Evidence map›Paper›PMID 41836400›Full record

ArticleFrontiers in immunology2026

Combination of single-cell and bulk RNA-seq reveals changes in the immune landscape in osteomyelitis.

Zhenhua Zhu, Xiaopeng Jing, Jun Chen, Siteng Li, Jie Tan, Ji Zeng, Zheng Jin

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

7 authors.

Zhenhua ZhuDepartment of Joint Surgery, Wuhan Fourth Hospital, Wuhan, China.
Xiaopeng JingDepartment of Clinical Laboratory, Wuhan Fourth Hospital, Wuhan, China.
Jun ChenOrthopedic Department, Wuhan Fourth Hospital, Wuhan, China.
Siteng LiSchool of Medicine, Nankai University, Tianjin, China.
Jie TanOrthopedic Laboratory, Orthopedic Department and Hubei Sports Medicine Center, Wuhan Fourth Hospital, Wuhan, China.
Ji ZengDepartment of Clinical Laboratory, Wuhan Fourth Hospital, Wuhan, China.
Zheng JinDepartment of Clinical Laboratory, Wuhan Fourth Hospital, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study presented a comprehensive characterization of the osteomyelitis immune microenvironment, identified driver genes and pathogenic cell populations underlying disease progression, and uncovered potential therapeutic targets through single-cell and bulk transcriptomic analysis. Methods: We analyzed time-series transcriptomic sequencing data from mouse osteomyelitis samples in the dataset GSE168896. Fuzzy c-means clustering was applied to reveal gene sets linked to disease progression. Immune cell infiltration analysis was conducted through the online tool ImmuCellAI-mouse. Furthermore, by leveraging single-cell sequencing data, we characterized immune cell subpopulations and pinpointed the key cell subtypes that were present in the osteomyelitis mice. Results: We identified six gene clusters exhibiting distinct temporal expression patterns and functional roles in osteomyelitis, such as leukocyte and lymphocyte activation and ossification. Single-cell sequencing analysis further showed seven distinct cellular subpopulations. Among these, macrophages demonstrated a significant increase following osteomyelitis, and the infiltration of Mif Conclusion: Our findings tracked the transcriptional dynamics and evolving immune landscape of osteomyelitis, highlighting macrophages as central regulators of disease progression. We identified that significant infiltration of Arg1

Indexed as

OsteomyelitisRNA-SeqSingle-Cell AnalysisAnimalsGene Expression ProfilingMacrophagesMiceSingle-Cell Gene Expression AnalysisTranscriptomegene expressionimmune cell infiltrationmacrophagesosteomyelitissingle-cell sequencingtherapeutic targetstranscriptomic analysis

Identifiers

PMID41836400
PMCPMC12982112

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