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http://dx.doi.org/10.21037/apm-22-1028 | DOI Listing |
Molecules
January 2025
Engelhardt Institute of Molecular Biology of the Russian Academy of Sciences, 32 Vavilov St., Moscow 119991, Russia.
In recent years, a number of synthetic potentiators of antibiotics have been discovered. Their action can significantly enhance the antibacterial effect and limit the spread of antibiotic resistance through inhibition of bacterial cystathionine-γ-lyase. To expand the known set of potentiators, we developed methods for the synthesis of five new representatives of 6-bromoindole derivatives-potential inhibitors of bacterial cystathionine-γ-lyase-namely potassium 3-amino-5-((6-bromoindolyl)methyl)thiophene-2-carboxylate () and its 6-bromoindazole analogs ( and ), along with two 6-broindazole analogs of the parent compound .
View Article and Find Full Text PDFEnvironmental historical geography is a diverse, dynamic and active subfield with close connections to environmental history. Here, I examine developments in three overarching and overlapping themes within the subfield: environmental reconstruction, environmental knowledges and discourses, and environmental impacts and interventions. For each area, I highlight recent approaches to, and applications of, environmental historical geography.
View Article and Find Full Text PDFPLoS One
January 2025
National Marine Science Centre, Southern Cross University, Coffs Harbour, NSW, Australia.
Discovering new antibiotics and increasing the efficacy of existing antibiotics are priorities to address antimicrobial resistance. Antimicrobial proteins and peptides (AMPPs) are considered among the most promising antibiotic alternatives and complementary therapies. Here, we build upon previous work investigating the antibacterial activity of a semi-purified hemolymph protein extract (HPE) of the Australian oyster Saccostrea glomerata.
View Article and Find Full Text PDFBiotechnol Bioeng
January 2025
State Key Laboratory of Bioreactor Engineering, Qingdao Innovation Institute of East China University of Science and Technology, East China University of Science and Technology, Shanghai, China.
High-performance strain and corresponding fermentation process are essential for achieving efficient biomanufacturing. However, conventional offline detection methods for products are cumbersome and less stable, hindering the "Test" module in the operation of "Design-Build-Test-Learn" cycle for strain screening and fermentation process optimization. This study proposed and validated an innovative research paradigm combining computer vision with deep learning to facilitate efficient strain selection and effective fermentation process optimization.
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