Evidence map›Paper›PMID 42245998›Full record

ArticleFrontiers in cellular and infection microbiology2026

Exploration of common immune mechanisms and hub genes in latent and active tuberculosis infection.

Xingzhen Yang, Ming Chang, Fengzhen Liu

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 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

3 authors.

Xingzhen YangDepartment of Respiratory Medicine, Taian Cancer Hospital, Tai'an, China.
Ming ChangDepartment of Respiratory Medicine, Taian Cancer Hospital, Tai'an, China.
Fengzhen LiuDepartment of Respiratory Medicine, Taian Cancer Hospital, Tai'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tuberculosis continues to pose a severe global public health challenge. This study aims to explore the shared hub genes of latent tuberculosis infection (LTBI) and active tuberculosis (ATB). Methods: The common differentially expressed genes were obtained for LTBI and ATB, followed by PPI network construction for common genes and hub genes identification by LASSO regression analysis. The nomogram based on hub genes was established, and its predictive performance was evaluated by ROC curve analysis and decision curve analysis. Gene set variation analysis (GSVA) and immune characteristics evaluation were performed as well. Results: In total, 180 common genes were shared by LTBI and ATB. Based on PPI network and LASSO regression analysis, four hub genes were obtained, including C1QB, MSR1, OLIG3 and TGFB1I1. The nomogram risk prediction models for LTBI and ATB showed significant clinical net benefits across a broad range of threshold probabilities, indicating potential clinical application value. GSVA revealed a highly complex, multi-pathway coordinated immune activation pattern shared by LTBI and ATB. Gamma delta T cell and Type 17 T helper cell may be important participants in the tuberculosis immune response. Conclusion: This study identified hub genes shared by LTBI and ATB, laying a solid foundation for future molecular mechanism research and offering a novel perspective for the diagnosis and treatment of tuberculosis.

Indexed as

Latent TuberculosisTuberculosisGene Expression ProfilingGene Regulatory NetworksHumansMycobacterium tuberculosisNomogramsProtein Interaction MapsROC Curveactive tuberculosis infectionimmunelatent tuberculosis infectionmycobacterium tuberculosisnomogram

Identifiers

PMID42245998
PMCPMC13231278

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.