Search Results (1,364)

Background: Liver disease is a growing global health burden. While individual environmental exposures like heavy metals (lead, cadmium, mercury) and behavioral factors such as smoking and alcohol use are known risk factors, their combined impact and the underlying physiological pathways are poorly understood. Allostatic load (AL), a measure of cumulative physiological stress, is a potential mediator or modifier in the relationship between these chronic exposures and liver disease. This study aimed to investigate the joint effects of heavy metals and behavioral exposures on liver health and to examine the mediating role of AL. Methods: This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) 2017–2018 cycle. We assessed blood concentrations of the environmental and lifestyle variables in relation to liver biomarkers and the Fatty Liver Index (FLI). Descriptive statistics were used to summarize participant characteristics. Multivariable linear regression and Bayesian Kernel Machine Regression–Causal Mediation Analysis (BKMR-CMA) were used to model combined, nonlinear effects of the exposure–outcome mixture and to evaluate the mediating role of AL. Results: Lead exposure was positively associated with higher AST (β = 0.65, p = 0.04) and GGT (β = 1.99, p = 0.05), while smoking increased GGT (β = 0.79, p = 0.03) and ALP (β = 0.78, p < 0.01). AL independently predicted higher FLI (β = 3.66, p < 0.001). Conclusions: This study highlights that liver health is influenced by the combined effects of environmental pollutants, behaviors, and cumulative biological stress. While lead exposure and smoking were independently linked to liver enzyme elevations, and AL to FLI, mediation by AL was limited, though trends suggest AL may still amplify chronic metabolic pathways leading to liver disease. Full article

Based on five years of data (2017–2021) from the China National Lightning Detection Network (CNLDN), this study compares and analyzes the temporal and spatial distribution characteristics of cloud-to-ground (CG) lightning activities in the Hengduan Mountain region and its surroundings. It explores the relationship between CG lightning occurrences and altitude, topography, and various meteorological elements. Our findings reveal a stark east–west divide: high lightning density in the Sichuan Basin and the central Yungui Plateau contrasts sharply with lower densities over the eastern Tibetan Plateau and Hengduan Mountains. This geographical dichotomy extends to the diurnal cycle, where positive cloud-to-ground (PCG) lightning activities are more prevalent in the western part of the study area, while significant nocturnal activity defines the eastern basin and plateau. The study also finds that the relationship between CG lightning activities in the four sub-regions and 2 m temperature, precipitation, convective available potential energy, and Bowen ratio (the ratio of sensible heat flux to latent heat flux) exhibits similarities. Furthermore, we show that the relationship between lightning frequency and altitude is highly region-specific, with each area displaying a unique signature reflecting its underlying topography: a normal distribution over the eastern Tibetan Plateau, a bimodal pattern in the Hengduan Mountains, a sharp low-altitude peak in the Sichuan Basin, and a complex trimodal structure on the Yungui Plateau. These distinct regional patterns highlight the intricate interplay between large-scale circulation, complex terrain, and local meteorology in modulating lightning activity. Full article

Background/Objectives: The increasing prevalence of multidrug-resistant Staphylococcus aureus represents a major clinical challenge, primarily driven by the acquisition of multiple resistance mechanisms. Among these, efflux pumps such as NorA play a pivotal role in quinolone resistance by promoting active drug extrusion and reducing intracellular antibiotic levels. This study evaluated the synthetic chalcone CMA4DMA as a potential NorA efflux pump inhibitor and modulator of bacterial resistance. Methods: Antimicrobial susceptibility assays were conducted against S. aureus SA1199 (wild-type) and SA1199B (NorA-overexpressing) strains. The minimum inhibitory concentration (MIC) of CMA4DMA and its modulatory effects on norfloxacin and ethidium bromide were determined. Efflux inhibition was assessed by ethidium bromide accumulation and SYTOX Green assays. Molecular docking and in silico ADMET analyses were performed to predict binding affinity and pharmacokinetic parameters. Results: CMA4DMA exhibited no intrinsic antibacterial activity (MIC ≥ 1024 µg/mL) but reduced the MIC of norfloxacin from 32 to 8 µg/mL and that of ethidium bromide from 32 to 8 µg/mL in SA1199. In SA1199B, reductions from 64 to 16 µg/mL and from 64 to 32 µg/mL were observed, respectively. Fluorescence increased by 15% without affecting membrane integrity. Docking revealed a binding affinity of −7.504 kcal/mol, stronger than norfloxacin (−7.242 kcal/mol), involving key residues Leu218, Ile309, Arg310, and Ile313. ADMET data indicated high intestinal absorption (88.76%) and permeability (Papp = 1.38 × 10⁻⁵ cm/s). Conclusions: CMA4DMA effectively restored norfloxacin susceptibility in resistant S. aureus strains, highlighting its potential as a promising scaffold for developing novel efflux pump inhibitors and antibiotic adjuvants. Full article

