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Lived experiences of type 2 diabetes self-management in Jordan: A qualitative study of sociocultural, religious, and healthcare influences
Aim To explore the experiences of Jordanian adults living with T2DM and understand the influence of sociocultural, religious, emotional, and healthcare factors on their daily self-management practices. Background T2DM prevalence is alarmingly high and increasing in Jordan. However, there is a lack of understanding about the daily experiences and challenges faced by T2DM patients in the complex cultural and social environment. Understanding the experiences of T2DM patients in the complex cultural and social environment is crucial for the design and implementation of appropriate interventions. Methodology A qualitative phenomenological approach was used for the study. Semi-structured in-depth interviews were conducted with 20 participants with T2DM. Participants were selected from the major tertiary care hospital in Northern Jordan. Reflexive thematic analysis, supported by NVivo software, was used for the data analysis. Triangulation, audit trail, peer debriefing, and member checking were used for the establishment of the trustworthiness of the study. Results Six major themes were identified. Cultural pressures concerning food, challenges in adhering to the prescribed medication, religious and cultural influences, emotional and psychological burdens, gaps in healthcare services, and facilitators and coping strategies. Conclusion Self-management practices for T2DM patients in Jordan are significantly influenced by cultural, religious, emotional, and healthcare factors. Interventions for T2DM patients in Jordan need to be appropriate and tailored to the culture and community. Implications for Nursing It is the duty and responsibility of the nurse to provide appropriate education and advice based on the culture and community. Family involvement in the care process for T2DM patients in Jordan is crucial.
Deep learning models built from PSMA PET of the primary tumor can predict synchronous and metachronous prostate cancer metastases
Objective The objective was to develop prognostic models that included convolutional neural networks (CNN) derived from 18 F-DCFPyL (PSMA) PET imaging of the primary tumor uptake patterns to prognose early metastatic progression after curative intent treatment for localized prostate cancer. Methods Due to the lack of sufficient cases with adequate follow-up and metastatic events to derive this model directly, we derived models that predict the presence of synchronous metastases using only data obtained from the primary tumor. Because early metastatic progression events are consequent to occult metastases present at the time of initial therapy, we hypothesized that a model trained to predict synchronous metastases might also predict metachronous metastatic progression. A convolutional neural network (CNN) model was generated using whole-prostate PSMA PET images and auto-segmented intraprostatic lesions and combined with clinicopathologic data and imaging parameters to develop a multimodal model. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) for predicting synchronous metastases and metachronous metastatic progression. Results The multimodal model and CNN model had AUCs of 0.82 (95% CI 0.69–0.92, p < 0.005) and 0.72 (95% CI 0.55–0.84, p 0.0059), respectively, for prediction of synchronous metastases. Shapley additive explanation analysis showed the CNN had the largest contribution to the combined model performance. For metastatic progression, the multimodal model had an AUC of 0.839 (95% CI: 0.6763–1.000, p = 0.0064). Conclusion The multimodal model trained to predict synchronous metastases also predicted metachronous metastatic progression. This supports the potential of artificial intelligence applied to primary tumor PSMA PET images for enhanced prognostication. However, significant limitations include the modest sample size, single center source of data, and potential for overfitting, which may limit generalizability. Therefore, further validation in a larger cohort is indicated.
