this compact TOF-MS instrument. Detailed description of the TOF-MS instrument was documented elsewhere . The voltages were set as follows for this work: capillary voltage 140 V, focusing mirror voltage 135 V; positive pulse voltage 950 V, negative pulse voltage –950V, acceleration zone voltage −4100 V, grid voltage −90 V, reflex zone voltage 1340 V. No other optimization was made to the TOF-MS instrument. Thermo Finnigan LTQ-XL mass spectrometer is a widely available bench-top type commercial instrument, with advanced functions including multi-stage tandem mass spectrometry. The LTQ-XL instrument worked under the following conditions: the mass range was m/z 50–1000 with a positive ion detection mode, the temperature of the heated capillary was 150 °C, the lens voltage was 60 V. Other LTQ-XL parameters were automatically optimized by the system.
|
study
| 99.94 |
Pharmaceutical samples were placed on the sample holder without any pretreatment. The active ingredients of the tablets can be desorbed and ionized by microwave plasma. Then full-scan mass spectra of the samples were obtained using both MPT-TOF-MS instrument and LTQ-XL-MS instrument. For CID experiments, the precursor ions were isolated with a mass-to-charge window width of 1.6 Da, and then subjected to CID with collision energy of 15%–35%. Mass spectra were recorded with an average time of 30 s, and all backgrounds were subtracted.
|
study
| 99.94 |
The distance from the apex of the torch to the tablet (h) and the time that the plasma worked on the sample (desorption time) were two of the most important parameters in the process of the MPTDI-MS experiment. The distance from the apex of the plasma to the ion entrance of the mass spectrometer was fixed at 17 mm (Figure 1). The influences of h and desorption time on signal intensities of analytes were studied. The representative plots obtained from metronidazole, acyclovir, and azithromycin are shown in Figure 2. The intensities of analyte ions achieved crest value when the distance was 4–5 mm. This trend could be explained from the perspective of energy and charge transfer. Because energy distribution of microwave plasma was variable in space, desorption and ionization capacities of the MPT were different in space. The abundance of fragment ions and ionization capacities increased when shortening desorption distance. However when the distance was too short (2–3 mm), the abundance of fragment ions decreased because the ionization capacity was too high and the fragment ions could be further cloven. Therefore, the MPT desorption distance of 5 mm was selected as the optimized parameter.Figure 2Effect of desorption distance (h) on abundance of major fragment ion of metronidazole (m/z 172→m/z 128), acyclovir (m/z 226→m/z 152), and azithromycin (m/z 750→m/z 592)
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study
| 100.0 |
In order to increase the ionization efficiency of MPTDI source, the relationship between desorption time and abundance of major fragment ions was studied; the curves of desorption time versus abundance for three typical pharmaceuticals are shown in Figure 3. This method could obtain the response signals of protonated molecular ions and fragment ions in less than 5 s. The results showed that efficiency of desorption and ionization increased with increasing desorption time, and significant changes of the signal intensities were observed in the range of 20–30 s desorption time, as depicted in Figure 3. Desorption times longer than 30 s did not lead to substantial increases in observed signals. With prolonged desorption time, not too much signal increase was observed. So the desorption time of 30 s was chosen as the optimal condition.Figure 3Desorption time (t) resulting the signal intensity variation of major fragment ion of metronidazole (m/z 128), acyclovir (m/z 152), and azithromycin (m/z 592)
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study
| 100.0 |
