Evidence map›Paper›PMID 42454160›Full record

ArticleJournal of inflammation research2026

Single-Cell and Spatial Transcriptomics Identify the Mono-S100A4 Subset Associated with Sepsis-Induced Lung Injury via the MIF-(CD74+CD44) Axis.

Aihua Wang, Chengfen Yin, Yue Jin, Lei Yang, Suiran Li, Jiaxin Li, Lei Xu, Ruoyu Shi, Maotong Weng, Wei Liu and 1 more

Abstract read
In one paragraph

Article in Journal of inflammation research, 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

11 authors.

Aihua Wang *Central Hospital, Tianjin University, Tianjin, People's Republic of China.ORCID 0000-0002-0967-3610
Chengfen Yin *Central Hospital, Tianjin University, Tianjin, People's Republic of China.
Yue Jin *First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China.
Lei YangTianjin Nankai Hospital, Tianjin, People's Republic of China.
Suiran LiFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China.
Jiaxin LiCentral Hospital, Tianjin University, Tianjin, People's Republic of China.
Lei XuCentral Hospital, Tianjin University, Tianjin, People's Republic of China.
Ruoyu ShiFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China.
Maotong WengSanta Clara University, Santa Clara, California, USA.
Wei LiuFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China.ORCID 0000-0002-3364-0966
Ximo WangCentral Hospital, Tianjin University, Tianjin, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In sepsis-induced immune dysregulation, monocytes contribute critically through their dual pro-inflammatory and immunosuppressive functions. Leading to multi-organ injury, the lungs are the most vulnerable initial target, dictating clinical outcomes. Thus, studying monocyte dynamics is essential to understand sepsis-induced acute lung injury (ALI) pathophysiology. Methods: We analyzed publicly available mouse-derived single-cell RNA sequencing (scRNA-seq) and spatial transcriptomic (ST) datasets for sepsis-induced ALI from the GEO database. Computational characterization of monocyte heterogeneity included cell-cell communication, single-cell trajectory analysis, and functional enrichment analyses to identify subtype-specific signaling and injury-related signatures. Spatial mapping further confirmed monocyte subtype localization. Experimental validation was performed in a mouse model of sepsis-induced ALI established by intraperitoneal LPS injection. Histological evaluation, immunohistochemistry, immunofluorescence, Quantitative real-time PCR, and Western blot were integrated to verify the spatial distribution of the Mono-S100A4 subset and its associated pathway molecules. Results: Clustering analysis revealed a restructured immune landscape in septic ALI, characterized by both cellular heterogeneity and prominent monocyte accumulation. Spatial transcriptomics revealed that inflammatory infiltration mediated by monocytes and other immune cells predominantly localized to bronchial and bronchiole regions. Monocyte heterogeneity analysis identified a distinct Mono-S100A4 subset, which exhibited enhanced intercellular communication capacity, influencing other subclusters through the (MIF)-(CD74+CD44) axis. KEGG and GSEA analyses of Mono-S100A4 revealed significant enrichment in the IL-17 signaling pathway and Th17 cell differentiation, suggesting a potential role in exacerbating inflammatory responses. In vivo experiments revealed a significant upregulation in both the mRNA and protein expression levels of S100A4, IL-17A, MIF, and CD74 in the lung tissue of ALI mice. Conclusion: The Mono-S100A4 subset is strongly associated with the activation of the Th17 signaling pathway via the MIF-(CD74+CD44) axis, and this correlative relationship supports a potential pathogenic role of Mono-S100A4 in sepsis-induced ALI, which forms a key hypothesis to be validated by subsequent functional experiments.

Indexed as

acute lung injurymonocyteMono-S100A4scRNA-seqsepsisspatial transcriptomics

Identifiers

PMID42454160
PMCPMC13367282

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.