Decadal patterns of disaster damage and recovery-to-damage dynamics in South Korea (2015–2024) with a context-sensitive comparison to Japan
Understanding disaster recovery is essential for effective risk management, yet recovery processes are often implicitly assumed to scale proportionally with disaster damage. This study examines disaster damage and recovery patterns in South Korea and Japan to assess whether recovery dynamics are linear, homogeneous, and comparable across contexts. Using official national statistics, we analyze annual disaster damage and recovery expenditure in South Korea from 2015 to 2024, disaggregated by hazard type and administrative region, and compare these patterns with disaster-related fatalities in Japan from 2015 to 2023. For South Korea, results show substantial interannual variability in recovery expenditure, while statistical analysis indicates a strong and approximately proportional relationship between damage and recovery at the aggregate level. Hazard-specific analysis reveals variation in recovery intensity across disaster types, while regional analysis highlights notable spatial disparities. Extreme disaster years exhibit deviations from proportional scaling, suggesting that large events can trigger additional recovery processes beyond direct asset restoration. The cross-national comparison illustrates that disaster response indicators show different temporal patterns between South Korea and Japan when aligned with national disaster management priorities. While recovery-to-damage ratios capture fiscal recovery intensity in South Korea, disaster-related fatalities reflect the human impacts emphasized in Japan. Comparisons using scaled indicators further show that temporal response patterns do not peak synchronously across the two countries, underscoring structural differences in disaster management systems. Overall, the findings suggest that disaster recovery is a context-dependent process shaped by hazard characteristics, spatial conditions, and institutional priorities, with variability emerging around an underlying proportional relationship. Meaningful international comparisons therefore require indicator choices sensitive to national frameworks rather than uniform metrics. This study provides empirical evidence supporting a more nuanced approach to analyzing and comparing disaster recovery across countries.
Identifying key factors in building fires: A novel approach fusing K-shell entropy gravity
Building fire key factors are the fundamental control variables that govern both the initiation of fires and dynamics of propagation. The accurate identification of key factors in building fires is crucial for enhancing the effectiveness of fire prevention strategies. To improve the accuracy of key factor identification in building fires, a novel K-shell Entropy Gravity (KEG) algorithm that integrates multiple topological metrics is proposed in this study. First, a complex network is constructed to characterize the relationships among accident factors, where nodes represent influencing factors and edges denote their co-occurrence in fire incidents. Subsequently, considering the positional importance and core connectivity of nodes, the information influence and irreplaceability of nodes, as well as the collaborative coupling and nonlinear characteristic among multiple indicators, a composite attribute integrating K-shell value, information entropy difference, and total shortest path length is developed to quantify node importance, thereby capturing both the local coreness and the global influence of nodes within the network. Then, these metrics are incorporated into an established gravity-based model to comprehensively assess the influential scope of each node, and the results are employed to identify the key factors. Finally, the proposed method is compared with baseline methods based on the Susceptible–Infected–Recovered (SIR) model and network robustness evaluation using the California Building Fire Dataset (2012–2024). In addition, a sensitivity analysis is performed to investigate how the removal of key factors affects accident propagation. To further verify the robustness of this method, fire data from Alaska are applied for comparison, and an ablation experiment is designed. The results indicate that the KEG algorithm achieves superior accuracy in identifying critical factors and offers a reliable analytical tool for developing targeted fire prevention and mitigation strategies.
Seasonal variation in species composition, deltamethrin susceptibility, and kdr mutations in anopheles mosquitoes in Northwest Ethiopia
Background Anopheles mosquitoes are the main vectors of malaria. Effective vector control depends on understanding their species composition, behavior, distribution, and insecticide resistance. This study investigated Anopheles species composition, susceptibility to deltamethrin, and the frequency of knockdown resistance ( kdr ) mutations in Maksegnit and Gendawuha, Northwest Ethiopia. Methods Anopheles larvae and pupae were collected from breeding sites during the rainy and post-rainy seasons and reared to adults under field insectary conditions following WHO guidelines. In addition, adult mosquitoes were collected from houses near larval habitats. Only field-derived mosquito populations were used in this study. Adult females (3–5 days old) reared from field-collected larvae were tested for susceptibility to 0.05% deltamethrin using WHO bioassays. Based on bioassay outcomes, mosquitoes were classified as phenotypically susceptible (died after exposure) or resistant (survived exposure), while field-collected adults represented an unexposed group. A total of 480 mosquitoes (160 resistant, 160 susceptible, and 160 field-collected unexposed adults) were subjected to genomic DNA extraction. Species identification and detection of knockdown resistance ( kdr ) mutations (L1014F and L1014S) were performed using PCR. Results WHO bioassays conducted on 776 mosquitoes revealed confirmed resistance to deltamethrin, with mortality rates ranging from 48.5% to 72.5% (overall resistance: 37.5%). Resistance intensity exhibited significant variation, peaking after the rainy season and showing a higher prevalence in Maksegnit compared to Gendawuha (p < 0.05). Molecular identification of 480 mosquitoes showed that Anopheles arabiensis was the predominant species (93%, 446/480), followed by An. pharoensis (6%, 29/480) and An. stephensi (1%, z/480), with the latter detected for the first time in Gendawuha. Regarding kdr mutation status, genotypic analysis showed that the L1014F mutation was the predominant allele, particularly among phenotypically resistant mosquitoes (67.8%), while lower frequencies were observed in susceptible (45.8%) and unexposed field-collected groups (61.4%). Conversely, the L1014S mutation was detected at low frequency (≤12.3%) and was restricted exclusively to the Maksegnit population. Conclusion Anopheles arabiensis predominated, with confirmed resistance to deltamethrin, particularly in the post-rainy season. The L1014F kdr mutation was prevalent, while L1014S kdr mutation was rare. Detection of Anopheles stephensi highlights emerging risks, underscoring the need for season-specific resistance monitoring and integrated control strategies .
