Evidence map›Paper›PMID 35531343›Full record

ReviewFrontiers in cellular and infection microbiology2022

Raman Spectroscopy-A Novel Method for Identification and Characterization of Microbes on a Single-Cell Level in Clinical Settings.

Katarina Rebrosova, Ota Samek, Martin Kizovsky, Silvie Bernatova, Veronika Hola, Filip Ruzicka

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cellular and infection microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
12.9field-weighted citation impact, top 1% of its field
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

30 citing papers in PubMed, 52 citations in OpenAlex.

  1. Review
  2. Review
  3. Characterization of theInternational journal of molecular sciences · 2026
    Article
  4. Article
  5. Characterization of theInternational journal of molecular sciences · 2026
    Article
  6. Article
  7. Raman signatures ofFrontiers in microbiology · 2026
    Article
  8. Review
  9. Raman Monitoring ofInternational journal of molecular sciences · 2025
    Article
  10. Article
  11. Review
  12. Review
  13. How AI can help us beat AMR.npj antimicrobials and resistance · 2025
    Review
  14. Review
  15. Review
  16. Article
  17. Review
  18. Article
  19. Review
  20. Analytical chemistry · 2024
    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

6 authors at 3 institutions in 1 country.

Katarina RebrosovaDepartment of Microbiology, Faculty of Medicine of Masaryk University and St. Anne's University Hospital, Brno, Czechia.
Ota SamekInstitute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czechia.
Martin KizovskyInstitute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czechia.
Silvie BernatovaInstitute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czechia.
Veronika HolaDepartment of Microbiology, Faculty of Medicine of Masaryk University and St. Anne's University Hospital, Brno, Czechia.
Filip RuzickaDepartment of Microbiology, Faculty of Medicine of Masaryk University and St. Anne's University Hospital, Brno, Czechia.
Czech Academy of Sciences, Institute of Scientific Instruments · CZSt. Anne's University Hospital Brno · CZMasaryk University · CZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid and accurate identification of pathogens causing infections is one of the biggest challenges in medicine. Timely identification of causative agents and their antimicrobial resistance profile can significantly improve the management of infection, lower costs for healthcare, mitigate ever-growing antimicrobial resistance and in many cases, save lives. Raman spectroscopy was shown to be a useful-quick, non-invasive, and non-destructive -tool for identifying microbes from solid and liquid media. Modifications of Raman spectroscopy and/or pretreatment of samples allow single-cell analyses and identification of microbes from various samples. It was shown that those non-culture-based approaches could also detect antimicrobial resistance. Moreover, recent studies suggest that a combination of Raman spectroscopy with optical tweezers has the potential to identify microbes directly from human body fluids. This review aims to summarize recent advances in non-culture-based approaches of identification of microbes and their virulence factors, including antimicrobial resistance, using methods based on Raman spectroscopy in the context of possible use in the future point-of-care diagnostic process.

Indexed as

Anti-Infective AgentsSpectrum Analysis, RamanHumansSingle-Cell AnalysisVirulence FactorsAnti-Infective AgentsVirulence Factorsantimicrobial resistancediagnosticsidentification of microorganismsmagnetic beadsmicrofluidic devicesRaman spectroscopyRaman tweezers

Identifiers

PMID35531343
PMCPMC9072635
OpenAlexW4224281878

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.