Expression of matrix metalloproteinase-9 (MMP-9) in human skin within 1 hour after injury through immunohistochemical staining: a pilot study.

Matrix metalloproteinase-9 (MMP-9) is involved in tissue remodeling and in skin wound healing. The present study focuses on the MMP-9 expression in epidermal wound healing within 1 h after injury, to test whether MMP-9 can be used to estimate the time of injury in forensic practice.A sample consisting of 5 individuals undergoing surgery was analyzed. With the consent of the patients, sections of skin were removed from the surgical wound at predefined time intervals. For each subject, 8 sections were taken, one for each time interval defined at 0 '- 1' - 3 '- 5' - 10 '- 15' - 30 '- 60' minutes. The specimens were immunostained with MMP-9, and the number of positively stained cells was examined.The number of positively stained cells showed an increasing trend as a function of time. Less than 30 positively stained cells were found in all cases within 3 min. At the post-infliction time of 5 min, the number of positively stained cells exceeded 30 in 3 out of 5 cases. The number of MMP-positive cells exceeded 40 in all cases in over 10 min.In the light of these results, the count of MMP-9 positive cells might be a useful marker in the wound-age estimation within 1 h in forensic setting. More research is required to collect more samples and to compare samples from the hyperacute phase with those from several days after injury.

Development of a screening system of gene sets for estimating the time of early skeletal muscle injury based on second-generation sequencing technology.

The present study is aimed to address the challenge of wound age estimation in forensic science by identifying reliable genetic markers using low-cost and high-precision second-generation sequencing technology. A total of 54 Sprague-Dawley rats were randomly assigned to a control group or injury groups, with injury groups being further divided into time points (4 h, 8 h, 12 h, 16 h, 20 h, 24 h, 28 h, and 32 h after injury, n = 6) to establish rat skeletal muscle contusion models. Gene expression data were obtained using second-generation sequencing technology, and differential gene expression analysis, weighted gene co-expression network analysis (WGCNA) and time-dependent expression trend analysis were performed. A total of six sets of biomarkers were obtained: differentially expressed genes at adjacent time points (127 genes), co-expressed genes most associated with wound age (213 genes), hub genes exhibiting time-dependent expression (264 genes), and sets of transcription factors (TF) corresponding to the above sets of genes (74, 87, and 99 genes, respectively). Then, random forest (RF), support vector machine (SVM) and multilayer perceptron (MLP), were constructed for wound age estimation from the above gene sets. The results estimated by transcription factors were all superior to the corresponding hub genes, with the transcription factor group of WGCNA performed the best, with average accuracy rates of 96% for three models' internal testing, and 91.7% for the highest external validation. This study demonstrates the advantages of the indicator screening system based on second-generation sequencing technology and transcription factor level for wound age estimation.

Immunohistochemical analysis of PDGFR-α for wound age determination.

Immunohistochemical analysis of platelet-derived growth factor receptor-α (PDGFR-α) was performed on human skin wounds obtained from forensic autopsy cases. Thirty human skin wounds were collected at different post-infliction intervals as follows: Group I, 4 h to 3 days (n = 16); Group II, 4 to 7 days (n = 7); Group III, 9 to 10 days (n = 3); and Group IV, 14 to 20 days (n = 4). Immunopositive reactions for PDGFR-α were not observed in the uninjured human skin specimens. In a semi-quantitative morphometrical analysis, the number of PDGFR-α-positive cells was observed increased in Group II, with the average number of PDGFR-α-positive cells being the highest in Group II. Additionally, in Group II, all specimens showed PDGFR-α-positive cells, with an average number of > 200 cells in five fields of view, suggesting a wound age of 4 to 7 days. Taken together, the immunohistochemical detection of PDGFR-α in human skin wounds can be a useful tool for wound age determination.

Dating Skin Lesions of Forensic Interest by Immunohistochemistry and Immunofluorescence Techniques: A Scoping Literature Review.

