Sugary snack restriction enhances body composition improvement in overweight women engaging in non-face-to-face walking during COVID-19.

Introduction: This study assesses the impact of dietary modification, specifically sugary snack restriction, in conjunction with a brisk walking program on overweight management in young overweight women, with a focus on changes in body composition and glucose metabolism. Method: An 8-week randomized controlled trial was conducted amidst the COVID-19 pandemic, utilizing a remote intervention approach to comply with health guidelines and ensure participant safety. The study's remote nature highlights adaptability in health interventions during challenging periods, such as the COVID-19 pandemic. Twenty-one overweight Korean women aged 20-39, with an average BMI of 24.6, were selected for the study. They were divided into two groups: one engaging in brisk walking and the other combining this exercise with a sugary snack restriction, demonstrating the study's focus on comparative intervention efficacy. Results: The exercise-only group showed notable reductions in glucose, insulin, HOMA-IR (p < 0.05), and total cholesterol levels (p < 0.01). In contrast, the group that combined exercise with dietary modification displayed more pronounced improvements in body weight, fat mass, and waist circumference (p < 0.05). This differential outcome emphasizes the added benefit of integrating dietary control with physical activity. Discussion: The findings suggest that adding a dietary component, particularly a sugary snack restriction, to an exercise regimen can significantly enhance the effectiveness of overweight management in young women. This study underscores the importance of holistic lifestyle interventions that combine dietary and physical activity modifications for improved health outcomes.

Effects of water-table changes following rainfall events on arsenic fate and transport in groundwater-surface water mixing zones.

This study investigated the effects of groundwater-surface water (GW-SW) interactions on the fate and transport of arsenic (As) following rainfall events and subsequent water-table changes in GW-SW mixing zones, comprising the riparian and hyporheic zones, near an abandoned gold mine. During the dry and wet periods, stream conditions changed from flow-through to gaining, respectively. Water-table changes caused by rainfall events controlled flow paths between riparian zones and the stream, affecting spatiotemporal variation in the redox and pH conditions of the aquatic environment. Subsequently, the fate and transport of As in GW-SW mixing zones was responsive to variations in redox and pH conditions. Through the oxidative dissolution of As-bearing sulfide minerals and the reductive dissolution of iron (Fe) oxides with adsorbed As, As was released into the groundwater in the riparian zones and transported to the stream and streambed along the baseflow discharge. However, As was also immobilized in the sediment through adsorption onto Fe-oxides and coprecipitation with calcium (Ca) and zinc (Zn), suggesting that the sediment acts as a sink-and-source of As in aquatic environments. Therefore, water-table changes and GW-SW interactions could play an important role in the fate and transport of As in aquatic environments, specifically groundwater-riparian-streambed-stream systems. The findings of this study will provide scientific insights into the mechanisms of As in aquatic environments, aiding in improved decision-making to ensure safe and sustainable water management in response to future climate change.

Computational drug repositioning with attention walking.

Drug repositioning aims to identify new therapeutic indications for approved medications. Recently, the importance of computational drug repositioning has been highlighted because it can reduce the costs, development time, and risks compared to traditional drug discovery. Most approaches in this area use networks for systematic analysis. Inferring drug-disease associations is then defined as a link prediction problem in a heterogeneous network composed of drugs and diseases. In this article, we present a novel method of computational drug repositioning, named drug repositioning with attention walking (DRAW). DRAW proceeds as follows: first, a subgraph enclosing the target link for prediction is extracted. Second, a graph convolutional network captures the structural features of the labeled nodes in the subgraph. Third, the transition probabilities are computed using attention mechanisms and converted into random walk profiles. Finally, a multi-layer perceptron takes random walk profiles and predicts whether a target link exists. As an experiment, we constructed two heterogeneous networks with drug-drug similarities based on chemical structures and anatomical therapeutic chemical classification (ATC) codes. Using 10-fold cross-validation, DRAW achieved an area under the receiver operating characteristic (ROC) curve of 0.903 and outperformed state-of-the-art methods. Moreover, we demonstrated the results of case studies for selected drugs and diseases to further confirm the capability of DRAW to predict drug-disease associations.

