There is a fair amount of evidence showing that increased risks of obesity and insulin resistance are associated with postmenopausal state, but can be modulated by diet and exercise. In this study, we evaluated the effects of Pueraria lobata/Rehmannia glutinosa combination (PR), exercise, or both on metabolic changes in ovariectomized (OVX) Sprague Dawley rats for 8 weeks: Sham control, OVX control, OVX+PR (200 and 400 mg/kg bw), OVX+EX, OVX+EX+PR (200 and 400 mg/kg bw) ( n =10/group). PR was fed by gavage and incremental treadmill exercise was used. Oral glucose tolerance test was measured at week 4 and week 8. After 8 weeks, fasting plasma levels of glucose, insulin, C‐peptide, total cholesterol, free fatty acids, leptin, and adiponectin were measured. mRNA expressions (Glut 4 and FOXO) and western blotting (p‐IRS and p‐AKT) were also studied in the muscle. Together, the results suggest the additive effects of PR supplementation and exercise in the management of postmenopausal metabolic changes. Grant Funding Source : This research was supported by MOTIE/KIAT (N0000697) and MEST/BK 21 PLUS (22A20130012143).
This study employs machine learning and population-based data to examine major factors of antidepressant medication including nitrogen dioxides (NO2) seasonality.Retrospective cohort data came from Korea National Health Insurance Service claims data for 43,251 participants with the age of 15-79 years, residence in the same districts of Seoul and no history of antidepressant medication during 2002-2012. The dependent variable was antidepressant-free months during 2013-2015 and the 103 independent variables for 2012 or 2015 were considered, e.g., particulate matter less than 2.5 micrometer in diameter (PM2.5), PM10, NO2, ozone (O3), sulphur dioxide (SO2) and carbon monoxide (CO) in each of 12 months in 2015.It was found that the Cox hazard ratios of NO2 were statistically significant and registered values larger than 10 for every three months: March, June-July, October, and December. Based on random forest variable importance and Cox hazard ratios in brackets, indeed, the top 20 factors of antidepressant medication included age (0.0041 [1.69-2.25]), migraine and sleep disorder (0.0029 [1.82]), liver disease (0.0017 [1.33-1.34]), exercise (0.0014), thyroid disease (0.0013), cardiovascular disease (0.0013 [1.20]), asthma (0.0008 [1.19-1.20]), September NO2 (0.0008 [0.01]), alcohol consumption (0.0008 [1.31-1.32]), gender - woman (0.0007 [1.80-1.81]), July NO2 (0.0007 [14.93]), July PM10 (0.0007), the proportion of the married (0.0005), January PM2.5 (0.0004), September PM2.5 (0.0004), chronic obstructive pulmonary disease (0.0004), economic satisfaction (0.0004), January PM10 (0.0003), residents in welfare facilities per 1,000 (0.0003 [0.97]), and October NO2 (0.0003).Antidepressant medication has strong associations with neighborhood conditions including NO2 seasonality and welfare support.
Influenza virus is well known for pandemics and epidemics with high morbidity.Many studies have been focused to this problematics, however, oxidative damage to DNA, lipids, and proteins and the expression of cytokines, antioxidant enzymes and heat-shock proteins (HSPs) in H1N1 virus-infected patients has not been investigated yet.Therefore we aimed this study at these issues.We found out that patients infected with the 2011 H1N1 virus as compared to control subjects exhibited an increased oxidative damage to DNA, lipids and proteins as assayed by levels of 8-hydroxydeoxyguanosine (8-OhdG) and malondialdehyde (MDA) and carbonyl content in plasma and urine.Moreover, the levels of antioxidant enzymes SOD and catalase, cytokines Il-6, 1L-10 and TNF-α and HSPs 90 and 27 were also significantly higher in the H1N1-infected patients.Our results suggest that the influenza H1N1 virus is a strong inducer of (i) oxidative damage to DNA, lipids, and proteins, (ii) antioxidant enzymes, (iii) cytokines and (iv) HSPs.
