Evidence map›Paper›PMID 23568030›Full record

ArticleJournal of the American Society for Mass Spectrometry2013

Establishing drug resistance in microorganisms by mass spectrometry.

Plamen A Demirev, Nathan S Hagan, Miquel D Antoine, Jeffrey S Lin, Andrew B Feldman

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of the American Society for Mass Spectrometry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
4.3field-weighted citation impact, top 6% 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

20 citing papers in PubMed, 53 citations in OpenAlex.

  1. Article
  2. Review
  3. Rapid detection of antimicrobial resistance in methicillin-resistantFrontiers in cellular and infection microbiology · 2023
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  5. Article
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  15. Miniaturized Digestion and Extraction of Surface Proteins fromInternational journal of proteomics · 2016
    Article
  16. Article
  17. Article
  18. Rapid detection of antibiotic resistance based on mass spectrometry and stable isotopes.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2014
    Article
  19. Review
  20. 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

5 authors at 1 institution in 1 country.

Plamen A DemirevJohns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Rd., Laurel, MD 20723, USA. plamen.demirev@jhuapl.edu
Nathan S Hagan
Miquel D Antoine
Jeffrey S Lin
Andrew B Feldman
Johns Hopkins University Applied Physics Laboratory · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A rapid method to determine drug resistance in bacteria based on mass spectrometry is presented. In it, a mass spectrum of an intact microorganism grown in drug-containing stable isotope-labeled media is compared with a mass spectrum of the intact microorganism grown in non-labeled media without the drug present. Drug resistance is determined by predicting characteristic mass shifts of one or more microorganism biomarkers using bioinformatics algorithms. Observing such characteristic mass shifts indicates that the microorganism is viable even in the presence of the drug, thus incorporating the isotopic label into characteristic biomarker molecules. The performance of the method is illustrated on the example of intact E. coli, grown in control (unlabeled) and (13)C-labeled media, and analyzed by MALDI TOF MS. Algorithms for data analysis are presented as well.

Indexed as

AlgorithmsBacillus anthracisComputational BiologyDatabases, GeneticData Interpretation, StatisticalDrug Resistance, BacterialEscherichia coliGenomicsSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationSpores, Bacterial

Identifiers

PMID23568030
OpenAlexW2065795307

What OpenQuestion holds

Textmetadata
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.