Environmental Health

Unraveling the complexity of organophosphorus pesticides: Ecological risks, biochemical pathways and the promise of machine learning.

Organophosphorus pesticides (OPPs) are widely used in agriculture but pose significant ecological and human health risks due to their persistence and toxicity in the environment. While microbial degradation offers a promising solution, gaps remain in understanding the enzymatic mechanisms, degradation pathways, and ecological impacts of OPP transformation products. This review aims to bridge these...

The NERVE-ML (neural engineering reproducibility and validity essentials for machine learning) checklist: ensuring machine learning advances neural engineering.

Machine learning's (MLs) ability to capture intricate patterns makes it vital in neural engineering research. With its increasing use, ensuring the validity and reproducibility of ML methods is critical. Unfortunately, this has not always been the case in practice, as there have been recent retractions across various scientific fields due to the misuse of ML methods and validation procedures. To a...

Neural Network With Attention Mechanism for Abnormality Detection and Localization in Diffusive Molecular Communication.

Diffusive molecular communication (DMC) is an emerging paradigm in nanotechnology, which provides biocompatibility and nanoscale communication for man...

Resolving multi-image spatial lipidomic responses to inhaled toxicants by machine learning.

Regional responses to inhaled toxicants are essential to understand the pathogenesis of lung disease under exposure to air pollution. We evaluate the ...

Assessing potential toxic metal threats in tea growing soils of India with soil health indices and machine learning technologies.

This study explores the impact of potentially toxic metals (PTMs) contamination in Indian tea-growing soils on ecosystems, soil quality, and human hea...

Reimagining the Kendall plot: using N and O of nitrate and advanced machine learning to improve N pollutant source classification.

Nitrate () pollution is a serious water quality issue in many countries due to contamination of lakes, rivers, and aquifers by intensive agriculture p...

Machine learning for predictive mapping of exceedance probabilities for potentially toxic elements in Czech farmland.

For efficient decision-making and optimal land management trajectories, information on soil properties in relation to safety guidelines should be proc...

Mitigation of the toxic effects of nitrite: Role and mechanism of isoleucine in mitigating mitochondrial DNA leakage-induced inflammation in grass carp (Ctenopharyngodon idella) under nitrite exposure.

The physiological and growth processes of fish are closely associated with their surrounding environment. This study investigated the role and underly...

Deep Learning-Based Detection of Aflatoxin B1 Contamination in Almonds Using Hyperspectral Imaging: A Focus on Optimized 3D Inception-ResNet Model.

Aflatoxin B1, a toxic carcinogen frequently contaminating almonds, nuts, and food products, poses significant health risks. Therefore, a rapid and non...

New and revised gene ontology biological process terms describe multiorganism interactions critical for understanding microbial pathogenesis and sequences of concern.

BACKGROUND: There is a new framework from the United States government for screening synthetic nucleic acids. Beginning in October of 2026, it calls f...

Forecasting the concentration of the components of the particulate matter in Poland using neural networks.

Air pollution is a significant global challenge with profound impacts on human health and the environment. Elevated concentrations of various air poll...

Risk assessment of potentially toxic elements and mapping of groundwater pollution indices using soft computer models in an agricultural area, Northeast Algeria.

Groundwater (GW) quality and contamination by potentially toxic elements (PTEs) are major concerns for environmental sustainability, particularly in a...

Enhancement of standardized precipitation evapotranspiration index predictions by machine learning based on regression and soft computing for Iran's arid and hyper-arid region.

Drought is a climate risk that affects access to safe water, crop development, ecological stability, and food production. Therefore, developing drough...

Accurate prediction of spatial distribution of soil heavy metal in complex mining terrain using an improved machine learning method.

Accurate prediction of heavy metals (HMs) spatial distribution in mining areas is crucial for pollution management. However, predicting the spatial di...

Artificial intelligence based detection and control strategies for river water pollution: A comprehensive review.

Water quality (WQ) is a metric for assessing the overall health and safety of water bodies like a river. Owing to the habitation of anthropogenic habi...

The need for epistemic humility in AI-assisted pain assessment.

It has been difficult historically for physicians, patients, and philosophers alike to quantify pain given that pain is commonly understood as an indi...

AI-aided chronic mixture risk assessment along a small European river reveals multiple sites at risk and pharmaceuticals being the main risk drivers.

The vast amount of registered chemicals leads to a high diversity of substances occurring in the environment and the creation of new substances outpac...

Prediction of acute toxicity of organic contaminants to fish: Model development and a novel approach to identify reactive substructures.

In this study, count-based Morgan fingerprints (CMF) were employed to represent the fundamental chemical structures of contaminants, and a neural netw...

Lung cancer detection with machine learning classifiers with multi-attribute decision-making system and deep learning model.

Diseases of the airways and the other parts of the lung cause chronic respiratory diseases. The major cause of lung disease is tobacco smoke, along wi...

Enhancing hydrogen sulfide control in urban sewer systems using machine learning models: Development of a new predictive simulation approach by using boosting algorithm.

Sewer networks are important urban infrastructure for transporting sewage to treatment plants, yet the generation of hydrogen sulfide within these sys...