Search Results (1,963)

Background: While a few studies suggest that depigmentation tends to develop more frequently in patients with malignant melanoma (MM), the association between vitiligo and MM has been sparsely investigated in the setting of controlled studies. Methods: A population-based case–control study compared 14,632 patients with vitiligo with 71,580 control subjects matched by age, sex, and ethnicity regarding the prevalence of preexisting MM. Logistic regression was used to calculate the odds ratio (OR) and 95% confidence intervals (CIs) of developing vitiligo both in univariate and multivariate models, adjusting for demographic variables and comorbidities. The OR was also stratified by age, sex, ethnicity, and ultraorthodox status. Results: The prevalence of preexisting MM was statistically comparable between individuals with vitiligo and controls (0.30% vs. 0.35%, respectively). In the general study population, a history of MM was not significantly associated with an elevated likelihood of developing vitiligo (multivariate OR, 1.03; CI 95%, 0.76–1.40). Among the Arab population, however, preexisting MM was associated with a sixfold-increased likelihood of subsequent vitiligo (univariate OR, 6.55; 95% CI, 1.46–29.27). Patients with vitiligo and comorbid MM were older at the onset of vitiligo, had a higher burden of comorbid conditions, and showed an overrepresentation of Jewish ancestry. Conclusions: A history of MM does not increase the probability of vitiligo in the general Israeli population, except among the Arab minority, who show a sixfold-elevated odds of vitiligo after MM. Further investigation is essential to gain deeper insights into this relationship. Full article

The Statistics Anxiety Rating Scale (STARS) is a 51-item scale commonly used to measure college students’ anxiety regarding statistics. To date, however, limited empirical research exists that examines statistics anxiety among ethnically diverse or first-generation graduate students. We examined the factor structure and reliability of STARS scores in a diverse sample of students enrolled in graduate courses at a Minority-Serving Institution (n = 194). To provide guidance on assessing dimensionality in small college samples, we compared the performance of best-practice factor analysis techniques: confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), and Bayesian structural equation modeling (BSEM). We found modest support for the original six-factor structure using CFA, but ESEM and BSEM analyses suggested that a four-factor model best captures the dimensions of the STARS instrument within the context of graduate-level statistics courses. To enhance scale efficiency and reduce respondent fatigue, we also tested and found support for a reduced 25-item version of the four-factor STARS scale. The four-factor STARS scale produced constructs representing task and process anxiety, social support avoidance, perceived lack of utility, and mathematical self-efficacy. These findings extend the validity and reliability evidence of the STARS inventory to include diverse graduate student populations. Accordingly, our findings contribute to the advancement of data science education and provide recommendations for measuring statistics anxiety at the graduate level and for assessing construct validity of psychometric instruments in small or hard-to-survey populations. Full article

Background/Objectives: Neuromedin U (NMU) is a highly conserved gene encoding a neuropeptide involved in the regulation of feeding behavior and energy homeostasis. We aimed to analyze the association between NMU genetic and epigenetic variations and cardio-metabolic parameters in an Italian population to identify the role of these variants in cardio-metabolic risk. Methods: A total of 4028 subjects were randomly selected from the Moli-sani study cohort. NMU haplotypes were estimated using seven SNPs located in the gene body and in the promoter region; DNA methylation levels in the promoter region, previously associated with lipid-related variables in the same population, were also used. Results: Among the haplotypes inferred, the haplotype carrying the highest number of minor variants (frequency 16.6%), when compared with the most frequent haplotype, was positively associated with insulin levels, HOMA-IR, and diastolic blood pressure, and negatively with HDL-cholesterol. The multivariable analysis that considered methylation levels along with their interactions with SNPs showed that increased methylation levels in two close CpG sites were associated with higher levels of lipid-related variables. Conclusions: This study supports a role for NMU as a regulator of human metabolism. This finding suggests that NMU could be a potential target for preventive interventions against coronary and cerebrovascular diseases, and that NMU genetic and epigenetic variability may serve as a biomarker for cardio-metabolic risk. Full article

