Environmental Health

Developmental neurotoxic effects of organophosphate flame retardants (OPFRs) across different life stages and the central role of pioneer transcription factors Neurog2/Ascl1 during the embryonic period.

In contemporary consumer products markets, organophosphorus flame retardants (OPFRs) are widely used, associated with non-carcinogenic health risks and exhibit multisystem toxicity. Based on the endocrine-disrupting properties, which are combined with the endocrine system's susceptibility and interaction with the nervous system during early developmental stages, developmental neurotoxicity (DNT) h...

Machine Learning-Driven Biomimetic MXene-Based Sensor Array for Ultraefficient Multiplexed Oxyanions Detection.

The pervasive contamination of groundwater by highly toxic oxyanions necessitates advanced sensing technologies capable of high-throughput screening. To overcome the intrinsic single-analyte limitation of conventional ion-selective electrodes (ISEs), we developed a biomimetic sensor array inspired by the cross-reactive principles of biological taste systems, which was constructed by self-assemblin...

Detecting Performance Drift in AI Models for Medical Image Analysis Using CUSUM Chart.

The use of artificial intelligence (AI) models to assist clinical decisions for diagnosis and prediction has been shown to improve patient outcomes an...

Hybrid multilayer perceptron models optimized by evolutionary algorithms for urban air quality forecasting: a case study of Shiraz, Iran.

Accurate air quality predictions are vital for environmental management and public health, especially in urban areas facing rising pollution levels. T...

Prenatal environmental exposures associated with ADHD diagnosis in children: a multicentre exposome analysis.

Attention deficit hyperactivity disorder (ADHD) is one of the most diagnosed neurodevelopmental conditions. While its aetiology is primarily attribute...

Spatial heterogeneity, source apportionment and ecological risks of trace metal(loid)s in lakes across China.

Anthropogenic activities increasingly influence trace metal(loid)s (TMs) inputs to inland waters, yet the large-scale drivers of their distribution an...

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape lea...

Air pollution and autism-like traits: sensitive periods and joint effects of exposure to sources and constituents of fine particulate matter.

Growing evidence suggests that exposure to air pollution during early life is associated with autism spectrum disorder (ASD). However, results have be...

Dynamic urban land surface monitoring in developing countries using remote sensing and machine learning: real-time investigational approach.

Land Surface Changes (LSC) are significantly impacted by dynamic environmental variations, particularly armed conflicts and associat-ed failures, acco...

Drivers and distribution of soil arsenic in China's yellow river irrigation area by machine learning.

Arsenic contamination in irrigated agricultural soils poses global health and ecosystem risks. Using China's Yellow River Irrigation District as a cas...

Portraying Ethical Risks of Medical AI: Mixed Methods Study From Connotation Definition to a Survey on Physicians' Cognition.

BACKGROUND: Ethical risks of medical artificial intelligence (AI) are a global concern, but existing understanding remains fragmented without an integ...

Future mercury emissions from coal-fired power plants in China under dual-carbon targets: An emission-driven sensitivity assessment integrating machine learning and GEOS-Chem modeling.

Mercury (Hg) is a highly toxic trace metal that poses severe threats to ecosystems and human health. Coal-fired power plants (CFPPs) have historically...

Ultrasound assisted persulfate for enhanced degradation of Alizarin Red S with experimental design and AI driven optimization.

This study investigates the enhanced degradation of Alizarin Red S (ARS) from aqueous solutions using an ultrasound-assisted persulfate (PS/US) system...

Explainable machine learning integrating environmental chemical biomarkers and maternal clinical factors for prediction of hypertensive disorder of pregnancy.

Hypertensive disorders of pregnancy (HDP) represent a leading cause of maternal morbidity, yet environmental chemical contributors to HDP risk remain ...

A near-standard soil spectral library to improve stability and transferability of hyperspectral remote sensing models for soil heavy metal prediction.

Limited sample sizes and regional differences in pollution characteristics and soil properties often obscure the characteristic bands of soil heavy me...

Deep learning-assisted chrysotile asbestos screening in soil: A hierarchical statistical approach to error propagation.

Manual polarized light microscopy (PLM) is widely used for asbestos screening in soil, yet the technique remains labor-intensive and susceptible to in...

Air quality and health implications of exposure to ultrafine particle pollution.

AIMS: Ultrafine particles (UFPs) smaller than 100 nm are ubiquitous in polluted air. Although they carry little mass, UFPs have a large exposure surfa...

Efficient Diagnosis of Spatiotemporal Evolution and Driving Factors of Surface Ozone Pollution Episodes: An Application in Jiangsu Province, China.

Severe ozone (O3) pollution is a major challenge for air quality improvement in China, primarily due to its spatiotemporal heterogeneity and nonlinear...

Physics-informed, uncertainty-aware surrogate screening of gamma-ray attenuation in lead-free multicomponent oxide glasses.

Lead-free multicomponent oxide glasses are attractive candidates for gamma-ray shielding because their attenuation behavior can be tuned through compo...

Context-Aware Multilevel Classification of Semantic Relations in Drug-Adverse Drug Reaction (ADR) Networks-Predicting Drug-Induced Liver Injury (DILI) as a Case Study.

Adverse drug reactions (ADRs) are a major concern for public health and patient safety and a burden in drug discovery, with drug-induced liver injury ...