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Comprehensive analysis of 73 Aconitum chloroplast genomes reveals their structure, codon usage bias, and phylogenetic relationships within family Ranunculaceae
Accuracy of owner-reported diagnoses for dogs enrolled in the Dog Aging Project as compared to veterinary electronic medical records
The objective of this project was to evaluate the accuracy of owner-reported health diagnoses in dogs compared to veterinary electronic medical records (VEMRs) using data from the Dog Aging Project (DAP), a longitudinal study of companion dogs in the United States. We hypothesized that owner-reported diagnoses would align more closely with VEMRs for acute or emergent conditions and less so for benign or self-limiting conditions. A subsample of 350 dogs was selected from the 2020 curated DAP dataset (n = 27,541). Dogs were included if they had VEMRs covering ≥ 85% of their life up to the time of survey completion. Forty-one dogs were excluded due to incomplete VEMRs, resulting in a final sample of 309 dogs included in this observational study comparing owner responses in the Health and Life Experience Survey (HLES) ( https://github.com/dogagingproject/dataRelease/tree/master/SurveyInstruments/HLES ) to VEMR data abstracted by masked reviewers. VEMR reviewers completed a survey mirroring HLES and identified supporting evidence for each diagnosis. Agreement between owner-reported and VEMR-verified diagnoses was assessed across 20 disease categories, with a focus on five target disease categories (TDCs). Agreement between owner and VEMR data was ≥ 90% in 10 of 20 disease categories. Agreement was highest in endocrine, immune, and “other” categories (99%) and lowest in dental/oral (44%). Among TDCs, orthopedic and traumatic conditions had higher agreement (>78%), while dermatologic and dental/oral categories showed the least. Owner-reported dog health data showed substantial concordance with VEMRs for many disease categories, supporting their utility in research. Thus, owner-reported diagnoses might provide a reliable and scalable supplement or alternative to VEMRs in veterinary research and epidemiology.
Haptic perception of 2.5D surface feature height
Identifying high-risk combinations of metformin during COVID-19
Background There is a lack of research addressing associations of antidiabetic drug combinations with COVID-19 deaths. We examined whether adding common second-line agents to metformin was associated with COVID-19 mortality risk to inform clinical decision-making when escalating diabetes treatment. Methods This is a nationwide retrospective analysis covering the years 2020 and 2021. Data from the National Diabetes Registry (CroDiab) were linked to primary healthcare data, Causes of Death Registry data, and the SARS-CoV-2 vaccination database. Multivariate logistic regression models were developed for each of the combinations to compare the combination with metformin monotherapy. To address confounders, inverse probability of treatment weighting (IPTW) analysis as well as analysis with stabilized weights was performed. Results Of 141014 analyzed patients, 1268 (0.90%) died of COVID-19 in 2 years. Weighted results of the drug combinations that showed statistically significant associations to COVID-19 death in comparison to metformin alone were metformin+DPP-4 inhibitor (OR 1.182, 95% CI 1.016–1.376), metformin+sulfonylurea (OR 1.195, 95% CI 1.015–1.406), and metformin+GLP-1 agonist (OR 2.992, 95% CI 2.117–4.229). Conclusions Some combinations of metformin with second-line antidiabetic drugs might require caution in the context of chronic diabetes mellitus type 2 therapy and COVID-19 related deaths. Findings should be interpreted as hypothesis-generating signals from real-world data rather than evidence of causal drug effects. Further research is needed, especially for metformin+GLP-1 agonist, as well as head-to-head comparisons of combinations therapies.
