Evidence map›Paper›PMID 39720696›Full record

ArticleJournal of inflammation research2024

Identification of Potential Drug Targets for the Treatment of Severe Burn Wounds from a Multi-Omics Perspective.

Gehua Zhu, Jiaqi Li, Jiamin Xu, Guanghua Guo, Feng Zhu

Abstract read
In one paragraph

Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

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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

5 authors.

Gehua Zhu *Medical Centre of Burn Plastic and Wound Repair, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, People's Republic of China.ORCID 0009-0001-0380-3525
Jiaqi Li *Department of Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, People's Republic of China.
Jiamin XuMedical Centre of Burn Plastic and Wound Repair, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, People's Republic of China.
Guanghua GuoMedical Centre of Burn Plastic and Wound Repair, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, People's Republic of China.
Feng ZhuDepartment of Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Severe burns result in significant skin damage, impairing its primary role as an infection barrier and presenting substantial treatment challenges. Despite improvements in the treatment of burn patients due to advancements in materials and techniques, there remains a need for novel therapeutic approaches to enhance burn prognosis further. Patients and Methods: Several types of genomic methods are used in this study, such as differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), machine learning, and Mendelian randomization (MR), to find genes that are linked to severe burns and create a diagnostic nomogram to see how well these genes can predict severe burns. Drug prediction was conducted using the DsigDB database, and molecular docking was used to validate the pharmacological value of drug targets. The effects of genes and drugs on burn wounds were validated through Western Blot (WB) and cell scratch assays. Results: In patients with severe burns, multi-omics analysis revealed increased CYP19A1 expression. In severe burn cell models, WB further confirmed the elevated expression of CYP19A1. Drug prediction indicated that mevastatin binds effectively to the CYP19A1 gene expression protein. The healing area of scalded HaCat cells was much bigger after 24 hours of mevastatin treatment compared to the scald-only group, as shown by cell scratch assays after 24 and 48 hours. Conclusion: This study innovatively integrates multi-omics approaches into burn wound research, uncovering for the first time that mevastatin promotes burn wound healing by downregulating CYP19A1 expression. This discovery may provide a new foundation for developing burn wound therapeutics and potentially reduce drug development costs.

Indexed as

burndrug targetsgeneticsmachine learningMendelian randomizationWGCNA

Identifiers

PMID39720696
PMCPMC11668339

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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.