AIMC Topic: Biodegradation, Environmental

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Emerging technologies for assessing the occurrence, fate, effects, and remediation of plastics in the environment.

Environmental monitoring and assessment
Plastic pollution and contamination originates from raw material handling, polymerization, compounding, and fabrication, contributing to environmental accumulation. Advanced analytical techniques such as Fourier transform infrared, Raman spectroscopy...

Synergistic potential of halophytes and halophilic/halotolerant plant growth-promoting bacteria in saline soil remediation: Adaptive mechanisms, challenges, and sustainable solutions.

Microbiological research
Salinity stress poses significant challenges to agriculture, reducing productivity and limiting arable land by causing ionic and osmotic imbalances in plants, disrupting physiological processes, and leading to soil degradation over time. Halophytes a...

Disturbance and stability dynamics in microbial communities for environmental biotechnology applications.

Current opinion in biotechnology
Microbial communities are corner stones of environmental biotechnology, driving essential processes such as waste degradation, pollutant removal, and nutrient cycling, all fundamental to industrial bioprocesses and sustainability. The structure and f...

Advancing Enzyme-Based Detoxification Prediction with ToxZyme: An Ensemble Machine Learning Approach.

Toxins
The aaccurate prediction of enzymes with environment detoxification functions is crucial, not only to achieve a better understanding of bioremediation strategies, but also to alleviate environmental pollution. In the present study, a novel machine le...

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

The Science of the total environment
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...

Unlocking the potential of Eudrilus eugeniae in mitigating the pollution risk of pesticides and heavy metals: Fostering machine learning tactics to optimize environmental health.

The Science of the total environment
Agro-industrial waste management remains a critical challenge in sustainable development, particularly due to contamination with heterogeneous micropollutants such as heavy metals (HMs), pesticides, and polyphenols. This study explores an innovative ...

Polymer Biodegradation in Aquatic Environments: A Machine Learning Model Informed by Meta-Analysis of Structure-Biodegradation Relationships.

Environmental science & technology
Polymers are widely produced and contribute significantly to environmental pollution due to their low recycling rates and persistence in natural environments. Biodegradable polymers, while promising for reducing environmental impact, account for less...

Predictive modeling of diazinon residual concentration in soils contaminated with potentially toxic elements: a comparative study of machine learning approaches.

Biodegradation
The widespread use of pesticides, including diazinon, poses an increased risk of environmental pollution and detrimental effects on biodiversity, food security, and water resources. In this study, we investigated the impact of Potentially Toxic Eleme...

Interpretation of machine learning-based prediction models and functional metagenomic approach to identify critical genes in HBCD degradation.

Journal of hazardous materials
Hexabromocyclododecane (HBCD) poses significant environmental risks, and identifying HBCD-degrading microbes and their enzymatic mechanisms is challenging due to the complexity of microbial interactions and metabolic pathways. This study aimed to ide...