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Combining CRP testing and patient information leaflets to safely reduce antibiotic use for acute respiratory tract infections in adults: Protocol for the 2CARE randomised controlled trial in Kyrgyz primary care
Background Antimicrobial resistance (AMR) is a major health challenge in Kyrgyzstan, where acute respiratory tract infections (ARTIs) are common and frequently treated with antibiotics. Although C-reactive protein (CRP) point-of-care testing can support rational prescribing, there is no consensus on safe CRP thresholds for adults. Patient information leaflets (PILs) may further reduce inappropriate antibiotic use by improving understanding of ARTIs and addressing expectations for antibiotics. The 2CARE trial evaluates whether combining PILs with CRP testing can safely reduce antibiotic use among adults with ARTIs in Kyrgyz primary care. Methods 2CARE is a multicentre, open-label, individually randomised controlled trial conducted in 15 primary healthcare centres in Kyrgyzstan. Adults aged 18–70 years with acute respiratory symptoms (<14 days) are randomised 1:1 to receive a PIL or no PIL, and independently 1:1:1 to one of three CRP cut-off levels (20, 40, or 60 mg/L), yielding six parallel groups. Primary outcomes are: (1) total antibiotic use within 21 days, and (2) hospital admission within 21 days. Secondary outcomes include baseline antibiotic prescribing, re-consultations, recovery, hospital referral, antiviral use, and mortality. Analyses will follow the intention-to-treat principle, with per-protocol analysis for non-inferiority, using regression models and generalized estimating equations. A total sample of 1,050 participants provides 90% power for both primary comparisons. Discussion This trial will generate evidence on the effectiveness of PILs in reducing antibiotic use and establish safe CRP thresholds for adults with ARTIs in a low-resource setting. Findings will inform antimicrobial stewardship policies and guide national CRP implementation in Kyrgyzstan. Trial registration ClinicalTrials.gov Identifier: NCT07261969 .
DNA source and primer choice affect the reliability of metabarcoding for nematode community profiling in agricultural soils
The advent of metabarcoding has greatly advanced our understanding of nematode ecology by overcoming many limitations associated with traditional morphology-based methods. The NF1–18Sr2b (NF1) is the standard and widely used primer pair to assess nematode communities. However, this primer also presents challenges, especially when applied to DNA extracted directly from soil, where it has been shown to underestimate species richness. Consequently, soil DNA extraction (SE) has been viewed as a less attractive option for metabarcoding studies. To explore whether nematode DNA extraction (NE) can serve as a viable option for metabarcoding studies, we compared two degenerate primer pairs, NemF–18Sr2b (NemF) and NemFopt–18Sr2bRopt (NemFopt) to NF1. The study used two DNA sources: NE, and SE derived from 10 g and 1.25 g of dry agricultural soils. Our findings indicate that the NemF and NemFopt primers yielded higher taxonomic resolution and species richness in both SE and NE compared to NF1. Specifically, NF1 detected only 2–4% of nematode sequences in SE and 69% in NE, whereas NemFopt detected the highest proportion, with 100% of nematode sequences in NE and >70% in SE. Although none of the primers amplified all taxa, NF1 was associated with higher undetected taxa. NemFopt in the 10 g SE identified nematode assemblages comparable to those from NE, suggesting that SE can effectively capture nematode communities similar to NE. Nematode community profiles and ecological indices were stable across soil DNA input volumes and DNA sources. Maturity index and enrichment index did not differ significantly between NE and SE. Community similarity across extraction methods varied with primer choice, with NemFopt showing the greatest consistency. Although this study was limited to two soil types, two field sites, and three primer sets, our results suggest that increasing primer specificity can reduce the amount of soil required for metabarcoding and make SE a viable option. Moreover, primer choice, soil type, and DNA source can significantly affect nematode diversity estimates and ecological interpretations, highlighting the need for primer standardization in nematode metabarcoding studies.
