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Reducing plastic waste from cable ties in food packaging through microbiological testing and behavioral intervention informed by stakeholder perspectives
Identification of potential pathogenic genes associated with the comorbidity of rheumatoid arthritis and renal fibrosis using bioinformatics and machine learning
The effect of pre-transplant dialysis duration on the relationship between delayed graft function and recipient death
The impact of green spaces, urban settings, seasonal changes, and pollutants on dissemination of antimicrobial genes in air
Zone adaptive fuel mapping for high resolution wildfire spread forecasting
Abstract Extreme wildfire events (EWE), although a rare natural hazard, account for a substantial portion of global wildfire damage, requiring proactive anticipation and mitigation due to their increasing occurrence. Wildfire spread simulators are crucial for reducing damage, but they rely heavily on accurate fuel maps, which are often outdated, have low resolution, or are unavailable in many regions. While land cover maps are more up-to-date, high-resolution globally, and widely available, there is no universally accepted method to convert land cover maps into fuel maps. In this work, an automatic methodology for generating high-resolution fuel maps from land cover maps called zone-adaptive fuel mapping (ZAFM) is proposed. ZAFM is a consistent local approach that makes use of public resources to create a fuel map. The proposed methodology has been tested using, as a study case, an EWE that occurred in the north-east of Spain during the summer of 2022. To assess the accuracy of the proposed fuel mapping method, we compared the fire spread forecast using the ZAFM fuel map with fire evolutions based on different fuel maps derived from the land cover map of the study area. The accuracy assessment, based on the F2-score metric, reveals that ZAFM achieves the highest F2-score of approximately 0.90, while the F2-scores for the other fuel maps range from 0.78 to 0.89, with no individual simulation reaching 0.90. ZAFM was also evaluated against other publicly available fuel maps covering Catalonia, and once again achieved higher F2-scores in the case study simulations. These results highlight the superior predictive performance of ZAFM and underscore the importance of using up-to-date, high-resolution data to improve wildfire spread forecasts. Furthermore, since ZAFM relies on open-access data maps, it can be applied worldwide with any available high-resolution land cover map.
Immune cell profiling reveals diverse niches of immune residents of the enteric nervous system and potential neuroimmune interactions
Gastrointestinal (GI) neuroimmune interactions are crucial sensors and regulators of tissue homeostasis. Most enteric neurons reside within the myenteric plexus of the enteric nervous system in the muscular region, forming a structure called the muscularis externa . Despite established interactions between muscularis macrophages and neurons, the presence and function of other immune cell types remains poorly characterized. Here, we mapped the muscularis immune cell landscape, revealing that diverse cell types are present within distinct locations of the GI tract, and they lie in proximity to neuronal cell bodies and their axons. Using a hypothesis-free computational approach, we identify putative ligand–receptor interactions from publicly available single-cell RNA datasets and further validate one of these (App-CD74). This study provides a valuable reference to encourage new avenues of research underpinning enteric neuroimmune interactions as key contributors to GI homeostasis and diseases.
Deep reinforcement learning model for Multi-Ship collision avoidance decision making design implementation and performance analysis
Abstract This paper proposes a novel multi-ship collision avoidance decision-making model based on deep reinforcement learning (DRL). The model addresses the critical challenge of preventing ship collisions while maintaining efficient navigation in complex maritime environments. Our innovation lies in the integration of a comprehensive state representation capturing key inter-ship relationships, a reward function that dynamically balances safety, efficiency, and COLREGs compliance, and an enhanced DQN architecture with dueling networks and double Q-learning specifically optimized for maritime scenarios. Experimental results demonstrate that our approach significantly outperforms state-of-the-art DRL methods, achieving a 30.8% reduction in collision rates compared to recent multi-agent DRL implementations, 20% improvement in safety distances, and enhanced regulatory compliance across diverse scenarios. The model shows superior scalability in high-density traffic, with only 12.6% performance degradation compared to 18.4–45.2% for baseline methods. These advancements provide a promising solution for autonomous ship navigation and maritime safety enhancement.
Association between adherence to Mediterranean-DASH intervention for neurodegenerative delay diet and disease severity in patients with ulcerative colitis
Global trends, health inequalities, and projections in the burden of neglected tropical diseases and malaria from 1990 to 2021
How content complexity and sensory modality influence student satisfaction in art education
Abstract Art education plays a vital role in preserving cultural heritage and promoting sustainable development. However, growing curricular complexity and abstraction present challenges to student satisfaction, a key metric in educational sustainability. This study investigates how perceived content complexity and modality structure affect student satisfaction in art-related programs, drawing on Construal Level Theory (CLT) to explain the psychological mechanisms involved. Based on aggregated data from 73,368 students across 1524 academic programs in China, the results indicate that higher content complexity significantly reduces satisfaction. Moreover, a lower auditory–visual (A/V) ratio—indicating reduced emphasis on visual input—also decreases satisfaction but moderates the negative effect of content complexity. The findings suggest that cognitive-perceptual mechanisms play a central role in shaping students’ evaluative responses and offer implications for improving curriculum design and institutional strategies in art education.
