Environmental Health

Projected westward advance of tropospheric formaldehyde over China.

Economic development and population aggregation are driving the east-to-west spread of tropospheric formaldehyde (HCHO) in China; yet the historical trajectory and future threat of this westward migration remain poorly understood. Here, we analyze OMI satellite observations utilizing a novel surface-to-line differentiation approach and machine learning to project spatiotemporal distribution of tro...

Integrated Multi-Omics Analysis of Gut Microbiota-Associated Metabolites and Related Host Molecular Signatures in Cervical Squamous Cell Carcinoma.

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is a common female malignancy. Gut microbiota and metabolites are critical regulators of tumor immunity and therapy, but their roles in CESC remain unclear. This study integrated TCGA and GEO datasets with gut microbiota information to construct a protein-protein interaction network. These targets were prioritized using machin...

A Deformable Lead-Attention Fusion Network for Multi-Label ECG Classification Integrating Clinical Metadata.

Cardiovascular diseases remain a major global health burden, making accurate elec-trocardiogram (ECG) analysis essential for timely diagnosis. While d...

Developing and evaluating automated deep learning and human-in-the-loop vision-language systems for microplastic characterization.

Microplastic (MP) pollution poses escalating environmental risks, demanding efficient and reproducible tools for morphological characterization of pla...

Intelligent engineering of Cs2AgBi0.75Sb0.25Br6 lead-free perovskite solar cells via machine learning-based optimization of charge transport materials and fabrication parameters.

This study presents a machine learning-driven framework to optimize environmentally friendly lead-free Cs2AgBi0.75Sb0.25Br6 perovskite solar cells (PS...

Measuring surprisal in sound sequences.

Sensory input that violates prior expectations attracts attention, making unpredictability an important perceptual property to measure. In the auditor...

From laboratory to field: a critical review of multi-modal sensing frameworks for emerging contaminant monitoring.

Emerging pollutants are now widely detected in water at trace concentrations (ng/L to µg/L). Conventional monitoring relies on laboratory methods such...

Next generation materials for environmental remediation through advanced mechanisms and future perspectives.

Escalating environmental pollution and the increasing complexity of contaminants pose significant challenges to conventional remediation technologies,...

Uncovering hidden industrial wastewater discharges in urban rivers via deep learning-enhanced fiber-optic distributed acoustic sensing.

Illicit wastewater discharges from concealed outfalls threaten urban river ecosystems, often evading conventional monitoring. This study introduces an...

Spiramycin (SPR) antibiotics degradation with WO3 photocatalyst and ML XGBoost model for process parameters screening.

The intensification of worldwide urbanization and industrial growth has led to a rise in the release of toxic substances into the environment. Antibio...

Is a (satellite) image worth a thousand data points? Comparing machine learning approaches to predict environmental and social inequalities in England.

Accurately mapping environmental and social inequalities at fine spatial scales is critical for urban policy, yet the data required are often costly a...

Epidemiologically validated spatial modelling reveals fine-scale heat health risks.

Heat exposure drives substantial global disease and mortality burdens, making spatially explicit heat health risk assessment essential for targeted ad...

Prediction of Atrial Fibrillation Occurrence With Handheld Mobile Electrocardiogram: Deep Learning Model Development Using Real-World Data.

BACKGROUND: Atrial fibrillation (AF) is a common arrhythmia associated with an increased risk of stroke and heart failure. To improve prevention, rece...

A critical review of mechanistic insights and technological advancement for the amelioration of Pb and Cd through phytoremediation.

Heavy metal contamination is a major environmental concern due to its persistence, bioaccumulation, and long-term impacts on ecosystems and human heal...

Applications of machine learning in microbial source tracking.

Microbial source tracking (MST) has become important in environmental ecology, food safety, and forensic investigation. With advances in microbiome te...

Long-term PM2.5 exposure and leukemia risk from childhood to early adulthood: A nationwide longitudinal cohort study with time-varying exposure analysis.

Long-term exposure to fine particulate matter (PM2.5) has been suggested as an environmental risk factor for childhood leukemia. This study examined t...

Toxicological Knowledge-Guided Graph Learning for Interpretable and Generalizable Molecular Toxicity Prediction.

Early identification of toxic liabilities is essential for improving drug safety and reducing attrition. However, structure-based deep learning models...

Drivers of cropland carrying capacity and pathways for mitigating livestock overloading in intensive agricultural systems.

Integrated crop-livestock systems support nutrient cycling and resource efficiency. Their long-term sustainability depends on whether livestock produc...

ADRB2 Modulates Asbestos-Induced Pleural Mesothelioma Progression by Influencing IL-17/NF-κB-Related Inflammatory Signalling: An Integrated Network Toxicology, Multi-Omics and Experimental Study.

Pleural mesothelioma (PM) is a highly aggressive asbestos-related malignancy with poor prognosis and limited early diagnostic options. In this study, ...

Semiparametric hybrid air quality forecasting using prophet ensemble and feature selection.

Due to air quality management and public health planning, accurately predicting PM2.5 concentrations is absolutely imperative. Having many lagged vari...