Screening criteria of mRNA indicators for wound age estimation.
Screening criteria of mRNA indicators for wound age estimation.
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DOI：
10.1080/20961790.2021.1986770
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发表时间：
2022
影响因子：
1.3
通讯作者：
Sun, Junhong
中科院分区：
文献类型：
--
作者：
Du, Qiuxiang;Dong, Tana;Liu, Yuanxin;Zhu, Xiyan;Li, Na;Dang, Lihong;Cao, Jie;Jin, Qianqian;Sun, Junhong
关键词：
创伤年龄推断是法医病理学中的一个重要而又具有挑战性的问题。虽然mRNA是最常用的伤口年龄估计指标，但缺乏筛选标准。在本研究中，使用mRNA的筛选标准，以确定损伤时间的基础上的腺苷酸-尿苷酸丰富的元素（ARE）的结构和基因本体论（GO）的类别的可行性进行了评估。共78只Sprague-Dawley雄性大鼠在造成损伤后4、8、12、16、20、24、28、32、36、40、44和48 h挫伤并取样。基于有或没有ARE结构和GO类别功能对候选mRNA进行分类。使用qRT-PCR检测mRNA表达水平。此外，基于mRNA表达水平计算标准偏差（STD）、平均偏差（MD）、相对平均偏差（d%）和变异系数（CV）。计算CV评分（CV）和CV的CV（CV'CV）以衡量异质性。最后，基于经典原则，使用判别分析来评估候选mRNA组合的准确性，以构建推断伤口年龄的多变量模型。基于CV的各组均匀性评价结果与MD、STD、d%和CV结果一致，表明基于CV的评价结果可信。不具有ARE结构并被分类为细胞组分（CC）GO类别（ARE-CC）的候选mRNA具有最高的CV，表明具有这些特征的mRNA是最同源的mRNA，并且最适合于伤口年龄估计。以不含ARE结构的mRNA作为判别模型，推断创伤年龄的准确率最高为91.0%。分类为CC或多功能（MF）GO类别的mRNA的准确性高于生物过程（BP）类别的mRNA。在所有亚组中，不含ARE结构的mRNA组成和分类为CC的复合识别模型的准确性高于其他亚组。不含ARE结构且属于CC GO类别的mRNA更均一，显示出更高的估计创伤年龄的准确性，并且适合于大鼠骨骼肌创伤年龄估计。本文的补充数据可在https://doi.org/10.1080/20961790.2021.1986770上获得。
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 .
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