Saengmaeksan, a traditional polyherbal formulation containing Panax ginseng, improves energy metabolism during exercise.

Saengmaeksan (SMS), a representative oriental medicine that contains Panax ginseng Meyer, Liriope muscari, and Schisandra chinensis (1:2:1), is used to improve body vitality and enhance physical activity. However, there is limited scientific evidence to validate the benefits of SMS. Here, we investigated the in vitro and in vivo regulatory effects of SMS and its constituents on energy metabolism and the underlying molecular mechanisms. For this, quantitative real-time polymerase chain reaction, 3D holotomographic microscopy, western blotting, and glucose uptake experiments using 18F-fluoro-2-deoxy-D-glucose (18F-FDG) were performed using L6 cells to investigate in vitro energy metabolism changes. In addition, 18F-fluorocholine (18F-FCH) and 18F-FDG positron emission tomography/computed tomography (PET/CT) analyses, immunohistochemistry, and respiratory gas analysis were performed in mice post-endurance exercise on a treadmill. In the energy metabolism of L6 cells, a significant reversal in glucose uptake was observed in the SMS-treated group, as opposed to an increase in uptake over time compared to the untreated control group. Furthermore, P. ginseng alone and SMS significantly decreased the volume of lipid droplets. SMS also regulated the phosphorylation of extracellular signal-regulated kinase (ERK), phosphorylation of p38, mitochondrial morphology, and the expression of apurinic/apyrimidinic endonuclease 1/redox factor-1 (APE/Ref-1) in H2O2-stimulated L6 cells. In addition, SMS treatment was found to regulate whole body and muscle energy metabolism in rats subjected to high-intensity exercise, as well as glucose and lipid metabolism in skeletal muscle. Therefore, SMS containing P. ginseng ameliorated imbalanced energy metabolism through oxidative stress-induced APE/Ref-1 expression. SMS may be a promising supplemental option for metabolic performance.

A Decline in Overutilization of Transfusion after Total Knee Arthroplasty Using Pharmacological Agents for Patient Blood Management in South Korea: An Analysis Based on the Korean National Health Insurance Claims Database from 2008 to 2019.

Background: This study aimed to evaluate the annual trends of transfusion rates and utilization of blood management agents in total knee arthroplasty (TKA) based on the operation type and to analyze the risk factors of transfusion after TKA. Methods: Using the Korean National Insurance claims database of 797,106 primary and revision TKAs between January 2008 and October 2019, data on the patients' characteristics, comorbidities, utilization of transfusion, and blood management agents were collected. The patients were categorized into three groups based on the operation type: primary, revision, and simultaneous bilateral TKA. The transfusion rate and utilization of blood management agents (intraoperative tranexamic acid [TXA] and preoperative iron supplements) were compared, and the risk factors for transfusion were evaluated. Results: After excluding the inaccurate data, 730,554 arthroplasties (636,292 primary, 10,540 revision, and 41,861 simultaneous bilateral TKAs) were identified. The transfusion rates of primary, revision, and simultaneous bilateral TKAs in 2019 were 64.0%, 67.7%, and 68.9%, respectively, which were significantly decreased compared with 83.2%, 88.0%, and 92.5% in 2008, respectively (p < 0.001). Conversely, the utilization of intraoperative TXA and preoperative iron supplements was significantly increased from 4.6% and 13.8%, respectively, in 2008 to 52.4% and 27.0%, respectively, in 2019 (p < 0.001). The utilization of intraoperative TXA and preoperative iron supplements significantly lowered the risk of transfusion after TKA (odds ratio [OR], 0.20; p < 0.001 and OR, 0.71; p < 0.001). Conclusions: The transfusion rate after TKA decreased gradually from 83.5% to 64.5% between 2008 and 2019 in South Korea corresponding with the increased utilization of blood management agents. Therefore, consistent attention to patient blood management should be emphasized to reduce the transfusion rate after TKA.

The role of continuous glucose monitoring in physical activity and nutrition management: perspectives on present and possible uses.