A computer vision approach for the grading of cotton base load ages in measuring the performance of washing machine
The performance testing standards for washing machines specify clear requirements regarding the age of the base load used. To enable non-contact detection of the service life of the test fabric and thereby improve the consistency of washing machine performance test results, this study employed computer vision techniques to investigate the feasibility of using image features of the base load for age grading. Base load samples underwent 1–100 accelerated washing cycles were categorized into five degradation stages (C1–C5 were used to represent base loads with ages of 1–20 cycles, 21–40 cycles, 41–60 cycles, 61–80 cycles, and 81–100 cycles, respectively). Wrinkle information and plain weave structure information were extracted from base load images, from which color, texture and area features were obtained. In addition, k-nearest neighbors (kNN), multilayer perceptron (MLP), linear discriminant analysis (LDA), and logistic regression (LR) classifiers were trained to grade the age of base load. As a result, LR classifier demonstrated robust overall performance, achieving accuracy of 0.75, 0.75, 0.62, 0.75, and 1.00 for C1, C2, C3, C4, and C5, respectively. Models utilizing exclusively plain weave structure-derived features consistently outperformed those using only wrinkle-derived features across all classifiers. These results validate computer vision as an effective tool for objective base load aging assessment, offering significant potential to streamline washing machine testing protocols and enhance sustainability. Future work can be focused on expanding sample sizes and exploring mobile-based implementation.
Spatial and temporal pattern evolution and driving characteristics of rural settlements in Xilingol League from 1915 to 1980
Population migration and agricultural expansion have profoundly reshaped the rural characteristics of Xilingol League, a typical pastoral region in northern China. From the perspective of historical geography, this study investigates the settlement evolution in Xilingol League during 1915–1980. Drawing on declassified statistical data and historical documents, and employing kernel density estimation, hotspot analysis, and the geographical detector, we reconstruct and interpret the settlement patterns during the period without remote sensing imagery. The results reveal that: (1) Between 1915 and 1980, settlement expansion in Xilingol League exhibited a fan-shaped trajectory centered on Taibus Banner and Duolun County, with clustering intensity diminishing with increasing distance. (2) The 42°N parallel demarcates pastoral areas from agro-pastoral transitional zones, with settlements concentrated mainly in the transitional zone and showing a fragmented northeastward expansion into pastoral areas over time. (3) Socio-economic conditions were the dominant drivers of settlement evolution during this period, with cultivated land area ( q = 0.6266) and livestock numbers ( q = 0.6215) exerting the strongest explanatory power. This study provides new insights into the processes and driving mechanisms of modern settlement evolution in Xilingol League.
Why do self-referent cues facilitate mathematical word problem-solving? Insights from eye tracking
Associating information with the self enhances processing of that information, with simple text cues like self-referent pronouns (i.e., ‘You’) increasing response speed and accuracy in processing tasks. Research suggests this can be applied in educational contexts, such as children’s mathematical word problem-solving. Whilst children show faster and more accurate word problem-solving when self-pronouns are included in the text, the mechanisms underlying these effects are unclear. The current study extends previous research by using eye-tracking to monitor 9- to 11-year-old children’s processing during mathematical word problem-solving. Children were faster to solve subtraction problems that contained a self-referential pronoun, but this was not the case for addition problems. Eye tracking data revealed that faster processing time was driven by reduced fixation length on referent information in the self-pronoun problems across problem types: children spent less time looking at self-pronouns than terms referring to another person (e.g., character names). This suggests that self-pronouns may facilitate problem-solving by supporting active storage of items bound to self in working memory, reducing the need for revisitation during mathematical word-problem solving. This is likely to be particularly beneficial for more cognitively challenging problems, providing an explanation for patterns of self-reference effects reported previously.
