Evidence map›Paper›PMID 42125733›Full record

ReviewTherapeutics and clinical risk management2026

Mesenchymal Stromal Cells in Knee Osteoarthritis: A Review of Nomenclature, Criteria, and Therapeutic Mechanisms.

Doo-Ho Lim, Chae-Chil Lee, Ki-Bong Park

Abstract readReview
In one paragraph

Review in Therapeutics and clinical risk management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Doo-Ho Lim *Department of Internal Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea.
Chae-Chil Lee *Department of Orthopedic Surgery, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea.
Ki-Bong ParkDepartment of Orthopedic Surgery, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea.ORCID 0000-0002-2978-8300

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell-based therapies, particularly utilizing mesenchymal cells, have garnered significant global attention for treating knee osteoarthritis (OA). However, interpreting clinical outcomes remains challenging due to substantial heterogeneity in study designs, cell sources, and preparation methods. This narrative review aims to clarify the evolving nomenclature, outline defining criteria, and elucidate the fundamental mechanisms of these therapies. We highlight the critical scientific transition from "mesenchymal stem cells" to "mesenchymal stromal cells", an adjustment strongly supported by recent clinical approvals emphasizing immune recalibration over direct tissue regeneration. Currently, robust evidence indicates that mesenchymal stromal cells exert their therapeutic effects primarily through paracrine signaling and immunomodulation, predominantly orchestrated by exosomes, rather than through lineage-driven direct structural repair. Furthermore, we address the practical implications of cell processing-differentiating between minimal manipulation (e.g. cell concentrates) and in vitro expansion-and the stringent regulatory frameworks governing them. Ultimately, standardizing the mechanism-accurate "stromal" terminology and optimizing cell preparation protocols are essential steps for advancing the efficacy and reliability of regenerative treatments in knee OA.

Indexed as

cell- and tissue-based therapyexosomeskneemesenchymal stem cellsosteoarthritisparacrine communicationregenerative medicine

Identifiers

PMID42125733
PMCPMC13159940

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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.