Evidence map›Paper›PMID 40950889›Full record

ArticleJournal of thoracic disease2025

The diagnostic value of CD101 in smear-negative pulmonary tuberculosis.

Jingjing Ren, Shengyan Qu, Keyun Bian, Min Yao, Fan Yao, Feifan Xu, Rui Zhang

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2025. 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

7 authors.

Jingjing Ren *Department of Immunology, School of Medicine, Nantong University, Nantong, China.
Shengyan Qu *Department of Clinical Laboratory, Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), Nantong, China.
Keyun Bian *Department of Microbiology Laboratory, Disease Control and Prevention Center of Rugao, Rugao, China.
Min YaoDepartment of Immunology, School of Medicine, Nantong University, Nantong, China.
Fan YaoDepartment of Tuberculosis, Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), Nantong, China.
Feifan XuDepartment of Clinical Laboratory, Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), Nantong, China.
Rui ZhangDepartment of Immunology, School of Medicine, Nantong University, Nantong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Unlike smear-positive tuberculosis (TB) which is more easily diagnosed due to the presence of Methods: Sixty-three newly treated patients with TB and negative smear results diagnosis by clinicians were included as the SN-TB group, while 59 healthy individuals [healthy control (HC)] were included as the control group. The expression of CD101 in PBMCs of the two groups was detected via real-time quantitative polymerase chain reaction (RT-qPCR). The expression of CD101 on T cells and NK cells, as well as the expression of T helper (Th) 1/2/17-related cytokines was detected by flow cytometry. Spearman analysis was used to analyze the correlation between CD101 expression, cytokines and clinical indicators in patients with SN-TB. Receiver operating characteristic (ROC) curve analysis was used to analyze the sensitivity and specificity of CD101 alone or in combination with other cytokines in diagnosing SN-TB. Results: Compared with the control group, the experimental group showed high CD101 expression in PBMCs and CD4 Conclusions: The expression of CD101 on CD4

Indexed as

CD101interferon-γ (IFN-γ)interleukin-2 (IL-2)molecular markersmear-negative pulmonary tuberculosis (SN-TB)

Identifiers

PMID40950889
PMCPMC12433048

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.