Wound age estimation is a significant issue in forensic pathology. Although various methods have been evaluated, no gold standard system or model has been proposed, and accurate injury time estimation is still challenging. The distinction between vital skin wounds-i.e., ante-mortem lesions-and skin alterations that occur after death is a crucial goal in forensic pathology. Once the vitality of the wound has been confirmed, the assessment of the post-trauma interval (PTI) is also fundamental in establishing the causal relationship between the traumatic event and death. The most frequently used techniques in research studies are biochemistry, molecular biology, and immunohistochemistry (IHC). Biochemical methods take advantage of the chemical and physical techniques. A systematic literature search of studies started on 18 February 2023. The search was conducted in the main databases for biomedical literature, i.e., PubMed and Scopus, for papers published between 1973 and 2022, focusing on different techniques of immunohistochemistry and immunofluorescence (IF) for estimating the PTI of skin wounds. The present study involves a comprehensive and structured analysis of the existing literature to provide a detailed and comprehensive overview of the different IHC techniques used to date skin lesions, synthesize the available evidence, critically evaluate the methodologies, and eventually draw meaningful conclusions about the reliability and effectiveness of the different markers that have been discovered and used in wound age estimation.

Novel ratio-expressions of genes enables estimation of wound age in contused skeletal muscle.

Given that combination with multiple biomarkers may well raise the predictive value of wound age, it appears critically essential to identify new features under the limited cost. For this purpose, the present study explored whether the gene expression ratios provide unique time information as an additional indicator for wound age estimation not requiring the detection of new biomarkers and allowing full use of the available data. The expression levels of four wound-healing genes (Arid5a, Ier3, Stom, and Lcp1) were detected by real-time polymerase chain reaction, and a total of six expression ratios were calculated among these four genes. The results showed that the expression levels of four genes and six ratios of expression changed time-dependent during wound repair. The six expression ratios provided additional temporal information, distinct from the four genes analyzed separately by principal component analysis. The overall performance metrics for cross-validation and external validation of four typical prediction models were improved when six ratios of expression were added as additional input variables. Overall, expression ratios among genes provide temporal information and have excellent potential as predictive markers for wound age estimation. Combining the expression levels of genes with ratio-expression of genes may allow for more accurate estimates of the time of injury.

Skin injuries in forensic histopathology: a descriptive study.

Histopathology is commonly used in forensic medicine. Only few studies are available in the literature about the correlation between skin wounds histopathology and survival time or other medicolegal data. The aim of this study was to illustrate the usefulness of histopathological analysis of skin wounds in forensic daily practice and to evaluate its correlation with the clinical and police investigation data. In this single-center, retrospective, and descriptive study, we included 198 forensic pathology cases, from the files of the Legal Medicine and Biopathology Departments of the University Hospital of Nancy, with a total of 554 skin samples. Basing on the police investigations (n = 43), the median survival time between the main related trauma and death was 83 min. The histopathological analysis concluded to 2% of post-mortem lesions (absence of hemorrhage) and 55% of perimortem or undetermined lesions (hemorrhage without inflammation); 8% of the lesions had an estimated time interval between more than 10 min and several hours, 22% between several hours and several days, and 14% between several days and several weeks. Histopathological dating was statistically associated with wound location (p < 0.01), the type of injury, hypothermia, positive toxicology, histopathological hepatic lesions, and survival time (p < 0.001). In conclusion, the histopathological analysis of skin wounds allowed to propose a survival time in almost half of cases, with a significant correlation with the police investigation-based estimation of survival time, but also other parameters such as wound location or toxicology. It however lacks of accuracy, and further studies are needed to develop new markers, notably based on immunohistochemistry.

Combined metabolomics and tandem machine-learning models for wound age estimation: a novel analytical strategy.

Wound age estimation is one of the most challenging and indispensable issues for forensic pathologists. Although many methods based on physical findings and biochemical tests can be used to estimate wound age, an objective and reliable method for inferring the time interval after injury remains difficult. In the present study, endogenous metabolites of contused skeletal muscle were investigated to estimate the time interval after injury. Animal model of skeletal muscle injury was established using Sprague-Dawley rat, and the contused muscles were sampled at 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, and 48 h postcontusion (n = 9). Then, the samples were analysed using ultraperformance liquid chromatography coupled with high-resolution mass spectrometry. A total of 43 differential metabolites in contused muscle were determined by metabolomics method. They were applied to construct a two-level tandem prediction model for wound age estimation based on multilayer perceptron algorithm. As a result, all muscle samples were eventually divided into the following subgroups: 4, 8, 12, 16-20, 24-32, 36-40, and 44-48 h. The tandem model exhibited a robust performance and achieved a prediction accuracy of 92.6%, which was much higher than that of the single model. In summary, the multilayer perceptron-multilayer perceptron tandem machine-learning model based on metabolomics data can be used as a novel strategy for wound age estimation in future forensic casework. Key Points: The changes of metabolite profile were correlated with the time interval after injury in contused skeletal muscle.A panel of 43 endogenous metabolites screened by ultraperformance liquid chromatography coupled with high-resolution mass spectrometry could distinguish the wound ages.The multilayer perceptron (MLP) algorithm exhibited a robust performance in wound age estimation using metabolites.The combination of matabolomics and MLP-MLP tandem model could improve the accuracy of inferring the time interval after injury.