Background: Fixed-dose combinations of rosuvastatin and ezetimibe are increasingly used in clinical practice, but real-world data on their effectiveness and safety in large populations remain limited. Methods: This prospective, single-group, open-label, non-interventional observational study was conducted in the Republic of Korea to evaluate the effectiveness and safety of Rovazet^® (a fixed-dose combination of rosuvastatin and ezetimibe). Patients were prospectively enrolled from 235 institutions (50 general hospitals and 185 private clinics) as part of routine clinical practice over a five-year period. Lipid profiles and medication compliance questionnaire results were collected at baseline, 12 weeks, and 24 weeks of treatment. Results: A total of 5527 patients with dyslipidemia, the majority were men (53.0%), and the mean age was 60.4 years. Rovazet^® significantly reduced low-density lipoprotein cholesterol (LDL-C) by 23.5% at 12 weeks (from 117.47 ± 50.65 mg/dL to 81.14 ± 38.20 mg/dL; p < 0.0001) and by 27.4% at 24 weeks (from 117.47 ± 50.65 mg/dL to 74.52 ± 33.36 mg/dL; p < 0.0001). Total cholesterol was significantly reduced by 17.7% at 12 weeks and by 19.8% at 24 weeks. Rovazet^® treatment reduced triglycerides by 4.1% at 12 weeks and by 7.2% at 24 weeks. High-density lipoprotein cholesterol increased by 4.5% at 12 weeks and by 7.9% at 24 weeks following Rovazet^® treatment. These changes in lipid profiles were consistent, regardless of cardiovascular risk profiles. By 24 weeks of treatment with Rovazet^®, 91.8% of patients had reached their target LDL-C goals. Adverse drug reactions were reported in 2.81% of patients, most of which were minor, indicating that Rovazet^® was well tolerated. Conclusions: Rovazet^® was effective in improving lipid profiles and well tolerated in Korean adults with dyslipidemia. Full article

As Thailand transitions into a super-aged society, falls are a rising public health issue. However, limited research focuses specifically on independent older adults in rural areas. This study examined intrinsic and extrinsic factors associated with falls among independent older adults in a rural district of southern Thailand, contributing to localized fall prevention strategies. A cross-sectional study was conducted using multi-stage probabilistic sampling with 325 older adults aged 60–79 years residing in Nakhon Si Thammarat. Data were collected through structured interviews, and multivariate logistic regression was used to identify fall predictors. A fall was defined as an unintended fall to a lower level within the previous 12 months. The fall prevalence was 29.8%, with the majority resulting in minor injuries. Multivariate analysis revealed protective factors, including sociodemographic factors such as higher monthly income (adjusted OR = 0.47; 95% CI: 0.30–0.74) and agricultural employment (adjusted OR = 0.50; 95% CI: 0.27–0.95), as well as the extrinsic factor of pet ownership (adjusted OR = 0.53; 95% CI: 0.35–0.81), were significantly associated with reduced fall risk. The study highlights context-specific protective factors that could inform community-based interventions. Future research should assess causality and intervention effectiveness in broader populations. Full article

Though previous studies have demonstrated the protective benefits of sports participation against illicit drug use for a general population, how these findings apply to LGBTQ youth remains unknown. This study specifically looks at the relationship between sports participation and prescription drug misuse among sexual and gender minority youth. Using secondary data from the 2019 YRBS, we analyze associations among sports participation, sexual orientation, gender identity, and prescription drug misuse among a representative sample of U.S. high school students in Florida. Our results show that sexual and gender minority youth are at increased risk for prescription drug misuse compared to their heterosexual and cisgender peers. Moreover, sports participation is associated with higher rates of prescription drug misuse among all students, and the nuances of these trends are discussed with particular attention paid to sexual and gender minority youth. These results challenge conventional wisdom about sports participation. Without the addition of new demographic survey questions and LGBTQ youth participation in the YRBS, common myths about sports might have persisted. Our findings point to the meaningful presence of LGBTQ youth in sports, call for research and programming on LGBTQ athletes’ unique needs regarding substance misuse risk, and encourage LGBTQ-inclusive policies and practices within schools and sports programs in particular. Full article