Theoretical foundations are presented for the application of information–entropy methods from statistical physics to the determination of stellar evolutionary stages. A balance equation involving normalized conditional information and entropy is proposed. The conditional information is defined as the difference between the entropy of the phase space and the conditional probability entropy. A correspondence is demonstrated between theoretical predictions and observational data from stellar emission spectra with respect to their evolutionary classification. The proposed methodology is further applied to the analysis of complex FS CMa-type objects, which exhibit dusty and gaseous structures with components at different evolutionary stages. In this context, the conditional information derived from asymmetric spectral lines is shown to be consistent with the theoretical criteria for the evolutionary status of single, binary, and unclassified stars. Full article

Electrocatalytic conversion of CO₂ to high-energy-density multicarbon products (C₂₊) offers a sustainable route for renewable energy storage and carbon neutrality. Precisely modulating Cu-based catalysts to enhance C₂₊ selectivity remains challenging due to uncontrollable reduction of Cu^δ+ active sites. Here, an efficient and stable Ge/Cu catalyst was developed for CO₂ reduction to ethanol via Ge modification. A Cu₂O/GeO₂/Cu core–shell composite was constructed by controlling Ge doping. The structure–performance relationship was elucidated through in situ characterization and theoretical calculations. Ge⁴⁺ stabilized Cu¹⁺ active sites and regulated the surface microenvironment via electronic effects. Ge modification simultaneously altered CO intermediate adsorption to promote asymmetric CO–CHO coupling, optimized water structure at the electrode/electrolyte interface, and inhibited over-reduction of Cu^δ+. This multi-scale synergistic effect enabled a significant ethanol Faradaic efficiency enhancement (11–20%) over a wide potential range, demonstrating promising applicability for renewable energy conversion. This study provides a strategy for designing efficient ECR catalysts and offers mechanistic insights into interfacial engineering for C–C coupling in sustainable fuel production. Full article

Cloud Top Height (CTH) is a fundamental parameter in atmospheric science, critically influencing Earth’s radiation budget and hydrological cycle. Satellite-based passive remote sensing provides the primary means of monitoring CTH on a global scale due to its extensive spatial coverage. However, these passive retrieval techniques often rely on idealized physical assumptions, leading to significant systematic biases. To quantify these biases, this study provides an evaluation of two prominent passive CTH products, i.e., Sentinel-5P (S5P, O₂ A-band) and Suomi-NPP (NPP, thermal infrared), by comparing their global data from July 2018 to June 2019 against the active CloudSat/CALIPSO (CC) reference. The results reveal stark and complementary error patterns. For single-layer liquid clouds over land, the products exhibit opposing biases, with S5P underestimating CTH while NPP overestimates it. For ice clouds, both products show a general underestimation, but NPP is more accurate. In challenging two-layer scenes, both retrieval methods show large systematic biases, with S5P often erroneously detecting the lower cloud layer. These distinct error characteristics highlight the fundamental limitations of single-sensor retrievals and reveal the potential to organically combine the advantages of different products to improve CTH accuracy. Full article

