Environmental Health

Identifying Shared Diagnostic Genes and Underlying Mechanisms Between Skin Exposure to Air Pollution and Skin Barrier Damage: A Bioinformatics Approach.

Air pollution poses a significant threat to skin health, contributing to inflammation, aging, and disruption of the epidermal barrier. This study aims to identify genes associated with skin exposure to air pollution and skin barrier damage, and to discover potential biomarkers for these effects. Datasets related to air pollution-exposed skin (PS) and skin barrier damage (SD) were obtained from the...

Spatial analysis of air pollution and cancer prevalence in Texas: a machine learning approach using satellite remote sensing data.

Cancer prevalence in the world has been attributed to exposure to air pollutants. However, spatial analyses utilizing remote sensing data have been limited. This study combined satellite-derived measurements of eight air pollutants (SO2, NO2, CO, HCHO, CH4, PM1, PM10, and AER AI) with machine learning algorithms to analyze the relationship between air pollution and cancer prevalence across all 254...

Digital Stethoscope-Derived Single-Lead Electrocardiogram and Artificial Intelligence to Detect Low Ejection Fraction: A Multicenter Observational Study.

OBJECTIVES: Identifying patients likely to benefit from an echocardiogram before surgery is prudent in resource-limited settings. Recently, artificial...

Carbon quantum dots exacerbate Parkinson's disease-like pathology through microglia-mediated neuroinflammatory responses with toxicological implications.

The global burden of Parkinson's disease (PD) is projected to double by 2050, with early-onset cases demonstrating accelerated progression and limited...

Three-Dimensional Burrowing Behavior of Earthworms for Ecotoxicological Studies.

Earthworm behavioral biomarkers provide more sensitive and comprehensive assessments for environmental contaminants. However, natural soil opaqueness ...

Selective Sensing of Hydrogen and Ammonia Using a Single CMOS-Compatible Sensor and Transfer Learning Methods.

The development of high-performance gas sensors is crucial for ensuring safety and efficiency in the emerging hydrogen economy, particularly for detec...

Source identification of sudden water pollution events in the Dongliao River using a hybrid machine learning framework.

Rapid and accurate identification of pollution sources is critical for emergency management but remains challenged by the high computational cost and ...

Advancing operational global aerosol forecasting with machine learning.

Aerosol forecasting is important for air-quality management, health risk assessment and climate change mitigation1,2. However, it is more complex than...

Real-time digital prescriptions unlock influenza dynamics: evidence from 21 million transactions.

Traditional influenza surveillance suffers from 1-2 week reporting delays that compromise outbreak response. We analyzed 21.08 million digital prescri...

Early electrocardiographic repolarization changes are associated with subclinical cancer therapy-related cardiac dysfunction in lymphoma patients: A machine learning-assisted longitudinal study.

UNLABELLED: Anthracycline-induced cardiotoxicity remains a significant clinical challenge. We evaluated longitudinal electrocardiographic (ECG) repola...

USEM: A Unified Model for Simultaneous Estimation of Multiple Nutrient Concentrations in Coastal Waters using Landsat 5/7/8 and Sentinel-2 imagery.

Accurate estimation of nutrient concentrations is vital for monitoring coastal eutrophication but remains challenging due to the lack of direct spectr...

AI fragmentation-based optimization of Sorafenib derivatives targeting VEGFR2 for angiogenesis-related pathologies: a structure-based in-silico study.

Vascular endothelial growth factor receptor 2 (VEGFR2) is a central regulator of angiogenesis and endothelial signaling and represents a validated the...

A cluster-aware synthetic resampling and machine learning framework for multi-class Air Quality Index classification.

The Air Quality Index (AQI) is a widely used indicator for assessing ambient pollution levels and associated health risks. However, AQI classification...

Algal Sentinel: a novel web application for early warning and forecasting of Ostreopsis cf. ovata blooms in the Italian Southern Adriatic Sea.

The toxic benthic dinoflagellate Ostreopsis cf. ovata causes harmful algal blooms (HABs) in the Apulia region of southern Italy. These HABs pose real ...

Construction of air quality health index based on multi-pollutant Bayesian kernel machine regression and deep learning early warning framework.

BACKGROUND: Efficient characterization and early warning of health risks associated with air pollution are critical issues in public health management...

Advancing Global Nursing Policy: AI-Driven Health Literacy Innovations for Migrant Domestic Workers.

AIM: This perspective proposes evidence-informed strategies to advance health literacy equity for migrant domestic workers (MDWs) globally, integratin...

Machine learning-based MPPT integration with quadratic double-extended DC-DC converter for grid-connected PV-powered BLDC electric vehicles.

To mitigate the environmental challenges posed by pollution and climate change, researchers are increasingly focused on developing highly efficient, e...

Satellite-Driven Modelling of NO2 and PM2.5 Across Germany (2019-2024): A Multi-Sensor Machine-Learning Approach.

Mapping air pollution across space remains challenging, even in countries with dense monitoring networks. In Germany, pollutant levels can change over...

Prediction of the joint toxicity of microplastics and organic pollutants on algae based on machine learning.

Complex joint toxicity driven by microplastic (MP)-organic pollutant mixtures in aquatic ecosystems remains poorly captured by conventional models. He...

Bacterial laccases for green remediation of contaminants of emerging concern: from molecular cloning to metagenomic and computational insights.

Contaminants of emerging concern (CECs) are increasingly recognized for their persistence, widespread occurrence, and potential risks to environmental...