Evidence map›Paper›PMID 33562161›Full record

ReviewPharmaceuticals (Basel, Switzerland)2021

Therapeutic Single Compounds for Osteoarthritis Treatment.

Hyemi Lee, Xiangyu Zhao, Young-Ok Son, Siyoung Yang

Abstract readReview
In one paragraph

Review in Pharmaceuticals (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. International journal of medical sciences · 2026
    Article
  2. Review
  3. Antioxidants (Basel, Switzerland) · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Review
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

4 authors.

Hyemi LeeDepartment of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon 16499, Korea.ORCID 0000-0002-7410-203X
Xiangyu ZhaoDepartment of Animal Biotechnology, Faculty of Biotechnology and Interdisciplinary Graduate Program in Advanced Convergence Technology and Science, Jeju National University, Jeju 63243, Korea.
Young-Ok SonDepartment of Animal Biotechnology, Faculty of Biotechnology and Interdisciplinary Graduate Program in Advanced Convergence Technology and Science, Jeju National University, Jeju 63243, Korea.
Siyoung YangDepartment of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon 16499, Korea.ORCID 0000-0002-6374-0140

Funding

National Research Foundation of Korea 2020R1A2C2004128, NRF-2019R1A2B5B03100464, 2020R1A6C101A188
6 · The paper itself

Abstract

Osteoarthritis (OA) is an age-related degenerative disease for which an effective disease-modifying therapy is not available. Natural compounds derived from plants have been traditionally used in the clinic to treat OA. Over the years, many studies have explored the treatment of OA using natural extracts. Although various active natural extracts with broad application prospects have been discovered, single compounds are more important for clinical trials than total natural extracts. Moreover, although natural extracts exhibit minimal safety issues, the cytotoxicity and function of all single compounds in a total extract remain unclear. Therefore, understanding single compounds with the ability to inhibit catabolic factor expression is essential for developing therapeutic agents for OA. This review describes effective single compounds recently obtained from natural extracts and the possibility of developing therapeutic agents against OA using these compounds.

Indexed as

natural compoundOsteoarthritistreatment

Identifiers

PMID33562161
PMCPMC7914480

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.