Environmental Health

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 powered, randomized, controlled, crossover trial under realistic conditions, we examined the salivary metabolome of 20 young men (habitual sleep duration 7-9 h) following three interventions: one night of total sleep deprivation, four consecutive nights...

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-frequency VOC measurements at a coastal mainland site (Haiyan) and an offshore island site (Daishan) during April-May 2024. To disentangle average source contributions from dynamic peak drivers, we developed a novel integrated framework combining photochemi...

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...

The melting properties of choline chloride in the representation of deep eutectic system phase diagrams.

Choline chloride (ChCl) is the cornerstone of deep eutectic solvents (DES), yet its melting properties remain an important source of uncertainty in th...

Combined Effects of Long-Term Sulfur Dioxide Exposure and Environmental Heat Stress on the Risk of Kidney Stone Disease.

OBJECTIVES: Kidney stone disease is influenced by environmental, metabolic, and climatic factors. Although sulfur dioxide and environmental heat stres...

Environmental Exposures and Neuroimaging in Children with Neurodevelopmental Disorders: A Scoping Review.

PURPOSE OF REVIEW: Neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) have...

Current Status of Smart Technology Applications and Food Safety Implications in Precision Millet Fermentation: A Critical Review.

Millet fermentation has gained significant attention due to its numerous health benefits, owing to its higher dietary fiber and gluten-free properties...

In silico identification of NPACT-derived PAK1 inhibitors using machine learning, molecular docking, and dynamic simulation approaches.

P21-activated kinase 1 (PAK1) is a key serine/threonine kinase involved in cytoskeletal remodeling, cell proliferation, and survival, and its aberrant...

Prediction Models of Polycyclic Aromatic Hydrocarbons in Urban Road Dust via Magnetic Properties, Particle Size, and Urban Environmental Features.

This study explores the novel application of artificial neural networks to predict polycyclic aromatic hydrocarbons (PAHs) pollution in urban road dus...

An integrative machine learning and structure-driven drug repositioning strategy for human IRAK4-targeted cancer therapy.

The upregulation of interleukin-1 receptor-associated kinase 4 (IRAK4) drives pro-tumorigenic signaling across various malignancies. Currently availab...

Lipase-Catalyzed Enantioselective Resolution of Chiral Pesticides and Herbicides: Advances in Biocatalysis and Enzyme Engineering.

Chiral pesticides and herbicides (CPHs) show significant enantioselective differences in bioactivity, toxicity, and environmental behavior, making sin...

Oil spill segmentation of noisy SAR images using domain adaptation based UNet.

Oil spills dampen the water bodies, causing serious threats to the marine environment. In this paper, oil spill detection and segmentation in satellit...

Physics-based models outperform AI weather forecasts of record-breaking extremes.

Artificial intelligence (AI)-based models are revolutionizing weather forecasting and have surpassed leading numerical weather prediction systems on v...