Extended characterization of IL-33/ST2 as a predictor for wound age determination in skin wound tissue samples of humans and mice.

Interleukin (IL)-33, an important inflammatory cytokine, is highly expressed in skin wound tissue and serum of humans and mice, and plays an essential role in the process of skin wound healing (SWH) dependent on the IL-33/suppression of tumorigenicity 2 (ST2) pathway. However, whether IL-33 and ST2 themselves, as well as their interaction, can be applied for skin wound age determination in forensic practice remains incompletely characterized. Human skin samples with injured intervals of a few minutes to 24 hours (hs) and mouse skin samples with injured intervals of 1 h to 14 days (ds) were collected. Herein, the results demonstrated that IL-33 and ST2 are increased in the human skin wounds, and that in mice skin wounds, there is an increase over time, with IL-33 expression peaking at 24 hs and 10 ds, and ST2 expression peaking at 12 hs and 7 ds. Notably, the relative quantity of IL-33 and ST2 proteins < 0.35 suggested a wound age of 3 hs; their relative quantity > 1.0 suggested a wound age of 24 hs post-mouse skin wounds. In addition, immunofluorescent staining results showed that IL-33 and ST2 were consistently expressed in the cytoplasm of F4/80-positive macrophages and CD31-positive vascular endothelial cells with or without skin wounds, whereas nuclear localization of IL-33 was absent in α-SMA-positive myofibroblasts with skin wounds. Interestingly, IL-33 administration facilitated the wound area closure by increasing the proliferation of cytokeratin (K) 14 -positive keratinocytes and vimentin-positive fibroblasts. In contrast, treating with its antagonist (i.e., anti-IL-33) or receptor antagonist (e.g., anti-ST2) exacerbated the aforementioned pathological changes. Moreover, treatment with IL-33 combined with anti-IL-33 or anti-ST2 reversed the effect of IL-33 on facilitating skin wound closure, suggesting that IL-33 administration facilitated skin wound closure through the IL-33/ST2 signaling pathway. Collectively, these findings indicate that the detection of IL-33/ST2 might be a reliable biomarker for the determination of skin wound age in forensic practice.

Maintaining and Restoring Gradients of Ions in the Epidermis: The Role of Ion and Water Channels in Acute Cutaneous Wound Healing.

Significance: Aquaporins and ion channels establish and regulate gradients of calcium, sodium, potassium, chloride, water, and protons in the epidermis. These elements have been found to play significant roles in skin biology and wound healing. In this study, we review our understanding of these channels and ion gradients, with a special emphasis on their role in acute wound healing. Recent Advances: Specifically, we assess the temporal and spatial arrangements of ions and their respective channels in the intact skin and during wound and healing to provide a novel perspective of the role of ionic gradients through the various stages of wound healing. Critical Issues: The roles of gradients of ions and channels in wound healing are currently not well understood. A collective analysis of their traits and arrangements in the skin during wound healing may provide a new perspective and understanding of the functionality of gradients of ions and channels in skin biology and wound healing. Future Directions: It is important to elucidate how the gradients of ions and ion channels regulate and facilitate wound healing. A better understanding of the ionic environments may identify novel therapeutic targets and improved strategies to promote wound healing and possibly treat other cutaneous diseases.

Detection of multiple biomarkers associated with satellite cell fate in the contused skeletal muscle of rats for wound age estimation.

