Montane red foxes (Vulpes vulpes ssp.) native to western North America are of broad conservation interest, occupying a narrow ecological niche and restricted to small, isolated populations across much of their distribution. Despite the need for robust information in guiding effective carnivore conservation, many aspects of montane red fox ecology are poorly understood due to their rarity. To improve ecological knowledge of Sierra Nevada red fox (V. v. necator), a montane red fox subspecies, we examined fox diet in an unstudied portion of their range in the central Cascades of Oregon, USA. In addition, we evaluated dietary overlap between montane red foxes and coyotes (Canis latrans), a presumably dominant carnivore that is expected to increase distributional overlap with montane red foxes under changing climatic regimes. We collected Sierra Nevada red fox and coyote scats via detection dog team surveys during 2017 in Oregon and used DNA metabarcoding to determine scat composition. Sierra Nevada red fox and coyote diets differed with respect to the most frequently occurring prey species and prey species that comprised the largest proportions of their diets (golden-mantled ground squirrel [Callospermophilus lateralis] and snowshoe hare [Lepus americanus], respectively). Despite some differences, Sierra Nevada red fox and coyote diets exhibited similar taxonomic richness and their dietary overlap was high (Pianka’s index = 0.74 via weighted percent occurrence, 0.69 via frequency of occurrence), with golden-mantled ground squirrel appearing to be an important prey item for both species. High dietary overlap suggests potential for competition between Sierra Nevada red foxes and coyotes where the two species occur sympatrically, which could be consequential for foxes in the future if spatial overlap indeed increases and results in niche compression. Our work addresses an aspect of data insufficiency for an imperiled species that can inform conservation strategies and species management.

The integration of large language models-cognitive assistants (LLM-CAs) in manufacturing within quality management systems (QMS – ISO 9001:2015) presents both transformative opportunities and significant challenges. This study systematically analysed 53 studies (2022–2024) to derive literature-based requirements for LLM-CAs in manufacturing within QMS according to the Humans, Technology, and Organization concept (HTO). Findings highlight persistent challenges, such as transparency, compliance risks, and workforce adaptation, with strong alignment between LLM-CAs and QMS principles. Requirements were categorized into HTO subsystems and their overlaps, ensuring a structured approach for seamless integration. As a result, the potential of LLM-CAs to enhance decision-making, operational efficiency, and human-centred governance within QMS is underscored. On that basis, an essential synergy between traditional practices in manufacturing such as QMS and novel technology is highlighted. This synergy represents a fundamental step to guarantee the deployment of LLM-CAs in manufacturing. Future research should explore stakeholder-driven validation, digital feedback loops, and LLM-CAs-driven continual improvement in manufacturing.

Tuberculosis-associated paradoxical immune reconstitution inflammatory syndrome in an HIV-negative patient presenting with a recurrent pleural effusion successfully treated with prednisolone:

Understanding rainfall partitioning and streamflow generation processes have become indispensable due to the increasing frequency of hydrological extremes globally. River catchments in the tropics are particularly vulnerable to changing characteristics of rainfall and decoding the rainfall partitioning into pre-event and event water becomes more critical in tropical catchments where runoff generation processes, are often poorly understood. In this context, the present study is aimed at understanding the runoff generation processes in Vamanapuram river – a humid tropical forested experimental catchment in the Southern Western Ghats, India utilizing high-resolution (30 min) hydrological measurements. Data from 78 and 76 storm events (during 2022 and 2023) were used for storm hydrograph separation using the conductivity mass balance method at Kallar River Gauging Station (KRGS) and Chettachal River Gauging Station (CRGS), respectively. Both KRGS and CRGS are found to be sub-surface dominated catchments irrespective of season. In 98% and 96% of the storm events respectively at KRGS and CRGS, pre-event water dominated the hydrograph.. The seasonality in the PEWF(avg) and Pre-Event Water Fraction at peak (PEWF(at peak)) has higher values in the dry period and lower values in the wet period. PEWF(avg) decreases from 0.82 to 0.80, and PEWF(at peak) from 0.76 to 0.73 from upstream to downstream reaches respectively. The beta distribution fits well the temporal variability in the PEWF(avg) and PEWF(at peak) at both river gauging stations. The effect of differential precipitation forcing in the subsequent year’s storm PEWFs has been studied, and it was observed that higher precipitation forcing results in higher PEWF at CRGS. However, the effect of precipitation forcing is not seen at KGRS, possibly due to significantly different geomorphic characteristics and higher forest cover. A more extended period of hydrological data in catchments with diverse climatic and geological settings will provide a better understanding on the effect of precipitation forcing on catchment rainfall partitioning and thus improve conceptualization of rainfall-runoff models.

