Evidence map›Paper›PMID 41948100›Full record

ArticleInternational journal of genomics2026

Integrative Single-Cell Transcriptomics and Network Pharmacology Analysis of Xiao Qing Long Tang in Pediatric Cough-Variant Asthma.

Mingming Cui, Qianqian Li, Xue Ding, Mengjie Zhou, Ximeng Lou, Lihong Xia

Abstract read
In one paragraph

Article in International journal of genomics, 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

6 authors.

Mingming CuiDepartment of Pediatrics, First Clinical College, Shandong University of Traditional Chinese Medicine, Jinan, 250000, Shandong, China, sdutcm.edu.cn.
Qianqian LiDepartment of General Internal Medicine, Jinan Shizhong People's Hospital, Jinan, 250002, Shandong, China.
Xue DingDepartment of Pediatrics, First Clinical College, Shandong University of Traditional Chinese Medicine, Jinan, 250000, Shandong, China, sdutcm.edu.cn.
Mengjie ZhouDepartment of Pediatrics, First Clinical College, Shandong University of Traditional Chinese Medicine, Jinan, 250000, Shandong, China, sdutcm.edu.cn.
Ximeng LouDepartment of Pediatrics, First Clinical College, Shandong University of Traditional Chinese Medicine, Jinan, 250000, Shandong, China, sdutcm.edu.cn.
Lihong XiaDepartment of Pediatrics, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, No. 16369 Jingshi Road, Jinan, 250000, Shandong, China, sdutcm.edu.cn.ORCID https://orcid.org/0009-0006-9995-370X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pediatric cough-variant asthma is characterized by chronic airway inflammation and epithelial dysfunction driven by complex cellular interactions and molecular regulatory networks. Understanding the cellular heterogeneity and molecular mechanisms underlying pediatric asthma pathogenesis remains challenging. Single-cell RNA sequencing (scRNA-seq) provides unprecedented resolution to dissect the molecular landscape of asthmatic airways at the individual cell level. Methods: We performed a comprehensive single-cell transcriptomic analysis of airway epithelial tissues from pediatric asthma patients using the 10x Genomics platform. Following stringent quality control, dimensionality reduction analysis, and cell clustering, we identified distinct cell populations and characterized their molecular signatures. Developmental trajectory analysis was performed using the Monocle algorithm, and functional enrichment analysis was conducted to elucidate biological pathways. Additionally, network pharmacology was employed to explore the multitarget mechanisms of the traditional Chinese medicine formula Xiao Qing Long Tang (XQLT) in treating asthma. Results: We successfully constructed a single-cell atlas of pediatric asthma airway epithelium, identifying seven major cell subtypes: eosinophil cells, basal cells, ciliated cells, goblet cells, club cells, ionocyte cells, and deuterosomal cells. High-resolution analysis revealed 23 distinct macrophage subpopulations (M1-M23) with unique transcriptional profiles. Key genes including KRT16, CXCL5, MMP10, ADAM12, and MALAT1 showed cell type-specific expression patterns. Pseudotime trajectory analysis revealed aberrant differentiation pathways from basal cells to specialized epithelial cells. Functional enrichment analysis highlighted inflammatory responses, immune system processes, and tissue remodeling as predominant biological processes in asthmatic airways. The network pharmacology analysis further identified 124 common targets, revealing that XQLT exerts multicomponent, synergistic therapeutic effects through core hubs such as NFE2L2 and NOS2. Conclusions: This comprehensive single-cell transcriptomic atlas provides novel insights into the cellular heterogeneity and molecular mechanisms of pediatric asthma. The identification of cell type-specific gene expression patterns and developmental trajectories offers potential targets for precision therapeutic interventions.

Indexed as

airway epitheliumbiomarkerscellular heterogeneitydevelopmental trajectorymacrophage polarizationpediatric asthmasingle-cell RNA sequencingtranscriptomics

Identifiers

PMID41948100
PMCPMC13051857

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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.