From the perspective of forensic wound age estimation, experiments related to skeletal muscle regeneration after injury have rarely been reported. Here, we examined the time-dependent expression patterns of multiple biomarkers associated with satellite cell fate, including the transcription factor paired box 7 (Pax7), myoblast determination protein (MyoD), myogenin, and insulin-like growth factor (IGF-1), using immunohistochemistry, western blotting, and quantitative real-time PCR in contused skeletal muscle. An animal model of skeletal muscle contusion was established in 30 Sprague-Dawley male rats, and another five rats were employed as non-contused controls. Morphometrically, the data obtained from the numbers of Pax7 + , MyoD + , and myogenin + cells were highly correlated with the wound age. Pax7, MyoD, myogenin, and IGF-1 expression patterns were upregulated after injury at both the mRNA and protein levels. Pax7, MyoD, and myogenin protein expression levels confirmed the results of the morphometrical analysis. Additionally, the relative quantity of IGF-1 protein > 0.92 suggested a wound age of 3 to 7 days. The relative quantity of Pax7 mRNA > 2.44 also suggested a wound age of 3 to 7 days. Relative quantities of Myod1, Myog, and Igf1 mRNA expression > 2.78, > 7.80, or > 3.13, respectively, indicated a wound age of approximately 3 days. In conclusion, the expression levels of Pax7, MyoD, myogenin, and IGF-1 were upregulated in a time-dependent manner during skeletal muscle wound healing, suggesting the potential for using them as candidate biomarkers for wound age estimation in skeletal muscle.

Novel Prediction Method Applied to Wound Age Estimation: Developing a Stacking Ensemble Model to Improve Predictive Performance Based on Multi-mRNA.

(1) Background: Accurate diagnosis of wound age is crucial for investigating violent cases in forensic practice. However, effective biomarkers and forecast methods are lacking. (2) Methods: Samples were collected from rats divided randomly into control and contusion groups at 0, 4, 8, 12, 16, 20, and 24 h post-injury. The characteristics of concern were nine mRNA expression levels. Internal validation data were used to train different machine learning algorithms, namely random forest (RF), support vector machine (SVM), multilayer perceptron (MLP), gradient boosting (GB), and stochastic gradient descent (SGD), to predict wound age. These models were considered the base learners, which were then applied to developing 26 stacking ensemble models combining two, three, four, or five base learners. The best-performing stacking model and base learner were evaluated through external validation data. (3) Results: The best results were obtained using a stacking model of RF + SVM + MLP (accuracy = 92.85%, area under the receiver operating characteristic curve (AUROC) = 0.93, root-mean-square-error (RMSE) = 1.06 h). The wound age prediction performance of the stacking models was also confirmed for another independent dataset. (4) Conclusions: We illustrate that machine learning techniques, especially ensemble algorithms, have a high potential to be used to predict wound age. According to the results, the strategy can be applied to other types of forensic forecasts.

miR-26a/30d/152 are reliable reference genes for miRNA quantification in skin wound age estimation.

MicroRNAs (miRNAs) are a class of small non-coding RNAs that exert their biological functions as negative regulators of gene expression. They are involved in the skin wound healing process with a dynamic expression pattern and can therefore potentially serve as biomarkers for skin wound age estimation. However, no reports have described any miRNAs as suitable reference genes (RGs) for miRNA quantification in wounded skin or samples with post-mortem changes. Here, we aimed to identify specific miRNAs as RGs for miRNA quantification to support further studies of skin wound age estimation. Overall, nine miRNAs stably expressed in mouse skin at certain posttraumatic intervals (PTIs) were preselected by next-generation sequencing as candidate RGs. These nine miRNAs and the commonly used reference genes (comRGs: U6, GAPDH, ACTB, 18S, 5S, LC-Ogdh) were quantitatively examined using quantitative real-time reverse-transcription polymerase chain reaction at different PTIs during skin wound healing in mice. The stabilities of these genes were evaluated using four independent algorithms: GeNorm, NormFinder, BestKeeper, and comparative Delta Ct. Stability was further evaluated in mice with different post-mortem intervals (PMIs). Overall, mmu-miR-26a-5p, mmu-miR-30d-5p, and mmu-miR-152-3p were identified as the most stable genes at both different PTIs and PMIs. These three miRNA RGs were additionally validated and compared with the comRGs in human samples. After assessing using one, two, or three miRNAs in combination for stability at different PTIs, PMIs, or in human samples, the set of miR-26a/30d/152 was approved as the best normalizer. In conclusion, our data suggest that the combination of miR-26a/30d/152 is recommended as the normalization strategy for miRNA qRT-PCR quantification in skin wound age estimation. Key points: The small size of miRNAs makes them less susceptible to post-mortem autolysis or putrefaction, leading to their potential use in wound age estimation.Studying miRNAs as biological indicators of skin wound age estimation requires the selection and validation of stable reference genes because commonly used reference genes, such as U6, ACTB, GAPDH, 5S, 18S, and LC-Ogdh, are not stable.miR-26a/30d/152 are stable and reliable as reference genes and their use in combination is a recommended normalization strategy for miRNA quantitative analysis in wounded skin.

