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Single-cell analysis indicating CCR8 modulates CD8+ tissue-resident memory T cells to attenuates rejection in transplantation

Associations between serum pigment epithelium-derived factor and physical performance in older women: The Otassha study

Pigment epithelium-derived factor (PEDF) contributes to the beneficial effects of exercise by suppressing cellular senescence in multiple organs. Its expression declines in the skeletal muscle of aged animals, suggesting a role in age-related frailty. To investigate the association between circulating PEDF and physical performance, we analyzed its associations with skeletal muscle mass and mobility in a cohort of older women. A cross-sectional analysis was conducted in 143 community-dwelling females (mean age 77.01 ± 4.16 years). Serum PEDF and body composition were measured, and physical performance was assessed via gait speed, handgrip strength, leg extension strength, and the Five Times Sit-to-Stand test. Serum PEDF levels positively correlated with skeletal muscle mass index (SMI) and gait speed, while no significant correlation was observed between serum PEDF levels and other physical function parameters. These findings suggest that circulating PEDF is associated with skeletal muscle mass and mobility in older adults, warranting further investigation into its potential role as a myokine in humans.

Interannual variability of net primary productivity in the northwest African coastal upwelling system and their relation to Dakar Niños

Abstract The Canary Current upwelling system, located along the northwest African coast between approximately 10ºN and 35ºN, is among the most productive marine ecosystems globally, supporting a rich marine biodiversity. In the southern part (9ºN–18ºN), pronounced interannual variability in net primary production (NPP) is influenced by extreme warm and cold events, known as Dakar Niños and Niñas, respectively. In this study, we analyze the physical mechanisms driving the interannual variability of NPP from 2003 to 2023, using a combination of satellite observations, reanalysis data, and ocean model outputs. Our results indicate that the interannual NPP variability is closely linked to changes in sea surface temperature, with the most pronounced effects occurring during March-April-May, i.e., the main upwelling season. A total of six undocumented extreme coastal low NPP events are identified, nearly all of which are associated with Dakar Niños. These low NPP events are linked to both local and remote forcing. The local forcing is associated with fluctuations of alongshore winds and near-coastal wind stress curl. The remote forcing involves the propagations of coastal trapped waves emanating from the equator and the northern Gulf of Guinea. Part of the local and remote forcing can be associated with large-scale climate modes.

Diagnostic performance of four AI tools in pharmacology MCQs: Accuracy, sensitivity, and specificity

Background The rapid rise of AI in medical and pharmaceutical education has engendered much interest; however, a knowledge gap still exists in the evaluation of performances of these tools in critical academic contexts. Objectives The aim of this study was to assess and compare the performances of four openly accessible AI language tools, Microsoft Copilot, ChatGPT-3.5, Google Gemini, and DeepSeek AI, in responding to pharmacology-related MCQs with regard to diagnostic accuracy, sensitivity, specificity, and reproducibility. Methods A total of 80 MCQs were generated and validated, representing four therapeutic systems: cardiovascular, respiratory, gastrointestinal, and endocrine, including four pharmacological domains: mechanism of action, side effects, pharmacokinetics, and drug-drug interactions. Answers were classified into true/false positives and negatives in order to calculate accuracy, sensitivity, and specificity. After two weeks, a second round of testing was performed with the questions to assess answer reproducibility. Results The top overall performer was Microsoft Copilot: 87.5% accuracy, a sensitivity of 94.6%, and a specificity of 70.8%. It continued to perform strongly across all therapeutic systems, especially in the cardiovascular and respiratory domains, with the highest accuracy in identifying drug mechanisms and side effects. ChatGPT-3.5 performed similarly to Google Gemini (76.3% and 75.0% accuracy, respectively) but with higher sensitivity for ChatGPT-3.5 and higher specificity for Gemini. DeepSeek AI had the lowest accuracy overall (68.8%) and the lowest specificity (29.2%), but the highest consistency of reproducibility (97.5%). The performance of all tools decreased significantly with increasing level of question difficulty (p < 0.05). Conclusion All tools have some value in pharmacology education, but Microsoft Copilot was the most consistently accurate. Limitations in complexity and reproducibility suggest that caution should be exercised in academic and clinical use, particularly given the variability seen with ChatGPT-3.5.

From prediction to sustainability: AI for smart energy management in wastewater treatment plants

Effect of obesity and exercise training on circulating lipids in American Indian adolescents

