Evidence map›Paper›PMID 38975331›Full record

ArticleFrontiers in cellular and infection microbiology2024

Severe acute respiratory syndrome coronavirus 2 pathology and cell tropism in tongue tissues of COVID-19 autopsies.

Longda Ma, Qian Liu, Manli Wang, Liang Liu, Zhihong Hu, Yiwu Zhou, Jia Liu

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

2 citing papers in PubMed.

  1. Review
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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

7 authors.

Longda MaDepartment of Forensic Medicine, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
Qian LiuDepartment of Forensic Medicine, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
Manli WangState Key Laboratory of Virology, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China.
Liang LiuDepartment of Forensic Medicine, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
Zhihong HuState Key Laboratory of Virology, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China.
Yiwu ZhouDepartment of Forensic Medicine, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
Jia LiuState Key Laboratory of Virology, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since 2019, Coronavirus Disease 2019(COVID-19) has affected millions of people worldwide. Except for acute respiratory distress syndrome, dysgeusis is also a common symptom of COVID-19 that burdens patients for weeks or permanently. However, the mechanisms underlying taste dysfunctions remain unclear. Here, we performed complete autopsies of five patients who died of COVID-19. Integrated tongue samples, including numerous taste buds, salivary glands, vessels, and nerves were collected to map the pathology, distribution, cell tropism, and receptor distribution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the tongue. Our results revealed that all patients had moderate lymphocyte infiltration around the salivary glands and in the lamina propria adjacent to the mucosa, and pyknosis in the epithelia of taste buds and salivary glands. This may be because the serous acini, salivary gland ducts, and taste buds are the primary sites of SARS-CoV-2 infection. Multicolor immunofluorescence showed that SARS-CoV-2 readily infects Keratin (KRT)

Indexed as

Angiotensin-Converting Enzyme 2AutopsyCOVID-19SARS-CoV-2Serine EndopeptidasesTongueViral TropismAgedFemaleHumansMaleMiddle AgedReceptors, VirusSalivary GlandsTaste BudsACE2 protein, humanAngiotensin-Converting Enzyme 2Receptors, VirusSerine EndopeptidasesTMPRSS2 protein, humanautopsied tonguecell tropismpathogenesisreceptor distributionsevere acute respiratory syndrome coronavirus 2taste dysfunction

Identifiers

PMID38975331
PMCPMC11224463

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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.