Research Progress of Metabolomics Techniques Combined with Machine Learning Algorithm in Wound Age Estimation.

Wound age estimation is the core content in the practice of forensic medicine. Accurate estimation of wound age is a scientific question that needs to be urgently solved by forensic scientists at home and abroad. Metabolomics techniques can effectively detect endogenous metabolites produced by internal or external stimulating factors and describe the dynamic changes of metabolites in vivo. It has the advantages of strong operability, high detection efficiency and accurate quantitative results. Machine learning algorithm has special advantages in processing high-dimensional data sets, which can effectively mine biological information and truly reflect the physiological, disease or injury state of the body. It is a new technical means for efficiently processing high-throughput big data. This paper reviews the status and advantages of metabolomic techniques combined with machine learning algorithm in the research of wound age estimation, and provides new ideas for this research.

Application of Linear Regression Model of Gpnmb Gene in Rat Injury Time Estimation.

OBJECTIVES: To investigate the effects of injury time, postmortem interval (PMI) and postmortem storage temperature on mRNA expression of glycoprotein non-metastatic melanoma protein B (Gpnmb), and to establish a linear regression model between Gpnmb mRNA expression and injury time, to provide aimed at providing potential indexes for injury time estimation. METHODS: Test group SD rats were anesthetized and subjected to blunt contusion and randomly divided into 0 h, 4 h, 8 h, 12 h, 16 h, 20 h and 24 h groups after injury, with 18 rats in each group. After cervical dislocation, 6 rats in each group were collected and stored at 0 ℃, 16 ℃ and 26 ℃, respectively. The muscle tissue samples of quadriceps femoris injury were collected at 0 h, 12 h and 24 h postmortem at the same temperature. The grouping method and treatment method of the rats in the validation group were the same as above. The expression of Gpnmb mRNA in rat skeletal muscle was detected by RT-qPCR. The Pearson correlation coefficient was used to evaluate the correlation between Gpnmb mRNA expression and injury time, PMI, and postmortem storage temperature. SPSS 25.0 software was used to construct a linear regression model, and the validation group data was used for the back-substitution test. RESULTS: The expression of Gpnmb mRNA continued to increase with the prolongation of injury time, and the expression level was highly correlated with injury time (P<0.05), but had little correlation with PMI and postmortem storage temperature (P>0.05). The linear regression equation between injury time (y) and Gpnmb mRNA relative expression (x) was y=0.611 x+4.489. The back-substitution test proved that the prediction of the model was accurate. CONCLUSIONS: The expression of Gpnmb mRNA is almost not affected by the PMI and postmortem storage temperature, but is mainly related to the time of injury. Therefore, a linear regression model can be established to infer the time of injury.

Wound age estimation based on chronological changes in chitinase 3-like protein 1 expression.

In forensic practice, wound age estimation is essential for making assessments of injuries; however, it remains challenging, and markers which correctly indicate wound age are required. Since our previous study showed that chitinase 3-like protein 3 (CHI3L3) expression changed chronologically in murine skin wounds, we hypothesized that other proteins of chitinase and chitinase-like protein (C/CLP) family, which CHI3L3 belongs to, might also have varied expression in wound healing. Therefore, we considered that some proteins of the C/CLP family could be used as markers of wound age estimation, and we aimed to test this hypothesis. Examinations of murine skin wounds revealed that the expression of chitinase 3-like protein 1 (CHI3L1) changed chronologically. CHI3L1 expression in human cadaver skin wounds, which was immunohistochemically analyzed by the average ratio of CHI3L1-expressed cells/total cells in 10 microscopic fields, was weak in wounds from days 0 to 1 after injury (0.11 ± 0.024; mean ± standard error of the mean); however, CHI3L1-positive cells appeared in wounds from days 2 to 3 (1.65 ± 0.19). The number of CHI3L1-expressed cells increased in wounds from days 4 to 6 (5.35 ± 0.35) but dropped from days 7 to 13 (1.53 ± 0.24). Receiver operating characteristic curve analysis indicated that wounds from days 4 to 6 after injury could be clearly distinguished from other wounds based on a cutoff value of 2.75, sensitivity of 92.31%, and specificity of 85.14%. Our findings suggest that CHI3L1 could be a reliable marker for wound age estimation in forensic practice.