Trait-based approaches provide robust tools to understand how spatial and temporal environmental variability shapes community assembly and functional diversity. Here, we investigated the thermal tolerance of three cereal aphid species (Sitobion avenae, Rhopalosiphum padi, and Metopolophium dirhodum) across a 1200 km longitudinal gradient from western to eastern Europe, comparing autumn and spring populations. We tested whether: 1) eastern populations (experiencing larger seasonality and harsher winters) exhibited broader thermal tolerance ranges than western ones; 2) autumn aphids were more tolerant to cold and less tolerant to heat comparing with spring aphids; and (3) larger seasonality drove trait convergence within the aphid guild. Our results revealed that thermal tolerance varied across the longitudinal gradient, with autumn populations in eastern Europe with larger temperature variability displaying broader thermal ranges, supporting the Climatic Variability Hypothesis. However, spring populations exhibited a counter-gradient pattern, where aphids from regions with milder winter (western Europe) had higher cold tolerance than those from regions with harsher winter (eastern Europe), likely explained by different overwintering strategies between western (as active adults) and eastern Europe population (as diapausing eggs). Seasonal differences were pronounced: autumn aphids were less heat-tolerant than spring individuals. At the guild level, eastern populations exhibited trait convergence driven by large intraspecific variation, while western populations showed interspecific divergence, suggesting environmental filtering shaped thermal traits differently across climates. These findings highlighted the importance of seasonal and geographic context in thermal adaptation. Increasing climate variability may drive functional homogenization in ectotherm communities, potentially stabilizing populations but reducing long-term resilience. Our study underscored the need to integrate seasonal dynamics and intraspecific variation when predicting species responses to climate change, emphasizing how temperature variability - not just warming - reshaped insect communities.

The photorespiratory CO 2 compensation point (Γ*) and the rate of CO 2 release in the light (D L) are critical parameters for understanding the carbon dynamics of C 3 plants. These two parameters can be derived from the widely-used Laisk method as the intercept of linear regression lines fitted to net assimilation rates (A net) versus chloroplast CO 2 partial pressures (C c) obtained at different low-irradiance levels. However, photosynthetic theory indicates curvature in the A net-C c relationship which conflicts with the use of linear relationships for analysis. We, therefore, systematically evaluated the limitations of the use of linear relationships across temperatures from 5 to 40 °C and quantified the sensitivity of errors in Γ* and D L estimates to the selected C c range. We found that wide CO 2 ranges, especially when they exclude the actual Γ*, can introduce substantial biases in parameter estimation with linear regressions, particularly at lower temperatures. It can lead to marked underestimates of Γ*, and biologically unrealistic D L. We propose refining the Laisk method by using a photosynthesis model to analyse data. The model better represents the non-linear A net-C c relationship and yields consistent Γ* and D L estimates, regardless of the CO 2 range used.

MicroRNA-122 (miR-122) is a sensitive biomarker for paracetamol-induced liver injury. This study evaluated Dynamic Chemical Labelling (DCL) combined with a clinical laboratory assay to quantify miR-122 in human serum, as a proof-of-concept for hospital use. Serum was collected from 19 healthy individuals and 19 patients with paracetamol drug-induced liver injury (DILI). miR-122 was labelled with a biotinylated SMART-Base and quantified using a multiplex, bead-based, fluorescence detection system. Median miR-122 concentration was 233.4pg/ml in DILI patients vs. 15.2pg/ml in controls. Concentrations ranged from 17.5–1376.9pg/ml (DILI) and 2.2–67.2pg/ml (controls). The Mann-Whitney U test showed significant group differences (p < 0.0001). ROC analysis yielded an AUC of 0.96, with a 29.7pg/ml cut-off providing 92.6% sensitivity and 89.4% specificity. miR-122 moderately correlated with ALT (r=0.56, p=0.03). DCL with fluorescence detection is a promising clinical tool for miR-122 quantification.