Microwave power is a key factor for ion fragmentation. The effect of microwave power on the signal intensities of main ions of analyte was investigated by using MPTDI-TOF MS. By raising the microwave power in increments of 10 watt from 30 to 150 watt, the protonated molecular ions with little fragmentation ions were mainly observed at low microwave power (≤40 W), as shown in the representative graph of theophylline (Figure 4a). The greatest signal intensities of the protonated species were observed when the microwave power reached to 50–70 watt for all 10 tablets. The highest signal intensity of protonated theophylline (m/z 181) with low signal intensity fragmentation ions (m/z 124, 96) were observed when the microwave power was at 70 watt (Figure 4a). In Figure 4b, the highest intensity of protonated metronidazole molecular ion at m/z 172 with its major fragment ions at m/z 128 and m/z 98 were observed at 60 watt. Higher microwave power (>60 watt) would induce MEISD and lead to high abundance of fragmentation ions, which corresponded to the MSn (n =2, 3) fragmentation ions detected by MPTDI-LTQ MS in selective ion mode, indicating a valid MEISD. The fragmentation pathways that occurred in ion source of MPTDI-TOF MS were verified by tandem and multi-stage MPT-LTQ mass spectra of analytes (Supplementary Figure S-1c, j). The MS2 ion at m/z 124 was formed from the fragmentation of parent ion at m/z 181; the MS3 ion at m/z 96 was produced from the MS2 ion at m/z 124 by MPTDI-LTQ MS in selected ion mode. The MS2 ion at m/z 128 was produced from the fragmentation of parent ion at m/z 172; the MS3 ion at m/z 98 was formed from the MS2 ion at m/z 128.Figure 4Influence of the microwave power of MPT ion source on signal intensities obtained for theophylline (a) and metronidazole, (b) in positive mode. *b1 is the signal intensity versus microwave curves for ions of metronidazole at m/z 172, 128, 98; b2 is the enlarged figure for ions at m/z 99 and 128. Instrument: MPT-TOF mass spectrometer
|
study
| 100.0 |
Influence of the microwave power of MPT ion source on signal intensities obtained for theophylline (a) and metronidazole, (b) in positive mode. *b1 is the signal intensity versus microwave curves for ions of metronidazole at m/z 172, 128, 98; b2 is the enlarged figure for ions at m/z 99 and 128. Instrument: MPT-TOF mass spectrometer
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other
| 65.5 |
In summary, high signal intensities of fragment ions, which are not typically observed in full scan MS with soft ambient ionization methods, were detected in our investigation. A key observation is that MPTDI-TOF MS is able to produce higher abundances of MSn fragmentation ions when microwave power is set to >60 watt. The information of protonated molecular ions, molecular ions, and fragment ions could be obtained in the full-scan mass spectra of MPTDI-TOF under the conditions of 30 s of desorption time, 5 mm of desorption distance, and 70 watt of microwave power.
|
study
| 100.0 |
In this work, 10 kinds of commonly used pharmaceutical drugs were detected by MPTDI-TOF MS without any sample pretreatment. The CID data of drugs obtained by other researchers [28–42] are listed in Table 1.Table 1Related Information of Active Ingredients in Tablets
|
study
| 99.94 |
Azithromycin (MW 748.98) is a semi-synthetic and 15-membered ring macrolide antibiotic, and mainly used for treatment of respiratory tract infections caused by susceptible bacteria. The full-scan mass spectrum and fragmentation mechanism of azithromycin acquired by MPTDI-TOF MS are shown in Figure 5a and Supplementary Figure S-2a, respectively.Figure 5MPTDI-TOF full-scan mass spectra of (a) azithromycin; (b) oxytetracycline; (c) metronidazole; (d) isoniazid; (e) ribavirin; (f) acyclovir in positive mode
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study
| 100.0 |
Main fragment ions of azithromycin at m/z 592,574,434,and 416 can be found in Figure 5a. In an effort to identify the analyte precisely, tandem mass spectrometric analysis was performed. The full-scan mass spectra data obtained by MPTDI-TOF MS were consistent with the MSn data obtained by MPT-LTQ MS (Supplementary Figure S-1a).
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study
| 100.0 |
Oxytetracycline (MW 460.43) belongs to an antibiotic tetracycline with broad-spectrum antimicrobial effect, and is one of the most commonly used pharmaceutical drugs. The main fragment ions of oxytetracycline, corresponding to peaks at m/z 443 and 426, can be found in the full-scan mass spectrum of MPTDI-TOF MS (Figure 5b), and similar result with MSn data can be obtained by MPT-LTQ MS (Supplementary Figure S-1b). The protonated oxytetracycline contains multiple alcoholic hydroxyl groups and forms the ion at m/z 443 easily by losing a water molecule, and then losing an ammonia molecule to generate the ion at m/z 426. The possible fragment pathway of oxytetracycline at the MPT ionization source is shown in Supplementary Figure S-2b. It can be proven that microwave plasma thermal desorption and ionization at atmospheric pressure technology is expected to simplify qualitative analysis.
