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...

Keystone microbial taxa identified by deep learning reveal mechanisms of phosphorus stoichiometric homeostasis in submerged macrophytes under different hydrodynamic states.

Water research
Phosphorus (P) pollution in aquatic ecosystems triggers eutrophication, disrupting ecological processes. Although phytoremediation using submerged macrophytes is promising, its efficacy depends on plant-microbe interactions and stoichiometric homeost...

Deep learning-enhanced hyperspectral imaging for rapid screening of Co-metabolic microplastic-degrading bacteria in environmental samples.

Journal of hazardous materials
Microbial biodegradation of microplastic (MP) emerges as an environmentally benign and highly promising strategy for alleviating MP pollution in the ecosystem. Conventional approaches for screening MP-degrading bacteria use pollutants as the sole car...

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...

Predicting the environmental fate of biodegradable mulch films: A machine learning approach for sustainable agriculture.

Journal of hazardous materials
Biodegradable plastic mulch films (BDM) have been proposed as one of the dominant strategies for plastic pollution prevention in agriculture. As the BDM degradation is a complex process affected by multiple factors, the degradation cycle of BDM has s...

Recent advances in occurrence, biotreatment, and integrated insights into bacterial degradation of phthalic acid esters in aquatic environments.

Journal of hazardous materials
Phthalic acid esters (PAEs) are prevalent as emerging contaminants owing to their widespread use as plasticizers in industry. Despite their environmental and health risks, a limited understanding of PAE contamination in aquatic environments hinders t...

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...