Environmental Health

Deep neural network-based detection of lead contamination via Förster resonance energy transfer in live cells.

Lead (Pb), a heavy metal with extensive industrial applications, poses significant risks to human health and the environment. These detrimental effects have driven strict global and local regulations, such as World Health Organization and Taiwan's drinking water limits, to minimize exposure and protect public health. To ensure compliance with these regulatory standards, we engineered lead ion bios...

Deep-learning-driven spectral image analysis for intelligent monitoring of multiple pesticides and antibiotics.

With the widespread use of pesticides and antibiotics in agriculture and healthcare, their associated environmental pollution and potential health hazards have emerged as a global concern. This study presents a novel deep learning-based spectral image analysis approach that is dedicated to the intelligent monitoring of multiple pesticides and antibiotics in agricultural water bodies. A total of 61...

Electrochemical sensors revolutionize plant nitrogen monitoring: Real-time, in situ detection for precision agriculture.

Driven by the dual imperatives of global food security and agricultural sustainability, dynamic plant nitrogen monitoring technology has emerged as a ...

Deep learning advances high-throughput toxicity screening of chemicals at multi-biological levels.

Deep learning (DL) has emerged as a powerful tool for modeling unstructured data, thereby improving prediction accuracy and expanding the application ...

Substance flow analysis combined with neural networks for predicting and reducing lead pollution in the secondary lead industry.

The recycling of spent lead-acid batteries has become increasingly crucial for lead (Pb) supply, yet it generates significant secondary pollutants inc...

Precise prevention of DEHP induced hepatic fibrosis: Early identifying high-risk populations, revealing key factors, and applying targeted intervention.

Metabolic dysfunction-associated fatty liver disease (MAFLD) poses a serious threat to human health. Hepatic fibrosis is a decisive factor in the deat...

Decoding the gut microbiota metabolite-matrix metalloproteinase-3 axis in breast cancer: a multi-omics and network pharmacology study.

Breast cancer is a malignant tumor originating from the breast epithelium, and emerging evidence suggests that the gut microbiota influences its devel...

Illuminating the universe of enzyme catalysis in the era of artificial intelligence.

Scientific research has revealed only a minuscule fraction of the enzymes that evolution has generated to power life's essential chemical reactions-an...

Computer Vision Detects an Association Between Gross Gill Score and Ventilation Rates in Farmed Atlantic Salmon (Salmo salar).

Poor gill health compromises the health and welfare of farmed Atlantic salmon (Salmo salar) by causing respiratory distress and increased ventilation ...

Computational glycosyltransferases masked deoxynivalenol toxicity and halted FHB spread in wheat grains.

INTRODUCTION: Contamination of cereal grains by deoxynivalenol (DON) poses a significant threat to food safety. This toxic secondary metabolite, produ...

Predicting nitrogen surplus in agricultural lands of China using a hybrid machine learning approach with smaller datasets and fewer features.

Global nitrogen pollution in agricultural lands poses a major environmental challenge, complicating both assessment and mitigation of nitrogen surplus...

Chronic Ocular Sequelae of Stevens-Johnson Syndrome: Recent Advances in Understanding of Patho-Physiology and Management.

BACKGROUND: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are severe mucocutaneous reactions primarily triggered by drugs or inf...

Exploring the impacts of key drivers on ground-level ozone in Southeast China using machine learning.

As a major atmospheric contaminant, ground-level ozone (O3) necessitates comprehensive analysis of the determinants influencing its concentration. Alt...

Combating Antimicrobial Resistance: Role of Key Stakeholders with Focus on the Pharmaceutical Sector.

Antimicrobial resistance is a pressing global health threat fueled by a complex interplay of biological, social, and economic factors. Despite widespr...

Machine learning combined with the PMF model reveals the sources and driving factors of PAHs and Cl-PAHs in urban runoff.

Urban rainwater runoff is an important source of nonpoint source pollution due to its transport of diverse contaminants, including polycyclic aromatic...

CTAB-modified Moroccan illite for sustainable removal of anionic and cationic dyes from simulated dye solutions: integrating experimental optimization and computational analysis.

Synthetic dyes in wastewater pose significant environmental risks, necessitating innovative removal solutions. This study explores the adsorption of A...

Insights into the Diagnosis, Treatment, and Management of Prion Diseases.

The normal cellular prion protein (PrPC) can misfold into an infectious and pathogenic form (PrPSc) to produce prion diseases, also known as transmiss...

Prediction of Internal Exposures after Virtual Oral Doses of Disparate Chemicals in Rats and Humans Using Simplified Physiologically Based Pharmacokinetic Models with Generated Input Parameters.

Toxicological evaluation of industrial chemicals with a broad range of chemical structures, for example, bioactive food components, toxic food-derived...

Metal oxide heterostructure towards gas sensing of trimethylamine: recent progress and challenges.

Gas sensors based on metal oxide heterostructures (MOHs) are popular due to their low cost, sensitivity, and eco-friendly production. MOHs significant...

Machine learning for predicting and optimizing the performance of a commercial-scale anaerobic digester with diverse feedstocks and operating conditions.

The improper disposal of food waste and livestock manure poses significant environmental risks, including nutrient pollution, water contamination, and...