An empirical study on social network analysis for small residential communities in Gangwon State, South Korea.

Social Network Analysis (SNA) provides a dynamic framework for examining interactions and connections within networks, elucidating how these relationships impact behaviors and outcomes. This study targeted small residential communities in Gangwon State, South Korea, to explore network formation theories and derive strategies for enhancing health promotion services in rural communities. Conducted in 12 small residential areas, the survey led to a network categorization model distinguishing networks as formal, informal, or non-existent. Key findings demonstrated that demographic and socio-economic factors, specifically age, income, living environment, leisure activities, and education level, significantly influence network formation. Importantly, age, environmental conditions, satisfaction with public transportation, and walking frequency were closely associated with the evolution of formal networks. These results highlight the importance of early community network assessments, which must consider distinct network traits to develop effective health promotion models. Utilizing SNA early in the assessment process can improve understanding of network dynamics and optimize the effectiveness of health interventions.

Cross-Cultural Adult ADHD Assessment in 42 Countries Using the Adult ADHD Self-Report Scale Screener.

OBJECTIVE: We analyzed adult ADHD symptoms in a cross-cultural context, including investigating the occurrence and potential correlates of adult ADHD and psychometric examination of the Adult ADHD Self-Report Scale (ASRS) Screener. METHOD: Our analysis is based on a large-scale research project involving 42 countries (International Sex Survey, N=72,627, 57% women, Mage=32.84; SDage=12.57). RESULTS: The ASRS Screener demonstrated good reliability and validity, along with partial invariance across different languages, countries, and genders. The occurrence of being at risk for adult ADHD was relatively high (21.4% for women, 18.1% for men). The highest scores were obtained in the US, Canada, and other English-speaking Western countries, with significantly lower scores among East Asian and non-English-speaking European countries. Moreover, ADHD symptom severity and occurrence were especially high among gender-diverse individuals. Significant associations between adult ADHD symptoms and age, mental and sexual health, and socioeconomic status were observed. CONCLUSIONS: Present results show significant cross-cultural variability in adult ADHD occurrence as well as highlight important factors related to adult ADHD. Moreover, the importance of further research on adult ADHD in previously understudied populations (non-Western countries) and minority groups (gender-diverse individuals) is stressed. Lastly, the present analysis is consistent with previous evidence showing low specificity of adult ADHD screening instruments and contributes to the current discussion on accurate adult ADHD screening and diagnosis.

Assessment of Equine Influenza Virus Status in the Republic of Korea from 2020 to 2022.

Equine influenza virus (EIV) causes acute respiratory disease in horses and belongs to the influenza A virus family Orthomyxoviridae, genus Orthomyxovirus. This virus may have severe financial implications for the horse industry owing to its highly contagious nature and rapid transmission. In the Republic of Korea, vaccination against EIV has been practiced with the active involvement of the Korea Racing Authority since 1974. In this study, we monitored the viral RNA for EIV using PCR, as well as the antibody levels against 'A/equine/South Africa/4/03 (H3N8, clade 1)', from 2020 to 2022. EIV was not detected using RT-PCR. The seropositivity rates detected using a hemagglutination inhibition assay were 90.3% in 2020, 96.7% in 2021, and 91.8% in 2022. The geometric mean of antibody titer (GMT) was 83.4 in 2020, 135.7 in 2021, and 95.6 in 2022. Yearlings and two-year-olds in training exhibited lower positive rates (59.1% in 2020, 38.9% in 2021, and 44.1% in 2022) than the average. These younger horses may require more attention for vaccination and vaccine responses against EIV. Continuous surveillance of EIV should be performed to monitor the prevalence and spread of this disease.

Compulsive sexual behavior disorder in 42 countries: Insights from the International Sex Survey and introduction of standardized assessment tools.

