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Correction: Rapid and sustainable deep testosterone reduction predicts effective androgen deprivation therapy for metastatic hormone-sensitive prostate cancer
Muscle electrical activity, functional mobility level, and handgrip strength in intensive care unit patients: a single-center observational study
A lightweight improved YOLOv11 framework for intracranial hemorrhage detection
Prevalence of kdr and ace-1 mutant genes and potential insecticide resistance among four field strains of Anopheles sinensis (Diptera: Culicidae) collected from high-malaria-risk areas in the Republic of Korea
Abstract The relationship between phenotypic resistance to organophosphate and pyrethroid insecticides and the frequencies of knockdown resistance ( kdr ) and acetylcholinesterase ( ace-1 ) target-site mutations was investigated in four field strains of Anopheles sinensis collected from high-malaria-risk areas in the Republic of Korea (ROK). Six kdr genotypes and six ace-1 genotypes were identified, and the overall frequencies of resistance-associated mutations ranged from 62.1% to 96.8% for kdr and from 84.5% to 100% for ace-1 . Among larvae that survived exposure to LC 50 concentrations of selected insecticides, resistance-associated genotypes, including Phe-Phe (TTT) in kdr and Gly (GGR)-Ser (YGC) in ace-1 , were predominantly detected. Although the mean frequency of ace-1 resistance-associated mutations was higher than that of kdr mutations, the difference was not statistically significant ( P = 0.42). In contrast, bioassay results showed that the mean resistance levels to pyrethroids were significantly higher than those to organophosphates ( P = 0.006). Correlation analyses revealed no statistically significant association between kdr mutation frequency and pyrethroid resistance or between ace-1 mutation frequency and organophosphate resistance. These findings suggest that resistance-associated target-site mutations are widespread in An. sinensis populations from high-malaria-risk areas near the DMZ, but their frequencies alone do not fully explain phenotypic resistance levels. Therefore, while molecular data are useful for monitoring the distribution of resistance-associated mutations, they should be interpreted alongside bioassay results when developing insecticide resistance management strategies.
Temporal concentration trends of ammonia (NH3) and nitrogen dioxide (NO2) derived from paddy fields in South Korea by real-time monitoring
Cyclophilin-a as a key paracrine factor replicating hPVSC therapeutic effects in a chemotherapy-induced ovarian damage model
Bisphenol A induces a pro-angiogenic-like phenotype via the G protein-coupled receptor 30 (GPR30) pathway
Development and validation of a forward-looking metacognitive AI readiness scale for Jordanian teachers
Assessing quantity combination and dissociation in giraffes
Abstract Several species have demonstrated the ability to mentally manipulate quantities in tasks requiring their combination and dissociation, reflecting perceptual memory–based mechanisms that may be the foundation of proto-arithmetic and in some cases more advanced arithmetic abilities. Yet, ungulates remain underrepresented in this line of research. Here, we present the first investigation in giraffes ( Giraffa camelopardalis ) assessing their ability to combine and dissociate quantities. We tested four captive giraffes in three experimental and two controls tasks. In the experimental tasks, the animals could only see the initial quantities and the items moved, but not the final amounts. Results revealed that giraffes performed above chance in the Combination task (where food was combined to one of two covered quantities). However, they performed at chance level in both the Dissociation task (where food was removed from one of two covered quantities) and the Subsequent Events task (where food was transferred from one of the two quantities to the other one). Further analyses suggested that while two subjects might have relied on simpler strategies (e.g., choosing or avoiding the dish manipulated by the experimenter), the other two succeeded even when this strategy could not be used, suggesting the potential use of more complex mental computations.
Satellite observations reveal the role of climate variability in the 2019 extreme rainfall and flood event in Karnataka, India
Abstract Multiple with extreme rainfall induced flash flooding pose significant challenges in monsoon dominated regions of India, yet reliable near-real-time monitoring is limited due to sparse ground observations. This study highlights the use of a satellite-based rainfall index (RI), derived from multispectral infrared and water vapor observations, to map short-lived localized multiple with extreme rainfall events with application to the August 2019 flood in Karnataka India. The information of RI integrates brightness temperature information using Meteosat-8 with precipitation estimates from TRMM and GPM-IMERG and is validated independently by using district scale India Meteorological department (IMD) rainfall data. To understand the impact of climatological context on 2019 rainfall event, rainfall anomalies are examined alongside ENSO and Indian Ocean Dipole (IOD) indices using partial correlation analysis over the period of 1998 to 2019. Results attribute statistically consistent co-variability between large-scale climate models and monsoon rainfall variability, with ENSO showing a strong and significant association than IOD. These relationships are interpreted as background climatic modulation rather than direct causal forcing. The study advances satellite-based rainfall monitoring by leveraging high-resolution analysis rainfall episodes with long-term climatological context, offering a transferable frame work for flood early-warning support in data-scarce regions.