Sex- and nationality-based participation and performance trends in the Swissman Xtreme Triathlon (2019–2025)
Background Participation and performance trends are well investigated for the IRONMAN ® triathlon. For Xtreme Triathlons (XTri World Tour) races, only one study has examined participation and performance trends for the ‘Norseman Xtreme Triathlon’ in Norway, but not for other XTri World Tour events. Therefore, the aim of the present study was to investigate participation and performance trends in the ‘Swissman Xtreme Triathlon’ as part of the XTri World Tour. Methods Finisher data from all ‘Swissman Xtreme Triathlon’ editions (2019–2025) were analyzed. DNS, DNF, missing information, and implausible finishing times were excluded. Participation patterns were described by sex and nationality. Sex differences in race time were evaluated using Mann–Whitney U tests. Differences among the ten most represented nationalities were tested using Welch’s ANOVA with Dunnett’s T3 post-hoc comparisons. Temporal changes in performance were assessed with quantile regression at the 0.25, 0.50, and 0.75 quantiles (p < 0.05). Results A total of 1,032 finishers were included, of whom 13.5% were women. Switzerland had the highest participation (n = 431). Performance was similar across most nationalities, with slower times observed only among athletes from the United States compared with Switzerland (p = 0.01), Germany (p = 0.02), and Norway (p = 0.03). No sex-based differences were found in any edition (overall p = 0.4922; r = −0.02). Quantile regression revealed clear temporal changes in performance. At the median (0.50), race time increased by 715 s·year ⁻ ¹ (95% CI: 434–997; p < 0.0001), and a similar rise occurred at the 0.75 quantile (β = 727 s·year ⁻ ¹; 95% CI: 498–955; p < 0.0001). In contrast, the 0.25 quantile showed a smaller and non-significant increase (β = 345 s·year ⁻ ¹; p = 0.0626), indicating that intermediate and slower athletes were primarily responsible for the overall temporal decline. Sex-specific analyses confirmed this pattern: significant increases at the median and 0.75 quantiles for men, and a significant increase only at the median quantile for women. Conclusions Swiss athletes formed the largest portion of competitors in ‘Swissman Xtreme Triathlon’, while performance was comparable across most nationalities. Women and men performed similarly throughout all editions. Race times increased across years, particularly among intermediate and slower finishers. These findings provide an updated overview of participation and performance trends in this major XTri World Tour event. Future studies need to investigate more races of the XTri World Tour.
Privacy-preserving multimodal federated learning pipeline for cyber-resilient healthcare systems
The integration of Internet of Things (IoT) devices and electronic medical records (EMRs) has transformed healthcare delivery but has also created new vulnerabilities to cyberattacks that threaten both data confidentiality and patient safety. Conventional centralized machine learning approaches for intrusion detection are impractical in this domain due to strict privacy regulations, heterogeneous data sources, and the risk of single points of failure. To address these challenges, we propose a secure distributed machine learning pipeline for cyber-resilient healthcare systems. The framework combines federated optimization with split learning for sensitive EMR data, robust aggregation to mitigate poisoned updates, and differential privacy with secure aggregation to protect against inference attacks. Multimodal fusion is enabled through temporal consistency regularization for IoT traffic and cross-layer contrastive alignment to link EMR representations, ensuring improved anomaly detection across diverse healthcare environments. Experiments conducted on representative IoT and EMR datasets demonstrate that the proposed pipeline achieves accuracy of 0.942 on IoT data, 0.931 on EMR data, and 0.953 in the combined setting, with corresponding F1-scores of 0.921, 0.908, and 0.932. Ranking metrics further confirm superiority with AUROC up to 0.961 and AUPRC up to 0.947, outperforming deep baselines by margins of +0.025 to +0.033. Robustness analysis shows graceful degradation under client poisoning ( 0.953 → 0.879 at 30% malicious clients) and resilience under severe communication constraints (accuracy 0.953 → 0.861 at 90% update sparsification). Detection latency is reduced to an average of 5.9 time steps, compared to 7.8 for the strongest deep baseline. These results highlight that secure distributed pipelines can deliver both strong detection capabilities and regulatory compliance, providing a practical path toward safeguarding next-generation healthcare infrastructures against evolving cyber threats.