Atmospheric motion vector (AMV) products from EUMETSAT’s MetOp satellite series, including MetOp-B, MetOp-C, and the MetOp-B/C tandem (MetOp-Dual), have been assimilated at many numerical weather prediction centers worldwide. However, they have not yet been applied in the China Meteorological Administration’s Global Forecast System (CMA-GFS). This study addresses this gap by developing assimilation techniques, including quality control and thinning methods for MetOp AMVs. Based on these techniques, one-month assimilation and forecasting experiments reveal that MetOp AMVs increased the AMV volume in CMA-GFS by 25%, filling certain gaps over polar and oceanic areas. Notable and steady improvements in the background of CMA-GFS have been found, particularly in polar and high-latitude regions. The usable forecast lead time for the global 500 hPa geopotential height is extended by 0.22 days, enhancing the reliability of medium-range forecasts. Furthermore, the more substantial improvements in short-range (0–3 days) forecasting, potentially benefit severe weather alerting. This study marks the first to successfully apply MetOp-B, MetOp-C and MetOp-Dual products in CMA-GFS, confirming their value for improving the performance of the system. Full article

Comprehensive Meta-Analysis (CMA) software, using data from 64 global studies (288 dietary assessments, 194,356 broilers) evaluated the effects of substituting inorganic trace minerals (ITM) with proteinate trace minerals (PTM) in broiler diets at various inclusion levels. Replacing ITM with PTM at equivalent (100%) or reduced (11–80%) levels improved performance metrics, showing reduced total feed intake (FI) (−6 g/bird), lower average daily feed intake (ADFI) (−0.43 g/bird), higher average daily gain (ADG) (+0.36g), greater body weight gain (BWG) (+4.29 g/bird), higher final body weight (BW) (+7.50 g/bird), improved feed conversion ratio (FCR) (−1.26%), and lower mortality (−10.95%), all significant (p < 0.05). Median mineral inclusion reductions of 40% Cu, 59.82% Fe, 41.41% Mn, and 34.67% Zn had no adverse effects, instead enhancing outcomes. Across 17 studies (25,144 broilers, 85 dietary assessments), mineral excretion decreased significantly with PTM versus ITM by 16% Cu, 14% Fe, 21% Mn, and 15% Zn (p < 0.001). When PTM replaced ITM at 50–80% inclusion, further benefits were observed, including lower total FI (−7 g/bird), lower ADFI (−1.07 g/bird), higher ADG (+1.67), higher BWG (+2.65 g/bird), lower FCR (−4.50%) and lower mortality (−11.09%) with mineral inclusion reductions of 17% Cu, 42.16% Fe, 42.89% Mn, and 50% Zn. Meta-regression identified significant influences (p < 0.05) from study variables such as strain, study duration, and region. Life cycle assessment modelling demonstrated PTM inclusion lowered gross carbon emissions by 3.5% and lower emission intensities per unit live weight of both feed use and overall lifecycle by 4.5% and 4.1%, respectively on diets of high and low soybean meal inclusion. Overall, replacing ITM with PTM in broiler diets can promote production performance of broilers and lower mineral excretion levels while contributing to a lower CFP. Full article

Soil viruses are increasingly recognized as key regulators of microbial communities and biogeochemical cycles, yet their responses to long-term fertilization strategies remain poorly characterized. We conducted a four-year pot experiment in subtropical China to evaluate how chemical fertilizer (CF), biochar (BC), and organic fertilizer (OF) application influenced soil viromes compared with an unfertilized control (CK) treatment. Metagenomic analyses recovered 1581 viral contigs with distinct community structures across treatments. Lytic viruses dominated overall, with higher proportions in BC and OF treatments, positively correlated with soil fertility indicators. Diversity indices indicated that BC and OF treatments significantly enhanced viral richness and evenness relative to CK and CF treatments, reflecting broader microbial host niches. Virus–host link predictions revealed expanded networks under BC and OF treatments, particularly with Pseudomonadota, Cyanobacteriota, and Acidobacteriota, suggesting amendment-specific viral regulation. Functional annotation showed that OF and BC application enriched viral KEGG categories related to metabolism, transport, and signal transduction. Moreover, BC and OF application promoted nitrate reduction, nitrogen fixation, and phosphorus mobilization. Together, these findings highlight organic amendments as critical drivers of soil viral diversity and functional potential, linking viromes dynamics to sustainable nutrient cycling in agroecosystems. Full article