Childhood dyslipidemia is predictive of future cardiometabolic disease. We determined the impact of obesity (Ob) and an exercise program on lipids in American Indian adolescents. This is a secondary analysis from a previously reported trial designed to determine the impact of financial incentives on exercise behavior in American Indian adolescents who were tested in Southeast Oklahoma between June 2013 and January 2017. We performed a cross-sectional comparison of fasting lipids in participants with Ob (n = 74) and a group with normal weight (NW, N = 39) at baseline prior to the exercise intervention. Measurements were repeated for the Ob group after they completed a 16-week exercise program (n = 53). Compared to the NW group, the Ob group at baseline had higher triglycerides (median [interquartile range]: 1.02 [0.67, 1.73] vs. 0.55 [0.40, 0.74] mmol/L), oxidized high density lipoprotein (HDL) (393 [311, 511] vs. 316 [281, 360] ng/mL), oxidized low density lipoprotein (LDL) (49.3 [38.0, 58.6] vs. 38.8 [29.8, 43.4] U/L), and 4 out of 11 targeted fatty acids measured, while HDL-C (mean ± SD: 0.61 ± 0.18 vs. 0.89 ± 0.20 mmol/L) was lower, all p < 0.001. Fatty acid ratios suggested that hepatic lipid metabolism was altered in the Ob group, with higher stearoyl desaturase, and lower elongase and delta-6 desaturase activities. Aerobic fitness increased 10% in the Ob group but among the lipids measured, only elaidic and myristic acid declined in response to exercise. This study is among the first to report that several plasma lipids were altered in American Indian adolescents with Ob and only minor changes occurred following an exercise program. These findings should be interpreted as exploratory and hypothesis-generating, given the study’s observational and secondary analysis design, but highlight the elevated cardiometabolic disease risk in this understudied population and the need for effective prevention and intervention strategies.

Compressive strength and maturity of UHPC cubes and cylinders: new conversion factors and recommendations for early-age quality control

PERMA-guided multi-topology graph neural networks for cross-cultural student well-being prediction

Student well-being prediction is of great significance for promoting personalized education and preventing mental health problems, but existing methods suffer from limitations including lack of psychological theory guidance, neglect of student relationship modeling, and insufficient cross-cultural adaptability. This study proposes the PERMA-GNN-Transformer model, which innovatively integrates Seligman’s PERMA positive psychology theory with graph neural networks and Transformer architecture. The model achieves the transformation from raw educational data to psychologically meaningful representations through a theory-driven feature embedding mechanism, designs four types of student relationship graphs based on cosine similarity, Euclidean distance, learning styles, and PERMA weighting, and employs a five-head attention mechanism corresponding to the five PERMA dimensions. Experiments on the Western cultural background Lifestyle and Wellbeing Data (n = 12,757) and the East Asian cultural background International Student Mental Health Dataset (n = 268) demonstrate that compared to the optimal baseline methods, our proposed model achieves an 18.9% performance improvement on large-scale datasets and a 27.8% improvement on small-scale datasets, with the PERMA comprehensive evaluation metric reaching 0.792 and passing statistical significance tests at p < 0.01. This research provides a theory-driven, relationship-aware, and culturally adaptive technical solution for student well-being prediction in cross-cultural educational environments.

Evaluation of Lens culinaris germplasm against ascochyta blight by applying phenotyping and defense genes attributes

Prevalence and factors associated with hyperglycemia among children living with HIV on dolutegravir in Kabale district, southwestern Uganda

Background Undiagnosed and poorly managed high blood sugar levels can result in short- and long-term complications in children. Following worldwide introduction of dolutegravir based antiretroviral treatment in 2018, several studies in adult people living with HIV have reported high prevalence of hyperglycemia. Little is known about hyperglycemia in children living with HIV on dolutegravir treatment combinations in Uganda. Objectives To determine the prevalence and factors associated with hyperglycemia in children living with HIV on dolutegravir in Kabale district, southwestern Uganda. Methods In a cross-sectional study, 271 HIV infected children on dolutegravir (DTG) were recruited using proportional to size and simple random sampling methods from 18 health facilities that provide Anti-retroviral therapy (ART) services in Kabale district. HIV infected children aged below 18 years were considered eligible to participate in the study. Data was collected using structured questionnaires. Blood samples were taken for random blood sugar and HbA1C. Data was analyzed using STATA 17.0 for both descriptive and inferential statistics. Logistic regression analysis was done, crude and adjusted odds ratios obtained. Results The prevalence of hyperglycemia was 20.3% (95% CI; 15.9–25.5): Of the children with hyperglycemia, 76% (42/55) had prediabetes and 24% (13/55) had diabetes mellitus. Red meat consumption (AOR:3.52; 95% CI: 1.4–9.0, p = 0.009) and being above 13 years of age (AOR:2.61; 95% CI 1.4–4.87, p = 0.003) were independently associated with hyperglycemia. Conclusion One in every five children with HIV on DTG had hyperglycemia. Among those with hyperglycemia, 24% had diabetes mellitus. Hyperglycemia was more likely to be present in adolescents and those who consumed red meat. Regular monitoring of blood sugar in children living with HIV on DTG is recommended.

Integration of fast charging EV infrastructure with high gain Z-source converters and hybrid optimized MPPT algorithm

Correction: From fishing village to atomic town and present: A grounded theory study

Hybrid local-global representation learning with stochastic Gaussian classification for underwater acoustic target recognition

Vehicle driving area detection and sensor data preprocessing based on deep learning

With the rapid development of intelligent vehicles, it has become particularly important to effectively detect the environment of the vehicle’s driving area. A vehicle driving road recognition algorithm on the basis of an improved bilateral segmentation network is built to address the poor real-time performance and low accuracy in current intelligent vehicle driving area detection methods. Combined with the algorithm, a vehicle driving area detection model based on bilateral segmentation network and data dimensionality reduction is designed. The performance comparison analysis between the recognition algorithm and other algorithms showed that the average frame processed per second and the average recognition time were 68.78FPS and 4.45ms, outperforming the comparison algorithms. The average precision and accuracy were 98.97% and 97.66%, both higher than the comparison models. Finally, the application effect analysis showed that it had good detection performance. The proposed recognition algorithm and detection model have effectiveness and practical value, which can help improve the real-time and accuracy of intelligent vehicle driving area detection, and provide theoretical basis for related research.

