Evidence map›Paper›PMID 38538920›Full record

ArticleWorld journal of microbiology & biotechnology2024

Differentiation of closely-related species within Acinetobacter baumannii-calcoaceticus complex via Raman spectroscopy: a comparative machine learning analysis.

Xue-Song Xiong, Lin-Fei Yao, Yan-Fei Luo, Quan Yuan, Yu-Ting Si, Jie Chen, Xin-Ru Wen, Jia-Wei Tang, Su-Ling Liu, Liang Wang

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In one paragraph

Article in World journal of microbiology & biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Xue-Song Xiong *Laboratory Medicine, The Fifth People's Hospital of Huai'an, Huai'an, Jiangsu Province, China.
Lin-Fei Yao *School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, Jiangsu Province, China.
Yan-Fei Luo *Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China.
Quan YuanSchool of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, Jiangsu Province, China.
Yu-Ting SiLaboratory Medicine, Medical Technology School of Xuzhou Medical University, Xuzhou, Jiangsu Province, China.
Jie ChenLaboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China.
Xin-Ru WenSchool of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, Jiangsu Province, China.
Jia-Wei TangLaboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China. 15061183455@163.com.
Su-Ling LiuLaboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China. liusuling@gdph.org.cn.
Liang WangLaboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China. wangliang@gdph.org.cn.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2022A1515220023Research Funding for Guangdong Provincial Medical Technology B2021010Talent Start-Up Funding of Guangdong Provincial People's Hospital KY012023293
6 · The paper itself

Abstract

Bacterial species within the Acinetobacter baumannii-calcoaceticus (Acb) complex are very similar and are difficult to discriminate. Misidentification of these species in human infection may lead to severe consequences in clinical settings. Therefore, it is important to accurately discriminate these pathogens within the Acb complex. Raman spectroscopy is a simple method that has been widely studied for bacterial identification with high similarities. In this study, we combined surfaced-enhanced Raman spectroscopy (SERS) with a set of machine learning algorithms for identifying species within the Acb complex. According to the results, the support vector machine (SVM) model achieved the best prediction accuracy at 98.33% with a fivefold cross-validation rate of 96.73%. Taken together, this study confirms that the SERS-SVM method provides a convenient way to discriminate between A. baumannii, Acinetobacter pittii, and Acinetobacter nosocomialis in the Acb complex, which shows an application potential for species identification of Acinetobacter baumannii-calcoaceticus complex in clinical settings in near future.

Indexed as

AcinetobacterAcinetobacter baumanniiAcinetobacter InfectionsHumansSpectrum Analysis, RamanAcinetobacter baumanniiMachine learningSERS spectraSupport vector machineSurface-enhanced Raman spectroscopy

Identifiers

PMID38538920

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.