Environmental Health

Inversion of soil heavy metal content in surface coal mine area based on fractional-order derivative and reindeer cyclone optimization algorithm support vector regression.

Open-pit mining activities lead to heavy metal accumulation in soils, posing a serious threat to ecosystems and public health, necessitating the development of efficient, large-scale monitoring methods. In recent years, machine learning has demonstrated significant potential in uncovering complex relationships between environmental data and pollutants, offering a new paradigm for heavy metal predi...

Rapid assessment of pesticide toxicity in aquatic ecosystems using deep learning-based automatic duckweed counting method.

Pesticides are widely used in agriculture to control weeds, insects, and diseases that threaten crop yields. However, their extensive use raises concerns about environmental impacts, particularly in aquatic ecosystems, which are vulnerable to contamination through runoff and leaching. To assess the toxicity of pesticides to aquatic plants, we applied an optimized automated duckweed (Wolffia globos...

Evaluating the accuracy of screening titles and abstracts for progressing to full-text screening by one vs two independent reviewers: part 1 of a meta-research study of rapid review methodological trade-offs.

OBJECTIVES: To determine the accuracy for progressing records to full-text screening using one vs two reviewers to screen title and abstracts in 3 rev...

On the importance of soil texture for predicting future global soil respiration.

Soil respiration, the flux of CO2 from soils to the atmosphere, is an important component of the global carbon budget, but our understanding of its fu...

Temporal dynamics of mercury exposure and associated health and economic burdens in China.

Mercury is a global highly toxic pollutant linked to neurodevelopmental impairments and cardiovascular risks. However, despite being the world's large...

Targeting autophagy in Duchenne muscular dystrophy: mechanistic insights and emerging therapeutic strategies.

Duchenne muscular dystrophy (DMD) is a severe X-linked myopathy characterised by progressive skeletal and cardiac muscle degeneration, loss of ambulat...

Quantifying Multi-pollutant Co-exposure via Deep Learning-Based Simultaneous Prediction Using Geostationary Satellite Data.

Simultaneous prediction of multiple air pollutants is essential for quantifying human co-exposure and evaluating the health impacts of pollutant mixtu...

Global Mega-Challenges and International Collaboration in Science, Education, and Health.

We live in an interdependent world riven by ideology, factions, and rivalries, and we face enormous challenges such as climate disruption, an aging po...

Predicting toxicity and bioactivity of the chemical exposome: a case study for the blood exposome database.

Humans are exposed to thousands of chemicals throughout their life. Many of these chemicals are detected in blood and have been catalogued in the Bloo...

Machine Learning Potentials for Inorganic and Hybrid Lead Halide Perovskites: From Phase Stability to Defects and Interfaces.

Inorganic and hybrid lead halide perovskites are among the most promising candidates for next-generation optoelectronic devices. However, their furthe...

Risks of Microplastics Shaping Viral Communities and Functions in Real Marine Environments.

Microplastic (MP) pollution has become a global issue, especially in the oceans. However, the extent of changes in the ecological states of viruses th...

Antibody-drug conjugate design and mechanisms of action for cancer treatment: state of the art and beyond.

Antibody-drug conjugates (ADCs) are a leading area of targeted cancer therapeutics, typically combining a tumour-associated antigen-specific antibody ...

Toxic chinese herbal medicine recognition in real-world images via multi-scale and attention-enhanced EfficientNetV2.

Accurate identification of toxic Chinese herbal medicines is critical for public health and clinical safety. However, real-world herbal images often e...

From mapping to modelling: the evolving multidimensional microplastic risks in China's farmlands.

Agricultural soils are major sinks for microplastic (MP) pollution, yet the cascading drivers that shape multidimensional MP risks remain poorly under...

Effects of climate and air pollution on rates of hospitalization for affective mood disorders in southern Brazil.

Climate change and air pollution are two of the most pressing global challenges, increasingly recognized for their implications on health. Thus, we ai...

Graph Machine Learning Can Estimate Drug Concentrations in Whole Blood from Forensic Screening Results.

LC-HRMS is widely used in forensic toxicology for broad-scope screening. When a newly emerging or rarely encountered compound is tentatively identifie...

Development and validation of an artificial intelligence-based model for predicting teicoplanin plasma concentrations in intensive care unit patients with pulmonary infections: a retrospective study.

INTRODUCTION: Teicoplanin is widely used to treat pulmonary infections, particularly in critically ill patients with gram-positive bacterial infection...

Multi-model forecasting of [Formula: see text] and [Formula: see text] in Abu Dhabi: benefits of correlation-based feature augmentation.

Air pollution, particularly Nitrogen Dioxide ([Formula: see text]) and ground-level ozone ([Formula: see text]), poses major risks to human health and...

Altitude-resolved prediction of roadside air pollution using UAV measurements and machine learning.

Machine Learning-Enhanced Raman Spectroscopy for Microfiber Detection: From Model Development to Coastal Investigation.

Microfibers are recognized as the most prevalent form of microplastics, with a widespread distribution across various ecosystems. The distinctive morp...