Evidence map›Paper›PMID 40718133›Full record

ArticleJournal of inflammation research2025

Rbms3 Upregulation in Mesenchymal Stem Cells Impairs Fracture Healing in Type 2 Diabetes Mellitus.

Changjiang Liu, Yifeng Yu, Liang Tian, Yuting Liu, Dong Zhang, Aixi Yu

Abstract read
In one paragraph

Article in Journal of inflammation research, 2025. 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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0citing papers in PubMed
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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

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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

Who cites it

0 citing papers in PubMed.

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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

6 authors.

Changjiang Liu *Department of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, 430071, People's Republic of China.
Yifeng Yu *Department of Orthopedics, Renmin Hospital, Wuhan University, Wuhan, Hubei, 430071, People's Republic of China.
Liang TianDepartment of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, 430071, People's Republic of China.
Yuting LiuDepartment of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, 430071, People's Republic of China.ORCID 0009-0006-0502-5110
Dong ZhangDepartment of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, 430071, People's Republic of China.ORCID 0000-0002-7173-7398
Aixi YuDepartment of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, 430071, People's Republic of China.ORCID 0000-0002-5723-6140

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Fracture healing can be delayed or impaired in individuals with abnormal conditions, including Type 2 Diabetes Mellitus (T2DM). Mesenchymal stem cells (MSCs) are critical to the process of fracture healing and are found to be impaired in T2DM. Although some research has been conducted to address this, the specific mechanisms remain poorly understood and warrant further exploration. Methods: We downloaded transcriptomic and single-cell RNA sequencing (scRNA-seq) data, performed multiple analyses (differential expression, ssGSEA, co-expression, GO, KEGG, GSEA, and cell clustering identification), and utilized tools (GeneMINIA and Metascape) to investigate alterations in MSCs under diabetic condition. Further validation and exploration were carried out through in vitro experiments (cell transduction, flow cytometry, ALP staining, ARS, qPCR, and Western blotting) and in vivo experiments (micro-CT, histological staining, and immunohistochemistry). Results: Our study identified differentially expressed genes from fracture healing and non-union cases in human samples, suggesting abnormal immune infiltration and disrupted biological processes. ScRNA-seq analysis further revealed significant alterations in MSCs under diabetic conditions with enriched pathways, including MAPK, TGF-β, and P53 signaling pathways. Integrating with transcriptomic analysis, we identified Conclusion: The upregulation of

Indexed as

bioinformaticsbone healingfracture non-unionsingle-cell RNA-sequencing analysisT2DM

Identifiers

PMID40718133
PMCPMC12292365

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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.