As catastrophic wildfires increasingly devastate the interior landscapes of British Columbia, Canada, conventional approaches to post-wildfire recovery often overlook Indigenous values, knowledge systems, and food sovereignty. In collaboration with six Northern St’át’imc communities and guided by the “walking on two legs” framework, which brings together Indigenous and Western knowledge systems led by Indigenous worldview, we reanalyzed post-wildfire vegetation trajectory data from the McKay Creek wildfire. We replaced colonial-era “native/non-native” plant classifications with culturally grounded categories to better reflect Indigenous wildfire recovery priorities. Vegetation trajectories were based on percent cover data collected across 80 plots, stratified by burn severity and pre-wildfire invasive plant presence. Our results show that conventional plant classifications may obscure critical vulnerabilities in traditional plant food systems and protein sources. While ”native” plant cover exceeded 25% across all treatments, our cultural plant classifications ranged from just 7% to 18%. While elevation emerged as a key factor in post-fire vegetation dynamics, government-defined “Mule deer forage” plant classification indicated increased forage at higher elevations, while the Indigenous-informed classification, “Mule deer preferred forage” showed the opposite trend. These findings demonstrate that classifying plants by cultural knowledges reveals a more accurate picture of post-wildfire recovery. Conventional plant classifications may overestimate ecosystem resilience and thus overlook areas requiring urgent intervention. Indigenizing Western scientific approaches can strengthen ecological restoration by aligning data interpretation with Indigenous sovereignty and community-led priorities. This study offers a concrete model for advancing culturally appropriate wildfire recovery while supporting the implementation of legal obligations to protect Indigenous food sovereignty under Section 35 of the Constitution Act, 1982, and British Columbia’s Declaration on the Rights of Indigenous Peoples Act (DRIPA). Our study suggests that reframing plant classification by Indigenous values not only deepens understanding of post-wildfire recovery but also supports more effective, place-based decision-making for long-term ecosystem stewardship.

Quantifying phenotypic plasticity, the capacity of organisms to adjust phenotypes in response to environmental changes is essential for understanding ecological and physiological resilience under climate stress. However, existing methods often lack flexibility and precision, especially under multi-dimensional environmental conditions. Here, we introduce a novel statistical approach, the Environmentally Standardised Plasticity Index (*ESPI), which integrates Hedges’ g for effect size quantification and Euclidean distance for characterizing environmental variability. We validated this method using both simulated datasets and empirical data from the marine diatom Thalassiosira weissflogii, investigating five key phenotypic traits over seven days under varying temperature, irradiance, and nutrient conditions. Our findings indicate distinct temporal patterns of plasticity: certain traits, such as photosynthetic efficiency (alpha) and saturation irradiance (Ek), demonstrated high initial plasticity followed by gradual acclimation, whereas others, like pigment composition, exhibited delayed phenotypic responses. This temporal dimension highlights the critical role of the growth phase in shaping plasticity responses. The proposed *ESPI method provides a robust, intuitive, and versatile framework for quantifying phenotypic plasticity, offering significant advances in predicting organismal adaptation to environmental change.