This study presents the most comprehensive machine-learning analysis for the predictors of blood transfusion, all-cause mortality, and hospitalization period in COVID-19 patients. Data came from Korea National Health Insurance claims data with 7943 COVID-19 patients diagnosed during November 2019−May 2020. The dependent variables were all-cause mortality and the hospitalization period, and their 28 independent variables were considered. Random forest variable importance (GINI) was introduced for identifying the main factors of the dependent variables and evaluating their associations with these predictors, including blood transfusion. Based on the results of this study, blood transfusion had a positive association with all-cause mortality. The proportions of red blood cell, platelet, fresh frozen plasma, and cryoprecipitate transfusions were significantly higher in those with death than in those without death (p-values < 0.01). Likewise, the top ten factors of all-cause mortality based on random forest variable importance were the Charlson Comorbidity Index (53.54), age (45.68), socioeconomic status (45.65), red blood cell transfusion (27.08), dementia (19.27), antiplatelet (16.81), gender (14.60), diabetes mellitus (13.00), liver disease (11.19) and platelet transfusion (10.11). The top ten predictors of the hospitalization period were the Charlson Comorbidity Index, socioeconomic status, dementia, age, gender, hemiplegia, antiplatelet, diabetes mellitus, liver disease, and cardiovascular disease. In conclusion, comorbidity, red blood cell transfusion, and platelet transfusion were the major factors of all-cause mortality based on machine learning analysis. The effective management of these predictors is needed in COVID-19 patients.
Chili pepper (<i>Capsicum annuum</i> L.), one of the most economically important vegetable crops globally, faces significant economic risks from anthracnose, leading to yield losses of 10% as well as decreasing marketability. Early and accurate detection is essential for mitigating these effects. Recent advancements in deep learning, particularly in image recognition, offer promising solutions for plant disease detection. This study applies deep learning models—MobileNet, ResNet50v2, and Xception—using transfer learning to diagnose anthracnose in chili peppers. A key challenge is the need for large, labeled datasets, which are costly to obtain. The study aims to identify the minimum dataset size required for accurate and efficient disease diagnosis using limited data. Performance metrics, including precision, recall, F1-score, and accuracy, were evaluated across different dataset sizes (500, 1,000, 2,000, 3,000, and 4,000 samples). Results indicated that model performance improves with larger datasets, with ResNet50v2 and Xception requiring more data to achieve optimal accuracy, while MobileNet showed strong generalization even with smaller datasets. These findings underscore the effectiveness of transfer learning-based models in plant disease detection, offering practical guidelines for balancing data availability and model performance in agricultural applications. Source code available at https://github.com/smart-able/Anthracnose.git.
Ceramides, one of the major lipid components in the stratum corneum, have been increasingly used in several topical applications of cosmetic and medical products, and the balanced use of ceramides has been shown to be critical to their stability. In this work, we performed molecular dynamics simulations of monolayer and bilayer structures composed of varying compositions of ceramide IIIb and a surfactant (c16‐alkyl glucosides). The monolayer was simulated in the interface between water and an oily phase composed of capric triglycerides and the bilayer was in explicit water. We investigated the effect of ceramide IIIb composition on the structural stability of monolayers and bilayers by calculating the area per lipid and the equilibrium structures by observing simulation snapshots and analyzing density profiles along the direction perpendicular to the layers. The results showed that the monolayers in the interface and the bilayers in water reached equilibrium within simulation duration of 100 ns and the layer structures were more ordered at higher ceramide contents. The composition‐dependent difference in the order of lipid molecules was interpreted in terms of the difference in the numbers of lipid tails in ceramides and surfactants and, hence, the difference in the spatial volume occupied by head and tail groups of both lipids. The differential volume occupation also resulted in different vertical arrangements of both lipid molecules.
Background/Objectives: The purpose of this study was to investigate the effects of core stabilization exercise combined with music of various tempo and mode on the power of agility.Method/Statistical Analysis: 65 healthy adults who didnot major in music were recruited and each participant were randomly divided five groups. All groups were performed core stabilization exercise for 3 weeks. To confirm the effect of core stabilization exercise combined with music of various tempo and mode, they were measured before and after the exercise.Findings: After applying the core stabilization exercise, the power of agility was improved in all groups, and the fast tempo groups improved the power of agility more than the slow tempo groups. However, there was no significant difference between the major mod and minor mode groups.Improvements/Applications: Tempo was affected on the power of agility. But mode was not affected on the power of agility.
This study was conducted to analyze the relationship between locomotive syndrome and sarcopenia in the old people using a functional evaluation tool. In this study, 237 Korean old people selected from the Miraeseum Seongnam Senior Complex and the Misa Riverside Welfare Center were diagnosed with the two diseases and the Berg balance scale was performed to confirm the deterioration of dynamic balance sensory. Through the diagnostic evaluation of the two diseases, the locomotive group (n= 180) and the sarcopenia group (n= 34) were classified and statistically analyzed. As a result of the study, a significant difference in dynamic balance sensory between the two diseases was confirmed, and a significant negative correlation was confirmed with 25-question geriatric locomotive function scale and grip strength among the diagnostic evaluation items of the two diseases. These results suggest that gradual deterioration of locomotive syndrome and sarcopenia occurs in the deterioration of physical performance in the old people, suggesting that the evaluation of locomotive syndrome can be used as a screening test for sarcopenia.
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