Background/Objective: Dry eye syndrome affects 16 million Americans with USD 52 billion in annual healthcare costs. With large language models (LLMs) increasingly used for healthcare information, understanding their performance in delivering equitable dry eye guidance across diverse populations is critical. This study aims to evaluate and compare five major LLMs (Grok, ChatGPT, Gemini, Claude.ai, and Meta AI) regarding dry eye syndrome information delivery across different demographic groups. Methods: LLMs were queried using standardized prompts simulating a 62-year-old patient with dry eye symptoms across four demographic categories (White, Black, East Asian, and Hispanic males and females). Responses were analyzed for word count, readability, cultural sensitivity scores (0–3 scale), keyword coverage, and response times. Results: Significant variations existed across LLMs. Word counts ranged from 32 to 346 words, with Gemini being the most comprehensive (653.8 ± 96.2 words) and Claude.ai being the most concise (207.6 ± 10.8 words). Cultural sensitivity scores revealed Grok demonstrated highest awareness for minority populations (scoring 3 for Black and Hispanic demographics), while Meta AI showed minimal cultural tailoring (0.5 ± 0.5). All models recommended specialist consultation, but medical term coverage varied significantly. Response times ranged from 7.41 s (Meta AI) to 25.32 s (Gemini). Conclusions: While all LLMs provided appropriate referral recommendations, substantial disparities exist in cultural sensitivity, content depth, and information delivery across demographic groups. No LLM consistently addressed the full spectrum of dry eye causes across all demographics. These findings underscore the importance for physician oversight and standardization in AI-generated healthcare information to ensure equitable access and prevent care delays. Full article

Background: Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder with significant racial and ethnic disparities in prevalence, disease severity, and outcomes. Cardiovascular complications, including pericarditis, myocarditis, valvular disease, and conduction abnormalities, contribute to increased morbidity and mortality in SLE patients. This study examines racial and ethnic disparities in cardiovascular outcomes among hospitalized SLE patients in the United States. Methods: This retrospective study utilized the National Inpatient Sample (NIS) database from 2016 to 2021 to analyze hospitalizations of adult patients (≥18 years) with a primary or secondary diagnosis of SLE. Patients were stratified into racial/ethnic groups: White, Black, Hispanic, Asian, Native American, and Other. Primary outcomes include major adverse cardiovascular events (MACEs), which are a composite of in-hospital mortality, myocardial infarction (MI), sudden cardiac death, and other SLE-related outcomes including cardiac, pulmonary, and renal involvement. Statistical analyses included multivariable logistic regression models adjusted for demographic, socioeconomic, and hospital-related factors to assess racial disparities. Results: The study included 514,750 White, 321,395 Black, and 146,600 Hispanic patients, with smaller proportions of Asian, Native American, and Other racial groups. Black patients had significantly higher odds of in-hospital mortality (OR = 1.17, 95% CI = 1.08–1.26, p < 0.001) and sudden cardiac death (OR = 1.64, 95% CI = 1.46–1.85, p < 0.001) compared to White patients. Asian patients also exhibited increased mortality risk (OR = 1.37, 95% CI = 1.14–1.63, p = 0.001) as compared to Whites. Conversely, Black (OR = 0.90, 95% CI = 0.85–0.96, p = 0.01) and Hispanic (OR = 0.87, 95% CI = 0.80–0.96, p = 0.03) patients had lower odds of MI. Racial disparities in access to care, socioeconomic status, and comorbidity burden may contribute to these differences. Conclusion: Significant racial and ethnic disparities exist in cardiovascular outcomes among hospitalized SLE patients. Black and Asian individuals face higher in-hospital all-causes mortality and sudden cardiac death risks, while Black and Hispanic patients exhibit lower MI rates. Addressing social determinants of health, improving access to specialized care, and implementing targeted interventions may reduce disparities and improve outcomes in minority populations with SLE. Full article

Solid biomass (agro-residue) is the most important source of renewable energy. The accelerating impacts of climate change and global population growth contribute to air pollution through the use of fossil fuels. These processes increase the demand for energy. The European Union has adopted a climate action plan to address the above challenges. The main aim of this study was to assess the economic performance of the producers of biomass for energy generation in Poland. The detailed objectives were to determine land resources in the studied agricultural farms and to determine the value of fixed and current assets in the analyzed farms. We used questionnaires as the main method to collect data. Purposive sampling was used to choose the farms. We conducted various tests to analyze the revenues from biomass sales and their normality, such as the Dornik–Hansen test, the Shapiro–Wilk test, the Liliefors test, and the Jargue–Berra statistical test. Moreover, we conducted regression analysis to find factors that are the basis for the economic performance (incomes) of farms that sell biomass. Results: This study demonstrated that biomass sales had a minor impact on the performance of agricultural farms, but they enabled farmers to maintain their position on the market. The economic analysis was carried out on a representative group of Polish agricultural farms, taking into account fixed and current assets, land use, production structure, and employment. The findings indicate that a higher income from biomass sales was generally associated with better economic results per farm and per employee, although not always per hectare of land. This suggests that capital intensity and strategic resource management play a crucial role in the profitability of bioenergy-oriented agricultural production. Conclusions: We concluded that biomass sales had a negligible influence on farm income. But a small income from biomass sales could affect a farm’s economic viability. Full article