The loss and fragmentation of habitats caused by anthropogenic activities in the last decades has affected foraging habitat quality and, therefore, foraging success (food quantity, quality and foraging range) of many animals, including many pollinators. Honeybees (Apis mellifera) are important pollinators of many plant species, and habitat change has also affected their ability to collect the resources they need to maintain the colony. Two important biological traits that might be affected by land use are body size and fat stores, which have the potential to affect body condition, and therefore success, and colony health. However, few studies have investigated these traits in different landscapes and different times of year. We surveyed 47 sites in three different landscape types (agriculture, urban and mixed habitats) in south-western Germany. We measured honeybee body size, wing wear and analysed body fat quantity and composition using GC-MS in the spring, summer and autumn. We found that summer honeybees were smaller in urban and mixed habitats, they showed the greatest wing wear, but they had 18.4-21.3% larger fat stores compared to agricultural sites. Bees in agricultural habitats experienced a drop in fat stores in summer, while body size remained unaffected. In autumn, just before honeybees enter the inactive winter period, bees in urban and mixed areas experienced a drop in fat stores. Wing length decreased from spring to autumn irrespective of habitat type. Our findings indicate that bees in agricultural settings experience physiological challenges in a central European region in summer, possibly because urban and mixed habitats provide better nutritional conditions during summer. Our findings, thus, confirm that honeybees undergo morphological and physiological changes in response to land use and season, which could impact their physiological condition and winter survival.

Lithium-ion batteries (LIBs) have dominated the energy storage field due to their high energy density, long cycle life, and environmental friendliness. In this study, we systematically investigated the electrochemical properties of phosphorus (P)-doped γ-graphyne as a promising LIBs anode material using density functional theory calculations. The formation energy and cohesive energy of γ-graphyne at varying doping concentrations are calculated, demonstrating excellent experimental synthesizability of P-doped γ-graphyne. Notably, the P-doped system exhibits enhanced electrical conductivity compared to pristine γ-graphyne. The adsorption energy of a single lithium (Li) atom on P-doped γ-graphyne is determined to be -3.72 eV, significantly higher than those of N-doped, Si-doped, and intrinsic γ-graphyne. Even with increasing Li storage, the Li adsorption energy remains greater than the cohesive energy of bulk lithium, while the average open-circuit voltage falls within the optimal range of 0-1 V, ensuring high operational safety. Remarkably, the theoretical Li storage capacity of P-doped γ-graphyne reaches 1150.68 mAh/g, which is 1.85 times that of pristine γ-graphyne and 3.09 times that of conventional graphite. Furthermore, the diffusion barrier calculations reveal that P-doped γ-graphyne substantially reduces the Li-ion migration energy barrier, indicating favorable lithium diffusion kinetics. In summary, P-doped γ-graphyne demonstrates exceptional advantages in specific capacity, structural stability, electrical conductivity, and Li-ion diffusion kinetics, providing critical theoretical insights and experimental guidance for designing next-generation high-performance LIBs anode materials.

We in this manuscript restudy the long time decay, extinction and blow-up for a singular p-biharmonic parabolic equation with logarithmic nonlinearity, which appears in many branches of physics. In the framework of potential well theory and the existence of global solution, by a way of establishing a nonlinearly integral inequality without non-increasing condition, we prove that W 2 , p -norm for the weak solutions is non-increasing, and establish two decay and extinction theorems that incorporate two kinds of polynomial decay, two kinds of exponential decay and two kinds of finite time extinction. By a way of establishing a improved Hardy-Sobolev inequality and applying a non-concavity method, we establish the four blow-up theorems independent of the potential well depth with J ( u 0 ) < 𝔐 ( 0 ) as the blow-up criterion, where two of them are finite time blow-up, one is at least exponential growth and blows up at least at infinity, the last one blows up at infinity, where 𝔐( t) is a nonlinear function of ∫ R n | u ( x , t ) | 2 | x | s d x . These generalize previous research results from three aspects: long time decay, extinction and blow-up.

Background: Implantable cardioverter-defibrillators are used globally and are reliable, but complications related to transvenous leads remain a concern. Evidence related to the incidence and costs of those complications is heterogeneous with respect to scope and healthcare system. This analysis aims to create estimates of the incidence and costs of tricuspid valve complications, lead failures, and lead extractions from a single large real-world dataset. Methods and Results: This retrospective longitudinal cohort study used the de-identified Medicare Fee for Service administrative claims database. A total of 116,036 patients with de novo transvenous ICD implant were analyzed. Mean hospital costs were $26,903 for tricuspid valve complications, $20,851 for lead failures, and $22,278 for lead extractions. Conclusions: Transvenous ICD lead complications incur significant costs to patients, hospitals, and payers when they occur. Advancements in lead technology that reduce these complications could bring significant clinical and economic value.