Leveraging nonlinear relationships and interactions to improve 30-day pneumonia readmission machine learning models
Background Research is needed to develop more accurate readmission prediction models that identify patients at the highest risk of readmission after their initial pneumonia hospitalization. Improving prediction accuracy will support the implementation of more effective, personalized interventions to lower readmission rates. Published models tend to rely on traditional methods or advanced machine learning models that exclude continuous variables, overlooking opportunities to uncover nonlinear relationships and interactions. In response, we used electronic medical record (EMR) data, including continuous variables such as vitals, alongside more advanced machine learning (ML) models. Methods Using EMR data from a single academic medical center, we identified adults with initial pneumonia admissions between April 2018 and February 2024. We predicted 30-day readmission using eXtreme Gradient Boosting (XGBoost) and deep neural networks, and compared their performance with that of traditional logistic regression. Results We identified 2,752 patients admitted with pneumonia during the study period (mean age = 70.0 years, 49.1% female). The 30-day readmission rate was 9.9%. The average AUROC for our ML models ranged from 0.62 to 0.64, and AUPRC was 0.15 to 0.16, comparable to traditional logistic regression (0.63 and 0.17, respectively). Previously underemphasized predictors included drug abuse and BUN values. Conclusion Using more advanced machine learning models and continuous variables yielded similar performance to logistic regression models. However, we identified previously understated predictors of readmission after pneumonia hospitalization. Future efforts should focus on gathering important data not readily available in EMR, such as social determinants of health, to potentially enhance the models.
Ceftibuten-polymyxin B combination alters resistance and cell wall gene expression in multidrug-resistant Klebsiella pneumoniae
Background Multidrug-resistant Klebsiella pneumoniae , including carbapenem- and polymyxin-resistant strains, poses a major public health threat by severely limiting therapeutic options. Although ceftibuten (CTB) and polymyxin B (PMB) show evidence of synergistic activity, their mechanisms of action remain unclear. In this context, this study evaluated the combined effect of CTB and PMB on the expression of genes involved in cell wall synthesis and antimicrobial resistance in K. pneumoniae . Methods Protein sequences of selected resistance- and cell wall-related genes were retrieved from UniProt and analyzed in silico for conserved domains, motifs, localization (PSORTb), and pathways (KEGG). The effects of CTB/PMB, alone and in combination, were evaluated on the expression of genes involved in cell wall synthesis regulation ( ftsL, dacA, and dacC ) and antimicrobial resistance mechanisms ( pagP, pagL, ampC) . The 16s gene was used as endogenous control. Bacterial cultures (1.5 × 10 6 CFU/mL) were incubated with CTB/PMB, PMB and CTB at 0.5× and 1 × minimum inhibitory concentrations (MIC) for 2 and 4 h, followed by mRNA extraction and gene expression analysis through qRT-PCR. Results In silico analyses revealed that pagP and pagL contain conserved domains associated with lipid A modification, while ampC and ftsL showed class C β-lactamase domains. DacA and dacC were linked to the PRK13482 domain of the cl44310 superfamily. Predicted localizations placed pagP/pagL in the outer membrane, ampC in the periplasm, and ftsL/dacA/dacC in the cytoplasmic membrane. KEGG annotation indicated that ftsI , dacC , ampC , and rtxB participate in essential pathways, including peptidoglycan biosynthesis and β-lactam resistance, highlighting their physiological and clinical relevance in K. pneumoniae . After 2 h of exposure, no significant changes were observed in the expression of the selected genes. However, after 4 h, dacA, ftsL, and pagP expression levels significantly increased in all groups treated with CTB/PMB. Additionally, dacC and pagL expression were upregulated in the group treated with the combination at 1 × MIC. Conclusions Thus, combined CTB/PMB exposure was associated with modulation of gene expression involved in cell wall synthesis and antimicrobial resistance, suggesting transcriptional adaptive responses under antimicrobial pressure. These findings provide preliminary molecular insights into the response of multidrug-resistant K. pneumoniae to CTB/PMB exposure.