Several single-nucleotide polymorphisms (SNPs) across the lipoprotein lipase (LPL) gene have been found to be associated with dyslipidemia and obesity. Several InDels and SNPs in exon 1, intron 2, and intron 7 have been reported; however, their association with lipid parameters and body mass index (BMI) remains unclear. Here, we aimed to investigate the relationship among LPL variants, lipid levels, and BMI in a Kuwaiti population. Sanger sequencing was performed on three targeted regions of the LPL gene. Based on the minor allele frequency, Hardy–Weinberg equilibrium, and linkage disequilibrium, five SNPs were selected and genotyped in a cohort of 688 Kuwaiti samples to investigate their association with lipid levels and BMI. A total of 30 variants (6 InDels and 24 SNPs) were identified; of them, 5 SNPs (rs1800590, rs74377536, rs8176337, rs303, and rs304) were selected for their association with BMI and lipid levels. The G-allele of rs8176337 was found to be associated with increased BMI (β = 1.41; 95% confidence interval = 0.22–2.60; p = 0.02). In addition, an association was observed for rs303 and rs304 with both cholesterol and LDL (p < 0.05). Overall, our results demonstrate an association between LPL variants and lipid levels, and the observed association between rs8176337 and BMI was novel. Full article

Ride-pooling, as a sustainable mode of ride-hailing services, enables different riders to share a vehicle while traveling along similar routes. The COVID-19 pandemic led to the suspension of this service, but Transportation Network Companies (TNCs) such as Uber and Lyft resumed it after a significant delay following the lockdown. This raises the question of what determinants shape ride-pooling in the post-pandemic era and how they spatially influence shared ride-hailing compared to the pre-pandemic period. To address this gap, this study employs geospatial analysis and machine learning to examine the factors affecting ride-pooling trips in pre- and post-pandemic periods. Using over 66 million trip records from 2019 and 43 million from 2023, we observe a significant decline in shared trip adoption, from 16% to 2.91%. The results of an extreme gradient boosting (XGBoost) model indicate a robust capture of non-linear relationships. The SHAP analysis reveals that the percentage of the non-white population is the dominant predictor in both years, although its influence weakened post-pandemic, with a breakpoint shift from 78% to 90%, suggesting reduced sharing in mid-range minority areas. Crime density and lower car ownership consistently correlate with higher sharing rates, while dense, transit-rich areas exhibit diminished reliance on shared trips. Our findings underscore the critical need to enhance transportation integration in underserved communities. Concurrently, they highlight the importance of encouraging shared ride adoption in well-served, high-demand areas where solo ride-hailing is prevalent. We believe these results can directly inform policies that foster more equitable, cost-effective, and sustainable shared mobility systems in the post-pandemic landscape. Full article

