Evidence map›Paper›PMID 40756419›Full record

ArticleJournal of inflammation research2025

An Integrated Machine Learning Framework for Developing and Validating a Diagnostic Model of Hub Genes Related to Lipid Metabolism in Chronic Rhinosinusitis.

Panhui Xiong, Lei Liu, Jingting Pi, Ji Wang, Tao Lu, Xia Ke, Yu Jiang, Yang Shen, Yucheng Yang

Abstract read
In one paragraph

Article in Journal of inflammation research, 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. 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

9 authors.

Panhui Xiong *Department of Otolaryngology Head and Neck Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.ORCID 0000-0003-4981-5553
Lei Liu *Department of Otolaryngology Head and Neck Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Jingting Pi *Department of Otolaryngology Head and Neck Surgery, Yongchuan Hospital Affiliated of Chongqing Medical University, Chongqing, 402160, People's Republic of China.ORCID 0009-0005-5140-3488
Ji WangDepartment of Otolaryngology Head and Neck Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Tao LuDepartment of Otolaryngology Head and Neck Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Xia KeDepartment of Otolaryngology Head and Neck Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Yu JiangDepartment of Otolaryngology Head and Neck Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Yang ShenDepartment of Otolaryngology Head and Neck Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.ORCID 0000-0003-4714-0839
Yucheng YangDepartment of Otolaryngology Head and Neck Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The study aimed to identify key genes related to lipid metabolism in chronic sinusitis and understand their biological implications, considering the growing interest in the association between chronic sinusitis - a complex inflammatory condition - and lipid metabolism due to lipids' role in inflammation and immunity. Methods: Gene expression data from bulk - RNA sequence was analyzed and intersected with lipid metabolism genes and WGCNA module genes from the MSigDB database. Immune infiltration analysis was conducted. Machine learning techniques were used to develop a diagnostic model. qRT - PCR and immunofluorescence techniques were employed to confirm gene involvement. Potential targeted drugs were identified through relevant analyses. Results: 41 hub genes were identified, which were involved in pathways like G protein - coupled receptor signaling, TGF - beta receptor signaling, and responses to oxidative stress and nitrogen compounds. Enrichment analyses suggested links to ubiquitin - mediated proteolysis, mTOR signaling, and MAPK signaling. A significant presence of immune cells was detected in the chronic sinusitis group. A combined RF+Stepglm model was developed, comprising six genes (KPNA3, RAB35, GLE1, RNF139, OSMR, and PDPK1), which demonstrated good diagnostic performance (AUC = 0.848). Potential targeted drugs such as Raloxifene and Hesperidin were identified. qRT - PCR and immunofluorescence confirmed that the expression levels of RAB35, GLE1, and OSMR were significantly higher in CRS samples compared to normal ones. Conclusion: This research highlights the role of lipid metabolism in chronic sinusitis and provides a basis for the development of targeted therapies.

Indexed as

chronic rhinosinusitisdiagnostic modeldrughub genelipid metabolismmachine learning

Identifiers

PMID40756419
PMCPMC12318519

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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.