Breaking barriers: Validation of a Spanish oral health knowledge tool to enhance patient-provider communication
Objectives This study aimed to develop and validate the Knowledge Related to Oral Health Literacy Spanish (KROHL- S) instrument to assess oral health knowledge among Spanish-speaking adults in the United States, a population facing significant oral health disparities. Design A cross-sectional study was conducted at NYU College of Dentistry. A convenience sample of 175 self-identified Spanish-speaking adults (70% female, mean age 49. 79 years) completed the orally administered KROHL- S questionnaire. Participants, mainly born outside the US (91. 9%), also completed the Comprehensive Measure of Oral Health Knowledge (CMOHK) and a single-item literacy screening tool in Spanish (SILS). Psychometric properties of the KROHL- S, including internal consistency (Cronbach’s alpha), discriminant validity (correlation with CMOHK), and known-group validity (comparison across education levels), were evaluated. Confirmatory factor analysis was used to test the original factor structure. Results The mean KROHL- S score was 8.34 (SD = 5.82), indicating a low level of oral health knowledge in the sample. Internal consistency for the overall KROHL- S was good (Cronbach’s alpha = 0.75), and interrater agreement was high. A moderate positive correlation was found between KROHL- S and CMOHK scores (r = 0.49, p < .0001). Participants with higher education levels showed significantly greater oral health knowledge on the KROHL- S. Confirmatory factor analysis suggested an average fit to the data (RMSEA = 0.064, CFI = 0.86, TLI = 0.83). Conclusion The KROHL- S could be used to assess oral health knowledge among Spanish-speaking adults and incorporates cultural and linguistic aspects, making it suitable for a wider range of individuals. KROHL-S offers a valuable tool for healthcare providers by not only helping identify individuals’ knowledge gaps to guide customized educational interventions but also helping enhance patient-provider communications.
Comprehensive chemical, morphological, thermal, and biological characterization of Agave tequilana extract and chitosan-based dissolving microneedle arrays
Dissolving microneedles have gained attention as minimally invasive platforms for transdermal research applications. In this study, chitosan‑based dissolving microneedle arrays incorporating a hydroalcoholic extract of Agave tequilana root were formulated and systematically characterized. Chemical profiling by UHPLC-ESI-Orbitrap-MS revealed a diverse phytochemical composition dominated by phenolic acids, particularly rosmarinic acid. Morphological and structural analyses showed that extract incorporation induced concentration‑dependent changes in microneedle geometry: arrays containing 0.25% extract preserved tip sharpness, whereas a 0.50% loading led to surface roughening and partial tip deformation. Thermal analyses demonstrated extract‑dependent modifications in material degradation behavior, consistent with interactions between chitosan and extract constituents. Biological assays confirmed that the agave extract exhibits high antioxidant capacity, moderate tyrosinase inhibition, and inhibitory activity against collagenase and hyaluronidase. Following incorporation into the microneedle arrays, antioxidant activity and inhibitory effects against tyrosinase and hyaluronidase were retained, while collagenase inhibition was reduced, particularly in the 0.25% formulation. In vitro cytotoxicity assays indicated biocompatibility toward HaCaT keratinocytes and concentration-dependent selective cytotoxicity in A375 melanoma cells. Taken together, these findings indicate that extract loading is a critical parameter influencing structural preservation and in vitro bioactivity of chitosan‑based dissolving microneedles. Further studies addressing mechanical performance, insertion behavior, matrix dissolution, and skin permeation are required to evaluate the functional reliability of this system.