PURPOSE: Continuous glucose monitoring (CGM) is on the rise as the prevalence of obesity and diabetes increases. This review aimed to explore the use of CGM and its potential novel applications in physical activity and nutrition management. METHODS: We searched PubMed, Web of Science, and Wiley Online Library databases using the keywords 'continuous glucose monitor,' 'nutrition,' 'physical activity,' and 'numerical modeling.' RESULTS: Continuous blood glucose measurement is useful for individuals with obesity and diabetes. Long-term blood glucose data allow for personalized planning of nutritional composition, meal timing, and physical activity type and intensity, as well as help prevent hypoglycemia and hyperglycemia. Thus, understanding the limitations of CGM is important for its effective use. CONCLUSION: CGM systems are being increasingly used to monitor and identify appropriate blood glucose controlling interventions. Blood glucose level is influenced by various factors such as nutrient composition, meal timing, physical activity, circadian rhythm, and cortisol levels. Numerical modeling can be used to analyze the complex relationship between stress, sleep, nutrition, and physical activity, which affect blood glucose levels. In future, blood glucose, sleep, and stress data will be integrated to predict appropriate lifestyle levels for blood glucose management. This integrated approach improves glucose control and overall wellbeing, potentially reducing societal costs.

Effects of exercise timing and intensity on physiological circadian rhythm and sleep quality: a systematic review.

PURPOSE: Humans show near-24-h physiological and behavioral rhythms, which encompass the daily cycle of sleep and wakefulness. Exercise stimulates circadian rhythms, including those of cortisol, melatonin, and core body temperature, and affects sleep quality. We systematically reviewed studies that examined the effects of exercise intensity and timing on physiological circadian rhythms and sleep quality. METHODS: In this systematic review, we used the online databases PubMed, Science Direct, Web of Science, and Embase. This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Two independent and experienced systematic reviewers performed the search and selected relevant studies. The participant, intervention, comparison, and outcome characteristics were: (1) adults; (2) exercise treatment; (3) no exercise treatment or different types of exercise (pre-exercise baseline); (4) cortisol, melatonin, or core body temperature measurement, and subjective or objective sleep quality assessments. RESULTS: We identified 9 relevant articles involving 201 participants (77.1% of whom were male). Our review revealed that short-term evening exercise delayed melatonin rhythm and increased nocturnal core body temperature; however, no negative effects on non-rapid eye movement sleep and sleep efficiency were observed. Moreover, no differences in sleep quality were observed between acute high-intensity and moderate-intensity exercises. With long exercise durations, the core body temperature tended to increase and return to baseline levels at 30-120 min. CONCLUSION: Our review showed that short-term evening exercise and high-intensity exercise did not have a significant negative effect on sleep quality but physiological circadian rhythm tended to alter. Longterm morning exercise tended to decrease cortisol concentrations after awakening and improve sleep quality. Future studies should examine the effects of long-term exercise timing and intensity on circadian rhythm and sleep.

Development of a one-shot dual aptamer-based fluorescence nanosensor for rapid, sensitive, and label-free detection of periostin.

Periostin is associated with several diseases, including cancers. Therefore, monitoring blood periostin levels is a powerful tool for diagnosing various diseases and identifying their severity. However, conventional detection methods pose several challenges, including high costs. To address these issues, we developed a novel one-shot dual aptamer-based fluorescence nanosensor for detecting periostin. The proposed nanosensor facilitates rapid, label-free, and sensitive detection of periostin using gold nanoprobes constructed by rhodamine-b isothiocyanate, PL2trunc aptamer, and gold nanoparticles and silver nanoprobes fabricated by the PL5trunc aptamer and silver nanoparticles. The two nanoprobes form a core-satellite structure by interacting with periostin, and the nanosensor detects periostin through the fluorescence regenerated by the increased proximity between them. The nanosensor successfully detected periostin with remarkable detection limits of 106.68 pM in buffer and 463.3 pM in serum-spiked conditions within 30 min without additional washing or signal amplification processes. Considering serum periostin levels in various diseases, the proposed nanosensor provides a suitable method for identifying patients with various diseases and determining disease severity. Moreover, the platform can be helpful as a practical method for on-site medical diagnosis because it can be adapted to detect other biomarkers simply by replacing the aptamer with other detection probes.