Investigating the diurnal variation characteristics of precipitation (DVCP) in Xinjiang, an arid region of Northwest China, is essential for improving water resource management and disaster mitigation strategies. This study examines the DVCP associated with diverse underlying surfaces in Eastern Xinjiang (EX)—one of the most arid regions in China—during summer (June–August) from 2015 to 2019, using hourly simulation data from the real-time forecasting system of Nanjing University (WRF_NJU). Evaluation against automatic weather station (AWS) observations indicates that WRF_NJU outperforms reanalysis (ERA5), satellite (CMORPH), and MESWEP datasets, demonstrating its reliability for regional precipitation analysis. Further investigation reveals that in the Turpan-Hami Basin (THB), below 1000 m above sea level (ASL), peaks in precipitation amount (PA), intensity (PI), and frequency (PF) occur at 06 local solar time (LST), whereas in mountainous areas above 3000 m ASL, these peaks are delayed until 13 LST. Analysis of the coefficient of variation (CV) shows that the most pronounced differences in DVCP between mountainous and basin regions are associated with PF and PI. Specifically, regions with high CV for PF are concentrated in the central to northern parts of the THB, while high CV for PI is found in the eastern Mid-Tianshan Mountains (MTM) and East Tianshan Mountains (ETM). Moreover, significant differences in DVCP are observed across land surface types: PA peaks over grasslands, forests, and water bodies occur around noon, whereas over impervious surfaces, croplands, and barren areas, they occur during the early morning hours. Full article

Background: Immunotherapy has emerged as a breakthrough for the treatment of advanced non-small-cell lung cancer (NSCLC), significantly improving patients’ progression-free survival (PFS) and overall survival (OS). However, the medical burden of response assessment has worsened for long-term maintenance therapy. It remains unclear whether a specific response assessment interval could provide both survival benefits and cost savings. Methods: We retrospectively included patients with advanced NSCLC who underwent immunotherapy and achieved PFS > 12 months. We utilized propensity score matching (PSM) to reduce the selection bias. The survival outcomes were evaluated using the log-rank test and Cox proportional hazard models, while the economic impact was assessed through the performance of a cost minimization analysis (CMA). A medical expenditure extrapolation model was developed based on epidemiological statistics and data from clinical trials. Results: After PSM, a total of 376 patients were included. The survival difference was not significant [hazard ratio (HR) = 0.78, 95% confidence intervals (CIs) = 0.53–1.14; p = 0.200] between the 2-month response assessment group (n = 188) and the 3-month response assessment group (n = 188). Patients receiving immunotherapy alone and those with a positive PD-L1 expression experienced a significant survival benefit. Our extrapolation model projects that, annually, there will be approximately 7026 new long-term responders to immunotherapy in the United States. Adopting a 3-month assessment strategy could reduce annual healthcare expenditure by nearly USD 6 million. Conclusions: This study presented the first statistical evidence supporting a refined response assessment strategy for long-term responders to immunotherapy with advanced NSCLC. These findings support the adoption of a less frequent, yet equally effective, monitoring approach to make tumor surveillance more precise and cost-effective. Full article

This study investigates the characteristics, meteorological drivers, and transport pathways of air pollution in Yining City from 2020 to 2024 based on meteorological records and air pollutant monitoring data. An integrated modeling approach combining the Weather Research and Forecasting (WRF) model and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was employed. Results reveal an overall annual decrease in ambient pollutant concentrations in Yining, with PM_2.5 and PM₁₀ consistently below the national secondary standards, In contrast, the O₃ concentration shows a marked yearly increase. Pronounced seasonal variations were identified: the elevated O₃ concentrations in summer were driven by high temperatures and intense solar radiation. The significant increase in PM_2.5 and PM₁₀ concentrations during winter was predominantly attributed to coal-based heating emissions and temperature inversion conditions. Pollutant concentrations were strongly associated with gaseous precursors (e.g., CO and NO₂) and meteorological factors. Higher temperatures and lower relative humidity aggravated O₃ formation, whereas lower temperatures and higher relative humidity favored PM_2.5 pollution. Correlation analysis revealed that NO₂ and CO showed the strongest correlations with PM_2.5 (r = 0.84) and O₃ (r = −0.62), respectively. Backward trajectory analysis revealed that higher pollution levels were associated with air masses originating from the southwest and southeast. Full article

