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Act now to clean up air

IFITM3 deficiency drives SARS-CoV-2 adaptation while preserving variant-specific traits

Swimming is superior to running in inducing physiological cardiac hypertrophy and enhancing myocardial performance

Factors contributing to Korean road accidents based on insurance records

This study aims to identify the key factors contributing to the severity of road accidents in Korea, analyzing more than 3,000 motor vehicle insurance records using the generalized ordered logit model (GOLogit). The model addresses the limitations of the parallel regression assumption, which ignores the differences between adjacent discrete levels of injury severity. The variable “Vehicle type (including pedestrian) with less liability”, which has been rarely examined in previous studies, demonstrated that individuals in the less responsible and more vulnerable position tend to suffer more severe injuries in South Korea. Consistent with this, the GOLogit estimates showed particularly high log-odds for severe injuries among pedestrians (4.912) and non-motorized cyclists (4.746), while speed-limit violations substantially increased the likelihood of fatal outcomes (2.456). In contrast, population density exhibited a protective effect, reducing injury severity (scaled log-odds = −1.055). This pattern is similar to broader societal trends, where economically disadvantaged regions tend to experience more severe traffic-related injuries. Specific road structures, such as the traditional right-angled crossroads, access roads to arterial roads, speedbumps on curved roads, and junctions between motor vehicle roads and sidewalks, pose significant safety challenges. Based on these findings, government policies on road safety should emphasize lowering the speed limits in residential areas, expanding the implementation of international pedestrian protection safety standards, and investing equitably in the safety of poor, low-population-density regions and older adults.

Electroacoustic alignment of robust and highly piezoelectric nylon-11 films

Model for the description of interactions between ellagitannins and Fe(II) ions

Optimization of a natural fermentative medium for submerged mycelial culture of Ganoderma lucidum and the nutritional and bioactive composition of the cultured food-grade mycelia

Ganoderma lucidum is a famous traditional Chinese medicinal fungus with health-promoting and pharmacological properties. The present study aimed to provide a liquid medium for G . lucidum submerged fermentation suitable for safely utilizing the mycelia and broth and as a solution to potentially improve the process’ economy. For this, a natural medium was formulated and optimized. The nutritional and bioactive composition of the mycelia cultivated in the optimized medium and a nutrient-rich (NR) medium were also determined. The one-variable-at-a-time experiments indicated that among various tested carbon sources, sucrose was favorable for mycelial growth. The supplementation of corn flour in the medium promoted mycelial growth and its optimal level was 7.0 g/L. A further study by response surface methodology obtained an optimal medium comprising of 300 g/L potato (use its extract), 25 g/L sucrose, and 7.5 g/L corn flour. Using the optimized medium, the mycelial yield reached 7.51 g/L. The crude ash (10.43%) and fiber (10.51%) content of the mycelia cultivated in the optimal medium was higher than those (ash 5.75% and fiber 5.93%) of the mycelia grown in the NR medium, while the proteins content and all examined amino acids were lower than those of the mycelia cultivated in the NR medium. The mycelia contained 32.24 mg/g triterpenoids and 3.42% intracellular polysaccharides, which is higher than those (triterpenoids 20.35 mg/g and intracellular polysaccharides 2.03%) of the mycelia cultivated with the NR medium. These findings indicated that the cultured food-grade mycelia had the potential for use in the pharmacological industry. Meanwhile, the broth had the potential for safe use in foods due to free of chemicals. The present study provides a reference for improving the economy of G . lucidum submerged culture by using a natural medium, and its industrial fermentation may be economically viable.

Stereoselective cyano translocation reaction enabled by photoenzymatic catalysis

RiemannInfer: improving transformer inference through Riemannian geometry

Abstract Understanding the reasoning process of Large Language Models(LLMs) is crucial for interpreting their decision-making mechanisms. However, existing methods primarily rely on conditional probability distributions within the model, resulting in computationally inefficient reasoning processes and difficulties in constructing rigorous logical chains. This paper presents RiemannInfer, an innovative computational framework based on Riemannian geometry for optimizing LLM reasoning paths. Our approach stems from a key observation: the hidden states formed through attention mechanisms and contextual encoding in the Transformer can be represented as high-dimensional vector spaces that encapsulate global dependencies captured by the model. Building on this insight, we first apply topology-preserving dimensionality reduction to these hidden states, then construct a Riemannian manifold structure utilizing attention distribution features. Notably, We discover a close relationship between the attention mechanism to the geodesics and the curvature of Riemannian manifolds. Based on this foundation, we implement efficient inference work calculation through geodesic and curvature to realize reasoning path planning, which not only significantly enhances inference efficiency but also provides geometric interpretations of model decision processes. Extensive experiments on various models, including LLaMA, GPT-4, and DeepSeek, demonstrate that RiemannInfer significantly improves the reasoning accuracy of LLMs and exhibits excellent effectiveness and robustness. This research provides a novel geometric perspective for enhancing the interpretability and efficient reasoning of LLMs.

