Evidence map›Paper›PMID 39045324›Full record

ArticleFrontiers in genetics2024

Identification of disulfidptosis- and ferroptosis-related transcripts in periodontitis by bioinformatics analysis and experimental validation.

Yu Fu, Tingrui Xu, Mengru Guo, Wenhao Lv, Ning Ma, Li Zhang

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

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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3 · Its place in the literature

Who cites it

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.

Yu FuHospital of Stomatology, Jilin University, Changchun, China.
Tingrui XuHospital of Stomatology, Jilin University, Changchun, China.
Mengru GuoHospital of Stomatology, Jilin University, Changchun, China.
Wenhao LvHospital of Stomatology, Jilin University, Changchun, China.
Ning MaHospital of Stomatology, Jilin University, Changchun, China.
Li ZhangHospital of Stomatology, Jilin University, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Disulfidptosis and ferroptosis are forms of programmed cell death that may be associated with the pathogenesis of periodontitis. Our study developed periodontitis-associated biomarkers combining disulfidptosis and ferroptosis, which provides a new perspective on the pathogenesis of periodontitis. Methods: Firstly, we obtained the periodontitis dataset from public databases and found disulfidptosis- and ferroptosis-related differentially expressed transcripts based on the disulfidptosis and ferroptosis transcript sets. After that, transcripts that are tissue biomarkers for periodontitis were found using three machine learning methods. We also generated transcript subclusters from two periodontitis microarray datasets: GSE16134 and GSE23586. Furthermore, three transcripts with the best classification efficiency were further screened. Their expression and classification efficacy were validated using qRT-PCR. Finally, periodontal clinical indicators of 32 clinical patients were collected, and the correlation between three transcripts above and periodontal clinical indicators was analyzed. Results: We identified six transcripts that are tissue biomarkers for periodontitis, the top three transcripts with the best classification, and delineated two expression patterns in periodontitis. Conclusions: Our study found that disulfidptosis and ferroptosis were associated with immune responses and may involve periodontitis genesis.

Indexed as

bioinformaticsdisulfidptosisferroptosisimmune infiltrationmachine learningperiodontitis

Identifiers

PMID39045324
PMCPMC11263038

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