Background and aims: Despite its inclusion in the 11th revision of the International Classification of Diseases, there is a virtual paucity of high-quality scientific evidence about compulsive sexual behavior disorder (CSBD), especially in underrepresented and underserved populations. Therefore, we comprehensively examined CSBD across 42 countries, genders, and sexual orientations, and validated the original (CSBD-19) and short (CSBD-7) versions of the Compulsive Sexual Behavior Disorder Scale to provide standardized, state-of-the-art screening tools for research and clinical practice. Method: Using data from the International Sex Survey (N = 82,243; Mage = 32.39 years, SD = 12.52), we evaluated the psychometric properties of the CSBD-19 and CSBD-7 and compared CSBD across 42 countries, three genders, eight sexual orientations, and individuals with low vs. high risk of experiencing CSBD. Results: A total of 4.8% of the participants were at high risk of experiencing CSBD. Country- and gender-based differences were observed, while no sexual-orientation-based differences were present in CSBD levels. Only 14% of individuals with CSBD have ever sought treatment for this disorder, with an additional 33% not having sought treatment because of various reasons. Both versions of the scale demonstrated excellent validity and reliability. Discussion and conclusions: This study contributes to a better understanding of CSBD in underrepresented and underserved populations and facilitates its identification in diverse populations by providing freely accessible ICD-11-based screening tools in 26 languages. The findings may also serve as a crucial building block to stimulate research into evidence-based, culturally sensitive prevention and intervention strategies for CSBD that are currently missing from the literature.

STK3/STK4 signalling in adipocytes regulates mitophagy and energy expenditure.

Obesity reduces adipocyte mitochondrial function, and expanding adipocyte oxidative capacity is an emerging strategy to improve systemic metabolism. Here, we report that serine/threonine-protein kinase 3 (STK3) and STK4 are key physiological suppressors of mitochondrial capacity in brown, beige and white adipose tissues. Levels of STK3 and STK4, kinases in the Hippo signalling pathway, are greater in white than brown adipose tissues, and levels in brown adipose tissue are suppressed by cold exposure and greatly elevated by surgical denervation. Genetic inactivation of Stk3 and Stk4 increases mitochondrial mass and function, stabilizes uncoupling protein 1 in beige adipose tissue and confers resistance to metabolic dysfunction induced by high-fat diet feeding. Mechanistically, STK3 and STK4 increase adipocyte mitophagy in part by regulating the phosphorylation and dimerization status of the mitophagy receptor BNIP3. STK3 and STK4 expression levels are elevated in human obesity, and pharmacological inhibition improves metabolic profiles in a mouse model of obesity, suggesting STK3 and STK4 as potential targets for treating obesity-related diseases.

A Comprehensive In Vivo and In Vitro Assessment of the Drug Interaction Potential of Red Ginseng.

Purpose: Red ginseng is one of the world's most popular herbal medicines; it exhibits a wide range of pharmacologic activities and is often co-ingested with other herbal and conventional medicines. This open-label, randomized, 3-period study investigated the in vivo herb-drug interaction potential for red ginseng extract with cytochrome P-450 (CYP) enzymes and organic anion-transporting polypeptide (OATP) 1B1. METHODS: Fifteen healthy male volunteers (22-28 years; 57.1-80.8 kg) were administered a single dose of cocktail probe substrates (caffeine 100 mg, losartan 50 mg, omeprazole 20 mg, dextromethorphan 30 mg, midazolam 2 mg, and pitavastatin 2 mg) and single or multiple doses of red ginseng extract for 15 days. FINDINGS: The pharmacokinetic profiles of the probe substrates and metabolites after single- or multiple-dose administration of red ginseng extracts were comparable to the corresponding profiles of the control group. The geometric mean ratio of AUC0-t and 90% CIs for the probe substrate drugs between the control and multiple doses of red ginseng for 15 days were within 0.8 to 1.25 (CYP2C9, CYP3A4, and OATP1B1 probe substrates) or slightly higher (CYP1A2, CYP2C19, and CYP2D6 probe substrates). Additional assessments of the in vitro drug interaction potential of red ginseng extracts and the ginsenoside Rb1 on drug-metabolizing enzymes and transporters using human liver microsomes, cryopreserved human hepatocytes, and transporter-overexpressed cells were negative. IMPLICATIONS: Red ginseng poses minimal risks for clinically relevant CYP- or OATP-mediated drug interactions and is well tolerated. Clinical Research Information Service registry no.