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study
| 100.0 |
Metronidazole (MW 171.15) has a broad-spectrum antibacterial and antiprotozoal effect, and is mainly used for the prevention and treatment of infections caused by anaerobic bacteria. The mass spectra data obtained by MPTDI-TOF MS is shown in Figure 5c. It can be seen that there are two peaks at m/z 172 and 128. After the analysis of MSn data obtained by MPT-LTQ MS (Supplementary Figure S-1c), it can be confirmed that the peaks at m/z 128 and 82 are the fragment ions of protonated metronidazole, and m/z 172 is the protonated molecular ion. The fragment ion at m/z 128 is likely formed by losing one molecule of vinyl alcohol from protonated metronidazole (Supplementary Figure S-2c). However, ion at m/z 82 is not found in the full-scan mass spectrum of MPTDI-TOF MS (Figure 5c), possibly because the bond cleavage to lose NO2 requires more energy.
|
study
| 100.0 |
Isoniazid (MW 137.14) is one of the widely used anti-tuberculosis drugs. Figure 5d shows the full-scan mass spectra of isoniazid obtained from MPTDI-TOF MS, protonated molecular ion at m/z 138, and main fragment ions at m/z 121, 93 can be found in the mass spectrum. This result is consistent with the MSn result obtained by LTQ MS (Supplementary Figure S-1d). The possible fragment pathway was that protonated isoniazid occurred α-cleavage. The ion at m/z 121 corresponds to a loss of ammonia, ion at m/z 93 corresponds to a continuing loss of a carbon monoxide molecule. It can be proven that MEISD has both soft and hard ionization characteristics based on the analysis of the data obtained by MPTDI-TOF MS and MPT-LTQ MS.
|
study
| 100.0 |
Ribavirin (MW 244.20) is a potent broad-spectrum antiviral drugs and now widely used for the prevention and treatment of viral diseases. It can be seen that there are peaks at m/z 245 and 113 in the Figure 5e. It can be confirmed that these ions corresponded to protonated molecular ion and major fragment ion, respectively, based on the results in previous literature . The fragment ion at m/z 113 for ribavirin analysis is due to the elimination of a stable 5-membered ring hydrofuran moiety. It was demonstrated that the MPT thermal desorption and ionization technology could achieve rapid and accurate qualitative analysis using only full-scan mass spectra data.
|
study
| 100.0 |
Similar with ribavirin, acyclovir (MW 225.21) is a kind of anti-viral drug, which is mainly used for herpes virus infection onset and recurrence. Both the protonated molecular ion m/z 226 and fragment ion m/z 152 of acyclovir can be observed in the full-scan mass spectrum obtained by the present simple TOF mass spectrometer, as shown in Figure 5f. Meanwhile, information of the fragment ion can be proven by the data from literatures [35, 36] and MSn spectrum by MPT-LTQ MS (Supplementary Figure S-1f). The fragment pathway (Supplementary Figure S-2f) can be speculated that protonated acyclovir loses a methanal to form the ion at m/z 196. The ion at m/z 196 goes on to lose of oxirane (ethylene oxide) to produce the ion at m/z 152. According to the above results, the main fragment ion of acyclovir can be obtained without tandem mass spectrometry, and accurate qualitative analysis of acyclovir can be completed using only the data of full-scan mass spectrum by MPT ionization source coupled with a simple mass spectrometer.
|
study
| 100.0 |
Acetaminophen (MW 151.16), also named paracetamol, is a commonly used noninflammatory and antipyretic analgesic, and is the main component of many common cold medicines. The protonated molecular ion m/z 152 and fragment ions at m/z 110, and 93 of acetaminophen can be found in the full-scan mass spectrum of MPTDI-TOF MS (Supplementary Figure S-3g), which is consistent with the result obtained by MPT-LTQ MS. However, the peak at m/z 121 is observed due to hydrolysis reaction that occurred and acetic acid molecules that is produced. Then, acetic acid dimer molecules formed in MPT ion source, and strong peak at m/z 121 is observed. The ion at m/z 110 might be produced by losing the group of CH2CO from the protonated acetaminophen (Supplementary Figure S-2g). The protonated acetaminophen lost an acetamide molecule CH3CONH2 to form the fragment ion at m/z 93. Comparing the mass spectral data of Supplementary Figure S-3g with Supplementary Figure S-1g, it can be acknowledged that MPT ionization source coupled with a simple mass spectrometer can achieve the same effects as with a tandem mass spectrometer in the aspect of qualitative analysis.