Aqueous Magnesium-Ion Battery Anode with 75,000 Cycles Lifespan
A conditioning factor selection framework considering sample heterogeneity in debris flow susceptibility mapping
Association between intrinsic capacity trajectories and risk of stroke incidence in middle-aged and older chinese adults: Evidence from a nationwide prospective cohort study based on CHARLS
Background Stroke is a major public health concern and a leading cause of disability and death in aging populations. Intrinsic capacity (IC), a concept introduced by the World Health Organization, reflects an individual's overall functional ability across multiple domains including cognition, psychological well-being, mobility, vitality, and sensory function. IC has emerged as a core metric within the healthy aging framework, but its prospective relationship with stroke risk remains unclear. A deeper understanding of this link may inform early, function-based prevention strategies. Methods This study used data from 10,751 participants aged 45 years or older from the China Health and Retirement Longitudinal Study (CHARLS). Cox proportional hazards models were used to estimate the association between IC and incident stroke, with stepwise adjustment for demographic, behavioral, and health-related covariates. Modeling IC as a continuous variable enabled examination of linear trends, while quartile-based classification allowed evaluation of potential non-linear associations and improved interpretability. Kaplan–Meier curves and log-rank tests were used to compare stroke-free survival across IC quartiles. Restricted cubic spline analysis was performed to explore the presence of a non-linear association between IC and stroke risk. Robustness was tested through sensitivity analyses excluding participants with baseline cognitive impairment and those aged ≥80 years. Statistical analyses were conducted using Stata and R. Results Over a 7-year follow-up, 243 participants (2.26%) experienced incident stroke. Stroke incidence decreased progressively with increasing IC levels, from 4.84% in the lowest quartile to 0.46% in the highest. Kaplan–Meier analysis showed significantly lower cumulative stroke incidence among individuals with higher IC (log-rank p < 0.001). In fully adjusted Cox models, each one-point increase in IC was associated with a 35.1% reduction in stroke risk (HR = 0.649; 95% CI: 0.599–0.702). Compared to the lowest IC quartile, the highest quartile had an 89.6% lower stroke risk (HR = 0.104; 95% CI: 0.055–0.197). Restricted cubic spline models confirmed a predominantly linear inverse association, with a steeper risk gradient at lower IC levels. Subgroup analyses revealed stronger protective associations in women, older adults (≥60 years), urban residents, and non-smokers or non-drinkers. Results remained consistent across all sensitivity analyses. Conclusions Higher IC was independently associated with a significantly reduced risk of incident stroke, underscoring IC's potential as a holistic, function-based indicator of cerebrovascular vulnerability. These findings provide empirical support for the World Health Organization's healthy aging framework, emphasizing IC as a modifiable reserve that reflects early, multidomain functional decline before clinical disease onset. Incorporating IC into routine screening and prevention strategies may enhance early identification of high-risk individuals and enable more targeted, function-oriented interventions, thereby promoting healthy aging and helping to reduce the future burden of stroke.
Genome-wide identification and characterization of CaM and CML gene family in chickpea (Cicer arietinum L.)
The frequency, risk factors and spatial distribution associated with having a diagnosis of leishmaniosis in dogs in the UK in 2019
Background Leishmaniosis in dogs is an important zoonotic disease, endemic in southern Europe but is increasingly being recorded in other parts of Europe including the UK. This study aimed to update the epidemiological knowledge of leishmaniosis in the UK dog population. Methods The estimated prevalence of leishmaniosis diagnosis in dogs under care at VetCompass UK participating practices in 2019 was calculated. Risk factor associations for leishmaniosis were investigated using mixed-effects multivariable logistic regression modelling. The spatial distribution of leishmaniosis was explored using standardised morbidity rates (SMR) at regional and county levels, and Moran’s I was used to identify significant spatial autocorrelation. Results The estimated annual prevalence was calculated as 0.0434% (95% CI 0.0427–0.0443) with 976 cases from this population of dogs (n = 2,250,741). Most of the dogs with leishmaniosis had originated from outside the UK (955/976, 97.9%) and of those, 60.8% (581) had already been diagnosed with leishmaniosis pre-import. In the risk factor analysis, the odds of leishmaniosis were higher in males (OR 1.29, 95% CI 1.12–1.49) and neutered dogs (OR 6.42, 95% CI 4.43–9.29) compared to female and entire dogs, respectively. Purebreds overall had lower odds of leishmaniosis compared to crossbreeds (OR 0.24, 95% CI 0.20–0.28) but there were specific breeds such as Brittany Spaniels (OR 53.0, 95% CI 25.3–111.1), Ibizan Hounds (OR 43.8, 95% CI 9.20–208.3) and English Pointers (OR 28.6, 95% CI 14.5–56.4) which had much higher odds of being a case compared to crossbreeds. Spatial analysis identified more leishmaniosis cases in southern England than were expected by random chance (SMR > 1). Conclusions This study identifies that imported animals are the commonest source of dogs having a leishmaniosis diagnosis. The breeds with very high odds for leishmaniosis may reflect selection bias towards breeds more likely to be imported, rescued or travelled from endemic areas rather than high intrinsic risk in these breeds towards leishmaniosis. These results support and update previous studies indicating that most cases are diagnosed in southern England.