Bayesian network ensemble as a multivariate strategy to predict radiation pneumonitis risk.

PURPOSE: Prediction of radiation pneumonitis (RP) has been shown to be challenging due to the involvement of a variety of factors including dose-volume metrics and radiosensitivity biomarkers. Some of these factors are highly correlated and might affect prediction results when combined. Bayesian network (BN) provides a probabilistic framework to represent variable dependencies in a directed acyclic graph. The aim of this study is to integrate the BN framework and a systems' biology approach to detect possible interactions among RP risk factors and exploit these relationships to enhance both the understanding and prediction of RP. METHODS: The authors studied 54 nonsmall-cell lung cancer patients who received curative 3D-conformal radiotherapy. Nineteen RP events were observed (common toxicity criteria for adverse events grade 2 or higher). Serum concentration of the following four candidate biomarkers were measured at baseline and midtreatment: alpha-2-macroglobulin, angiotensin converting enzyme (ACE), transforming growth factor, interleukin-6. Dose-volumetric and clinical parameters were also included as covariates. Feature selection was performed using a Markov blanket approach based on the Koller-Sahami filter. The Markov chain Monte Carlo technique estimated the posterior distribution of BN graphs built from the observed data of the selected variables and causality constraints. RP probability was estimated using a limited number of high posterior graphs (ensemble) and was averaged for the final RP estimate using Bayes' rule. A resampling method based on bootstrapping was applied to model training and validation in order to control under- and overfit pitfalls. RESULTS: RP prediction power of the BN ensemble approach reached its optimum at a size of 200. The optimized performance of the BN model recorded an area under the receiver operating characteristic curve (AUC) of 0.83, which was significantly higher than multivariate logistic regression (0.77), mean heart dose (0.69), and a pre-to-midtreatment change in ACE (0.66). When RP prediction was made only with pretreatment information, the AUC ranged from 0.76 to 0.81 depending on the ensemble size. Bootstrap validation of graph features in the ensemble quantified confidence of association between variables in the graphs where ten interactions were statistically significant. CONCLUSIONS: The presented BN methodology provides the flexibility to model hierarchical interactions between RP covariates, which is applied to probabilistic inference on RP. The authors' preliminary results demonstrate that such framework combined with an ensemble method can possibly improve prediction of RP under real-life clinical circumstances such as missing data or treatment plan adaptation.

Analytical modelling of regional radiotherapy dose response of lung.

Knowledge of the dose-response of radiation-induced lung disease (RILD) is necessary for optimization of radiotherapy (RT) treatment plans involving thoracic cavity irradiation. This study models the time-dependent relationship between local radiation dose and post-treatment lung tissue damage measured by computed tomography (CT) imaging. Fifty-eight follow-up diagnostic CT scans from 21 non-small-cell lung cancer patients were examined. The extent of RILD was segmented on the follow-up CT images based on the increase of physical density relative to the pre-treatment CT image. The segmented RILD was locally correlated with dose distribution calculated by analytical anisotropic algorithm and the Monte Carlo method to generate the corresponding dose-response curves. The Lyman-Kutcher-Burman (LKB) model was fit to the dose-response curves at six post-RT time periods, and temporal change in the LKB parameters was recorded. In this study, we observed significant correlation between the probability of lung tissue damage and the local dose for 96% of the follow-up studies. Dose-injury correlation at the first three months after RT was significantly different from later follow-up periods in terms of steepness and threshold dose as estimated from the LKB model. Dependence of dose response on superior-inferior tumour position was also observed. The time-dependent analytical modelling of RILD might provide better understanding of the long-term behaviour of the disease and could potentially be applied to improve inverse treatment planning optimization.