Evidence map›Paper›PMID 39084404›Full record

ArticleJournal of advanced research2025

Single-cell atlas of human gingiva unveils a NETs-related neutrophil subpopulation regulating periodontal immunity.

Wei Qiu, Ruiming Guo, Hongwen Yu, Xiaoxin Chen, Zehao Chen, Dian Ding, Jindou Zhong, Yumeng Yang, Fuchun Fang

Abstract read
In one paragraph

Article in Journal of advanced research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Review
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  3. Non-Coding RNAs in Oral Diseases: From Pathogenesis to Clinical Translation.International journal of molecular sciences · 2026
    Review
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  12. Cell-Free DNA-Based Theranostics for Inflammatory Disorders.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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  14. Article
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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

9 authors.

Wei QiuDepartment of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Ruiming GuoDepartment of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Hongwen YuDepartment of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Xiaoxin ChenDepartment of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Zehao ChenDepartment of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Dian DingDepartment of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Jindou ZhongDepartment of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Yumeng YangDepartment of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Fuchun FangDepartment of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China. Electronic address: fangfuchun@smu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionExaggerated neutrophil recruitment and activation are the major features of pathological alterations in periodontitis, in which neutrophil extracellular traps (NETs) are considered to be responsible for inflammatory periodontal lesions. Despite the critical role of NETs in the development and progression of periodontitis, their specific functions and mechanisms remain unclear.

objectivesTo demonstrate the important functions and specific mechanisms of NETs involved in periodontal immunopathology.

methodsWe performed single-cell RNA sequencing on gingival tissues from both healthy individuals and patients diagnosed with periodontitis. High-dimensional weighted gene co-expression network analysis and pseudotime analysis were then applied to characterize the heterogeneity of neutrophils. Animal models of periodontitis were treated with NETs inhibitors to investigate the effects of NETs in severe periodontitis. Additionally, we established a periodontitis prediction model based on NETs-related genes using six types of machine learning methods. Cell-cell communication analysis was used to identify ligand-receptor pairs among the major cell groups within the immune microenvironment.

resultsWe constructed a single-cell atlas of the periodontal microenvironment and obtained nine major cell populations. We further identified a NETs-related subgroup (NrNeu) in neutrophils. An in vivo inhibition experiment confirmed the involvement of NETs in gingival inflammatory infiltration and alveolar bone absorption in severe periodontitis. We further screened three key NETs-related genes (PTGS2, MME and SLC2A3) and verified that they have the potential to predict periodontitis. Moreover, our findings revealed that gingival fibroblasts had the most interactions with NrNeu and that they might facilitate the production of NETs through the MIF-CD74/CXCR4 axis in periodontitis.

conclusionThis study highlights the pathogenic role of NETs in periodontal immunity and elucidates the specific regulatory relationship by which gingival fibroblasts activate NETs, which provides new insights into the clinical diagnosis and treatment of periodontitis.

Indexed as

Extracellular TrapsGingivaNeutrophilsPeriodontitisAdultAnimalsDisease Models, AnimalFemaleHumansMaleMiceSingle-Cell AnalysisGingival fibroblastsMachine learningNeutrophil extracellular trapsPeriodontitisPrediction modelSingle-cell RNA sequencing

Identifiers

PMID39084404
PMCPMC12147643

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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.