Prevalence and incidence of balance disorders in community-dwelling older adults: Protocol for the EPIBAS epidemiological balance study
Background Poor balance leads to falls, which can cause a loss of personal autonomy and reduced quality of life. Epidemiological studies of balance disorders (BDs) are limited. Identifying their prevalence and accessible diagnostic markers is crucial for prevention and monitoring. Aims 1) Assess the prevalence of BDs in men and women aged 65–72 using posturography and different balance tests, and track the annual incidence of BD; 2) Analyze the association between retinal microvasculature abnormalities and BD; 3) Evaluate the effectiveness of the Wii Balance Board™ for balance assessments compared to posturography; 4) Explore whether knee extensor strength and a combined measure of physical and cognitive function can serve as predictors for BD and fall risk: and 5) Conduct an external validation of the Health Assessment Tool (HAT) in the Spanish population. Methods Two-phase, observationals study. Phase I: Descriptive, cross-sectional. Phase II: Follow-up of cohorts at 18 months. Sample: 1,316 people aged 65–75 residing in Mataró (Barcelona, Spain) shall be included in the study, excluding individuals who cannot walk independently. They shall undergo posturography, retinal photography, knee extensor strength assessment, as well as the Tinetti Test, Timed Up and Go test, Unipedal stance test, Short Physical Performance Battery (SPPB), and balance assessment using the Nintendo Wii at baseline and at the end of the follow-up period. Bimonthly phone calls shall be made to detect the occurrence of falls. Applicability and relevance BDs are underdiagnosed and under-treated, and current awareness only scratches the surface. Expanding knowledge in this field is essential to avoid the loss of functional autonomy in individuals. Doing so will make it possible to develop specific preventive measures for the population at greatest risk of falls, thus making the approach to this significant geriatric syndrome more efficient. The EPIBAS study is registered on Clinicaltrials.gov under the code NCT06965660.
Longitudinal employment patterns and parental health: A cross-country look
Study aims Using a cross-country lens, we investigate the links between longitudinal work trajectories and health among parents with children under age 18. Background Employment serves as a valuable resource, affording us a decent standard of living. The rising dominance of digital and technology, together with the service economy since the 1980s, has transformed the utility of employment from a resource to a vulnerability, subjecting more families to uncertain, unstable, and insecure work. Nonstandard work schedules or shiftwork, which often fall outside regular 9-to-5 daytime hours and can be unpredictable, carry potential health consequences. Methods Using the longitudinal data from Australia (HILDA), Germany (SOEP), the UK (UKHLS), and the US (NLSY79), we used sequence analysis to first chart parental work schedule patterns between three stages of the life course, 25–34, 35–44, and 45–54, to show the changes and transitions in work patterns. We then conducted multivariate regression analysis to examine how variations in parental work patterns may shape individual health (i.e., physical and mental health) at ages 35/40, 45/50, and 55/60 while controlling for a rich set of sociodemographic characteristics. Results Our sequence analyses uncovered roughly 4–6 work patterns during those three periods, revealing the heterogeneities of parental work trajectories that might correspond to childrearing demands and their sociodemographic backgrounds. We also found that mainly not-working pattern or volatile work arrangements (e.g., switching between daytime and non-daytime hours) were associated with significantly poorer physical and mental health; however, the persistence and magnitude of these associations varied by country. Conclusions This study advances our understanding of the critical role of employment in our health from a cross-country perspective and bears important implications for the intergenerational transmission of employment and health vulnerabilities.
