Evidence map›Paper›PMID 39444146›Full record

ArticleAnnals of medicine2024

The Masquelet technique triggers the formation of a network involving LncRNA, circRNA, miRNA, and mRNA during bone repair.

Muguo Song, Xiaoyong Yang, Xijiao Zhang, Junyi Li, Yongqing Xu, Jian Shi

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Article in Annals of medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Muguo SongDepartment of Orthopaedics, 920th Hospital of the Joint Logistics Support Force of the PLA, Kunming City, Yunnan Province, China.
Xiaoyong YangDepartment of Orthopaedics, 920th Hospital of the Joint Logistics Support Force of the PLA, Kunming City, Yunnan Province, China.
Xijiao ZhangDepartment of Orthopaedics, 920th Hospital of the Joint Logistics Support Force of the PLA, Kunming City, Yunnan Province, China.
Junyi LiDepartment of Orthopaedics, 920th Hospital of the Joint Logistics Support Force of the PLA, Kunming City, Yunnan Province, China.
Yongqing XuDepartment of Orthopaedics, 920th Hospital of the Joint Logistics Support Force of the PLA, Kunming City, Yunnan Province, China.
Jian ShiDepartment of Orthopaedics, 920th Hospital of the Joint Logistics Support Force of the PLA, Kunming City, Yunnan Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe ceRNA network, which is competitive endogenous RNA, uncovers a fresh mechanism of RNA interaction and holds significant importance in diverse biological processes. The aim of this study is to investigate the molecular process of induced membrane (IM) formation in bone defects using the Masquelet's induced membrane technique (MIMT), in order to offer novel insights and a theoretical foundation for enhancing the treatment of bone defects with MIMT.

methodsIn this work, we identified differentially expressed mRNAs (DEGs), lncRNAs (DELs), circRNAs (DECs), and miRNAs (DEMs). To explore the primary functions of the shared DEGs, we utilized Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Next, predictions were made for lncRNA-miRNA and miRNA-mRNA interactions, and the Cytoscape software was utilized to construct the regulatory network for ceRNA.

resultsBy integrating GO and KEGG enrichment analysis, a total of 385 differentially expressed genes (DEGs) were discovered in the samples from the MIMT-treated group. Additionally, after re-annotating the probes and intersecting two sets of differently expressed miRNAs, 1304 differentially expressed lncRNAs (DELs) and 23 differentially expressed circRNAs (DECs) were identified. Furthermore, 13 differentially expressed miRNAs (DEMs) were obtained. Moreover, utilizing the anticipated objectives of DEMs, we acquired 1203 pairs of lncRNA-miRNA-mRNA interactors (comprising 24 lncRNAs, 10 miRNAs, and 115 mRNAs) and 250 pairs of circRNA-miRNA-mRNA interactions (comprising 7 circRNAs, 9 miRNAs, and 115 mRNAs). CEBPA, DGAT2, CDKN1A, PLIN2, and CIDEC were identified as the five hub proteins in the PPI network. LncRNA/circRNA-hsa-miR-671-5p could potentially regulate the primary central protein, CEBPA.

conclusionsIn this study, we described the potential regulatory mechanism of the MIMT in treating bone defects. We proposed a new lncRNA-miRNA-mRNA ceRNA network that could help further explore the molecular mechanisms of bone repair.

Indexed as

Gene Regulatory NetworksMicroRNAsRNA, CircularRNA, Long NoncodingRNA, MessengerAnimalsBone RegenerationGene Expression ProfilingGene OntologyHumansMicroRNAsRNA, CircularRNA, Long NoncodingRNA, MessengerBone defectslncRNA/circRNA-miRNA-mRNA ceRNA networkMasquelet technique

Identifiers

PMID39444146
PMCPMC11504341

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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.