Photocatalytic Direct Deoxytrifluoromethoxylation of Phenols
Modeling the impacts of climate-smart practices on soil–water interaction and wheat yield under climate change in central Ethiopia
Exploring measures of sustainability in the WHO Joint External Evaluation and the WOAH performance of veterinary services tools—A qualitative assessment of perceived usefulness and acceptability to one health and global health security experts
Introduction Amidst global policy reforms including the 2024 amendments to the International Health Regulations (IHR) and the ongoing Pandemic Agreement negotiations, there is a renewed emphasis on sustainability, equity, and multisectoral coordination in global health security. However, the operationalization of sustainability in core assessment tools—such as the WHO Joint External Evaluation (JEE) and the WOAH Performance of Veterinary Services (PVS)—remains poorly defined and underdeveloped, particularly as they relate to low- and middle-income countries (LMICs). Methods We conducted a qualitative study involving semi-structured interviews with 29 global experts across human, animal and environment health from both high and low/middle income countries affiliated with the One Health High-Level Expert Panel, the World Bank Pandemic Fund Technical Advisory Panel, and technical focal points from Quadripartite institutions. Using thematic analysis grounded in the Social Construction Framework and an adapted Schell et al. sustainability model, we explored how sustainability is conceptualized and measured across human, animal, and environmental health domains. Results Participants critiqued existing tools for framing sustainability narrowly, including their focus on short-term processes and compliance, rather than long-term outcomes, equity, or resilience. Sectoral and contextual differences emerged: human health experts emphasized workforce and financing; animal health experts stressed economic and institutional continuity; environmental health experts highlighted ecosystem resilience and intergenerational equity. LMIC respondents underscored the impact of donor dependency, weak local ownership, and limited transition planning. Several determinants of sustainability—such as financing, governance, workforce retention, and community engagement—are already measured in existing reporting tools but are not explicitly or coherently framed as sustainability indicators. Discussion We recommend that future iterations of JEE and PVS incorporate a clear definition of sustainability and explicitly integrate sustainability metrics, aligned with the revised IHR, the One Health Joint Plan of Action, relevant SDG targets and national planning cycles. Tools must also reflect sectoral and contextual nuances and integrate long-term monitoring frameworks that promote domestic accountability. In the field of One Health and GHS, strengthening the sustainability components of these tools is essential to build equitable and resilient health systems globally.
Ultrafast Relaxation of MLCT Excited States in Manganese Tricarbonyl Complexes: Insights from Polarization-Resolved Femtosecond X-ray Absorption Spectroscopy at the Mn and Br K-Edges
Heavy metal pollution and health risk assessment in surface waters impacted by pharmaceutical effluents in Gazipur and Narayanganj, Bangladesh
Increased secreted PLA2 in epithelial cells promotes the progression of chronic non-atrophic gastritis to chronic atrophic gastritis through the TGF-β signaling
Introduction The progression of Chronic gastritis seems to follow a pattern from chronic non-atrophic gastritis (CNAG) to chronic atrophic gastritis (CAG) to cancer, so it is particularly important to block key targets in disease progression. A gene that synthesizes secreted phospholipase A2, attracted our attention. Objectives To study whether phospholipase A2 group 10 (PLA2G10) in epithelial cells promote the progression of CNAG to CAG through the transforming growth factor-β (TGF-β) signaling. Methods We used RNA microarray and single-cell RNA sequencing datasets for bioinformatics analysis. The effects of PLA2G10 were verified by in vivo and in vitro experiments. The in vivo experiments used SD rats to establish a CNAG model for PLA2G10 and TGF-β intervention to observe the effects on gastric mucosal inflammation. In vitro experiments were conducted using human gastric mucosal epithelial cells (GES-1) for similar interventions. Results PLA2G10 inhibition led to the downregulation of TGF-β expression and attenuated the inflammatory response of the gastric mucosa. And the blockade of TGF-β signalling delayed the progression of CNAG to CAG, as evidenced by a reduction in inflammatory cell infiltration, a more regular cellular arrangement, and a reduction in collagen deposition. Conclusions Our study shows that PLA2G10 plays a key role in the progression of chronic gastritis and highlights the important role played by the TGF-β signalling pathway in this process.
Cobalt-Doping Unlocks Copper Self-Healing Chemistry in Copper Hexacyanoferrate for Long-Cycling Aqueous Mg-Ion Storage
Resveratrol alleviates neuropathic pain associated with restoration of mitochondrial fission–fusion balance in CCI mice
A novel multi objective grey wolf optimization fuzzy miner for process discovery: Incorporating robustness and explainability in model evaluation
Process mining provides methodologies for analyzing, monitoring, and improving processes based on event logs. This study introduces Fuzzy Multi-Objective Grey Wolf Optimization (Fuzzy MOGWO), which integrates fuzzy modeling with a multi-criteria metaheuristic optimization approach. The proposed framework simultaneously optimizes six metrics: Fitness, Precision, Generalization, Simplicity, Robustness, and Explainability with the latter two newly proposed to evaluate noise resilience and analyst interpretability. A normalized scoring mechanism, based on the L₂ norm of all metrics, ensures balanced evaluation across objectives. Fuzzy MOGWO is benchmarked against Alpha Miner, Inductive Miner, and Fuzzy Miner using 10 synthetic noise-free logs, 10 synthetic noisy logs with 5–20% injected noise, and 3 real-world logs. Under noise-free conditions, it achieved a normalized score of 0.329, surpassing the best baseline (0.288) by 14.24%. In noisy environments, its score (0.440) exceeded the top competitor (0.378) by 16.40%. On real-world logs, it outperformed competitors in 4 out of 6 metrics, compared to 2 out of 6 for the PSO-based miner. These results demonstrate substantially improved effectiveness, robust performance in the presence of noise, and enhanced interpretability, establishing Fuzzy MOGWO as a comprehensive and reliable solution for challenging process discovery tasks.