The application of large language models in bariatric surgery: A scoping review
Background Exploratory applications of large language models within the specialized field of metabolic and bariatric surgery have begun to emerge. Nevertheless, existing research remains fragmented, lacking comprehensive integration. Objective To conduct a scoping review of studies on the application of large language models in the field of metabolic and bariatric surgery, aiming to provide a reference for clinical practice and future research. Methods This scoping review adhered to the Joanna Briggs Institute methodological framework and followed the preferred reporting items for systematic reviews and meta-Analyses extension for scoping reviews (PRISMA-ScR) guidelines.PubMed, Web of Science, The Cochrane Library, Embase, CINAHL, CNKI, Wanfang, and VIP databases were searched for relevant studies, with the search timeframe from database inception to November 2025. The included literature was summarized and analyzed. Results A total of 21 English-language studies were included. LLMs were primarily applied in scenarios such as patient education and information consultation, clinical decision support, and professional knowledge assessment. While LLMs performed well in information-provision tasks, they showed low consistency with expert opinions in complex clinical tasks such as individualized surgical recommendations. Performance varied across different models, with GPT-4 generally demonstrating superior performance, and domain-specific models showing professional potential. Current research still faces challenges regarding information accuracy, readability, and clinical applicability. Conclusion Large language models hold auxiliary potential in the field of metabolic and bariatric surgery, particularly for knowledge dissemination and patient education. However, their reliability in complex clinical decision-making remains limited. Future efforts should focus on conducting high-quality studies, advancing model specialization and standardized evaluation, and exploring safe and effective human-AI collaboration models.
Genomic insights into population structure and adaptive variation of Pimelodus yuma and Pimelodus grosskopfii in the Magdalena-Cauca Basin
The biodiversity of the Magdalena–Cauca Basin, Colombia’s main fluvial system, is under severe threat from anthropogenic activities, imperiling endemic fish species such as Pimelodus yuma and Pimelodus grosskopfii . Using a population genomic approach based on single nucleotide polymorphisms (SNPs), we analyzed 64 individuals of P. grosskopfii and 57 individuals of P. yuma collected across ~1,600 km of the Magdalena–Cauca Basin. We identified two coexisting genetic stocks in both species, maintained by restricted gene flow that is associated with adaptive divergence rather than geographic distribution. Selection pressures, likely linked to the basin’s bimodal hydrological regime, were detected as major drivers of genetic structure. Historical demographic reconstruction analyses indicate that stock 1 in both P. grosskopfii and P. yuma was established in the basin during the Late Miocene–Pliocene (~4.5–5.5 MYA), with P. grosskopfii exhibiting an early expansion followed by long-term stability up to the present, while P. yuma maintained a stable population size until a recent decline. Stock 2 in both species was established during the Early Pleistocene (~1.7–2.5 MYA), followed by expansion and stability in P. grosskopfii , and a stable population size followed by a contraction–recovery–expansion dynamic in P. yuma , suggesting long-term persistence of neutral/adaptive processes shaping these stocks. Each stock should be considered a Management and Adaptive Unit, highlighting the need for targeted conservation actions and broader strategies to ensure their persistence under ongoing environmental and anthropogenic pressures in the Magdalena–Cauca Basin.
ICU-acquired infections and mortality in community-acquired pneumonia–induced sepsis: Insights from a transcriptomic analysis
Objectives To evaluate the association between ICU-acquired infections and 28-day mortality in pneumonia-induced sepsis and to explore associated immune-related gene expression patterns. Methods A secondary analysis was performed using the publicly available GSE65682 dataset, including adult ICU patients with sepsis secondary to community-acquired pneumonia (CAP) or hospital-acquired pneumonia (HAP). Patients were stratified based on the development of ICU-acquired infections. 28-day mortality and whole-blood leukocyte gene expression at ICU admission were compared between groups. Results Among 144 patients, 20 developed ICU-acquired infections. In the CAP subgroup, ICU-acquired infections were associated with numerically higher 28-day mortality compared to those without infection (45.5% vs. 18.2%, p = 0.05), although this finding should be interpreted with caution given the retrospective study design and limited sample size. In HAP patients, a similar pattern was not observed (22.2% vs. 19.6%). Transcriptomic analysis showed significant downregulation of the interleukin-7 receptor (IL7R) in CAP patients who developed ICU-acquired infections, with PRKACB and CD3D also demonstrating a downward trend. Conclusion These findings suggest that early immune dysregulation may be associated with an increased susceptibility to secondary infections and potentially worse outcomes among CAP patients. IL7R may represent a candidate signal of immune dysregulation and warrants further investigation and validation in future studies.
