Evidence map›Paper›PMID 38520499›Full record

ArticleMolecular biotechnology2025

Identification of Potential Hub Genes Related to Acute Pancreatitis and Chronic Pancreatitis via Integrated Bioinformatics Analysis and In Vitro Analysis.

Lu Yuan, Yiyuan Liu, Lingyan Fan, Cai Sun, Sha Ran, Kuilong Huang, Yan Shen

Abstract read
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In one paragraph

Article in Molecular biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
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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 at 2 institutions in 1 country.

Lu Yuan *School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China.
Yiyuan Liu *School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China.
Lingyan FanQingdao Central Hospital, University of Health and Rehabilitation Sciences (Qingdao Central Medical Group), Qingdao, 266042, China.
Cai SunSchool of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China.
Sha RanSchool of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China.
Kuilong HuangSchool of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China.
Yan ShenSchool of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China. shenbmy@126.com.ORCID http://orcid.org/0000-0003-3696-7590
Chongqing University of Technology · CNQingdao University · CN

Funding

Funding Achievements of the Action Plan for High Quality Development of Graduate Education at Chongqing University of Technology gzlcx20233384National Natural ScienceFoundation Incubation project of Chongqing University of Technology 2022PYZ037National Natural Science Foundation of China No. 82100684Natural Science Foundation of Chongqing China CSTB2022NSCQ-MSX1493
6 · The paper itself

Abstract

Acute pancreatitis (AP) and chronic pancreatitis (CP) are considered to be two separate pancreatic diseases in most studies, but some clinical retrospective analyses in recent years have found some degree of correlation between the two in actual treatment, however, the exact association is not clear. In this study, bioinformatics analysis was utilized to examine microarray sequencing data in mice, with the aim of elucidating the critical signaling pathways and genes involved in the progression from AP to CP. Differential gene expression analyses on murine transcriptomes were conducted using the R programming language and the R/Bioconductor package. Additionally, gene network analysis was performed using the STRING database to predict correlations among genes in the context of pancreatic diseases. Functional enrichment and gene ontology pathways common to both diseases were identified using Metascape. The hub genes were screened in the cytoscape algorithm, and the mRNA levels of the hub genes were verified in mice pancreatic tissues of AP and CP. Then the drugs corresponding to the hub genes were obtained in the drug-gene relationship. A set of hub genes, including Jun, Cd44, Epcam, Spp1, Anxa2, Hsp90aa1, and Cd9, were identified through analysis, demonstrating their pivotal roles in the progression from AP to CP. Notably, these genes were found to be enriched in the Helper T-cell factor (Th17) signaling pathway. Up-regulation of these genes in both AP and CP mouse models was validated through quantitative real-time polymerase chain reaction (qRT-PCR) results. The significance of the Th17 signaling pathway in the transition from AP to CP was underscored by our findings. Specifically, the essential genes driving this progression were identified as Jun, Cd44, Epcam, Spp1, Anxa2, Hsp90aa1, and Cd9. Crucial insights into the molecular mechanisms underlying pancreatitis progression were provided by this research, offering promising avenues for the development of targeted therapeutic interventions.

Indexed as

Computational BiologyPancreatitisPancreatitis, ChronicAcute DiseaseAnimalsGene Expression ProfilingGene OntologyGene Regulatory NetworksMiceSignal TransductionTranscriptomeAcute pancreatitisChronic pancreatitisHelper T-cell factor signaling pathwayHub genes

Identifiers

PMID38520499
OpenAlexW4393113088

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.