Evidence map›Paper›PMID 40688271›Full record

ArticleJournal of thoracic disease2025

Validation of

Hui Zhang, Limei Han, Huiyong Ding, Jie Li, Aierken Kailiman, Jiepeng Li, Feifei Wang, Abudu Abudukahaer, Rong Liu, Wushou'er Qimanguli and 1 more

Abstract read
PubMed Full text at PMC Publisher
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. 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. Review
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

11 authors.

Hui ZhangDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xinjiang Medical University, Urumchi, China.
Limei HanDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xinjiang Medical University, Urumchi, China.
Huiyong DingDeparment of Orthopedics and Traumatology, Hangzhou Hospital of Integrated Chinese and Western Medicine, Hangzhou, China.
Jie LiDepartment of Pediatrics, Zhejiang Sian International Hospital, Jiaxing, China.
Aierken KailimanDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xinjiang Medical University, Urumchi, China.
Jiepeng LiDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xinjiang Medical University, Urumchi, China.
Feifei WangDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xinjiang Medical University, Urumchi, China.
Abudu AbudukahaerDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xinjiang Medical University, Urumchi, China.
Rong LiuDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xinjiang Medical University, Urumchi, China.
Wushou'er QimanguliDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xinjiang Medical University, Urumchi, China.
Shun GeADICON Holdings Limited, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Asthma is a heterogeneous chronic inflammatory disease of the airway, and its development is the result of genetic factors, environmental factors, immune dysfunction, and other factors. This study aimed to identify biomarkers of asthma. Methods: A differential gene expression (DGE) analysis and a weighted gene co-expression network analysis (WGCNA) were conducted to identify the asthma-related genes in the GSE67472 dataset, and these genes were intersected with immune genes from the Immuport database to identify the asthma-associated immune genes. Least absolute shrinkage and selection operator (LASSO) regression was used to identify the key asthma-associated immune genes, and receiver operating characteristic (ROC) curves were used to assess the diagnostic potential of these genes. Subsequently, the mechanism of action of the inducible factor interleukin 13 (IL-13) in human bronchial epithelial (HBE) cells and its effect on markers of asthma were verified Results: The DGE analysis and WGCNA identified 62 asthma-related genes, and eight asthma-associated immune genes were identified after the intersection of the asthma-related genes and the immune-related genes. Utilizing LASSO regression, five key immune genes linked to asthma were uncovered. These included S100 calcium binding protein A16 ( Conclusions: This study identified a new biomarker,

Indexed as

AsthmaferroptosisS100A16weighted gene co-expression network analysis (WGCNA)

Identifiers

PMID40688271
PMCPMC12268608

What OpenQuestion holds

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Registered trials

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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.