How different life-history strategies respond to changing environments: a multi-decadal study of groundfish communities
Prevalence and clinical impact of severe anaemia in referral hospitals in southern Benin
Abstract Severe anaemia is a critical public health issue worldwide, disproportionately affecting children in Africa, where approximately 40% of children aged 6 to 59 months are impacted. It leads to significant hospital and post-hospital complications. However, there is a notable lack of research on its burden and clinical impact, particularly in Benin, where existing data are outdated. This study aims to assess the prevalence and impact of severe anaemia in two areas of perennial transmission in southern Benin. We conducted a retrospective cross-sectional study at two referral hospitals in Benin, Lagune Mother and Child University Hospital Centre (CHU-MEL) and the Departmental Hospital Centre-Zou (CHD-Z). Sociodemographic, clinical and biological information were extracted from medical records of patients admitted to paediatric ward in 2023, using a standardised questionnaire. Clinical severe anaemia was defined as anaemia with decompensation requiring blood transfusion, and biological severe anaemia as haemoglobin < 5 g/dl. A total of 7152 paediatric hospital records were included in the analysis (CHU-MEL = 4388; CHD-Z = 2764). The median (IQR, range) age was 32 (13–61; 1–228) months. Severe malaria (N = 3653/7152 [51.1%]) and clinical severe anaemia (3586/7152 [50.1%]) were the most common diagnoses with four out of five children (2836/3586 [79.0%]) clinically diagnosed with severe anaemia cases had malaria. In children with severe anaemia, the risk of death decreased slightly with year of age (aOR 0.95, 95% CI 0.92–0.99, p = 0.019). In contrast, severe malnutrition increased the risk of death (aOR 1.80, 95% CI 1.33–2.43, p < 0.001) being significant risk factors. Severe anaemia is a major contributor to paediatric hospital admissions, with severe malaria being a leading cause in these regions. This study highlights the critical need for a comprehensive management strategy for severe anaemia, particularly in the youngest children. An integrated strategy of effective malaria chemoprevention, such as post-discharge malaria chemotherapy combined with targeted nutritional interventions, are essential to mitigate mortality rates in areas with high malaria transmission, where the dual burden of malaria and nutritional deficiencies exacerbates paediatric morbidity and mortality.
Role of lysine acetylation-related genes in the diagnosis and prognosis of glioma
Artificial neural network-driven approaches to improved forecasting of disability care expenditures in an aging Kingdom of Saudi Arabia population
Winters restrict a climate change–driven butterfly range expansion despite rapid evolution of seasonal timing traits
Climate change pushes species toward higher latitudes and altitudes, but the proximate drivers of range expansions vary, and it is unclear whether evolution facilitates climate change–induced range changes. In a temporally replicated field experiment, we translocated wall brown butterflies ( Lasiommata megera ) descending from range interior and range margin populations to sites at 1) the range interior, 2) the range margin, and 3) beyond the current northern range edge. Thereby, we tested for local adaptation in seasonal timing and winter survival and evaluated to what extent local adaptation influences the ongoing, climate-driven range expansion. Almost all individuals from all populations entered diapause at an appropriate time, despite previously identified among-population variation in diapause induction thresholds. Caterpillars of northern descent, however, grew faster than those from southern populations at all field sites. This may be a countergradient adaptation to compensate for the short, northern growing seasons, but we found no evidence for prewinter body mass affecting winter survival. In fact, winter survival was low overall—extremely so at the beyond range site—regardless of population origin, indicating that the primary constraint to range expansion is an inability to adapt to winter conditions. Hence, although range-expanding wall browns show clear local evolution of two traits related to seasonal timing, these putative local adaptations likely do not contribute to range expansion, which is instead limited by winter survival. To predict future range changes, it will be important to distinguish between the traits that evolve during range expansion and those that set the range limit.
Mendelian randomization study revealed a gut microbiota-immune system-kidney junction axis in chronic kidney disease
Abstract The alterations of the gut microbiome and cytokine profiles and an elevated risk has correlated with kidney disease progression. However, the causal relationship between gut microbiota and chronic kidney disease (CKD) or related kidney function, and whether cytokines and immune cells act as mediators, remains unclear. Using genome-wide association studies (GWAS) data for CKD, estimated glomerular filtration rate (eGFR) and UACR (urinary albumin to creatinine) from the CKDGen consortium, microbiome data from the MiBioGen consortium and the Dutch Microbiome Project (DMP), 41 cytokine and 731 immune cell traits were identified from large-scale GWAS summary data. We performed two-sample Mendelian randomization (MR) analysis to analyses the causal relationships between gut microbiome, circulating cytokines, immune cells and CKD, eGFR and UACR. In addition, we investigated whether cytokines and immune cells are the mediating factor in the pathway from gut microbiome to CKD, eGFR and UACR. We demonstrated the causal relationships between 8 gut microbiotas in MiBioGen and 8 gut microbiota and 6 metabolism pathways in DMP with CKD, 7 gut microbiotas in MiBioGen and 7 gut microbiota and 3 metabolism pathways with eGFR and 4 gut microbiotas in MiBioGen and 10 gut microbiota and 3 metabolism pathways in DMP with UACR. Additionally, we identified 25 cytokine and immune cell characteristics associated with CKD, 18 with eGFR and 22 with UACR. Importantly, we identified no cytokine, but several immune cell properties that mediate the effects of microbiome on CKD, eGFR and UACR through mediation MR analysis. For instance, Alistipes indistinctus and Alistipes putredinis affects CKD via CD28 + CD45RA + CD8 + T cell. The mediation effects highlighted the intricate relationship between gut microbiome exposure, immune cell activity, and their combined influence on CKD. This data supports a causal effect of the gut microbiome on CKD, eGFR and UACR and underscores the value of MR in clarifying causal relationships identified in microbiome-wide association studies. Circulating immune cells may act as mediators in the pathway linking gut microbiota to CKD progression.