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Environmental Pollutants

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[Short-term effects of PM10 on cause-specific mortality and the role of long-term environmental pressures in the industrial areas of Brindisi and Civitavecchia].

Epidemiologia e prevenzione
OBJECTIVES: the health status of people living near industrial plants is often exposed to several environmental risk factors, including air pollution. The aim of this study is to assess the relationship between daily PM10 levels and cause-specific mo...

Screening the phytotoxicity of micro/nanoplastics through non-targeted metallomics with synchrotron radiation X-ray fluorescence and deep learning: Taking micro/nano polyethylene terephthalate as an example.

Journal of hazardous materials
Microplastics (MPs) and nanoplastics (NPs) are global pollutants with emerging concerns. Methods to predict and screen their toxicity are crucial. Elemental dyshomeostasis can be used to assess toxicity of environmental pollutants. Non-targeted metal...

Deciphering exogenous chemical carcinogenicity through interpretable deep learning: A novel approach for evaluating atmospheric pollutant hazards.

Journal of hazardous materials
Cancer remains a significant global health concern, with millions of deaths attributed to it annually. Environmental pollutants play a pivotal role in cancer etiology and contribute to the growing prevalence of this disease. The carcinogenic assessme...

Advancing chronic toxicity risk assessment in freshwater ecology by molecular characterization-based machine learning.

Environmental pollution (Barking, Essex : 1987)
The continuously increased production of various chemicals and their release into environments have raised potential negative effects on ecological health. However, traditional labor-intensive assessment methods cannot effectively and rapidly evaluat...

Identification of biological indicators for human exposure toxicology in smart cities based on public health data and deep learning.

Frontiers in public health
With the acceleration of urbanization, the risk of urban population exposure to environmental pollutants is increasing. Protecting public health is the top priority in the construction of smart cities. The purpose of this study is to propose a method...

Immune Regulation Patterns in Response to Environmental Pollutant Chromate Exposure-Related Genetic Damage: A Cross-Sectional Study Applying Machine Learning Methods.

Environmental science & technology
Exposure to hexavalent chromium damages genetic materials like DNA and chromosomes, further elevating cancer risk, yet research rarely focuses on related immunological mechanisms, which play an important role in the occurrence and development of canc...

Construction of an antidepressant priority list based on functional, environmental, and health risks using an interpretable mixup-transformer deep learning model.

Journal of hazardous materials
As emerging pollutants, antidepressants (AD) must be urgently investigated for risk identification and assessment. This study constructed a comprehensive-effect risk-priority screening system (ADRank) for ADs by characterizing AD functionality, occur...

Deciphering the environmental chemical basis of muscle quality decline by interpretable machine learning models.

The American journal of clinical nutrition
BACKGROUND: Sarcopenia is known as a decline in skeletal muscle quality and function that is associated with age. Sarcopenia is linked to diverse health problems, including endocrine-related diseases. Environmental chemicals (ECs), a broad class of c...

Machine learning predicts the serum PFOA and PFOS levels in pregnant women: Enhancement of fatty acid status on model performance.

Environment international
Human exposure to per- and polyfluoroalkyl substances (PFASs) has received considerable attention, particularly in pregnant women because of their dramatic changes in physiological status and dietary patterns. Predicting internal PFAS exposure in pre...

ARKA: a framework of dimensionality reduction for machine-learning classification modeling, risk assessment, and data gap-filling of sparse environmental toxicity data.

Environmental science. Processes & impacts
Due to the lack of experimental toxicity data for environmental chemicals, there arises a need to fill data gaps by approaches. One of the most commonly used approaches for toxicity assessment of small datasets is the Quantitative Structure-Activit...