Evolutionary game analysis of emergency medical supply production capacity reserves in nonprofit organizations: A theoretical perspective
Since the 21st century, global public health emergencies have occurred frequently, posing severe threats to the economic development and social stability of countries worldwide. Against this backdrop, emergency medical supply reserves are particularly crucial—especially the production capacity reserves of non-durable medical materials characterized by high demand, short production cycles, and limited shelf lives. As a theoretical modeling study, this paper adopts the core ideas and analytical methods of evolutionary game theory to construct dynamic evolutionary game models for the cooperative production capacity reserves of emergency medical supplies between nonprofit organizations (NPOs) and reserves enterprises under two scenarios: “perfect competition” and “government incentive policy intervention.” Key factors including reputation benefits, social disaster reduction benefits, and opportunity costs are incorporated to systematically explore the impacts of multiple variables on the decision-making of both cooperative parties. Meanwhile, numerical simulation is employed to quantitatively analyze the operational mechanisms of government incentive policies, specifically one-time subsidies, revenue sharing, cost subsidies, and supervisory penalties. The research findings are as follows: First, the synergistic effect of perfect competition and government incentive policies can promote the evolutionary game system toward cooperative equilibrium. Among these factors, the impact of the incentive allocation coefficient is context-dependent, requiring scientific calibration to balance the interest demands of both parties. Second, the reserves cost-benefit ratio is a core threshold variable determining cooperative behavior. Perfect competition alone tends to fail under high cost-benefit ratios, while the “government-led—NPO-supplemented” collaborative incentive model can break through this threshold constraint via “long-term empowerment + short-term efficiency improvement.” Third, enterprises’ opportunity costs exert a significant negative impact on cooperation, whereas supervisory penalties exceeding a critical threshold can inhibit speculative behaviors and enhance cooperative willingness. Finally, the research findings of this paper are verified through simulation with the background of emergency medical reserves in Chongqing, China. Based on these findings, this study proposes countermeasures including optimizing the incentive allocation mechanism, constructing a collaborative incentive system, and improving the disciplinary constraint mechanism. This research provides new perspectives and practical guidance for optimizing the emergency medical material reserves system and ensuring the stable development of emergency reserves cooperation.
Predicted meta-omics: A potential solution to multi-omics data scarcity in microbiome studies
Imbalances in the gut microbiome have been linked to conditions such as inflammatory bowel disease, diabetes, and cancer. While metagenomics and amplicon sequencing are commonly used to study the microbiome, they do not capture all layers of microbial functions. Other meta-omics data can provide more insights, but these are more costly and laborious to procure. The growing availability of paired meta-omics data offers an opportunity to develop machine learning models that can infer connections between metagenomics data and other forms of meta-omics data, enabling the prediction of these other forms of meta-omics data from metagenomics. We evaluated several machine learning models for predicting meta-omics features from various meta-omics inputs. Simpler architectures such as elastic net regression and random forests generated reliable predictions of transcript and metabolite abundances, with correlations of up to 0.77 and 0.74, respectively, but predicting protein profiles was more challenging. We also identified a core set of well-predicted features for each meta-omics output type, and showed that multi-output regression neural networks performed similarly when trained using fewer output features. Lastly, our experiments demonstrated that predicted features can be used for the downstream task of inflammatory bowel disease classification, with performance comparable to that of experimental data.
Examining the mediating effects of metabolic syndrome components on the relationship between dairy product consumption and nonalcoholic fatty liver disease in Korean adults
Objective Dairy products are known to improve blood lipid profiles and insulin sensitivity and to reduce risk factors for metabolic syndrome (MetS) and nonalcoholic fatty liver disease (NAFLD). However, the mechanisms through which dairy product consumption influences NAFLD via MetS components remain unclear. This study examined the mediating effects of MetS components on the association between dairy product consumption and NAFLD. Methods This study included 12,775 Korean adults from the Korea National Health and Nutrition Examination Survey (KNHANES) 2019–2021. Dairy product intake was assessed using a 24-hour dietary recall. NAFLD was defined using a hepatic steatosis index score >36, and MetS was classified according to the National Cholesterol Education Program Adult Treatment Panel III criteria. Multivariable logistic regression analyses were conducted to examine the associations among dairy intake, NAFLD, and MetS components. Mediation analyses with bootstrapping (n = 1,000) were performed to investigate the mediating effects of individual MetS components on the association between dairy consumption and NAFLD. Results Consumption of more than one serving of dairy products was associated with a lower prevalence of NAFLD among women (adjusted odds ratio [AOR], 0.75; 95% confidence interval [CI], 0.59–0.96). Regarding MetS components, intake of one serving of dairy products was associated with lower odds of elevated triglycerides in men (AOR, 0.75; 95% CI, 0.63–0.89). In women, consumption of at least one serving was associated with decreased hyperglycemia (AOR, 0.84; 95% CI, 0.73–0.97), abdominal obesity (AOR, 0.69; 95% CI: 0.55–0.87), low high-density lipoprotein cholesterol (AOR, 0.83; 95% CI: 0.72–0.95), and elevated triglyceride levels (AOR, 0.71; 95% CI, 0.60–0.85). Mediation analyses indicated that, among women, significant proportions of the associations between dairy product consumption and NAFLD were mediated by waist circumference (58.0%), systolic blood pressure (18.2%), and high-density lipoprotein cholesterol (51.7%), whereas no significant mediation effects were observed among men. Conclusions Dairy product consumption was associated with a lower prevalence of MetS and NAFLD among women. Mediation analysis further suggested that dairy product consumption may reduce the risk of NAFLD by improving metabolic dysfunction among women.
