Environmental Health

Integrating machine learning and structure-based simulations to prioritise Z4P as a mutation-resilient IRE1α inhibitor for breast cancer.

Breast cancer is one of the most prevalent and lethal malignancies affecting women globally. The increasing resistance to current therapeutic strategies highlights the need for novel molecular targets. Inositol-requiring enzyme 1 alpha (IRE1α), a key sensor in the unfolded protein response (UPR), has emerged as a promising therapeutic target due to its role in tumour progression and survival. This...

Artificial intelligence-guided and first-principles design and optimization of Rb₂YAgX₆ (X = F, Cl) double perovskite photodetectors.

Halides perovskites of lead have already shown very good optoelectronic behavior, but because of their toxicity and environmental issues, lead-free materials have been sought faster. The paper investigates the performance of Rb2YAgX6 (X = F, Cl) lead-free double perovskite photodetectors by means of a hybrid, first-principles and artificial intelligence (AI)-directed computational model. The stabi...

Divergent drivers of winter PM2.5 pollution in representative cities of the Sichuan Basin: Insights from observation and machine learning.

Fine particulate matter (PM2.5) continues to pose a significant challenge to regional air quality and human health in Chinese urban areas. This study ...

Microbially driven microplastic degradation: From mining functional microbiota to enhancing remediation potential in diverse environments.

Microplastic (MPs) pollution poses a global threat to ecosystems and human health. Traditional physicochemical methods face limitations like high cost...

Unraveling the adverse outcome pathways of metabolic dysfunction-associated steatotic liver disease triggered by environmental mixtures via biological knowledge-driven machine learning.

Environmental pollutant mixtures are potential risk factors for metabolic dysfunction-associated steatotic liver disease (MASLD), yet their joint effe...

Rapid detection of urinary tract infection by analyzing the dried spots of biological fluids using convolutional neural networks.

To find the cause of infectious diseases such as urinary tract infections, a the diagnostic patterning test was used. In this method, the whole blood ...

Decadal restructuring of driving forces for macroinvertebrate communities in China's Greater Bay Area.

As a vital ecological buffer zone and biodiversity hotspot, the structure and composition of macroinvertebrate communities in estuarine wetlands are u...

A PLM-based method for predicting protein ion channel modulators for drug discovery and safety evaluation.

Ion channels are central to regulating neuronal communication, cardiac rhythm, and muscle contraction. Their modulation can induce therapeutic benefit...

Finite-Element-Informed Pyramid Neural Network With Draco Lizard Optimizer for Accurate and Efficient Water Contamination Classification.

Water Contamination is a major issue of concern in the aquaculture industry, and it affects the sustainability of the ecosystem as well as the health ...

Screening of Medicinal and Edible Homology Substances for Diabetic Kidney Disease Based on GraphBAN.

BACKGROUND: Diabetic kidney disease (DKD) is a critical microvascular complication of diabetes mellitus, and the current pharmacotherapies are limited...

Comparison of High Spatial Resolution PM2.5, PM10, and NO2 Estimates Using a Deep Ensemble Machine Learning Framework in a Low Pollution Setting.

Recent studies report improved performance of ensemble models over machine learning (ML) models for air pollution estimation, although there is little...

Machine learning early warning for urban heat risk with CMIP6 projections.

Extreme heat (EH) has become an increasing threat to urban resilience, especially in rapidly urbanizing arid regions where environmental pressures int...

Prenatal exposure to particulate matter and risk of autism spectrum disorder in children: a population-based cohort study in South Korea.

BACKGROUND: Prenatal exposure to particulate matter has been investigated as a potential environmental factor for autism spectrum disorder (ASD), but ...

PM2.5 performance analysis under varying imputation strategies for incomplete sensor data.

Air pollution remains a primary global health concern, with one of its most hazardous components, fine particulate matter PM2.5, being recognized as a...

Machine learning prediction of mechanical dilatation in transvenous lead extraction for cardiac device-related infections: insights from a high-volume centre.

BACKGROUND: Transvenous lead extraction (TLE) requires high expertise in mechanical dilatation (MD), with double the risk of death and failure in low-...

Sustainable air pollution management in coal mining through low-cost sensors and smart monitoring platform.

Open-pit coal mining is a significant source of air pollution, especially in developing countries, where dust and gaseous emissions from mining operat...

Deep learning analysis of 12-lead electrocardiograms for bloodstream infection prediction: a multi-center validation study.

BACKGROUND: Prompt diagnosis of bloodstream infections (BSIs) is critical for antimicrobial stewardship but hindered by blood culture delays of 48 h o...

Hyperspectral image processing techniques for environmental monitoring: a comprehensive review.

Remote sensing and environmental monitoring have significantly advanced with the emergence of hyperspectral image processing techniques, offering unpa...

AI in Drug Discovery and Development.

Artificial intelligence (AI) is transforming drug discovery and development, fields historically constrained by long timelines, high costs, and substa...

Identifying the ideal deep learning algorithm to quantify the threshold effect of parental smoking on child nutritional status in South Asia.

BACKGROUND: Accurate identification of modifiable risk factors for child malnutrition is of great importance in the formulation of policies to protect...