机器学习在抗生素的鉴定识别、微生物作用机制以及去除效果评估中的应用研究进展  

Research progress in the application of machine learning in the identification of antibiotics,microbial mechanism of action and evaluation of removal effect

作　　者：庞蕊蕊 邵博群 李烨 谢冰[1,2] 苏应龙 PANG Ruirui;SHAO Boqun;LI Ye;XIE Bing;SU Yinglong(Shanghai Engineering Technology Research Center of Organic Solid Waste Bioconversion,School of Ecological and Environmental Sciences,East China Normal University,Shanghai,200241,China;Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration,School of Ecological and Environmental Sciences,East China Normal University,Shanghai,200241,China)

机构地区：[1]华东师范大学生态与环境科学学院,上海有机固废生物转化工程技术研究中心,上海200241 [2]华东师范大学生态与环境科学学院,上海市城市生态过程与生态修复重点实验室,上海200241

出　　处：《环境化学》2022年第6期1947-1956,共10页Environmental Chemistry

基　　金：国家自然科学基金(41807462);上海有机固废生物转化工程技术研究中心(19DZ2254400)资助.

摘　　要：抗生素在医疗卫生、养殖业等领域的广泛应用导致其随着医疗废弃物、废水等进入到自然环境并对人体健康和生态环境造成不利影响,而系统分析环境中残留抗生素的种类、明确其与微生物的作用机制以及开展不同处理方法的效果分析,对于准确评估抗生素的风险和控制其不利影响具有重要意义.作为一种辅助手段,机器学习算法在大量数据解析的基础上可进行结果评估和预测,因此可高效、低成本分析环境污染物的行为特征.基于此,本文综述了机器学习算法在抗生素鉴定识别、微生物作用机制和去除效果评估预测方面的应用现状,并概括了不同算法的应用特点和局限性.鉴于机器学习当前在抗生素研究中的重要作用,为其未来研究方向和发展提出展望,如在其它新兴污染物的环境行为、效应及控制等方面的应用.The wide application of antibiotics in medical and health,breeding and other fields leads to their entry into the natural environment along with medical waste and waste water.It causes adverse effects on human health and ecological environment.It is of great significance for accurately assessing the risk of antibiotics and controlling their adverse effects to analyze the types of residual antibiotics in the environment,the mechanism of their interaction with microorganisms and the effect analysis of different treatment methods.As an auxiliary method,machine learning algorithms can evaluate and predict the results based on the analysis of large amounts of data,which can effectively and cheaply analyze the behavioral characteristics of environmental pollutants.Based on this,this paper reviewed the application status of machine learning algorithms in antibiotic identification,microbial mechanism of action and evaluation of removal effect.The application characteristics and limitations of different algorithms are also summarized.In view of the important role of machine learning in the current antibiotic research,the future research direction and development of machine learning are proposed,such as its application in the environmental behavior,effect and control of other emerging pollutants.

关 键 词：机器学习 抗生素 鉴定识别 作用机制 去除效果评估 

分 类 号：X505[环境科学与工程—环境工程] TP181[自动化与计算机技术—控制理论与控制工程]