Integrative bioinformatics and machine learning identify shared molecular mechanisms and diagnostic biomarkers between Helicobacter pylori infection and atrial fibrillation
Background Helicobacter pylori ( H. pylori ) infection and atrial fibrillation(AF) are major global health concerns. Emerging evidence has suggested a potentially chronic inflammation-mediated link between them, but the shared genetic mechanisms remain unclear. Methods We analyzed multidataset gene expression profiles from the Gene Expression Omnibus (GEO) database. Differential expression analysis, weighted gene co-expression network analysis (WGCNA), functional enrichment, and machine learning were employed to identify common genes, pathways, and diagnostic biomarkers. Protein-protein interaction (PPI) networks, drug-gene analysis, and molecular docking were used to identify hub genes and potential therapeutics. Results We identified 73 common differentially expressed genes (DEGs) between H. pylori infection and AF, which were predominantly enriched in immune-related processes including leukocyte activation, neutrophil migration, and myeloid cell-mediated immunity. Machine learning identified 15 and 23 key feature genes for H. pylori and AF, respectively, with S100A8 emerging as a shared diagnostic biomarker. Ten hub genes including TYROBP, ITGB2, and SPI1, were identified from the PPI network. Drug repositioning analysis suggested retinoic acid, indirubin, and ropivacaine as candidate therapeutics targeting these key hub genes. Conclusion Our integrative analysis highlights the central role of immune-inflammatory pathways in linking H. pylori infection to AF. We propose S100A8 and other identified hub genes as potential biomarkers and therapeutic targets. The predicted candidate therapeutics, particularly retinoic acid, may offer novel avenues for intervention, warranting further experimental validation.
Inconsistent condom use and its associated factors among female sex workers in African countries: Systematic review and meta-analysis
Background Inconsistent condom use represents the most proximal behavioral risk factor for acquisition and transmission of sexually transmitted infections, including human immunodeficiency virus. However, certain situations hinder female sex workers from practicing consistent condom use. This study aimed to assess the pooled estimate of inconsistent condom use among female sex workers and identify factors associated with it. Methods This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, 2020 reporting checklist. Electronic databases (PubMed, Cochrane Library, Epistemonikos, Hinari, and Science Direct), Google Scholar, and other university repositories were searched until March 20, 2024, based on the eligibility criteria. Three independent reviewers screened the titles, abstracts, and full texts. Two independent reviewers extracted the data. The Joanna Briggs Institute quality appraisal checklist was used. The Higgin’s I² test was used to quantify heterogeneity. Pooled analysis was conducted using a random-effects model. Sensitivity and subgroup analyses were done. Publication bias was assessed using Egger’s regression test and funnel plot. The pooled prevalence and statistical association were declared at a p-value < 0.05 with the 95% CI. Results A total of 24 studies involving 23,496 female sex workers with a median age of 27.3 years were included. The overall pooled prevalence of inconsistent condom use among FSW in Africa was estimated at 46.73% (95% CI: 37.60, 55.86), I² = 99.59%, and p = 0.00. Condom availability (AOR = 0.68; 95% CI: 0.50, 0.92), depression (AOR = 1.51; 95% CI: 1.00, 2.30), no education (AOR = 1.87; 95% CI: 1.19, 2.93), two or more nonpaying clients (AOR = 2.90; 95% CI: 1.51, 5.54), having >9 current client number (AOR = 0.46; 95% CI: 0.29, 0.74), violence (AOR = 1.74; 95% CI: 1.33, 2.27), and police harassment (AOR = 2.28; 95% CI: 1.03, 5.05) were significant factors. Conclusion and recommendation Inconsistent condom use was high in Africa. Factors including availability of condoms, depression, and education, having two or more nonpaying clients, client numbers, violence, and police harassment were significant factors. Strategies like improving peer education, providing mental health support, empowering women, and improving female sex workers educational status, ensuring condom availability, and strengthening supply for easily accessible condoms can decrease inconsistent condom use and protect FSWs from STI including HIV.