Management of Phlegmasia Cerulea Dolens Alongside Neurologic Contraindication to Anticoagulation: A Therapeutic and Diagnostic Dilemma

Solitary fibrous tumors of the submandibular gland: a case report

A Unique Presentation of Early Onset Colon Cancer in the Setting of Helicobacter Pylori Positivity, IgA Deficiency and a Germline 18p DeletionKelsey Gay, DO1, Smita Dandekar, MBBS, MD11Division of Pediatric Hematology-Oncology, Penn State Health Children’s Hospital, Hershey, PA

Background: High-frequency oscillatory ventilation (HFOV) presents challenges for non-invasive CO 2 monitoring due to its rapid oscillations. This study examines the feasibility of instantaneous CO 2 partial pressure (INST CO 2) monitoring during HFOV with a capnometer equipped with a mainstream CO 2 sensor. Methods: This study included seven neonates receiving HFOV in the neonatal intensive care unit (NICU) at Shizuoka Children’s Hospital. INST CO 2 values were recorded over 3- and 5-min intervals surrounding each blood gas sampling to determine the maximum INST CO 2 value (INST CO 2 MX). The primary outcome was the correlation between INST CO 2 MX and arterial partial pressure of carbon dioxide (PCO 2). Results: A total of 216 paired INST CO 2 MX and PCO 2 values were analyzed. The coefficient of determination ( R 2) was 0.571 for INST CO 2 MX (3 min) and 0.579 for INST CO 2 MX (5 min). Univariable and multivariable analyses revealed that a lower fraction of inspired oxygen (FiO 2), reduced minute ventilation, and increased postnatal age were associated with improved concordance between INST CO 2 MX and PCO 2. Conclusion: INST CO 2 MX demonstrated a strong correlation with PCO 2 in neonates undergoing HFOV. This novel, non-invasive monitoring approach may serve as a valuable tool for neonatal respiratory management. Future research is needed to validate these findings in broader patient populations and across various ventilatory settings.

Background The healthcare sector contributes ~5% of global greenhouse gas emissions, with medicines responsible for ~10% throughout their lifecycle. Understanding how the environmental impact of medicines influences patients’ preferences relative to ease of use and cost supports interventions promoting appropriate medicine consumption, reduced waste, and environmental sustainability. Objective To investigate patient preferences and attitudes regarding the environmental impact of medicines in relation to ease of use and cost. Methods A cross-sectional survey (Dec 2022–Jan 2023) was conducted using the Dutch AMP pharmacy panel (>25,000 chronic medicine users). It included a discrete choice experiment (DCE) on medicines’ environmental impact, ease of use, and cost, and questions on environmental sustainability in medicine use and daily life. Latent class analysis identified groups with shared preferences. An environmental sustainability attitude score was calculated from daily life behavior. Results Of 25,787 invited panel members, 6,390 responded (24.8%), with 4,122 respondents included in the analysis (16.0%; mean age 68 years; 42.6% female). Four preference groups were identified: Eco-focused (55.7%), Cost-focused (20.1%), Indifferent (16.4%), and Eco-skeptical (7.8%). Environmental sustainability attitude scores were highest in the Eco-focused and Eco-skeptical (median 75.0%), followed by Indifferent and Cost-focused (median 66.7%). Important factors influencing this were environmental concerns (Eco-focused), environmental and personal health concerns (Eco-skeptical), costs (Cost-focused), and environmental, cost, and personal health concerns (Indifferent). Only 8.8–15.5% had good or very good knowledge about the environmental impact of medicines. Conclusion Environmental sustainability significantly affects medicine preferences, though heterogeneity exists. Tailored initiatives are required to promote environmentally sustainable pharmaceutical care.