|
study
| 100.0 |
Amantadine (MW 151.25) hydrochloride and acetaminophen are often added to cold medicine as main components. The protonated amantadine molecular ion and the fragment ions at m/z 152 and 135 can be observed in the full-scan mass spectrum (Supplementary Figure S-3h). The fragment ion at m/z 135 is consistent with that obtained by MPT-LTQ MS (Supplementary Figure S-1h). At the beginning of desorption and ionization, amantadine hydrochloride loses hydrochloric acid under the effect of microwave plasma. The fragment pathway of amantadine is relatively simple (Supplementary Figure S-2h). The peak at m/z 135 corresponds to the ion that formed by the loss of an ammonia molecule from protonated amantadine.
|
study
| 100.0 |
Salbutamol (MW 239.31) is a selective β2-receptor agonist, main effect for the treatment of asthmatic bronchitis, bronchial asthma, and emphysema-induced bronchospasm. The protonated molecular ion at m/z 240 and fragment ions at m/z 222, 166, and 148 can be found in the full-scan mass spectrum (Supplementary Figure S-3i). The ionic fragments of m/z 222, 166, and 148 are generated by the loss of H2O, [H2O+C(CH3)2CH2], [2H2O+C(CH3)2CH2]. According to the data of collision-induced dissociation of protonated salbutamol (Supplementary Figure S-1i), MPT ionization technology can help to obtain abundant, accurate information of protonated molecular ion and fragment ions of analytes without a tandem mass spectrometer.
|
study
| 100.0 |
Theophylline (MW 180.16) has direct effect on relaxation of airway smooth muscle, and is the drugs for bronchial asthma, asthmatic bronchitis, and other respiratory diseases. In the full-scan mass spectrum of theophylline obtained by MPTDI-TOF MS, the protonated molecular ion at m/z 181 and fragment ions at m/z 124, and 96 can be found (Supplementary Figure S-3j). The result is consistent with the MSn data obtained by MPT-LTQ MS (Supplementary Figure S-1j) and reported in the literature. ISD fragmentation pathway of theophylline is proposed as depicted in Supplementary Figure S-2j. Six-membered ring of protonated theophylline can be opened under high energy, and thus loss of the CONCH3 group from protonated theophylline leads to the observation of the fragment ion at m/z 124, followed by the generation of the ion at m/z 96 by further loss of the CO molecule from the ion at m/z 124.
|
study
| 100.0 |
When analyzing active ingredients with the same molecular weight in solid pharmaceuticals such as acetaminophen and amantadine, DESI and DART ionization sources should be used in conjunction with tandem mass spectrometry for providing additional selectivity that helps to confirm the analytes. By changing the microwave power of MPT ionization source and selecting a proper desorption distance, ions information of tandem mass spectra of active ingredients were obtained in MPTDI-TOF MS without CID process, and the ingredients can be identified easily. In summary, a simple mass spectrometer coupled with MPT ionization source is a powerful tool for fast analysis of active ingredient in tablets.
|
study
| 99.8 |
Understanding how the ions work in MPTDI can be used to explore possible reactions in the gas phase and will be very helpful for researchers involved in the analysis or structural elucidation of compounds. During the Ar-MPTDI process, both protonated molecular ions and molecular ions of the analytes are observed (Figure 5). In Figure 5a, the base peak at m/z 750 corresponds to the protonated molecular ion of azithromycin. In addition, a relatively low-abundance molecular ion peak at m/z 749 is also detected. Similarly, both protonated molecular ions and molecular ions are observed in the full mass spectra of oxytetracycline (Figure 5b, m/z 461 and 460), isoniazid (Figure 5d, m/z 138 and 137), ribavirin (Figure 5e, m/z 245 and 244), acetaminophen (Supplementary Figure S-3g, m/z 152 and 151), salbutamol (Supplementary Figure S-3i, m/z 240 and 239), and theophylline (Supplementary Figure S-3j, m/z 181 and 180). It is speculated that these ions are generated by the reactions of Penning ionization (formation of molecular ions) and proton transfer (formation of protonated molecular ions). In the Ar-MPTDI process, Penning ionization ensues under an ultimate working condition of MPT, and molecular ions are generated by a cascade of gas-phase reactions. During the Penning ionization, the high densities of metastable argon (Arm) atom [ionization energy (IE), 11.55 eV for the 3P2 state and 11.72 eV for the 3P0 state] can ionize these investigated analyte molecules. The proposed reactions caused by metastable argon atoms are listed as reactions 1–3 in Scheme 1. They can take place since the energy of Arm is greater than the first or second