Evidence mapPaperPMID 41766874Full record

ArticleFrontiers in immunology2026

Identification of potential biomarkers related to the Bitong mixture in osteoarthritis based on bioinformatics and network pharmacology, and exploration of the mechanism involved.

Ziwei Shen, Suming Li, Teng Li, Lining Wang

Abstract read
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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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

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Ziwei ShenDepartment of Orthopedics and Traumatology, Nanjing Hospital of Traditional Chinese Medicine, Nanjing, Jiangsu, China.
Suming LiDepartment of Orthopedics and Traumatology, Nanjing Hospital of Traditional Chinese Medicine, Nanjing, Jiangsu, China.
Teng LiDepartment of Orthopedics and Traumatology, Nanjing Hospital of Traditional Chinese Medicine, Nanjing, Jiangsu, China.
Lining WangDepartment of Orthopedics and Traumatology, School of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Bitong Mixture (BM) has shown efficacy in alleviating pain in knee osteoarthritis (OA) in clinical practice; however, the molecular mechanisms underlying its therapeutic effects remain to be fully elucidated. This study aimed to identified BM-related OA biomarkers and explore their functional implications. Methods: An integrative strategy combining bioinformatics prediction and experimental validation was used. Biomarkers were screened from public OA transcriptomic data using differential expression analysis, network pharmacology, and machine learning. Their functions were explored via enrichment and immune infiltration analyses. Molecular docking predicted interactions between herbal compounds and targets. Single-cell analysis characterized biomarker expression in chondrocyte subsets. A rat OA model and reverse transcription quantitative polymerase chain reaction (RT-qPCR) were employed for Results: Bioinformatic prediction identified three potential biomarkers: MMP9, MMP2, and SPP1. They demonstrated certain diagnostic performance for OA and were implicated in pathways related to extracellular matrix organization and immune regulation. Immune analysis revealed significant correlations, notably between MMP2 and activated dendritic cells (cor = 0.66) and between SPP1 and CD4+ central memory T cells (cor = -0.75). Molecular docking suggested strong binding affinity between luteolin (a BM component) and MMP9. Single-cell analysis indicated high expression of these potential biomarkers in hypertrophic chondrocytes, inflammatory chondrocytes, and fibrochondrocytes. Conclusion: MMP9, MMP2, and SPP1 are potential therapeutic biomarkers for BM in OA. The efficacy of BM may be attributed to its regulation of extracellular matrix remodeling and immune responses, which provides a possible mechanistic explanation for its clinical use.

Indexed as

Drugs, Chinese HerbalOsteoarthritisAnimalsBiomarkersChondrocytesComputational BiologyGene Expression ProfilingHumansLuteolinMaleMatrix Metalloproteinase 2Matrix Metalloproteinase 9Molecular Docking SimulationNetwork PharmacologyOsteopontinRatsBiomarkersDrugs, Chinese HerbalLuteolinMatrix Metalloproteinase 2Matrix Metalloproteinase 9OsteopontinbioinformaticsbiomarkersBitong mixturemolecular dockingnetwork pharmacologyosteoarthritisRT-qPCRsingle-cell analysis

Identifiers

PMID41766874
PMCPMC12946070

What Socratic holds

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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 Socratic graph.