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环境中抗菌耐药性选择的预测无影响浓度的关键荟萃分析。

A critical meta-analysis of predicted no effect concentrations for antimicrobial resistance selection in the environment.

机构信息

European Centre for Environment and Human Health, University of Exeter Medical School, Faculty of Health and Life Sciences, Environment & Sustainability Institute, Penryn Campus, Cornwall TR10 9FE, United Kingdom.

UK Centre for Ecology and Hydrology, Wallingford OX10 8BB, United Kingdom.

出版信息

Water Res. 2024 Nov 15;266:122310. doi: 10.1016/j.watres.2024.122310. Epub 2024 Aug 26.

DOI:10.1016/j.watres.2024.122310
PMID:39217643
Abstract

Antimicrobial resistance (AMR) is one of the greatest threats to human health with a growing body of evidence demonstrating that selection for AMR can occur at environmental antimicrobial concentrations. Understanding the concentrations at which selection for resistance may occur is critical to help inform environmental risk assessments and highlight where mitigation strategies are required. A variety of experimental and data approaches have been used to determine these concentrations. However, there is minimal standardisation of existing approaches and no consensus on the relative merits of different methods. We conducted a semi-systematic literature review to collect and critically appraise available minimal selective concentration (MSC) and predicted no effect concentration for resistance (PNECR) data and the approaches used to derive them. There were 21 relevant articles providing 331 selective concentrations, ranging from 0.00087 µg/L (ciprofloxacin) to 2000 µg/L (carbenicillin). Meta-analyses of these data found that selective concentrations are highly compound-dependent, and only a subset of all antimicrobials have been the focus of most of the research. The variety of approaches that have been used, knowledge gaps and future research priorities were identified, as well as recommendations for those considering the selective risks of antimicrobials in the environment.

摘要

抗菌药物耐药性(AMR)是对人类健康的最大威胁之一,越来越多的证据表明,环境中抗菌药物浓度可导致耐药性选择。了解可能发生耐药性选择的浓度对于帮助进行环境风险评估和突出需要采取缓解策略的地方至关重要。已经使用了各种实验和数据方法来确定这些浓度。然而,现有的方法几乎没有标准化,也没有就不同方法的相对优点达成共识。我们进行了半系统文献综述,以收集和批判性评估可用的最小选择浓度(MSC)和预测抗药性无影响浓度(PNECR)数据以及推导这些数据的方法。有 21 篇相关文章提供了 331 个选择浓度,范围从 0.00087 µg/L(环丙沙星)到 2000 µg/L(羧苄青霉素)。对这些数据的荟萃分析发现,选择浓度高度依赖于化合物,而且只有一部分抗菌药物是大多数研究的重点。确定了所使用的各种方法、知识差距和未来的研究重点,以及对那些考虑环境中抗菌药物选择风险的人的建议。

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