Evidence map›Paper›PMID 34792860›Full record

ArticleProteomics. Clinical applications2022

Descriptive proteomics of paired human vocal fold and buccal mucosa tissue.

Tanja Grossmann, Barbara Darnhofer, Ruth Birner-Gruenberger, Andrijana Kirsch, Markus Gugatschka

Open access · greenAbstract read
In one paragraph

Article in Proteomics. Clinical applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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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 1 country.

Tanja GrossmannDivision of Phoniatrics, Medical University of Graz, Graz, Austria.
Barbara DarnhoferDiagnostic and Research Institute of Pathology, Diagnostic and Research Center of Molecular Medicine, Medical University of Graz, Graz, Austria.
Ruth Birner-GruenbergerDiagnostic and Research Institute of Pathology, Diagnostic and Research Center of Molecular Medicine, Medical University of Graz, Graz, Austria.
Andrijana KirschDivision of Phoniatrics, Medical University of Graz, Graz, Austria.ORCID 0000-0002-6623-0234
Markus GugatschkaDivision of Phoniatrics, Medical University of Graz, Graz, Austria.
Medical University of Graz · ATTU Wien · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The vast majority of voice disorders is associated with changes of the unique, but delicate, human vocal fold mucosa. The ability to develop new effective treatment methods is significantly limited by the physical inaccessibility and the extremely rare occasions under which healthy tissue biopsies can be obtained. Therefore, the interest in laryngological research has shifted to human oral (buccal) mucosa, a similar and more easily available tissue. The harvesting process is less invasive and accompanied with faster healing and less scarring, compared to vocal fold mucosa. Here we report a descriptive proteomic comparison of paired human buccal and vocal fold mucosa by high-resolution mass spectrometry (CID-MS/MS). Our study identified a total of 1575 proteins detected within both tissues that are highly consistent in several crucial biological processes, cellular components, and molecular functions. Hence, our proteomic analysis will provide a fundamental resource for the laryngological research community.

Indexed as

ProteomicsVocal CordsCicatrixHumansMouth MucosaTandem Mass Spectrometrydescriptive proteomicshuman tissueoral buccal mucosavocal folds

Identifiers

PMID34792860
PMCPMC9286793
OpenAlexW3214136803

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.