Genetic diversity of Schima superba based on physiological traits and SSR markers
Schima superba is an ecologically and economically valuable evergreen tree that plays a key role in reforestation, firebreak establishment, and urban landscaping in subtropical China. To evaluate its adaptive diversity, this study combined physiological trait assessment with SSR-based genetic analysis across eight natural populations comprising 122 individuals. Five physiological traits, including chlorophyll, malondialdehyde, proline, soluble protein, and soluble sugar, showed significant variation among and within populations ( p < 0.01), with HTHL and HBB populations exhibiting the greatest phenotypic variability. Using 20 polymorphic SSR loci, we detected high genetic diversity (He = 0.804, PIC = 0.786) and moderate differentiation (Fst = 0.111) with strong gene flow (Nm = 2.23). STRUCTURE and PCoA analyses revealed five genetic clusters, and the HBN and HTHL populations displayed distinct genotypes. Mixed linear model analysis identified 14 significant SSR–trait associations, with SS30 and SS32 strongly correlated with malondialdehyde and chlorophyll content. These results demonstrate a close relationship between genetic and physiological diversity in S. superba and provide essential molecular resources for its conservation, breeding, and adaptive improvement.
Assessment of peak bone mineral density and its associated factors in Vietnamese adults: A cross-sectional study
Introduction Osteoporosis is a growing public health concern in Vietnam, yet population-specific reference data for peak bone mineral density (PBD) remain limited. This study aimed to establish a standard PBD dataset and identify factors associated with bone mineral density (BMD) in Vietnamese adults. Methods A cross-sectional study included 1,378 participants (410 men, 968 women) in Hue City, Vietnam. BMD was measured at the lumbar spine (LS), femoral neck (FN), and total hip (TH) using dual-energy X-ray absorptiometry (DXA). A cubic polynomial regression models were performed to identify peak bone density (PBD). Age-standardized prevalence of osteoporosis was calculated using the 2024 Vietnamese population structure. Results Men exhibited higher BMD than women across all skeletal sites. The estimated age of PBD attainment was 20–29 years in men and approximately 30 years in women. Age was the strongest negative predictor of BMD, while body weight and height showed positive correlations. The age-standardized prevalence of osteoporosis was highest at the LS (33.58%), followed by the TH (12.77%) and FN (2.69%). Women showed a markedly higher prevalence than men, with a sharp increase observed after menopause. Conclusion This study provides an updated reference dataset for PBD in the Vietnamese population, notably revealing that men attain peak bone density earlier than women. Furthermore, the findings underscore the high prevalence of osteoporosis at the lumbar spine, suggesting a need for early screening strategies targeting high-risk groups.
An automatic weighing device for measuring the consumption of cleaning agents in mechanical cleaning equipment
Objective This study aims to develop an automatic weighing device based on embedded technology for accurately monitoring the consumption of various cleaning agents during each cleaning cycle of mechanical cleaning equipment used in the Central Sterile Supply Department (CSSD). Methods The hardware of the automatic weighing device included an ESP32 development board, HX711 module, infrared sensor, load cell, and display screen, with the circuit having been designed using a printed circuit board. After each cleaning cycle of the mechanical cleaning equipment, the device automatically calculated the consumption of cleaning agents. To validate its accuracy, the device’s measurements were compared with the gold standard (volumetric measurement method). Additionally, the device was installed on a washer-disinfector for practical application testing to evaluate its performance. A mobile APP was also developed to enable real-time synchronization of data displayed on the screen of the automatic weighing device. Results A total of 20 comparative tests were conducted between the automatic weighing device and the volumetric method. The mean difference in measured cleaning agent consumption was 0.16 mL (95% CI: −0.24 to 0.56), with the interquartile range of absolute differences being 0.54 mL–1.06 mL. The expected consumption values for enzymatic and alkaline cleaning agents for the washer-disinfector were 100 g and 60 g per cycle, respectively. During the first 52 cleaning cycles, the average consumption of enzymatic detergent was 88.46 g (95% CI: 85.81–91.18), and that of alkaline detergent was 49.45 g (95% CI: 48.51–50.40), both significantly below the expected values. After replacing the peristaltic pump hose, a subsequent test of 55 cleaning cycles showed average consumptions of 97.70 g (95% CI: 96.40–99.00) for enzymatic detergent and 59.67 g (95% CI: 58.90–60.44) for alkaline detergent, both closely approaching the expected values. Conclusion The automatic weighing device demonstrated reliable measurement performance, simple structure, high compatibility, and stable operation. It is easy to install, use, and maintain, offering a feasible and scientifically effective technical solution for accurately monitoring cleaning agent consumption in CSSD.