RNA metagenomic profiling of mosquito viromes associated with Vector-Borne diseases in Quebec, Canada
Mosquitoes harbor diverse viral communities, including both medically important arboviruses and insect-specific viruses, yet the viromes of mosquito populations in northern temperate regions remains poorly characterized. In this study, we used metagenomic sequencing to analyse pools of archived mosquito samples from Québec, Canada representing multiple species previously identified as arbovirus carriers. Our analyses identified 60 viral species, including three arboviruses, several insect-specific viruses, and multiple dual-host non-pathogenic viruses, revealing the rich viral diversity present in these mosquito populations. Phylogenetic analysis of complete viral genomes demonstrated genetic relationships with viruses reported from diverse geographic regions. We describe, a newly proposed bipartite Culex tombus- like virus and report the complete resolution of thirty-five viral genomic sequences. These results highlight the utility of metagenomic approaches for comprehensive characterization of the mosquito virome and underscore their potential to enhance surveillance of emerging arboviruses, including West Nile virus, in Québec and similar northern ecosystems.
Association of Brachial-Ankle pulse pressure with coronary artery stenosis severity: A sex-specific cross-sectional study in Chinese adults
Objectives To investigate the association between brachial and ankle pulse pressure and the severity of coronary artery stenosis, as well as to explore sex-specific differences in these associations. Methods A total of 218 patients who attended a tertiary hospital in China from 1 July 2023–31 January 2024 were selected for the study. The brachial artery pulse pressure, ankle artery pulse pressure, degree of coronary artery stenosis, and the number of major vascular lesion branches were standardized and measured. Multiple logistic regression and receiver operating characteristic curves were employed for analysis. Results Pulse pressure values at all four measurement sites (left and right brachial, left and right ankle) were significantly higher in the severe coronary stenosis group (T3) compared with the mild stenosis group (T1; all P < 0.001). Multivariate logistic regression analysis showed that left brachial pulse pressure (LPP) was independently associated with severe coronary stenosis (OR: 0.048, 95% CI: 0.010–0.227, P = 0.01). ROC analysis revealed that LPP had favorable predictive performance for severe coronary stenosis, with AUC values of 0.862 in men and 0.854 in women. Gender differences were observed in ankle pulse pressure: right ankle PP showed numerically higher AUC values in men (0.847), while left ankle PP showed numerically higher AUC values in women (0.842). Conclusion Depending on gender and the patient’s specific condition, brachial and ankle pulse pressure are critical in assessing coronary stenosis. Site-specific pulse pressure measurements may help identify patients at higher risk of coronary stenosis, enabling effective interventions to better safeguard their cardiovascular health.
Baseline endocrine factors influencing live birth outcomes in Chinese infertile women undergoing their first fresh IVF cycle: A multistate model-based cohort study
Conventional in vitro fertilization (IVF) outcome prediction is limited by static, single-endpoint analyses. We aimed to overcome this by using a multistate model to dissect the stage-specific and, crucially, the non-linear influence of endocrine factors across the entire pregnancy continuum in a large-scale cohort. We applied multistate regression models to a large cohort of 12,674 women undergoing their first fresh IVF cycle. This advanced method allowed us to analyze three sequential transitions (from infertility to biochemical pregnancy, from biochemical pregnancy to clinical pregnancy, and ultimately to live birth) and test for non-linear effects of baseline hormones, including anti-Müllerian hormone (AMH), luteinizing hormone (LH), and antral follicle count (AFC), on the hazard of success at each stage. The principal finding was a significant non-linear relationship between baseline AMH, LH, and AFC and pregnancy success (P < 0.05 for non-linearity). This directly challenges the “higher is better” paradigm, revealing that optimal hormonal “windows”, not just maximum levels, are linked to clinical success. The multistate model further distinguished AMH and LH as robust predictors across all stages, while AFC’s predictive power was confined to achieving initial pregnancy. The predictive value of baseline hormones in IVF is fundamentally non-linear. Our use of a multistate model demonstrates that while AMH and LH are consistent predictors for the entire pregnancy journey, their clinical interpretation must shift from a linear scale to identifying optimal ranges. This finding provides a more precise scientific basis to personalize ART treatment and improve live birth rates.