Total energy expenditure of collision team sports players measured using doubly labeled water: a systematic review.

PURPOSE: Total energy expenditure (TEE) is crucial for energy balance and recovery in athletes who participate in collision team sports with high training volumes. This study aimed to review the existing evidence on TEE measured using the doubly labeled water (DLW) technique in soccer, basketball, and rugby players. Furthermore, this systematic review summarized the training volume, match details during the measurement period, and body composition of the athletes. METHODS: This systematic review used the PubMed, Science Direct, Web of Science, and Embase databases. Only articles presenting objectively measured data on the TEE of adolescent and adult collision team sports players were included, as measured using the DLW method. The measurement period, training, match information, and body composition data were also obtained. The search strategy identified 1497 articles, of which 13 met the selection criteria. RESULTS: The 13 studies included four rugby players, six soccer players, and three basketball players; six of the 13 studies involved young players. The TEE measured using the DLW method was 3862.3-5783.9 kcal/day for rugby, 2859-3586 kcal/day for soccer, and 4006-4921 kcal/day for basketball players. CONCLUSION: The TEE of collision sports players varies depending on the training or match load, body composition, and measurement period. Individual approaches to nutritional prescriptions for collision sports players should also account for different periods, anthropometric profiles, training, and game loads. This review provides evidence for developing nutritional guidelines to optimize the recovery and performance of collision team players.

Physical activity levels and energy intake according to the presence of metabolic syndrome among single-household elderly in Korea: Korean National Health and Nutrition Examination Survey 2016-2018.

Background: Exercise and dietary and nutritional intake affect the risk and prevalence of metabolic syndrome (MetS) in elderly people, effects that may differ according to sex in elderly single households (ESH). This study aimed to analyze the differences in physical activity (PA) levels and energy intake according to sex and prevalence of MetS among elderly people in Korea to investigate the relationships between these factors. Methods: Data from 893 elderly individuals (aged >65 years) were obtained from the Korean National Health and Nutrition Examination Survey (2016-2018). We analyzed PA levels (occupational and recreational PA and place movement) and energy intake (EI; total, carbohydrate, protein, and fat), and found that there were sex differences in both according to the presence or absence of MetS in ESH. Results: Among both males and females, the MetS group had a significantly lower recreational moderate PA than the non-MetS group. However, total PA in males was significantly higher in the non-MetS than in the MetS group, but there was no significant difference in females. Furthermore, the EI of females did not differ in the presence or absence of MetS, except for fat intake, and in the nutritional intake of ESH in males, no difference was found in the presence or absence of MetS. We also found that in Odd ratio, "active" was associated with lowering high waist circumference (OR = 0.40, 95%CI = 0.21-0.76), and "very active" was associated with lower MetS occurrence (OR = 0.51, 95%CI = 0.33-0.81) and low high-density lipoprotein cholesterol (HDL-C) (OR = 0.55, 95%CI = 0.37-0.83). Conclusions: Therefore, in the MetS group of ESH, there was a significant correlation of the MetS component in PA rather than EI. Male ESH require interventions that increase PA, while female ESH require nutrition interventions that increase and balance PA. Therefore, a new program is needed that promotes continuous interest and healthy lifestyles in consideration of the characteristics of ESH.

Effects of Whey Protein Supplement on 4-Week Resistance Exercise-Induced Improvements in Muscle Mass and Isokinetic Muscular Function under Dietary Control.