Wound age estimation based on next-generation sequencing: Fitting the optimal index system using machine learning.

Accurate estimation of the wound age is critical in investigating intentional injury cases. Establishing objective and reliable biological indicators to estimate wound age is still a significant challenge in forensic medicine. Therefore, exploring an objective, flexible, and reliable index system selection method for wound age estimation based on next-generation sequencing gene expression profiles is necessary. We randomly divided 63 Sprague-Dawley rats into a control group, seven experimental groups (n = 7 per group), and an external validation group. After rats in the experimental and external validation groups suffered contusions, we sacrificed them at 4, 8, 12, 16, 20, 24, and 48 h after contusion, respectively. We selected 54 genes with the most significant changes between adjacent time points after contusion and defined set A. The Hub genes with time-related expression patterns were set B, C, and D through next-generation sequencing and bioinformatics analysis. Four different machine learning classification algorithms, including logistic regression, support vector machine, multi-layer perceptron, and random forest were used to compare and verify the efficiency of four index systems to estimate the wound age. The best combination for wound age estimation is the Genes ascribed to set A combined with the random forest classification algorithm. The accuracy of external verification was 85.71%. Only one rat was incorrectly classified (4 h post-injury incorrectly classified as 8 h). This study demonstrated the potential advantage of the index system selection based on next-generation sequencing and bioinformatics analysis for wound age estimation.

Time-dependent expression of high-mobility group box-1 and toll-like receptors proteins as potential determinants of skin wound age in rats: Forensic implication.

The skin wound age determination in living subjects is an imperative task for forensic experts. In this study, we investigated the time-dependent expression of high-mobility group box-1 (HMGB1) and toll-like receptors 2 and 4 (TLR2 and 4) in rat skin wounds using real-time PCR and seek their forensic potentials during the skin wound repair process. In addition, the levels of serum pro-inflammatory cytokines (tumor necrosis factor-alpha (TNF-α) and interleukin 6 (IL-6)), as well as nitric oxide (NO) production, were measured. The wound tissue and serum samples were collected after 30 min, 2 h, 6 h, 12 h, 1 day, 3 days, 5 days, and 7 days after incision. As a control (zero time), skin specimens and blood samples were collected without incision. The results reveal that the HMGB1, TLR2, and TLR4 expression levels were increased in a time-dependent manner until the first day where the peak level was achieved for the three tested genes compared with the zero time. On the 7th day, the statistical significance was lost for TLR2 and TLR4 but persisted for HMGB1. The serum TNF-α, IL6, and NO levels peaked within 30 min and 1st and 3rd day after injury, respectively. On the 7th day after incision, no significant differences exist in the TNF-α serum level compared to the control group, but the statistical significance persisted for IL6 and NO. It was apparent that the analyzed genes in the wound tissues showed higher R2 values rather than the serum biochemical indicators. Of note, a strong positive correlation was evident between the HMGB1 and that of TLR2 and TLR4 relative expression as well as IL-6 serum level. Conclusively, based on the observed changes in the analyzed markers in wound tissues and serum and R2 values obtained from mathematical models established to determine the wound age, the relative expression of HMGB1, TLR2, and TLR4 could be a reliable indicator for wound age determination in living subjects. Further investigation of these markers and mathematical models in human tissues is necessary.

Bone Marrow-Derived Cells and Wound Age Estimation.

Appropriate technology as well as specific target cells and molecules are key factors for determination of wound vitality or wound age in forensic practice. Wound examination is one of the most important tasks for forensic pathologists and is indispensable to distinguish antemortem wounds from postmortem damage. For vital wounds, estimating the age of the wound is also essential in determining how the wound is associated with the cause of death. We investigated bone marrow-derived cells as promising markers and their potential usefulness in forensic applications. Although examination of a single marker cannot provide high reliability and objectivity in estimating wound age, evaluating the appearance combination of bone marrow-derived cells and the other markers may allow for a more objective and accurate estimation of wound age.

Screening criteria of mRNA indicators for wound age estimation.

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 .