Evidence map›Paper›PMID 42079606›Full record

ArticleFrontiers in immunology2026

Single-cell RNA sequencing unravels T cell exhaustion underlying the chronicity of chromoblastomycosis.

Kexin Lei, Jie Tian, Lu Zhang, Zhuoqing Gong, Wenjie Liu, Zhe Wan, Yang Wang, Ruoyu Li, Bilin Dong, Xiaowen Wang

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

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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Kexin LeiDepartment of Dermatology and Venerology, Peking University First Hospital, Beijing, China.
Jie TianDepartment of Dermatology and Venerology, Peking University First Hospital, Beijing, China.
Lu ZhangDepartment of Dermatology and Venerology, Peking University First Hospital, Beijing, China.
Zhuoqing GongDepartment of Dermatology and Venerology, Peking University First Hospital, Beijing, China.
Wenjie LiuDepartment of Dermatology and Venerology, Peking University First Hospital, Beijing, China.
Zhe WanDepartment of Dermatology and Venerology, Peking University First Hospital, Beijing, China.
Yang WangDepartment of Dermatology and Venerology, Peking University First Hospital, Beijing, China.
Ruoyu LiDepartment of Dermatology and Venerology, Peking University First Hospital, Beijing, China.
Bilin DongDepartment of Dermatology, Hubei Province & Key Laboratory of Skin Infection and Immunity, Center for Infectious Skin Diseases, Wuhan No.1 Hospital, Wuhan, China.
Xiaowen WangDepartment of Dermatology and Venerology, Peking University First Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Chromoblastomycosis (CBM) is a chronic, neglected tropical fungal infection. Its immunopathogenesis, particularly the mechanism underlying its chronicity, remains poorly understood. Methods: We performed single-cell RNA sequencing (scRNA-seq) on lesional skin from a CBM patient, followed by comprehensive bioinformatics analyses. We then used multiplex immunofluorescence (mIF) to validate CD4 Results: We identified a significantly expanded population of exhausted CD4 Discussion: Our findings establish CD4

Indexed as

CD4-Positive T-LymphocytesChromoblastomycosisT-Cell ExhaustionAnimalsChronic DiseaseDisease Models, AnimalFemaleFonsecaeaHumansMiceSequence Analysis, RNASingle-Cell AnalysisSingle-Cell Gene Expression Analysischromoblastomycosischronic fungal infectionLAG-3PD-1single-cell RNA sequencingT cell exhaustionTIM-3

Identifiers

PMID42079606
PMCPMC13133555

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.