Research on hybrid cloud resource scheduling optimization algorithm based on EMPA-ASA
Hybrid–cloud scheduling must balance cost, performance, and reliability; yet existing approaches often suffer from burdensome parameter tuning, a limited set of optimized QoS indicators, and high computational overhead. To address these issues, we propose an EMPA–ASA–based hybrid–cloud resource scheduling algorithm and make three contributions: 1) we realize state-driven adaptive scheduling and resource allocation via MDP + Q-learning, updating the policy online as system conditions evolve; 2) we introduce an M / M / c queueing model to quantitatively encode QoS constraints, thereby improving responsiveness and load adaptivity; and 3) we fuse EMPA with Adaptive Simulated Annealing (ASA), augmented by Lévy flights to strengthen global exploration and accelerate convergence. We implement a full prototype and conduct performance evaluations. The results show that EMPA–ASA outperforms baselines across multiple QoS metrics—including end-to-end delay, response time, throughput, and packet-loss rate—and reduces total cost by approximately 48% and 70% relative to GA and PSO, respectively; its advantages in QoS and cost are especially pronounced under high-load scenarios. These findings indicate a superior cost–performance trade-off, providing an efficient and reliable solution for hybrid–cloud resource scheduling.
Prevalence, associated factors, and association of intimate partner violence and suicidal behaviors among women of reproductive age in Asia: Protocol for a systematic review and meta-analysis of cross-sectional studies
Intimate partner violence (IPV) is strongly linked to suicidal behaviors (ideation, plans, attempts), affecting 1 in 3 women globally, with prevalence varying across regions. Sociocultural and economic factors shape IPV and SB risk differently. This review will estimate prevalence, risk factors, and associations of IPV and SBs among women of reproductive age in Asia to provide region-specific evidence for targeted interventions. We will systematically search PubMed, Scopus, PsycINFO, Web of Science, EMBASE, CINAHL, and Google Scholar for studies published up to 30 November 2025, following PRISMA guidelines. The search will also include grey literature and citation chaining, using keyword truncation, string searches, and standardized indexing terms. Cross-sectional observational studies among Asian women (19–45 years) exposed to intimate partner violence (physical, psychological, sexual) will be included, reporting suicidal behaviors (ideation, plans, attempts) compared with unexposed women. Only English-language, peer-reviewed studies will be considered, while reviews, abstracts, and unpublished studies will be excluded. Two independent reviewers will screen studies for the central concepts of “Intimate Partner Violence (IPV)” and “Suicidal Behaviors (SB)”, with disagreements resolved by a third reviewer. Data on prevalence, associated factors, mediator variables, and numerical estimates of IPV–SB associations will be extracted. Meta-analysis using a random-effects model will be conducted alongside a narrative synthesis. Findings will be visualized with forest and funnel plots, heterogeneity assessed using the Q Cochrane statistic and I² index, and subgroup and sensitivity analyses performed. Risk of bias will be evaluated using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist. Early identification of psychological distress using culturally validated tools, combined with understanding context-specific drivers of IPV, is essential for preventing suicidal behaviors among Asian women of reproductive age. Findings from this review will inform targeted interventions, guide policy, and address gender norms that perpetuate violence and elevate mental health risks.