ionization energy of analyte (M), Em(Ar) ≥ Eion(M). Reaction 1 is often followed by ion excitation (reaction 2). Reactions 2 and 3 involve direct excitation by metastable argon, and a more rigorous condition is required for the occurrence of reaction 2, Em(Ar) = Eexc(M). Excited species with high excitation energies in the microwave plasma reacting with analyte molecules can generate molecular ions (reactions 4 and 5). Free electrons with high kinetic energy colliding inelastically with gas atoms in plasma and analyte molecules in the sample is another reason for the generation of analyte molecular ions (reactions 6–8). These reactions are similar to those that happen in microwave-induced plasma (MIP) [45–48]. The protonated molecular ions are produced by proton transfer reaction, which is a dominant reaction in the MPTDI process. The proton affinity (PA) of water is 165 Kcal·mol−1, higher than that of hydroxyl radical (PAOH• = 142 Kcal·mol−1) , so the proton transfer reaction between water and water molecular ion can occur, as shown in reaction 9. The protonated molecular ions [M + H]+ generated by proton transfer were observed because the analyte molecular ion M has a higher proton affinity (PAs of nitrogenous compounds are 200–240 kcal·mol−1 ) than the ionized water clusters (reaction 10). Although the molecular ions are also observed, the signal intensities are not high (Figure 5a, b, d, and e). They even disappear in MPTDI mass spectra of metronidazole (Figure 5c), acyclovir (Figure 5f), and amantadine (Supplementary Figure S-3h). Owing to the high PA of nitrogen atom and the relatively high PA of carbonyl oxygen, the added proton is initially located at them, and these analytes prefer to form protonated molecular ions with relatively high signal intensities during ionization. Thus, molecular ions are observed with low signal intensities or they disappear. The MS data in Figure 5 and Supplementary Figure S-3 confirms the reaction mechanism in MPTDI process proposed in Scheme 1.Scheme 1Probable Reaction Occurring in Ar-MPT. Arm, the metastable states of argon; Em(Ar), the metastable energy of Ar; Eion(M), the ionization energy of M; Eexc(M), the excitation energy of M; PA, proton affinity
|
study
| 100.0 |
Moreover, expected cleavage reactions that take place in the gas phase between MPT plasma and tablets produce abundant MS fragment ions, which provide rich structural information and would become a powerful tool to figure out the structure exactly by using a simple mass spectrometer. To clarify this phenomenon, we took azithromycin as an example. The ions at m/z 592 ([M-C8H16O2N + H]+), m/z 574 ([M-C8H18O3N + H]+), and ions at m/z 434 ([M-C8H16O2N-C8H14O3 + H]+), m/z 416 ([M-C8H18O3N-C8H14O3 + H]+) in MPTDI-TOF full-scan mass spectrum of azithromycin (Figure 5a) correspond to the MS2 ions and MS3 ions (Supplementary Figure S-1a) in tandem mode obtained by LTQ mass spectrometer, respectively.
|
study
| 100.0 |
Many applications using MPT ambient sources have been presented [24–26]. However, mechanisms for MPTDI have not yet been reported. Our investigation improves the understanding of the fundamental desorption and ionization processes in MPT, which will be helpful in the rapid and reliable identification of analytes in solid samples with complex matrices using MPTDI mass spectrometry.
|
study
| 100.0 |
To examine the analytical performance of the present method, acetaminophen was used as the representative of the samples. Acetaminophen powder and corn starch were mixed (the ratio of acetaminophen powder in the mixture was 0%–100%) and then mixed powder was pressed into tablets using tableting machine. The re-pressed tablets containing acetaminophen were analyzed by the present method under the conditions of optimized desorption distance, time, and other parameters. The major fragment ion (m/z 110) of acetaminophen was selected as the quantitative ion and calibration curve was plotted using average value (n = 10) of net response signal of m/z 110 versus the concentration of acetaminophen powder in the mixture (Figure 6).Figure 6Calibration curve for acetaminophen. *The error bar in the curve is the standard deviation of net response signal
|
study
| 100.0 |
The results showed that the signal intensity and the concentration of acetaminophen displayed a good linear relationship in the 0%–100% range. The linear regression equation was I = 235.29 C + 120.58, and the correlation coefficient R = 0.9797. The real samples were analyzed and acetaminophen content was 60%. The relative standard deviation (RSD) was 7.33% (n = 10), and limit of detection (LOD, S/N = 3) of acetaminophen was 0.763 mg/g. The results showed that this method can meet the analysis of commercial tablets.
