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Screening Criteria of mRNA Indicators for Wound age Estimation

Bibliographic Data

ID13119853
AuthorsQiu-xiang Du (Shanxi Medical University), Qiuxiang Du, Ta-na Dong (Ministry of Public Security of the People's Republic of China), Tana Dong, Yuanxin Liu (0009-0008-2911-3304, Shanxi Medical University), Xiyan Zhu (0000-0002-1751-4433, Army Medical University), Na Li (0000-0002-1103-6864, Shanxi Medical University), Li-hong Dang (Shanxi Medical University), Lihong Dang, Jie Cao (0000-0001-8268-954X, Shanxi Medical University), Qianqian Jin (0000-0002-2224-1185, Shanxi Medical University), Junhong Sun (0000-0002-6970-2620, Shanxi Medical University, corresponding author)
Year2022
Volume7
Issue4
Pages714-725
Publication date2022-05-11
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueForensic Sciences Research (JOURNAL)
Journal identifiersISSN: 2471-1411 • E-ISSN: 2096-1790
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/20961790.2021.1986770
PMID36817234
OpenAlexW4280624782
LanguageEN
References cited37

Wound age estimation is a crucial and challenging problem in forensic pathology. Although mRNA is the most commonly used indicator for wound age estimation, screening criteria are lacking. In the present study, the feasibility of screening criteria using mRNA to determine injury time based on the adenylate-uridylate-rich element (ARE) structure and gene ontology (GO) categories were evaluated. A total of 78 Sprague-Dawley male rats were contused and sampled at 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, and 48 h after inflicting injury. The candidate mRNAs were classified based on with or without ARE structure and GO category function. The mRNA expression levels were detected using qRT-PCR. In addition, the standard deviation (STD), mean deviation (MD), relative average deviation (d%), and coefficient of variation (CV) were calculated based on mRNA expression levels. The CV score (CVs) and the CV of CV (CV'CV) were calculated to measure heterogeneity. Finally, based on classic principles, the accuracy of combination of candidate mRNAs was assessed using discriminant analysis to construct a multivariate model for inferring wound age. The results of homogeneity evaluation of each group based on CVs were consistent with the MD, STD, d%, and CV results, indicating the credibility of the evaluation results based on CVs. The candidate mRNAs without ARE structure and classified as cellular component (CC) GO category (ARE-CC) had the highest CVs, showing the mRNAs with these characteristics are the most homogenous mRNAs and best suited for wound age estimation. The highest accuracy was 91.0% when the mRNAs without ARE structure were used to infer the wound age based on the discrimination model. The accuracy of mRNAs classified into CC or multiple function (MF) GO category was higher than mRNAs in the biological process (BP) category. In all subgroups, the accuracy of the composite identification model of mRNA composition without ARE structure and classified as CC was higher than other subgroups. The mRNAs without ARE structure and belonging to the CC GO category were more homogenous, showed higher accuracy for estimating wound age, and were appropriate for rat skeletal muscle wound age estimation. Supplemental data for this article is available online at https://doi.org/10.1080/20961790.2021.1986770

Bioinformatics · Biology · Coefficient of variation · Gene · Messenger RNA · Standard deviation · Statistics · Forensic Entomology and Diptera Studies · Mathematics · Medicine · Molecular Biology Techniques and Applications · Wound Healing and Treatments · Genetics · Molecular Biology

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