Evidence map›Paper›PMID 26751976›Full record

ReviewProteomics. Clinical applications2016

Recent development of mass spectrometry and proteomics applications in identification and typing of bacteria.

Keding Cheng, Huixia Chui, Larissa Domish, Drexler Hernandez, Gehua Wang

Open access · hybridAbstract readReview
In one paragraph

Review in Proteomics. Clinical applications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
13.9field-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

38 citing papers in PubMed, 118 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Immunoassay-mass spectrometry to identifyFrontiers in cellular and infection microbiology · 2025
    Article
  7. Culture and amplification-free nanopore sequencing for rapid detection of pathogens and antimicrobial resistance genes from urine.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2024
    Article
  8. Article
  9. Identification of Microbial Strains via 2D Cross-Correlation of LC-MS Data.Journal of the American Society for Mass Spectrometry · 2024
    Article
  10. Review
  11. Antibiotics (Basel, Switzerland) · 2023
    Article
  12. Article
  13. Article
  14. Article
  15. Advancement inBiosensors · 2021
    Review
  16. Article
  17. Article
  18. Article
  19. Frontiers in microbiology · 2021
    Article
  20. 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

5 authors at 2 institutions in 2 countries.

Keding ChengNational Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada.
Huixia ChuiHenan Centre of Disease Control and Prevention, Henan Province, P. R. China.
Larissa DomishNational Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada.
Drexler HernandezNational Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada.
Gehua WangNational Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada.
Public Health Agency of Canada · CAHenan Provincial Center for Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification and typing of bacteria occupy a large fraction of time and work in clinical microbiology laboratories. With the certification of some MS platforms in recent years, more applications and tests of MS-based diagnosis methods for bacteria identification and typing have been created, not only on well-accepted MALDI-TOF-MS-based fingerprint matches, but also on solving the insufficiencies of MALDI-TOF-MS-based platforms and advancing the technology to areas such as targeted MS identification and typing of bacteria, bacterial toxin identification, antibiotics susceptibility/resistance tests, and MS-based diagnostic method development on unique bacteria such as Clostridium and Mycobacteria. This review summarizes the recent development in MS platforms and applications in bacteria identification and typing of common pathogenic bacteria.

Indexed as

Bacterial ToxinsBacterial Typing TechniquesCampylobacter jejuniClostridiumEscherichia coliHumansListeria monocytogenesMicrobial Sensitivity TestsMycobacteriaceaePeptide FragmentsProteolysisProteomicsSalmonellaSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationTrypsinBacterial ToxinsPeptide FragmentsTrypsinBacteriaIdentificationMass spectrometryTyping

Identifiers

PMID26751976
PMCPMC5067657
OpenAlexW2229751746

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.