|
study
| 100.0 |
In this paper, a new type ion source based on atmospheric pressure MPT coupled with a simple mass spectrometer is used to obtain protonated molecular ions, molecular ions, and fragment ions of the analytes by adjusting the desorption distance, desorption time, and microwave power. After the discussion of the structures and the MEISD mechanism of the obtained ions, the probable gas-phase reaction in MPT ion source is described. By comparison of the full-scan spectra obtained by the present method with the MSn results obtained by MPT-LTQ MS, the accuracy of the present method is proven. The developed MPTDI-TOF-MS is expected to facilitate the qualitative and quantitative analysis of complex samples instead of using an expensive tandem mass spectrometer.
|
study
| 100.0 |
Spina bifida is the most common and complex central nervous system malformation in humans. Management of these patients involves various disciplines to ensure the best possible outcome achieved and provide a good quality of life for its patients [1, 2]. The study of this condition is extremely relevant in that even in the 20 years since the discovery of the benefits of folic acid this condition is highly prevalent around the world and its occurrence does not seem to decrease . Interestingly, the debate is very much ongoing upon the evidence that the United States of America has seen a decline in cases of spina bifida (https://www.cdc.gov/ncbddd/spinabifidadata.html). This review paper intends to compare and contrast spina bifida in humans and spina bifida in the mouse, which is the leading animal model of this devastating condition in light of the information studies on animal models have shed on the human counterpart [4–6].
|
review
| 99.9 |
Development of the central nervous system including the brain and spinal cord is a complex process beginning with a flat sheet of cells which undergoes sequential thickening, elevation, mediolateral convergence accompanied by rostrocaudal extension, and finally adhesion to form the neural tube (NT) which is the precursor of the brain and the spinal cord. Perturbations of these interconnected processes result in neural tube defects (NTDs), which are the most common congenital malformation affecting this system and are associated with significant complications. NTDs can occur in two major forms: spina bifida (SB) aperta, which is the open-lesion NTD, and the closed-lesion NTD, more commonly known as SB occulta.
|
review
| 99.9 |
Spina bifida is the most common nonlethal malformation in the spectrum of NTDs and has an incidence generally around 0.5 per 1,000 births, although higher frequencies have been reported [7–11]. In the United Kingdom, the population prevalence of spina bifida is 7.8–8.4 per 10,000 for males and 9.0–9.4 per 10,000 for females . While the prevalence in the United States of America is more than 3 in every 10,000 births [8, 13], studies in parts of Asia, such as Malaysia, have also shown a lower occurrence of spina bifida than that of the UK . More recent efforts by our group (“Spina Bifida: A 10-Year Retrospective Study at University of Malaya Medical Centre, Malaysia,” manuscript in submission), however, have found that the lower rate of NTDs may not be completely representative as in our hospital alone from the years 2003 to 2012 we have had over 10 cases of neural tube defects per year (spina bifida and anencephaly). Furthermore, certain regions of China have shown much higher preponderance of this condition than in other parts of the world [15–18]. In Africa, for example, spina bifida has been recorded as being low in occurrence in comparison to other birth defects but questions have arisen with regard to record-taking and data management . Gender preponderance differs according to country; in the USA, spina bifida is thought to be more prevalent in girls than in boys [20, 21].
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study
| 99.9 |
Spina bifida aperta (SBA), sometimes referred to as spina bifida cystica, is usually visible at birth as an exposed neural tissue with or without a protruding sac at the site of the lesion. SBA may be referred to as either myeloschisis (Figure 1(a)) or myelomeningocele (Figure 1(b)). Myelomeningocele is when the spinal cord protrudes from the spinal canal into a fluid-filled sac resulting from incomplete closure of the primary neural tube. Myeloschisis is when the incomplete closure of the primary neural plate results in a cleft spinal cord with the edges flush with the defect. The extent and severity of the neurological deficits depend on the location of the lesion along the neuraxis .