(1) The purpose of this study was to investigate the effect of whey protein supplementation under dietary control on improvements in muscle mass and function following resistance exercise training. (2) Thirty-two men were randomly assigned to a whey protein supplementation group taking whey protein isolate (PSG, n = 17) and a placebo group (CON, n = 15). Participants were provided with three meals per day corresponding to the estimated individual daily energy intake. The supervised resistance exercise program was conducted 60 min per day, six days per week, for four weeks. (3) Post-intervention, there was a significant interaction between groups in terms of muscle mass increase (p = 0.033, η2 = 0.14), with a greater increase in the PSG. There were also significant interactions between the groups and increases in peak torque of the dominant knee flexors (p = 0.048, η2 = 0.12), dominant shoulder extensors, and non-dominant shoulder extensors (p = 0.028, η2 = 0.15; p = 0.015, η2 = 0.18), and the total work of the dominant knee and shoulder extensors (p = 0.012, η2 = 0.19; p = 0.013, η2 = 0.19), with greater increases in the PSG. (4) These results suggest that whey protein supplementation enhances resistance exercise-induced increase in muscle mass and overall muscular strength and endurance, independent of dietary influence.

Protein-Added Healthy Lunch-Boxes Combined with Exercise for Improving Physical Fitness and Vascular Function in Pre-Frail Older Women: A Community-Based Randomized Controlled Trial.

Purpose: Preventive or therapeutic interventions are key to maintaining independence in pre-frail and/or frail elderly. Therefore, we investigated whether multi-component interventions were effective in physical fitness levels and vascular functions in pre-frail older women. Patients and Methods: Sixty participants aged ≥ 65 years (81.5 ± 4.3 yrs) were divided equally into control group, diet group, aerobic exercise and diet group, and aerobic exercise with electromyostimulation and diet group. For 8 weeks, the participants received a set of protein-added meals twice daily on weekdays. The aerobic exercise groups performed 45 mins of stepping exercise at 50-70% of the maximal heart rate for 3 days/week, and the aerobic exercise with electromyostimulation was applied on each limb in 8 weeks. Blood pressure, physical fitness, cardiovascular biomarkers, pulse wave velocity, and flow-mediated dilation were measured before and after the 8-week. Results: There were no group differences in age, height, weight, body mass index, free fat mass, and %body fat at baseline. The right grip strength significantly increased in the diet group, aerobic exercise and diet group, and aerobic exercise with electromyostimulation and diet group (p < 0.05). Short physical performance battery, 6-min walking distance, and flow-mediated dilation significantly increased in the aerobic exercise and diet group and aerobic exercise with electromyostimulation and diet group (p < 0.05). Blood pressure and pulse wave velocity did not differ between interventions. High-density lipoprotein-cholesterol levels significantly increased after 8 weeks in all intervention groups (p < 0.05). There were no significant differences in glucose, HbA1c, total cholesterol, low-density lipoprotein-cholesterol, triglyceride, insulin, Homeostatic Model Assessment for Insulin Resistance, nitric oxide, and C-reactive protein levels. Conclusion: These results show that multi-component interventions appear to improve physical fitness and vascular function in pre-frail older women. Thus, possible strategies to prevent early frailty including proper nutrition and exercise may be needed.

Total energy expenditure measured by doubly labeled water method in children and adolescents: a systematic review.

Total energy expenditure (TEE) is essential for understanding the growth, development, and physical activity of children and adolescents. This study aimed to summarize the existing evidence on TEE measured using the doubly labeled water (DLW) technique in children and adolescents aged 1-18 years. Furthermore, this review compared TEE between obese and normal-weight participants. This systematic review used the PubMed, ScienceDirect, Web of Science, and EBSCO databases. These studies were limited to those published in English between January 2000 and December 2021. Articles presenting objectively measured data on the TEE of children and adolescents aged 1-18 years measured using the DLW method were included. Physical activity level (PAL; TEE/basal metabolic rate [BMR]) and BMR data were also obtained. The search strategy identified 2,351 articles, of which 63 (n=4,283 children and adolescents; 45.4% male) met the selection criteria. The participants in the 10 studies were overweight or obese (n=413). In our study, TEE increased in male and female participants aged 1-18 years. PAL increased with age in males (y=0.0272x+1.3887, r2=0.511) and females (y=0.0199x+1.401, r2=0.335), and the slope of PAL with age did not differ between males and females. The TEE of obese and overweight participants was higher than that of normal-weight participants, but the slope of TEE did not differ between normal-weight (y=132.99x+702.24, r2=0.877) and obese individuals (y=136.18x+1,037.9, r2=0.842). In conclusion, this review provides convincing evidence that daily TEE progressively increases with growth in males and females aged 1-18 years.

