Evidence map›Paper›PMID 33117162›Full record

ReviewFrontiers in pharmacology2020

Potential Advantages of Bioactive Compounds Extracted From Traditional Chinese Medicine to Inhibit Bone Destructions in Rheumatoid Arthritis.

Yingjie Shi, Haiyang Shu, Xinyu Wang, Hanxiao Zhao, Cheng Lu, Aiping Lu, Xiaojuan He

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
  2. Total saponins ofJournal of ginseng research · 2025
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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.

Yingjie ShiShanghai Innovation Center of TCM Health Service, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Haiyang ShuInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Xinyu WangInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Hanxiao ZhaoInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Cheng LuInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Aiping LuShanghai Innovation Center of TCM Health Service, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Xiaojuan HeInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bone destruction is an important pathological feature of rheumatoid arthritis (RA), which finally leads to the serious decline of life quality in RA patients. Bone metabolism imbalance is the principal factor of bone destruction in RA, which is manifested by excessive osteoclast-mediated bone resorption and inadequate osteoblast-mediated bone formation. Although current drugs alleviate the process of bone destruction to a certain extent, there are still many deficiencies. Recent studies have shown that traditional Chinese medicine (TCM) could effectively suppress bone destruction of RA. Some bioactive compounds from TCM have shown good effect on inhibiting osteoclast differentiation and promoting osteoblast proliferation. This article reviews the research progress of bioactive compounds exacted from TCM in inhibiting bone destruction of RA, so as to provide references for further clinical and scientific research.

Indexed as

bioactive compoundsbone destructionbone metabolismrheumatoid arthritistraditional Chinese medicine

Identifiers

PMID33117162
PMCPMC7577042

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.