Association between depression during pregnancy and preterm birth: Results from population cohorts and mouse experimental models

Background Depression is a prevalent psychological challenge during pregnancy, with established links to adverse outcomes like preterm birth (PTB) globally. However, epidemiological data from China’s multiethnic regions are scarce, and experimental evidence supporting a causal relationship remains limited. This study aimed to investigate the association between prenatal depressive symptoms and the risk of PTB in a cohort from Yunnan, China, and to provide supportive evidence using a mouse model of depression. Methods We recruited 1,466 women during their first-trimester routine visits at Qujing Hospital. Depressive symptoms were assessed using the Chinese version of the Edinburgh Postnatal Depression Scale (EPDS), a screening tool, with a score ≥12 indicating elevated symptoms suggestive of depression. PTB was defined as delivery before 37 gestational weeks, confirmed by ultrasound. In parallel, a mouse model of depression was established using Chronic Unpredictable Mild Stress (CUMS) for 6 weeks prior to mating. PTB in mice was defined as delivery before 19 days of gestation. Results In the cohort study, the incidence of PTB was significantly higher in women with prenatal depressive symptoms compared to those without (8.43% vs. 3.83%, P < 0.001). The association remained significant after adjusting for sociodemographic and clinical confounders, with an adjusted risk ratio (aRR) of 2.19 (95% CI: 1.32–3.63). This association showed a significant dose-response pattern (P for trend = 0.03), with the risk being highest for women with moderate depressive symptoms (aRR = 2.44, 95% CI: 1.30–4.58). In the animal experiments, PTB did not occur in the control mice, whereas 40% of the mice exposed to CUMS (depression model group) delivered prematurely. Conclusion This study demonstrates a significant association between prenatal depressive symptoms and an increased risk of preterm birth in a Chinese multiethnic cohort. Experimental findings from a mouse model further suggest a potential contributory role of depression to PTB. These results underscore the importance of screening for and addressing maternal mental health during pregnancy. Future research should focus on underlying mechanisms and intervention strategies to mitigate this risk.

Preserving the respiratory system

Electrographic cue-reactivity co-localizes with accumbens deep brain stimulation in a case of opioid use disorder

Harnessing epitope reciprocity and multimeric epitope density for a novel multiepitope vaccine design against Acinetobacter baumannii

Workplace stress, support and stress management strategies for healthier lifestyles among healthcare workers in Ethiopia

Introduction Workplace stress is an ongoing global and local challenge in healthcare, driven by high demands, long hours, and emotional strain, requiring urgent attention to safeguard workers’ well-being and ensure quality care. Objective This study assessed workplace stress, support systems, and coping strategies among healthcare professionals in Jimma Zone, Ethiopia Methods A facility based cross sectional study was conducted in Jimma Zone, Ethiopia, in August 2023. A total of 496 healthcare professionals from five different hospitals were randomly selected to participate in the study. Various validated scales, including the Workplace Stress Scale (WSS), Workplace Support for Health Scale (WSHS), and Oslo Social Support Scale (OSSS-3) were used to assess the participants’ stress levels, social support systems, and their utilization of coping strategies. The data analysis involved descriptive statistics and ordinal logistic regression techniques. Results Results showed that 53% of healthcare workers experienced stress, with 25% reporting low, 16% moderate, and 12% severe stress. Positive workplace support for a healthier life was reported by 54% of respondents. Stress levels were significantly linked to factors like qualifications, facility type, and salary level (p < 0.05). Female workers had slightly lower stress odds than males. Workers aged 30–39 and 50–59 had lower odds of stress compared to those under 30. Higher income and working in primary hospitals were associated with reduced stress odds compared to lower income and referral hospitals. Conclusions This study found considerable workplace stress driven by individual, organizational, and external factors, calling for targeted interventions like stress management training and resilience building programs to enhance health workers’ coping skill and improve healthcare environments in Ethiopia.

A quantitative, multimodal wearable bioelectronic device for comprehensive stress assessment and sub-classification

Abstract Stress is a universal experience impacting mental and physical health. However, no precise, objective wearable tool exists for continuous, long-term stress monitoring, which is essential for understanding stress-related health outcomes. To address this gap, we introduce SQC-SAS, a multimodal wearable device that simultaneously and continuously measures multiple physiological and molecular stress biomarkers for quantitative stress assessment and sub-classification. This device features exceptional environmental stability, reusability, and fully wireless data and power operation. Machine learning enables data-driven stress assessment and classification across multiple stress states, allowing biomarker profiles to be correlated with each state. Its wristband-like design enables continuous stress monitoring and real-time visualization. We envision our wearable will greatly advance precise, objective stress assessment and monitoring, offering unprecedented capabilities and laying the foundation for personalized interventions and a deeper understanding of stress-related outcomes.