Blood Transfusion, All-Cause Mortality and Hospitalization Period in COVID-19 Patients: Machine Learning Analysis of National Health Insurance Claims Data.

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.

Spatio-Temporal Epidemiology of the Spread of African Swine Fever in Wild Boar and the Role of Environmental Factors in South Korea.

Since the first confirmation of African swine fever (ASF) in domestic pig farms in South Korea in September 2019, ASF continues to expand and most notifications have been reported in wild boar populations. In this study, we first performed a spatio-temporal cluster analysis to understand ASF spread in wild boar. Secondly, generalized linear logistic regression (GLLR) model analysis was performed to identify environmental factors contributing to cluster formation. In the meantime, the basic reproduction number (R0) for each cluster was estimated to understand the growth of the epidemic. The cluster analysis resulted in the detection of 17 spatio-temporal clusters. The GLLR model analysis identified factors influencing cluster formation and indicated the possibility of estimating ASF epidemic areas based on environmental conditions. In a scenario only considering direct transmission among wild boar, R0 ranged from 1.01 to 1.5 with an average of 1.10, while, in another scenario including indirect transmission via an infected carcass, R0 ranged from 1.03 to 4.38 with an average of 1.56. We identified factors influencing ASF expansion based on spatio-temporal clusters. The results obtained would be useful for selecting priority areas for ASF control and would greatly assist in identifying efficient vaccination areas in the future.

Comparison of total energy intakes estimated by 24-hour diet recall with total energy expenditure measured by the doubly labeled water method in adults.

BACKGROUND/OBJECTIVES: The doubly labeled water (DLW) method is the gold standard for estimating total energy expenditure (TEE) and is also useful for verifying the validities of dietary evaluation tools. In this study, we compared the accuracy of total energy intakes (TEI) estimated by the 24-h diet recall method with TEE obtained using the doubly labeled water method. SUBJECTS/METHODS: This study involved 71 subjects aged 20-49 yrs. Over a 14-day period, three 24-h diet recalls per subject (2 weekdays and 1 weekend day) were used to estimate energy intakes, while TEE was measured using the DLW method. The paired t-test was used to determine the significance of differences between TEI and TEE results, and the accuracy of the 24-h recall method was determined by accuracy predictions percentage, root mean square error, and bias. RESULTS: Average study subject age was 33.4 ± 8.6 yrs. The association between TEI and TEE was positive and significant (r = 0.463, P < 0.001), and the difference between TEI (2,084.3 ± 684.2 kcal/day) and TEE (2,401.7 ± 480.3 kcal/day) was also significant (P < 0.001). In all study subjects, mean TEI was 12.0% (307.5 ± 629.3 kcal/day) less than mean TEE, and 12.2% (349.4 ± 632.5 kcal/day) less in men and 11.8% (266.7 ± 632.5 kcal/day) less in women. Rates of TEI underprediction for all study subjects, men, and women, were 60.5%, 51.4%, and 66.7%, respectively. CONCLUSIONS: This study shows that 24-h diet recall underreports energy intakes. More research is needed to corroborate our findings and evaluate the accuracy of 24-h recall with respect to additional demographics.

Drug-Disease Association Prediction Using Heterogeneous Networks for Computational Drug Repositioning.

Drug repositioning, which involves the identification of new therapeutic indications for approved drugs, considerably reduces the time and cost of developing new drugs. Recent computational drug repositioning methods use heterogeneous networks to identify drug-disease associations. This review reveals existing network-based approaches for predicting drug-disease associations in three major categories: graph mining, matrix factorization or completion, and deep learning. We selected eleven methods from the three categories to compare their predictive performances. The experiment was conducted using two uniform datasets on the drug and disease sides, separately. We constructed heterogeneous networks using drug-drug similarities based on chemical structures and ATC codes, ontology-based disease-disease similarities, and drug-disease associations. An improved evaluation metric was used to reflect data imbalance as positive associations are typically sparse. The prediction results demonstrated that methods in the graph mining and matrix factorization or completion categories performed well in the overall assessment. Furthermore, prediction on the drug side had higher accuracy than on the disease side. Selecting and integrating informative drug features in drug-drug similarity measurement are crucial for improving disease-side prediction.

