Evidence map›Paper›PMID 38757042›Full record

ArticleArchives of medical science : AMS2024

A network pharmacological study to unveil the mechanisms of xianlinggubao capsule in the treatment of osteoarthritis and osteoporosis.

Jianwei Zeng, Cheng Li, Zuchao Gu

Abstract read
In one paragraph

Article in Archives of medical science : AMS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
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  3. Article
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  5. Article
  6. 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

3 authors.

Jianwei ZengDepartment of Orthopaedics, Chengdu Integrated TCM and Western Medicine Hospital, Chengdu, China.
Cheng LiDepartment of Orthopaedics, Chengdu Integrated TCM and Western Medicine Hospital, Chengdu, China.
Zuchao GuDepartment of Orthopaedics, Chengdu Integrated TCM and Western Medicine Hospital, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Xianlinggubao (XLGB) capsule is a traditional Chinese medicine, which is approved by the Chinese State Food and Drug Administration (CFDA) for osteoarthritis (OA) and osteoporosis (OP). However, as a capsule with complex ingredients, the molecular mechanisms supporting the therapeutic effects have not been explored. Material and methods: A network pharmacology-based approach was conducted to explore the complex interactome among the targets of the XLGB active compounds. Results: The herbs in the capsule contain 41 compounds with 246 high score targets, which cover four known OA targets (PTGS1, PTGS2, PTGER4 and TNF) and six known OP targets (AR, ESR1, PGR, PTGER2, TNFSF11 and VDR) of FDA-approved drugs or drugs undergoing clinical trials. The protein-protein interaction (PPI) network of the 246 targets had six key modules. Among the six modules, neuroactive ligand-receptor interaction, cAMP signaling pathway and calcium signaling pathway are the key pathways, which are all closely associated with the degeneration of joint cartilage and bone formation and resorption. Conclusions: Neuroactive ligand-receptor interaction, cAMP signaling pathway, and calcium signaling pathway might be the critical pathways upon which the capsule might act. The present study laid down a foundation to understand the molecular mechanisms of the XLGB capsule and also provided fundamental information for better improvement of the drug with the concept "less herbal materials for achieving equal treatment efficacy".

Indexed as

KEGGnetwork pharmacologyosteoarthritisosteoporosistraditional Chinese medicine

Identifiers

PMID38757042
PMCPMC11094832

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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.