A hierarchical conformal framework for uncertainty-aware length of stay prediction in multi-hospital settings

Analysis of serum calprotectin levels in ménière’s patients and investigation of its effect on disease severity

Objective This prospective observational study aimed to evaluate serum calprotectin levels in patients with definite Ménière’s Disease (MD) and to investigate their association with symptom duration and disease severity. Materials and methods Thirty-nine patients (16 males, 23 females; mean age 37.2 ± 11.9 years) diagnosed with definite MD according to the AAO–HNS criteria and 28 age- and sex-matched healthy controls (14 males, 14 females; mean age 39.2 ± 13.3 years) without vestibular or auditory complaints were included. Individuals with active infection, autoimmune or chronic inflammatory disease, recent antibiotic or steroid use, or other otologic pathologies were excluded. Serum calprotectin levels were measured during an acute vertigo attack in the MD group and once in controls. Between-group differences and correlations with clinical variables were analyzed using appropriate parametric and non-parametric tests. Results Mean serum calprotectin levels during acute attack were significantly higher in the MD group than in controls (1031 ± 364 vs. 611 ± 231 ng/mL, p < 0.001). Within the MD group, calprotectin levels showed a strong positive correlation with symptom duration (Spearman’s ρ = 0.914, p < 0.001). In patients with MD, calprotectin levels decreased significantly after treatment, from 1031 ± 364 to 582 ± 339 ng/mL (mean difference 449 ng/mL, 95% CI 353–545; t (38) = 9.46, p < 0.001; Cohen’s d = 1.51), indicating a large effec t size. Conclusion Patients with Ménière’s Disease exhibit elevated serum calprotectin levels during acute attacks, which correlate strongly with symptom duration and decrease significantly after treatment. These findings suggest that calprotectin may be a potential inflammatory biomarker associated with disease burden and treatment response in MD; however, longitudinal studies with larger cohorts are needed to determine its diagnostic and prognostic utility.

Human brain prefrontal cortex proteomics identifies compromised energy metabolism and neuronal function in Schizophrenia

Abstract Understanding the pathophysiological substrates of schizophrenia is a major challenge for current neuropsychiatric research. As part of a set of multi-omics experiments, we performed an extensive case-control proteomics study on 192 post-mortem tissue sections from prefrontal cortex from 96 individuals, including 47 cases with schizophrenia and 49 healthy controls. Using two independently measured cortical datasets, we identified 387 proteins differentially expressed between schizophrenia cases and controls at a 5% FDR threshold. This significantly regulated set of proteins contains genes located in GWAS-identified schizophrenia loci and proteins identified by pQTL analysis. Gene ontology analysis using GOAT provided evidence for regulation of several major protein categories, emphasizing downregulation of mitochondrial oxidative respiration, ribosomes and the proteasome, upregulation of kinases and (small) GTPases. SynGO analysis supports the notion of synaptic dysfunction in schizophrenia, with major regulators of pre- and postsynaptic function compromised. Our findings highlight the complex molecular dysregulation in schizophrenia, with mitochondrial function downregulated versus signaling and trafficking upregulated, and synapse function disrupted; in combination with prior avenues of research, these finding support a role for energy deficits compromising highly ATP dependent neuronal function as a target for therapeutic interventions.

Restoration of aquatic vegetation can mitigate the risk of eutrophication in large shallow lakes

Development and implementation of a Digital Twin workshop for a smoke alarm production line

To address issues such as low manual production efficiency, inability to track production status, and lack of traceability for quality defects in smoke alarm manufacturing, this paper proposes a method for constructing a digital twin workshop for smoke alarm production lines. First, through demand analysis of the smoke alarm production workshop, a digital twin workshop system architecture is established. Then, by constructing a workshop digital twin model, building the workshop information system architecture, and completing multi-source heterogeneous data collection, a virtual-physical mapping between the virtual workshop and the physical workshop is achieved. Finally, the feasibility is validated in a company’s smoke alarm production workshop, demonstrating that the system can realize functions such as production progress tracking, quality control, and equipment operation monitoring. Compared to traditional transmission production, the application of this digital twin workshop significantly enhances production efficiency. Defect identification rates increased by 3.2%, product defect rates dropped significantly below 0.1%, and labor costs decreased by 96.7%.