Evidence map›Paper›PMID 35874955›Full record

ReviewInternational journal of biological sciences2022

Natural tannins as anti-SARS-CoV-2 compounds.

Shao-Chun Wang, I-Wen Chou, Mien-Chie Hung

Abstract readReview
In one paragraph

Review in International journal of biological sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Current drug discovery technologies · 2024
    Article
  10. Antiviral Effects of Secondary Metabolites fromPlants (Basel, Switzerland) · 2023
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Prospects of Coffee Leaf against SARS-CoV-2 Infection.International journal of biological sciences · 2022
    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.

Shao-Chun WangGraduate Institute of Biomedical Sciences, College of Medicine, China Medical University, Taichung, Taiwan, 40402.
I-Wen ChouResearch Center for Cancer Biology, China Medical University, Taichung, Taiwan, 40402.
Mien-Chie HungGraduate Institute of Biomedical Sciences, College of Medicine, China Medical University, Taichung, Taiwan, 40402.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tannins are polyphenols enriched in wood, bark, roots, leaves, seeds and fruits of a variety of plants. Over the last two decades, there has been an increasing interest in understanding the biological functions of tannins and their applications as antioxidants, anticancer drugs, and food additives. Since the outbreak of the COVID-19 pandemic, much effort has been devoted to finding an expedient cure. Tannins have been put forward as having possible anti-COVID-19 properties; however, owing to the profuse nature of the structurally diverse derivatives of tannins, the tannin species in the family associated with an indication of anti-COVID-19 have been poorly defined, compounded by frequent terminology misnomers. This article reviews the tannin family in fruits and the current knowledge about the activities of the compounds with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It will aid molecular and cellular biologists in developing natural anti-viral chemicals as means of overcoming the current and future pandemics.

Indexed as

COVID-19 Drug TreatmentSARS-CoV-2Antiviral AgentsHumansPandemicsTanninsAntiviral AgentsTannins

Identifiers

PMID35874955
PMCPMC9305278

What OpenQuestion holds

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LicenceCC BY
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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.