Evidence map›Paper›PMID 42669785›Full record

ArticleThe Journal of international medical research2026

A single-cell atlas of peripheral immunity suggests immune subset attrition during tuberculosis dissemination.

Hairui Jiang, Chunlong Liu, Chunling Liu, Dapeng Wang

Abstract read
In one paragraph

Article in The Journal of international medical 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

4 authors.

Hairui JiangSchool of Clinical Medicine, Bengbu Medical University, China.
Chunlong LiuDepartment of Pathophysiology, School of Basic Medicine, Bengbu Medical University, China.
Chunling LiuDepartment of Pathophysiology, School of Basic Medicine, Bengbu Medical University, China.
Dapeng WangDepartment of Pathophysiology, School of Basic Medicine, Bengbu Medical University, China.ORCID 0000-0002-6950-0105

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ObjectiveThis study investigated immune lineage remodeling and intercellular communication to elucidate the mechanisms driving the progression from active tuberculosis to disseminated tuberculosis.MethodsWe integrated single-cell RNA-sequencing datasets of peripheral blood mononuclear cells from healthy controls, patients with active tuberculosis, and patients with disseminated tuberculosis (n = 3 for each group) to perform cellular clustering, functional assessment, and communication network analyses.ResultsAnalysis identified 16 clusters across 5 major lineages. Although global cellular proportions remained statistically stable across patient cohorts, disease progression was characterized by distinct cell-intrinsic transcriptomic shifts and subset-specific remodeling. This landscape was highlighted by the systematic peripheral depletion of homeostatic "guardian" monocytes, alongside functional disruptions in natural killer and B-cell states, and a severe-stage-specific accumulation of exhausted T cells. Consequently, circulating intercellular communication networks were broadly attenuated in infected groups, featuring diminished receptor-ligand interactions between peripheral dendritic cells and naïve CD8

Indexed as

Leukocytes, MononuclearMycobacterium tuberculosisTuberculosisB-LymphocytesCD8-Positive T-LymphocytesCell CommunicationDendritic CellsDisease ProgressionFemaleHumansKiller Cells, NaturalMaleMonocytesSingle-Cell AnalysisSingle-Cell Gene Expression AnalysisT-Cell Exhaustionimmunitysingle-cell RNA sequencingTuberculosis

Identifiers

PMID42669785
PMCPMC13527331

What OpenQuestion holds

Textmetadata
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.