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other
| 60.25 |
Meningocele (Figure 1(c)) is often described as a less severe variant of myelomeningocele in which the spinal cord is not found in the sac and is described by embryologists to be absent of neural matter in its herniated sac; and its description is often coupled with that of myelomeningocele which clearly has neural matter herniating at the site of the open lesion. Therefore, the status of meningocele being an open (aperta) or closed (occulta) defect is still debatable in terms of embryogenesis. However, imaging evidence by radiologists has firmly placed meningocele as spina bifida occulta [3, 7, 121–123].
|
review
| 99.9 |
Myelomeningocele (MMC) is usually associated with a type II Chiari hindbrain malformation, ventriculomegaly, and hydrocephalus [124, 125]. Chiari type II malformation is the downward displacement of the cerebellar vermis into the cervical vertebral canal [22, 125]. It is often symptomatic and is diagnosed prenatally with ultrafast fetal magnetic resonance imaging (MRI) [126, 127]. This malformation causes elongation of the brain stem and obliteration of the fourth ventricle, leading to obstruction of cerebrospinal fluid circulation and development of hydrocephalus in 90% of patients . Treatment of such accompanying hydrocephalus is needed in about 82% of cases and involves draining of cerebrospinal fluid into either the peritoneal or other body cavity via a subcutaneous shunt .
|
review
| 99.8 |
Spina bifida occulta (SBO) is the second major form of NTDs, where the site of the lesion is not left exposed [129, 130]. Spina bifida occulta encompasses lipomyelomeningocele (Figure 1(d)), lipomeningocele (Figure 1(e)), and spinal dorsal dermal sinus tract (Figure 1(f)) ranging phenotypically from (i) dysplastic skin, (ii) tuft of hair, and (iii) vestigial tail as well as other forms of spinal dysraphism, which lack a pathogenic representation when the vertebrae develop abnormally leading to absence of the neural arches [131, 132]. In symptomatic cases, tethering of the spinal cord within the vertebral canal can result in pain, weakness, and incontinence in otherwise normal, healthy children or adults .
|
review
| 99.8 |
Management of patients with myelomeningocele has improved drastically from the mid-1970s when patients were sometimes denied treatment based on the severity of their condition to the current state-of-the-art prenatal in utero repairs performed at highly specialized centers [127, 128]. Neonatal surgical closure of the lesion is considered the standard of care against which all novel management options are compared [22, 135, 136].
|
review
| 99.9 |
NTDs have a profound impact on society. The morbidity and mortality rates of spina bifida patients decrease with improving medical care. Taking the United Kingdom as an example, Bowman et al. in their 25-year follow-up of 71 spina bifida aperta patients found that at least 75% of these children can be expected to reach their early adult years . Moreover, as many as 85% are attending or have graduated from high school and/or college. More than 80% of young adults with spina bifida have social bladder continence. In the same study, 49% had scoliosis, with 43% eventually requiring a spinal fusion. Approximately one-third of patients were allergic to latex, with six patients having experienced a life-threatening reaction. Renal failure was 6.8–9.0 times more common for males and 9.2–11.5 times more common for female patients compared with the general population in each of the years 1994–1997 in the UK . Therefore, longer life equates with the need for progressively better quality of life.
|
review
| 99.75 |
The sequelae of NTDs are staggering and appear to have not only anatomical effects secondary to the primary defect but also functional, emotional, and psychological morbidities including bladder and bowel incontinence, paralysis, musculoskeletal deformity, and shunt malfunctions and infections, among others. Moreover, the costs involved in maintenance of spina bifida patients include mobility aids (orthoses, wheelchairs, and crutches), medications, and the cost associated with shunt revisions, in addition to the cost of modifications to public utilities that are required to enable disabled access. Ultimately, its compound nature results in an immense financial burden amounting to $1,400,000 per child affected by NTD over a 20-year life span [139–142].
|
review
| 99.9 |
A small proportion of NTDs in live born infants are associated with specific syndromes that are associated with chromosomal or single-gene disorders . NTDs are currently considered as “complex” disorders with genetic and environmental factors playing roles in causation , which have been summarized in Table 1. Craniorachischisis and encephalocoele have the highest rate of syndromic association, anencephaly and high spina bifida have intermediate rates, and caudal spina bifida has the lowest rate . The role of folic acid in preventing syndromic NTDs turned out to be not as gratifying as for nonsyndromic (isolated), multifactorial NTDs . It should be noted that while syndromic NTDs may have identifiable genetic causes, many of the nonsyndromic (isolated) NTDs have unidentified genetic etiology. Most of human neural tube defects are nonsyndromic with NTD being the only defect. The focus of this review paper is on nonsyndromic (isolated) spina bifida apart from the clearly stated syndromic spina bifida mentioned specifically in Table 1.