Analysis of energy intakes, physical activities and metabolic syndrome according to the income level in Korean elderly people: Korean National Health and Nutrition Examination Survey 2016‒2018.

PURPOSE: To determine the correlations of differences in the income level with the presence of metabolic syndrome (MetS), energy intake, and physical activity across Korean elderly populations. METHODS: We obtained data from 2,139 elderly individuals (aged >65 years) based on the Korea National Health and Nutrition Examination Survey (KNHANES) (2016‒2018). We analyzed the levels of physical activity (PA) and energy intake using the survey data. Moreover, we analyzed the differences in energy intake and PA levels according to the income level and MetS. RESULTS: Compared with the non-MetS group, the MetS group displayed significantly higher levels of waist circumference (p=0.000), triglycerides (p=0.000), systolic blood pressure (p=0.000), diastolic blood pressure (p=0.016), and fasting blood glucose (p=0.000) for both high and low income levels. However, the level of high-density lipoprotein cholesterol was significantly lower in the MetS group than that in the non-MetS group (p=0.000). The level of smoking in non-MetS men was significantly higher than that in MetS men across all participants (p=0.047). Except carbohydrate intake, the total energy intake (p=0.022), fat intake (p=0.009), and protein intake (p=0.005) were significantly lower in the MetS group than those in the non-MetS group for high income levels. We obtained similar results for low income levels. The two-way analysis of variance (ANOVA) did not identify an interaction between the income level and the presence of MetS; however, the total energy, i.e., the level of total energy intake, was significantly lower in participants with low income levels than in those with high income levels. For high income levels, transport PA (p=0.002), vigorous recreational PA (p=0.001), moderate recreational PA (p=0.001), and total PA (p=0.000) were significantly lower in the MetS group than those in the non-MetS group. For low income levels, moderate occupational PA (p=0.012), transport PA (p=0.018), and total PA ((p=0.000) were significantly lower in the MetS group than those in the non-MetS group. The total PA, i.e., the level of energy consumption, was significantly lower in the elderly with low income levels than in those with high income levels. CONCLUSION: Regardless of the income level, the elderly with MetS exhibited low levels of energy intake and PA, compared with those without MetS. In addition, regardless of the presence of MetS, the elderly with low income levels exhibited lesser energy intake and PA. These findings implied the need for balanced nutrient intake and increased participation in PA as well as education and program development to prevent MetS in the elderly.

Network-Based Approaches for Disease-Gene Association Prediction Using Protein-Protein Interaction Networks.

Genome-wide association studies (GWAS) can be used to infer genome intervals that are involved in genetic diseases. However, investigating a large number of putative mutations for GWAS is resource- and time-intensive. Network-based computational approaches are being used for efficient disease-gene association prediction. Network-based methods are based on the underlying assumption that the genes causing the same diseases are located close to each other in a molecular network, such as a protein-protein interaction (PPI) network. In this survey, we provide an overview of network-based disease-gene association prediction methods based on three categories: graph-theoretic algorithms, machine learning algorithms, and an integration of these two. We experimented with six selected methods to compare their prediction performance using a heterogeneous network constructed by combining a genome-wide weighted PPI network, an ontology-based disease network, and disease-gene associations. The experiment was conducted in two different settings according to the presence and absence of known disease-associated genes. The results revealed that HerGePred, an integrative method, outperformed in the presence of known disease-associated genes, whereas PRINCE, which adopted a network propagation algorithm, was the most competitive in the absence of known disease-associated genes. Overall, the results demonstrated that the integrative methods performed better than the methods using graph-theory only, and the methods using a heterogeneous network performed better than those using a homogeneous PPI network only.