Advancements in genomic technologies have transformed prenatal genetic testing, offering more accurate, comprehensive, and noninvasive approaches to reproductive care. This review provides an in-depth overview of current methodologies and emerging innovations, including expanded carrier screening (ECS), cell-free DNA (cfDNA) testing, chromosomal microarray analysis (CMA), and sequencing-based diagnostics. We highlight how next-generation sequencing (NGS) technologies have revolutionized carrier screening and fetal genome analysis, enabling detection of a broad spectrum of genetic conditions. The clinical implementation of cfDNA has expanded from common aneuploidies to include copy number variants (CNVs), and single-gene disorders. Diagnostic testing has similarly evolved, with genome sequencing outperforming traditional CMA and exome sequencing through its ability to detect both sequence and structural variants in a single assay. Emerging tools such as optical genome mapping, RNA sequencing, and long-read sequencing further enhance diagnostic yield and variant interpretation. This review summarizes major technological advancements, assesses their clinical utility and limitations, and outlines future directions in prenatal genomics. Full article

Under global warming, drought frequency and its severity have risen notably, posing considerable challenges to vegetation growth. Central Asia (CA), recognized as the largest non-zonal arid zone globally, features dryland ecosystems that are particularly vulnerable to drought stress. This research examines how plant life in CA reacts to prolonged dry spells by analyzing multiple datasets, including drought indices and satellite-derived NDVI measurements, spanning four decades (1982–2022). This study also delves into the compound impact of drought, revealing how its influence on vegetation unfolds through both cumulative stress and delayed ecological responses. Based on the research results, the vegetation coverage in CA exhibited a notable rising tendency from 1982 to 1998. Specifically, it increased at a rate of 4 × 10⁻³ per year (p < 0.05). On the other hand, the direction of this trend shifted to a downward one during the period from 1999 to 2022. During this latter phase, the vegetation coverage decreased at a rate of −4 × 10⁻³ per year (p > 0.05). Vegetation changes in the study area underwent a fundamental reversal around 1998, shifting from widespread greening during 1982–1998 to persistent browning during 1999–2022. Specifically, 98.6% of the region underwent pronounced summer drought stress, which triggered a substantial rise in vegetation browning. The vegetation response to the accumulated and lagged effects of drought varied across seasons, with summer exhibiting the strongest sensitivity, followed by spring and autumn. The lagged effect of drought predominantly influences the vegetation during the growing season and spring, affecting 59.44% and 79.27% of CA, respectively. In contrast, the accumulated effect of drought is more prominent in summer and autumn, affecting 54.92% and 56.52% of CA. These insights offer valuable guidance for ecological restoration initiatives and sustainable management of dryland ecosystems. Full article

Student exam pass prediction (EPP) is a key task in educational assessment and can help teachers identify students’ learning obstacles in a timely manner and optimize teaching strategies. However, existing EPP models, although capable of providing quantitative analysis, suffer from issues such as complex algorithms, poor interpretability, and unstable accuracy. Moreover, the evaluation process is opaque, making it difficult for teachers to understand the basis for scoring. To address this, this paper proposes an approximate belief rule base (ABRB-a) student examination passing prediction method based on adaptive reference point selection using symmetry. Firstly, a random forest method based on cross-validation is adopted, introducing intelligent preprocessing and adaptive tuning to achieve precise screening of multi-attribute features. Secondly, reference points are automatically generated through hierarchical clustering algorithms, overcoming the limitations of traditional methods that rely on prior expert knowledge. By organically combining IF-THEN rules with evidential reasoning (ER), a traceable decision-making chain is constructed. Finally, a projection covariance matrix adaptive evolution strategy (P-CMA-ES-M) with Mahalanobis distance constraints is introduced, significantly improving the stability and accuracy of parameter optimization. Through experimental analysis, the ABRB-a model demonstrates significant advantages over existing models in terms of accuracy and interpretability. Full article