Evidence map›Paper›PMID 34055009›Full record

ReviewEvidence-based complementary and alternative medicine : eCAM2021

Progress of Interference of Traditional Chinese Medicine on Cirrhosis Treated with Bone Marrow Mesenchymal Stem Cells.

Yaxin Wang, Huicun Zhang, Hongbing Wang

Open access · hybridAbstract readReview
In one paragraph

Review in Evidence-based complementary and alternative medicine : eCAM, 2021. 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
0.1field-weighted citation impact, top 53% 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. Exploring Cirrhosis: Insights into Advances in Therapeutic Strategies.International journal of molecular sciences · 2025
    Review
  2. Review
  3. 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 at 1 institution in 1 country.

Yaxin WangBeijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China.ORCID https://orcid.org/0000-0002-8518-7251
Huicun ZhangBeijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China.ORCID https://orcid.org/0000-0002-0591-1060
Hongbing WangBeijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China.ORCID https://orcid.org/0000-0003-4811-8617
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transplantation of bone marrow mesenchymal stem cells has attracted more and more attention as a regenerative therapy for the treatment of liver diseases. A large number of studies have shown that this kind of cells can inhibit the activation of hepatic stellate cells and regulate tissue homeostasis and immune system via a variety of ways. Meanwhile, bone marrow mesenchymal stem cells can inhibit apoptosis of hepatocyte, improve liver function, and reduce inflammation through multiple pathways. These cells have a broad prospect in the treatment of liver cirrhosis. At present, there are many studies on the specific mechanism of bone marrow mesenchymal stem cells transplantation in the treatment of liver cirrhosis. This paper reviews the pathogenesis of liver cirrhosis and the mechanism of bone marrow mesenchymal stem cells transplantation in the treatment of liver cirrhosis, discusses the effectiveness of traditional Chinese medicine method in enhancing the efficacy of bone marrow mesenchymal stem cells transplantation, and looks forward to its application prospect in the future.

Identifiers

PMID34055009
PMCPMC8131131
OpenAlexW3163696687

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.