Bifurcation, quasi-periodic dynamics, chaos, and soliton waves in the van der Waals normal form for fluidized granular matter
Interaction model of client health behavior-based nursing intervention improves outcomes in patients with pressure injury: A quasi-experimental study
Buffering the constraint: exploring the role of TOE in supporting enterprise digital transformation in resource-based cities
Positive changes in 24-hour movement behaviors and blood pressure in socioeconomically vulnerable schoolchildren after a 16-week health promotion intervention
Abstract This study aimed to analyze sex-specific changes in blood pressure (BP), anthropometric variables, and movement behaviors following a 16-week educational intervention of the BeE-school project. This intervention study included 735 children aged 6–10 years from 10 primary schools in the Northern region of Portugal. Schools were randomly assigned to either an intervention group ( n = 353) or a control group ( n = 382). The intervention consisted of a 16-week teacher education and training program, based on health promotion and its implementation in the classroom. Twice a month, challenges were sent to families during this period. Trained researchers evaluated body mass, height, waist circumference (WC), systolic BP (SBP), diastolic BP (DBP), screen time, sedentary behavior (SB) and physical activity before and after 16 weeks. Body mass index (BMI), tri-ponderal mass index (TMI), and age at peak height velocity were calculated. Data were analyzed using the Mann-Whitney tests, repeated measures ANOVA with Bonferroni post hoc, and Friedman ANOVA for nonparametric variables, with significance set at p ≤ 0.05. After the intervention, girls in the intervention group showed a significant reduction in TMI, while girls in the control group showed an increase in BMI ( p < 0.01). Reductions in SBP were observed in both groups, whereas DBP decreased mainly in the intervention group ( p < 0.01). In addition, the intervention group showed reduced SB and increased physical activity levels ( p < 0.05). The BeE-school intervention was associated with favorable changes in BP, SB, physical activity, and indicators of body adiposity, particularly among girls, supporting the potential benefits of multicomponent school-based health promotion strategies for children from socioeconomically vulnerable contexts. Clinical trial registration: The study was registered in Clinical Trials database/platform (NCT05395364).
Stochastic tumor immune dynamics with saturating response
Cardiovascular-diabetes-stroke multimorbidity patterns are differentially associated with cognitive trajectories in older Chinese adults
Abstract To identify multimorbidity patterns using latent class analysis (LCA) and examine their associations with cognitive trajectories among older Chinese adults. This longitudinal study utilized data from the China Health and Retirement Longitudinal Study (CHARLS) conducted between 2011 and 2015. Participants aged ≥ 45 years with at least one of three target chronic conditions (cardiovascular disease, diabetes, stroke) and complete cognitive function data were included. LCA identified distinct multimorbidity patterns. Linear mixed-effects models examined cognitive trajectories across multimorbidity patterns and disease burden (defined as single disease versus multimorbidity) categories, adjusting for age, sex, education, and residential location. A total of 3,155 participants were included in the final analysis. Three multimorbidity patterns were identified: Heart Disease-Dominant (57.1%), Stroke-Dominant (9.8%), and Diabetes-Dominant (33.2%). The Stroke-Dominant group exhibited significantly lower baseline cognitive function (β=-2.055, p < 0.001) compared to the Heart Disease-Dominant group. Compared to the single disease group, multimorbidity (≥ 2 conditions) was associated with accelerated cognitive decline, operationally defined as a significantly negative Time × Group interaction in the linear mixed-effects model (Time × Multimorbidity: β=-0.411, p = 0.017), with the multimorbidity group declining by 0.296 points biennially versus slight improvement (+ 0.115 points) in the single disease group. Specific multimorbidity patterns and disease burden demonstrate differential associations with cognitive trajectories among older adults. Stroke-dominant patterns and multimorbidity represent high-risk groups requiring targeted cognitive screening and integrated chronic disease management interventions.