Numerical and experimental assessment of hydrogen enrichment effects on ci engine characteristics fuelled with dual biodiesel blends: A comprehensive study
The growing need for energy around the world is putting pressure on established power sources like fossil fuels, making renewable energy solutions more concern. The high calorific value of hydrogen has made it an attractive technique for increasing combustion rates. To get the best possible results from a dual biodiesel blend of juliflora and kapok, this research seeks to improve the hydrogen enrichment ratio. When compared to diesel, the combined effects of 12H 2 + JK B20 increased BTE by 11.5%, CP by 6.9%, and HRR by 5.9%. The use of H 2 and JK B20 improved combustion, leading to a decrease of 8.5% in BSFC, 10.9% in CO and HC emissions, 11.5% in smoke, and 14.6% in both. The increase in NOx emissions is a result of the trade-off. The RSM results demonstrate that the test blend B20, which included 12% H 2 at 100% load, exhibited an attractiveness index of 0.995. An effective and trustworthy prediction framework for optimizing CI engine properties, the ANN model was fitted using experimental data and validated. Sustainable transportation and environmental protection stand to benefit greatly from the synergistic effects of H 2 enrichment and dual biodiesel.
J-shaped relationship between stress hyperglycemia ratio and delirium risk in critically ill patients: A population-based study
Background The incidence of delirium in critically ill patients is strongly correlated with poor prognosis. The stress hyperglycemic ratio has emerged as a novel marker for assessing the response to acute hyperglycemia. Glycemic fluctuations during periods of stress play a crucial role in precipitating or directly causing delirium. However, the association between SHR and delirium in hospitalized ICU patients remains uncertain. Objective This study aimed to investigate the potential relationship between SHR and delirium in ICU patie nts and to examine possible subgroup differences in this association. Methods A total of 2,093 Intensive care unit (ICU) patients were included in this retrospective cohort study. The relationship between SHR and delirium was explored using multifactorial logistic regression, subgroup analyses, smoothed curve fitting, and threshold effect analysis models. Results Among the 2,093 participants, 59.05% were male and 40.95% were female, with a mean age of 64.19 ± 16.31 years. We identified a non-linear positive correlation between SHR and delirium, with an inflection point at 0.68, and the odds ratio (95% CI) after the inflection point was 1.88 (1.35, 2.62), P < 0.001. This interaction was statistically significant concerning the APACHE II scores and C-reactive protein levels at admission. Conclusion We found a nonlinear positive association between SHR and delirium. Our study highlights that managing SHR levels in critically ill patients may help to prevent or mitigate the development of delirium, emphasizing the potential value of SHR as an early intervention and precision treatment for delirium.
Mechanical response of high-porosity rocks under high triaxial confining pressure and experimental study of indentation tests
As oil and gas exploration and development continue to advance, ultra-deep and extra-deep formations have become the primary battleground for increasing global oil and gas reserves and production. The influence of high formation pressure on the macro-mechanical response of rock, particularly the mechanical response of indentations, remains unclear. This paper takes high-porosity rocks, which are commonly found in ultra-deep and extra-deep formations, as the research object. True triaxial compression test(TTCT) and conventional triaxial compression tests(CTCT) were conducted on high-porosity red sandstone to analyze brittle-ductile transition characteristics. A high confining pressure indentation test apparatus was developed to investigate the mechanical response of spherical indentation under high confining pressure. Numerical simulations were employed to analyze the underlying mechanism of this mechanical response. The results indicate that as the confining pressure increases, the sample undergoes three failure modes: shear failure, dilatant failure, and compactive cataclastic flow. The peak points of the stress‒strain curves present two distinct failure surfaces on the p-q meridian plane, and the location of these failure surfaces on the p-q meridian plane largely determines the stiffness response of the indentation. The indentation stiffness does not always increase with the increase of confining pressure, but rather exhibits a significant reduction near the brittle-ductile transition point. The release of residual stress leads to significant side crack propagation during indenter unloading, but this phenomenon is significantly inhibited under confining pressure. This paper offers preliminary insights into the mechanical behavior of oil and gas drilling scenarios under high confining pressures, such as those in ultra-deep and extra-deep formations, and provides an initial understanding of the indentation mechanical response of high-porosity rocks under high confining pressure.