Despite targeting mainly the respiratory tract, SARS-CoV-2 disrupts T cell homeostasis in ways that may explain both acute lethality and long-term immunological consequences. In this study, we aimed to evaluate the T-cell-mediated chain of immunity and formation of TCR via TREC assessment in COVID-19 and long COVID (LC). For this study, we collected 231 blood samples taken from patients with acute COVID-19 (n = 71), convalescents (n = 51), people diagnosed with LC (n = 63), and healthy volunteers (n = 46). With flow cytometry, we assessed levels of CD4+ and CD8+ minor T cell subpopulations (i.e., naïve, central and effector memory cells (CM and EM), Th1, Th2, Th17, Tfh, Tc1, Tc2, Tc17, Tc17.1, and subpopulations of effector cells (pE1, pE2, effector cells)). Additionally, we measured TREC levels. We found distinct changes in immune cell distribution—whilst distribution of major subpopulations of T cells was similar between cohorts, we noted that COVID-19 was associated with a decrease in naïve Th and CTLs, an increase in Th2/Tc2 lymphocyte polarization, an increase in CM cells, and a decrease in effector memory cells 1,3, and TEMRA cells. LC was associated with naïve CTL increase, polarization towards Th2 population, and a decrease in Tc1, Tc2, Em2, 3, 4 cells. We also noted TREC correlating with naïve cells subpopulations. Our findings suggest ongoing immune dysregulation, possibly driven by persistent antigen exposure or tissue migration of effector cells. The positive correlation between TREC levels and naïve T cells in LC patients points to residual thymic activity. The observed Th2/Th17 bias supports the hypothesis that LC involves autoimmune mechanisms, potentially driven by molecular mimicry or loss of immune tolerance. Full article

Asia minor bluegrass (Polypogon fugax), a widespread Poaceae weed, exhibits broad tolerance to abiotic stresses. Validated reference genes (RGs) for reliable RT-qPCR normalization in this ecologically and agriculturally significant species remain unidentified. This study identified eight candidate RGs using transcriptome data from seedling tissues. We assessed the expression stability of these eight RGs across various abiotic stresses and developmental stages using Delta Ct, BestKeeper, geNorm, and NormFinder algorithms. A comprehensive stability ranking was generated using RefFinder, with validation performed using the target genes COR413 and P5CS. Results identified EIF4A and TUB as the optimal RG combination for normalizing gene expression during heat stress, cold stress, and growth stages. EIF4A and ACT were most stable under drought stress, EIF4A and 28S under salt stress, and EIF4A and EF-1 under cadmium (Cd) stress. Furthermore, EIF4A and UBQ demonstrated optimal stability under herbicide stress. Additionally, application of validated RGs revealed higher acetyl-CoA carboxylase gene (ACCase) expression in one herbicide-resistant population, suggesting target-site gene overexpression contributes to resistance. This work presents the first systematic evaluation of RGs in P. fugax. The identified stable RGs provide essential tools for future gene expression studies on growth and abiotic stress responses in this species, facilitating deeper insights into the molecular basis of its weediness and adaptability. Full article

This study investigates the critical link between child care accessibility and local labor force participation, addressing a gap in current research that often lacks local spatial granularity. While over half of the U.S. population resides in child care deserts, disproportionately affecting rural, low-income, and minority communities, the economic implications for local labor markets remain underexplored. Leveraging Michigan child care license data and Census tract-level demographic and employment characteristics, this research employs a spatial econometric approach to estimate the impact of geographic distance to child care facilities on labor supply using descriptive data. Our findings consistently demonstrate that increased distance to child care is significantly associated with reduced labor force participation. While female labor force participation is lower in areas with constrained access to child care, we also found that households with two parents are also less likely to have full labor force participation when access to child care is constrained. The cost-effective framework used here can be replicated to identify specific communities most impacted by child care-related employment disruptions. The analytical findings can be instrumental in targeting and prioritizing child care policy interventions. Full article

Metabolome studies have already been carried out in patients with systemic sclerosis (SSc). However, polyneuropathy (PNP) as a complication of SSc has been overlooked in these studies. To the best of our knowledge, this is the first study to examine metabolic changes in SSc patients with PNP. Patients with SSc (n = 62) and a healthy control group (HC) (n = 72) were recruited from two Latvian hospitals. Blood plasma samples were collected and analyzed using an LC-MS-based targeted metabolomics workflow. Our plasma sample cohort consisted of 62 patients with SSc, 42% of whom had PNP. Differences between SSc patients and the HC group with fold changes > 2 were observed for aspartic acid, glutamic acid, valine, and citrulline, all of which were reduced. In contrast to the SSc to HC discrimination, no metabolites had a high fold change; only minor changes were observed using FC > 1.3. We identified elevated concentrations of kynurenine, asparagine, and alanine. Changes in metabolite regulation in patients with SSc, compared to controls, are not identical to those observed in SSc patients with PNP, with elevated concentrations of kynurenine and alanine specific to the SSc subgroup. SSc patients with PNP should probably be considered a distinct population with important metabolomic features. Full article