Polycyclic aromatic hydrocarbons (PAHs) are a complex group of environmental contaminants, many having long environmental half-lives. As these compounds degrade, the changes in their structure can result in a substantial increase in mutagenicity compared to the parent compound. Over time, each individual PAH can potentially degrade into several thousand unique transformation products, creating a complex, constantly evolving set of intermediates. Microbial degradation is the primary mechanism of their transformation and ultimate removal from the environment, and this process can result in mutagenic activation similar to the metabolic activation that can occur in multicellular organisms. The diversity of the potential intermediate structures in PAH-contaminated environments renders hazard assessment difficult for both remediation professionals and regulators. A mixture of structural and energetic descriptors has proven effective in existing studies for classifying which PAH transformation products will be mutagenic. However, most existing studies of environmental PAH mutagens primarily focus on nitrogenated derivatives, which are prevalent in the atmosphere and not as relevant in soil. Additionally, PAH products commonly found in the environment can range from as large as five rings to as small as a single ring, requiring a broadly inclusive methodology to comprehensively evaluate mutagenic potential. We developed a combination of supervised and unsupervised machine learning methods to predict environmentally induced PAH mutagenicity with improved performance over currently available tools. K-means clustering with principal component analysis allows us to identify molecular clusters that we hypothesize to have similar mechanisms of action. Recursive feature elimination identifies the most influential descriptors. The cluster-specific regression outperforms available classifiers in predicting direct-acting mutagens resulting from the microbial biodegradation of PAHs and provides direction for future studies evaluating the environmental hazards resulting from PAH biodegradation.
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http://dx.doi.org/10.1021/acs.chemrestox.1c00187 | DOI Listing |
Int J Biol Macromol
January 2025
College of Technology and Engineering, MPUAT, Udaipur, Rajasthan-313001, India. Electronic address:
Lipases, enzymes that perform the hydrolysis of triglycerides into fatty acids and glycerol, present a potential paradigm shift in the realms of food and detergent industries. Their enhanced efficiency, energy conservation and environmentally friendly attributes make them promising substitutes for chemical catalysts. Motivated by this prospect, this present study was targeted on the heterologous expression of a lipase gene, employing E.
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January 2025
Iranian Research Organization for Science and Technology (IROST), Sh. Ehsani Rad St., Enqelab St., Ahmadabad Mostoufi Rd., Azadegan Highway, P. O. Box 33535-111, Tehran 3313193685, Iran.
Bacterial cellulose, with mechanical strength, high water absorption, and crystallinity, is used in eco-friendly packaging, wound dressings, and drug delivery systems. Despite its potential, industrial-scale production is limited by inefficiency and high costs, requiring high-yield strains and optimized growth conditions. This study found that indigenous isolates produce superior bacterial cellulose compared to standard strains.
View Article and Find Full Text PDFJ Biotechnol
January 2025
Key Laboratory of Industrial Fermentation Microbiology, Ministry of Education, Tianjin Key Laboratory of Industrial Microbiology, College of Biotechnology, Tianjin University of Science & Technology, Tianjin 300457, China. Electronic address:
11α-Hydroxyandrost-4-ene-3,17-dione (11α-OH AD) is an essential steroid hormone drug intermediate that exhibits low biotransformation efficiency. In this study, a mixed-strain fermentation strategy was established for the efficient production of 11α-OH AD from phytosterols (PS). Initially, strains were screened for efficient transformation of AD to produce 11α-OH AD.
View Article and Find Full Text PDFSci Total Environ
January 2025
China National Environmental Monitoring Centre, Beijing 100012, China.
The riverine dissolved organic matter (DOM) pool constitutes the largest and most dynamic organic carbon reservoir within inland aquatic systems. Human activities significantly alter the distribution of organic matter (OM) in rivers, thereby affecting the availability of DOM. However, the impact of total suspended solids (TSS) on DOM under anthropogenic influence remains insufficiently elucidated.
View Article and Find Full Text PDFActa Psychol (Amst)
January 2025
School of Business, International University, Ho Chi Minh City, Vietnam; Vietnam National University, Ho Chi Minh City, Vietnam. Electronic address:
As the green transformation sweeps across industries in the digital age, tourism stakeholders face a pressing need to utilize online platforms and digital influencers for sustainability messaging. Drawing on the Motivation-Opportunity-Ability framework, this study investigates the influence of green ownership psychology and green knowledge sharing on tourists' repatronage intentions. It focuses on the mediating role of cooperative green activity programs and the moderating impact of tourists' green trust in social media influencers.
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