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| 99.9 |
The etiology of spina bifida is heterogeneous [147–150]. Most nonsyndromic spina bifida is thought to be of multifactorial origin with influence of both genetic and environmental factors [144, 152]. Among the environmental factors associated with increased risk of spina bifida are increased pregnancy weight [153–158], maternal smoking [159–161], drug intake specifically of antiepileptic drugs [162–164], and maternal illnesses such as diabetes [165, 166] and hyperthermia . Dietary factors including water chlorination [168–170], inositol intake , simple sugar intake , and the intake of trace elements and other micronutrients [173–176] have been proposed to act as either contributory or preventive factors for spina bifida. Isolated spina bifida is caused by cytogenetic abnormalities in 2–16% of cases [177–179].
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review
| 99.9 |
Elevated levels of maternal serum alpha-fetoprotein are usually indicative of spina bifida aperta [180, 181] but can be associated with other conditions (e.g., twin gestation and abnormalities of placentation including placental lakes and placenta previa) and ultrasound is needed to confirm the diagnosis. Screening obstetrical ultrasonography is the initial routine method for the detection of NTDs during pregnancy in many countries. However, it sometimes fails to detect closed spina bifida [182, 183]. In highly specialized fetal centers, use of ultrafast fetal MRI has enabled detailed anatomical evaluation of the defect and accurate assessment of its accompanying effects .
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review
| 99.8 |
It has been over 15 years since the Medical Research Council Vitamin Trial involving 33 centers around the world conclusively showed that 72% of recurrent NTD cases could be prevented by folic acid supplements in the periconceptional period . A further study showed that the first occurrence of spina bifida could also be prevented by folic acid. However, not all NTDs are responsive to folic acid and inositol has been shown as a possible additional therapy, based on prevention of spina bifida in folate-resistant NTDs in mice as well as the PONTI human trial [186, 187]. Calcium formate too has been shown to have preventive effects on NTD in mice but evidence is not yet forthcoming in prevention of human NTDs [188–190]. There still remains room to study whether there are other supplements out there that can prevent spina bifida.
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review
| 99.9 |
Surgical management of spina bifida here is discussed as a 2-point discussion: first is surgical management prior to the advent of in utero repair of open spina bifida and second is in utero repair leading to the Management of Myelomeningocele Study (MOMS) trial . Postnatal repair of open spina bifida repair is a requirement in order to prevent further mechanical damage and infection. The lesion either may be closed primarily with the aid of skin and muscle flaps or may require a synthetic patch such as AlloDerm (LifeCell Corp., Branchburg, NJ) , gelatin, or collagen hybrid sponges . In utero MMC repair in humans was first reported in the landmark paper published in 1998 . However, since then, a handful of centers have been offering in utero repair. Furthermore, its popularity has increased in Europe . The principle of in utero repair is to prevent the 2-hit hypothesis much described in previous literature that the child is exposed to neurological deterioration contributed first by failure of the neural tube to form and secondly by physical and chemical perturbation inflicted on the exposed neurological tissue of the open lesion [128, 194]. In an elegant experimental study, Meuli et al. concluded that surgical exposure of the normal spinal cord to the amniotic space in a 75-day sheep fetus results in a MMC-type pathology at birth with clinical, histological, and morphological attributes comparable to human MMC. Heffez et al. has demonstrated that spinal cord injury caused by exposure to the intrauterine milieu can be prevented by primary closure of the fetal skin incision as late as hours after creating the defect. It also demonstrated that ongoing exposure beyond 24 hours leads to spinal cord damage and permanent neurological deficit. Moreover, animal studies have previously shown that prenatal coverage of a spina bifida-like lesion preserves neurologic function and improves hindbrain herniation [195, 197, 198].
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review
| 99.9 |
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