Correction: The harmful effects of acute PM2.5 exposure to the heart and a novel preventive and therapeutic function of CEOs

Spatiotemporal variation characteristics and influencing factors of snow density in the High Mountain Asia from 1960 to 2023

Under the context of climate change, significant variations in snow density have been observed in the High Mountain Asia, however, its spatiotemporal patterns and underlying drivers remain incompletely understood. By integrating ERA5 and ERA5-Land reanalysis datasets with large-scale atmospheric circulation data, combined with advanced statistical methods, this study systematically analyzes the spatiotemporal patterns and driving factors of snow density across multiple scales in the High Mountain Asia. The results indicate that: The snow density exhibited a significant decreasing trend at a rate of −0.4 kg/m 3 ·per decade (p < 0.01) from 1960 to 2023. Spatially, snow density consistently demonstrated a “high in mountains, low in plateaus” distribution pattern, which is closely associated with snow depth and snow accumulation. Significant decreases in snow density were concentrated in areas with relatively low snow accumulation, such as the southwestern (S 2 ) and southeastern (S 3 ) Tibetan Plateau, where snowpack exhibits higher sensitivity to temperature variations. Snow depth and air temperature serves as key geographical factor influencing snow density, the latter primarily affects snow density by modulating the proportion of snowfall in total precipitation and altering snow phenology. The East Atlantic/Western Russia (EA/WR) teleconnection pattern indirectly influences snow density through its control on temperature. A weakened EA/WR pattern facilitates increased advection of warm air from the southeast into the Asian High Mountain region, thereby elevating summer temperatures and contributing to reduced snow density.

Cedrol mitigates hepatic lipid accumulation and adipocyte hypertrophy induced by corticosteroids through the inhibition of glucocorticoid receptor activity

Treating a friend to voter registration in a Divided America

As partisanship strengthens in the United States, unaffiliated voter registration is also increasing. We conducted an original survey experiment to understand voter registration choices among registered voters in Florida and North Carolina, two states with substantial shares of unaffiliated registrants and persistent partisan polarization, but with differing primary participation rules. Institutionally, Florida holds closed primaries where only those registered with a political party may participate in the respective primary for that party. North Carolina holds semi-closed primaries that allow those not registered with a political party (i.e., unaffiliated registrants) to vote in party primary elections. The results of our experiment demonstrate that institutional context matters. Specifically, informing respondents of primary participation rules shapes voter registration recommendations. Among registrants who identify as independents, exposure to Florida’s closed primary rule causes them to be more likely to recommend party registration, whereas awareness of the semi-closed North Carolina primary rule makes independents and partisans more likely to advise unaffiliated registration. However, in the absence of information explaining rules for primary participation, respondents are more likely to suggest that their friend register in alignment with their own political identity. In summary, our study provides valuable insights into how registration choices are conditioned by political identities and exposure to treatments that emphasize political conditions and primary participation rules.

Selenium speciation analysis for the investigation of selenium uptake for the hydroponically cultivated garlic samples

Ambient temperature, suicide, and urbanicity: A nationwide time-stratified case-crossover study in South Korea

Several studies have examined the nationwide or multi-region relationship between ambient temperature and suicide mortality; however, evidence of comprehensive roles of urbanicity that can affect temperature, suicide, and risk-risk populations was limited. To reduce the gaps in knowledge, this study examined the nationwide ambient temperature-suicide association and heterogeneous high-risk populations by urbanicity levels and sex/age groups, based on a time-stratified case-crossover design with national mortality data (2015–2019). In the total population (65,645 suicides), we found an inverted J-shaped relationship between ambient temperature and suicide, and across all populations, higher temperature was associated with an increased risk of suicide mortality. Nevertheless, the association differed by urbanicity level, sex, and age group. First, in the total population, metropolitan and less-urban areas showed the stronger ORs (odd ratios between the maximum suicide temperature and 20th percentile of the temperature; metropolitan OR: 1.471, 95% CI: 1.141–1.898; less-urban OR: 1.631, 95% CI: 0.968–2.747) than mid-urban areas. In metropolitan areas, stronger ORs were observed in individuals aged 65 years or older (1.926, 1.175–3.157) and 0–44 years (1.575, 0.951–2.608) than in those aged 45–64 years. In mid-urban areas, all subgroups showed no evident association except for people aged 65 years or older. Whereas, less-urban males showed a marginally higher OR (1.667, 0.911–3.051) than less-urban females, although we could not observe sex differences in other areas. Our findings provide evidence for establishing more precise urban health policies and social interventions to reduce the risk of suicide related to ambient temperatures.