Evidence map›Paper›PMID 37409114›Full record

ArticleFrontiers in immunology2023

Deciphering the contributions of cuproptosis in the development of hypertrophic scar using single-cell analysis and machine learning techniques.

Binyu Song, Wei Liu, Yuhan Zhu, Yixuan Peng, Zhiwei Cui, Botao Gao, Lin Chen, Zhou Yu, Baoqiang Song

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.6field-weighted citation impact, top 11% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

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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

9 authors at 1 institution in 1 country.

Binyu SongDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Wei LiuDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Yuhan ZhuDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Yixuan PengDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Zhiwei CuiDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Botao GaoDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Lin ChenDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Zhou YuDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Baoqiang SongDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Xijing Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertrophic scar (HS) is a chronic inflammatory skin disease characterized by excessive deposition of extracellular matrix, but the exact mechanisms related to its formation remain unclear, making it difficult to treat. This study aimed to investigate the potential role of cuproptosis in the information of HS. To this end, we used single-cell sequencing and bulk transcriptome data, and screened for cuproptosis-related genes (CRGs) using differential gene analysis and machine learning algorithms (random forest and support vector machine). Through this process, we identified a group of genes, including ATP7A, ULK1, and MTF1, as novel therapeutic targets for HS. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to confirm the mRNA expression of ATP7A, ULK1, and MTF1 in both HS and normal skin (NS) tissues. We also constructed a diagnostic model for HS and analyzed the immune infiltration characteristics. Additionally, we used the expression profiles of CRGs to perform subgroup analysis of HS. We focused mainly on fibroblasts in the transcriptional profile at single-cell resolution. By calculating the cuproptosis activity of each fibroblast, we found that cuproptosis activity of normal skin fibroblasts increased, providing further insights into the pathogenesis of HS. We also analyzed the cell communication network and transcription factor regulatory network activity, and found the existence of a fibroblast-centered communication regulation network in HS, where cuproptosis activity in fibroblasts affects intercellular communication. Using transcription factor regulatory activity network analysis, we obtained highly active transcription factors, and correlation analysis with CRGs suggested that CRGs may serve as potential target genes for transcription factors. Overall, our study provides new insights into the pathophysiological mechanisms of HS, which may inspire new ideas for the diagnosis and treatment.

Indexed as

ApoptosisCicatrix, HypertrophicAlgorithmsCopperHumansMachine LearningSingle-Cell AnalysisSkinCoppercuproptosisGEOhypertrophic scarmachine learningsingle-cell

Identifiers

PMID37409114
PMCPMC10318401
OpenAlexW4381334892

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.