首页|Chinese Academy of Sciences Reports Findings in Machine Learning (Occurrence and Distribution of Antibacterial Quaternary Ammonium Compounds in Chinese Estuarie s Revealed by Machine Learning-Assisted Mass Spectrometric Analysis)
Chinese Academy of Sciences Reports Findings in Machine Learning (Occurrence and Distribution of Antibacterial Quaternary Ammonium Compounds in Chinese Estuarie s Revealed by Machine Learning-Assisted Mass Spectrometric Analysis)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting from Beijing, People’s Republ ic of China, by NewsRx journalists, research stated, “Antimicrobial resistance ( AMR) undermines the United Nations Sustainable Development Goals of good health and wellbeing. Antibiotics are known to exacerbate AMR, but nonantibiotic antim icrobials, such as quaternary ammonium compounds (QACs), are now emerging as ano ther significant driver of AMR.” The news correspondents obtained a quote from the research from the Chinese Acad emy of Sciences, “However, assessing the AMR risks of QACs in complex environmen tal matrices remains challenging due to the ambiguity in their chemical structur es and antibacterial activity. By machine learning prediction and high-resolutio n mass spectrometric analysis, a list of antibacterial QACs ( = 856) from indust rial chemical inventories is compiled, and it leads to the identification of 50 structurally diverse antibacterial QACs in sediments, including traditional hydr ocarbon-based compounds and new subclasses that bear additional functional group s, such as choline, ester, betaine, aryl ether, and pyridine. Urban wastewater, aquaculture, and hospital discharges are the main factors influencing QAC distri bution patterns in estuarine sediments. Toxic unit calculations and metagenomic analysis revealed that these QACs can influence antibiotic resistance genes (par ticularly sulfonamide resistance genes) through cross- and coresistances. The po tential to influence the AMR is related to their environmental persistence.”
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