Phytochemicals from Astragalus zederbaueri as Acetylcholinesterase Inhibitors for Alzheimer’s Therapy
Alzheimer’s Disease (AD), the dominant form of dementia that evolves with age, involves several mechanisms by which it progresses. The cholinergic hypothesis proposes that the activity of Acetylcholinesterase (AChE) causes the decline of cholinergic neurotransmission, which leads to Alzheimer’s Disease. Considerable studies are being conducted to determine the best AChE inhibitor. This study evaluated 40 phytocompounds from the Astragalus zederbaueri plant as potential AChE inhibitors for Alzheimer’s disease. The analysis of the phytochemicals was conducted using the control drug donepezil (co-crystallized ligand) through various computational tools and biological databases for docking, visualization, and simulation. The findings of our research showed that the key ligands according to the docking analysis were Rutin (AZ-29), Kaempferol-3-O-rutinoside (Nicotiflorin) (AZ-32), and Isoquercitrin (AZ-28); nevertheless, it was found that Rutin played the most effective role of an anti-AChE compound with an exceptional binding affinity of −15.043 kcal/mol. TRP341 and TYR286 were key amino acid residues in hydrogen bonds and π-π stacking interactions, respectively. The results of pharmacokinetic and toxicological analyses of these compounds were within the acceptable range. Moreover, the molecular dynamics simulation confirmed the stability of the complexes. Our findings suggest a novel phytochemicals from Astragalus zederbaueri for Alzheimer’s disease, paving the way for further experimental validation and drug development.
Genomic characterization of Comamonas kerstersii isolated from diarrheal patients in Bangladesh
This study marks the first identification and genomic characterization of Comamonas kerstersii isolates from diarrheal patients in Bangladesh. We carried out the whole genome sequencing of three C. kerstersii isolates to analyze genomic features using bioinformatics tools. We hypothesize that C. kerstersii can contribute to the diarrheal disease process through indirect mechanisms, potentially by interacting synergistically with other enteric pathogens such as Vibrio cholerae (both O1 and non-O1 serogroups). The presence of diverse virulence factors, including type IV pili, type VI secretion systems, chemotaxis proteins, and toxin genes such as zot and RTX, suggests a capacity for adhesion, motility, and immune evasion. Notably, genomic analyses indicate that C. kerstersii shares several offensive and defensive virulence factors with other pathogenic Comamonas spp, including mechanisms for biofilm formation, nutrient acquisition, and stress tolerance. These factors, combined with antimicrobial resistance genes identified genes – aph(6)-Id, aph(3”)-Ib, mph(E), mph(F), msr(E), sul2, and tet(A), may enhance survival and adaptability of C. kerstersii in the gut environment, potentially augmenting the pathogenicity of co-infecting diarrheal pathogens. These initial findings highlight the need for extensive genomic surveillance across diarrheal patients, along with further investigation into molecular interactions with co-pathogens that could reveal novel pathways influencing diarrheal disease outcomes.
Low ALDH1A1 expression in relation to nodal metastasis and survival in tongue squamous cell carcinoma
Background/Aims Multiple biomarkers have been proposed to identify cancer stem cells in tongue squamous cell carcinoma. This study evaluated ALDH1A1, an ALDH1 subtype implicated in head and neck cancer stem cells, and examined its association with histopathological features (depth of invasion, worst pattern of invasion, perineural invasion, grade, inflammation, TNM stage) and prognostic outcomes in tongue tumors. Materials and methods This cohort study included 55 confirmed cases of tongue squamous cell carcinoma retrieved from the pathology archives of the Cancer Institute, Imam Khomeini Hospital Complex, Tehran, Iran. Four-μm sections were stained immunohistochemically using a mouse monoclonal ALDH1A1 antibody. Histopathological variables were obtained from pathology reports and/or reassessed on slides. Patient contact information was used to follow up on recurrence and death. Results High and low ALDH1A1 expression was observed in 27 (49.1%) and 28 (50.9%) cases, respectively, with follow-up periods ranging from 1 to 62 months. The mean age of patients was 57.24 ± 17.82 years, with a range of 24–101 years. The study included 26 men and 29 women. Low ALDH1A1 expression was linked to regional lymph node metastasis (p = 0.01). Disease-specific survival was independently associated with low ALDH1A1 expression (p = 0.045) and T category (p = 0.01). Overall survival was independently associated with age (p-value = 0.04) and T category (p-value = 0.02). Conclusion Low ALDH1A1 expression in tongue squamous cell carcinoma was associated with regional lymph node metastasis and reduced disease-specific survival. Larger studies, including analyses across different oral subsites, are needed to clarify the relationship between ALDH1A1 expression and clinicohistopathological factors in oral squamous cell carcinoma.