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识别复杂情况的自动化技术进展。

Advances in automated techniques to identify complex.

作者信息

Bagudo Ahmad Ibrahim, Obande Godwin Attah, Harun Azian, Singh Kirnpal Kaur Banga

机构信息

Department of Medical Microbiology and Parasitology, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, 16150Kubang Kerian, Kelantan, Malaysia.

出版信息

Asian Biomed (Res Rev News). 2020 Oct 31;14(5):177-186. doi: 10.1515/abm-2020-0026. eCollection 2020 Oct.

Abstract

species, particularly those within complex (ACB complex), have emerged as clinically relevant pathogens in hospital environments worldwide. Early and quick detection and identification of infections is challenging, and traditional culture and biochemical methods may not achieve adequate levels of speciation. Moreover, currently available techniques to identify and differentiate closely related species are insufficient. The objective of this review is to recapitulate the current evolution in phenotypic and automated techniques used to identify the ACB complex. Compared with other automated or semiautomated systems of bacterial identification, matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) demonstrates a high level of species identification and discrimination, including newly discovered species and .

摘要

某些菌种,特别是复杂菌属(ACB 菌属)中的那些菌种,已在全球医院环境中成为具有临床相关性的病原体。对这些感染进行早期快速检测和鉴定具有挑战性,传统的培养和生化方法可能无法达到足够的菌种鉴定水平。此外,目前用于识别和区分密切相关菌种的技术并不充分。本综述的目的是概述用于鉴定 ACB 菌属的表型和自动化技术的当前进展。与其他细菌鉴定的自动化或半自动系统相比,基质辅助激光解吸电离飞行时间质谱(MALDI-TOF MS)在菌种鉴定和区分方面表现出较高水平,包括新发现的菌种和……

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03dc/10373397/baaacac9cfe3/j_abm-2020-0026_fig_001.jpg

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