Evidence map›Paper›PMID 40572221›Full record

ArticleMicroorganisms2025

A Pilot Study on Single-Cell Raman Spectroscopy Combined with Machine Learning for Phenotypic Characterization of

Li Liu, Junjing Xue, Yang Song, Taijie Zhan, Yang Liu, Xiaohui Song, Li Mei, Duochun Wang, Yu Vincent Fu, Qiang Wei

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Microorganisms, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Genotypic and Phenotypic Characterisation ofPathogens (Basel, Switzerland) · 2026
    Article
  3. Review
  4. Article
  5. Review
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.

Li LiuNational Pathogen Resource Center, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Junjing XueChina General Microbiological Culture Collection Center (CGMCC), State Key Laboratory of Microbial Diversity and Innovative Utilization, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Yang SongKey Laboratory of Surveillance and Early-Warning on Infectious Disease, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Taijie ZhanSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Yang LiuNational Pathogen Resource Center, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Xiaohui SongNational Pathogen Resource Center, Chinese Center for Disease Control and Prevention, Beijing 102206, China.ORCID 0009-0002-8371-4107
Li MeiTuberculosis Prevention and Control Institute, Beijing Center for Disease Control and Prevention, Beijing 100013, China.
Duochun WangNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.ORCID 0000-0003-2372-1532
Yu Vincent FuChina General Microbiological Culture Collection Center (CGMCC), State Key Laboratory of Microbial Diversity and Innovative Utilization, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0001-8251-2306
Qiang WeiNational Pathogen Resource Center, Chinese Center for Disease Control and Prevention, Beijing 102206, China.

Funding

the National Key Research and Development Program 2022YFC2602200, 2022YFC2602301the National Natural Science Foundation of China 52091541
6 · The paper itself

Abstract

Rapid and accurate identification of pathogenic bacteria phenotypic traits, including virulence, drug resistance, and metabolic activity, is essential for clinical diagnosis and infectious disease control. Traditional methods are time-consuming, highlighting the need for more efficient approaches. This study develops a single-cell Raman spectroscopy approach to detect multiple phenotypic traits of

Indexed as

machine learningphenotypic characteristicsRaman spectroscopyrapid detectionStaphylococcus aureus

Identifiers

PMID40572221
PMCPMC12195336

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.