Environmental Health

Identifying potential relationships between air pollutants and neutrophil extracellular traps formation in metabolic dysfunction-associated fatty liver disease by integrating computational toxicology and multi-omics data.

Metabolic dysfunction-associated fatty liver disease (MASLD) is a highly prevalent liver condition with a complex etiology increasingly linked to air pollution. However, the molecular mechanisms through which air pollutants exacerbate MASLD remain poorly understood. In this study, we integrated computational toxicology, multi-omics analyses, and machine learning to identify critical molecular targ...

Combination of Chromatographic and Machine Learning-Driven Virtual Fractionation Identifies Aryl Hydrocarbon Receptor Agonists in Sediments.

Complex organic chemical mixtures in aquatic ecosystems may cause adverse effects on aquatic and sediment-dwelling organisms. Identified chemicals typically explain less than 10% of the observed in vitro bioactivities of such complex mixtures extracted from sediments. In a proof-of-concept study, we combined high-resolution fractionation with machine-learning-driven virtual fractionation to identi...

Change-point detection and early warning systems.

This paper presents a statistical framework for early warning change-point detection in electrical grid frequency time series. Frequency deviations ou...

Atrial repolarization wave: a new approach using spline-based feature engineering and explainable AI for atrial arrhythmia diagnosis.

OBJECTIVES: The atrial repolarization (Ta wave) characteristics remains largely unexplored, given its inherently low amplitude and obscured by the QRS...

AI-enhanced system dynamics simulation for sustainable urban development under water constraints: A case study of Langfang, China.

Water-scarce cities undergoing rapid urbanization must sustain economic growth while complying with stringent water-resource and environmental constra...

Quantifying wildfire impacts on atmospheric pollutants using fire exposure metrics and machine-deep learning approaches.

Wildfires are increasingly recognised as major contributors to atmospheric pollution, yet their spatial-temporal influence on regional air quality rem...

Machine learning and multi-dimensional transcriptomics reveal the key molecular network of benzo(a)pyrene/NNK in promoting laryngeal cancer and develop prognostic models.

Benzo(a)pyrene (BaP) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), as typical environmental carcinogens, are widely present in tobacco smo...

The detectability paradox: bilingual medical report generation with open-weight models and the limits of human oversight.

OBJECTIVES: The automation of medical report generation using large language models (LLMs) could significantly reduce physicians' documentation burden...

Unveiling the drivers of groundwater quality in an industrial plain: An integrated hydrogeochemical and stacking ensemble learning approach.

Understanding the hydrochemical evolution and primary chemical components governing groundwater quality in industrial regions is crucial for sustainab...

Ensemble Machine Learning for Interpretable Prediction of Acute Toxicity in Metal-Organic Framework Linkers.

Metal-organic frameworks (MOFs) are promising platforms for drug delivery due to their high porosity, tunable chemistry, and controlled release capabi...

Leveraging the Metabolic Fingerprint of Sleep Deprivation and Sleep Restriction for Forensic Applications: A Machine Learning Study in Oral Fluid Metabolomics.

As sleep loss leads to accidents and impaired safety, a direct metabolic marker would be beneficial for forensic interpretation. In a sufficiently pow...

Underestimation of industrial contributions to VOC fluctuation in the Hangzhou Bay: Insights from simultaneous measurements and ML-SHAP analysis.

As a major petrochemical hub, the Hangzhou Bay suffers from severe volatile organic compound (VOC) pollution. Here, we conducted parallel high-frequen...

Integrated source apportionment, ecological risk assessment, and machine learning-based human health risk evaluation of potentially toxic elements in stream sediments of Odisha, eastern India.

Stream sediments, as long-term sinks for potentially toxic elements (PTEs), provide valuable insights into both natural and anthropogenic contaminatio...

Regional disparities and metabolic determinants of type 2 diabetes in women aged 55 and older.

OBJECTIVE: To assess long-term trends, regional disparities, determinants, and quality of care for type 2 diabetes mellitus (T2DM) among women aged 55...

Mechanistic and Data-Guided Design of Biochar Adsorbents for Gas Phase Pollution Control: A State-of-the-Art Review.

Air pollution remains critical global challenge, with sulfur oxides (SOx), nitrogen oxides (NOx), and volatile organic compounds (VOCs) contributing t...

DDA/DIA mass spectrometry coupled with molecular networking and machine learning: high-coverage profiling of pyrrolizidine alkaloids.

Pyrrolizidine alkaloids (PAs) are naturally occurring toxic secondary metabolites found in plants. However, the identification of PAs often relies on ...

Identifying factors associated with vaping cessation in young adults: A machine learning and XAI approach.

The public health impact of vaping in the United States reflects a complex balance of potential benefits and emerging risks, as e‑cigarettes may reduc...

Deciphering the potential pathogenic mechanisms of 3-BHA in ovarian cancer through integrated bioinformatics and machine learning strategies.

Ovarian cancer (OC) remains a malignancy characterized by obscure risk factors and unfavorable prognosis. While 3-tert-butyl-4-hydroxyanisole (3-BHA) ...

Advancing air pollution forecasting: a review of physical, statistical, and machine learning methods.

Air pollution is one of the important environmental and public health hazards that requires a combination of assessments, monitoring, and mitigation a...

Clustering and machine learning techniques identify air pollution regimes in Greater Cairo.

Air pollution is a major environmental and public health challenge in Greater Cairo due to rapid urbanization, intense traffic activity, and recurrent...