Evidence map›Paper›PMID 35674952›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Gas Chromatography-Mass Spectrometry (GC-MS) Analysis of Candida auris Metabolites.

Bahgat Fayed, Ghalia Kohder, Sameh S M Soliman

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. 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

3 authors.

Bahgat FayedResearch Institute for Medical and Health sciences, University of Sharjah, Sharjah, UAE.
Ghalia KohderResearch Institute for Medical and Health sciences, University of Sharjah, Sharjah, UAE.
Sameh S M SolimanResearch Institute for Medical and Health sciences, University of Sharjah, Sharjah, UAE. ssoliman@sharjah.ac.ae.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unique metabolic features allow fungi to colonize and persist within the human host. Investigations of unique metabolic fingerprints of a pathogenic fungus can provide a more complete understanding of the infection process and an interpretation of associations between genotype and phenotype. Gas chromatography-mass spectrometry (GC-MS) has proved to be one of the most powerful analytical techniques used for qualitative and quantitative detection of cellular metabolites. This technique has been used for comparative metabolomic analyses of both intracellular and secreted metabolites under variable conditions. This book chapter describes the use of GC-MS in the detection of both intracellular and secreted metabolites from Candida auris, a newly emerging fungal pathogen representing a serious global health threat due to its multidrug resistance profile. The identified fungal metabolites are compared using available software in order to assign a correlation between the pattern of accumulation of metabolites and behavior of the organism.

Indexed as

Candida aurisMetabolomicsGas Chromatography-Mass SpectrometrySoftwareCandida aurisGas chromatography–mass spectrometryGC–MSMetabolic profilingMetabolomics

Identifiers

PMID35674952

What OpenQuestion holds

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Registered trials

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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.