An “up, no change, or down” system: Time-dependent expression of mRNAs in contused skeletal muscle of rats used for wound age estimation

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.

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.

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.

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 7^th 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 1^st and 3^rd day after injury, respectively. On the 7^th 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.

Identifying biomarkers for evaluating wound extent and age in the contused muscle of rats using microarray analysis: a pilot study

Wound age estimation is still one of the most important and significant challenges in forensic practice. The extent of wound damage greatly affects the accuracy and reliability of wound age estimation, so it is important to find effective biomarkers to help diagnose wound degree and wound age. In the present study, the gene expression profiles of both mild and severe injuries in 33 rats were assayed at 0, 1, 3, 24, 48, and 168 hours using the Affymetrix microarray system to provide biomarkers for the evaluation of wound age and the extent of the wound. After obtaining thousands of differentially expressed genes, a principal component analysis, the least absolute shrinkage and selection operator, and a time-series analysis were used to select the most predictive prognostic genes. Finally, 15 genes were screened for evaluating the extent of wound damage, and the top 60 genes were also screened for wound age estimation in mild and severe injury. Selected indicators showed good diagnostic performance for identifying the extent of the wound and wound age in a Fisher discriminant analysis. A function analysis showed that the candidate genes were mainly related to cell proliferation and the inflammatory response, primarily IL-17 and the Hematopoietic cell lineage signalling pathway. The results revealed that these genes play an essential role in wound-healing and yield helpful and valuable potential biomarkers for further targeted studies.

The Role of miRNAs as New Molecular Biomarkers for Dating the Age of Wound Production: A Systematic Review

BACKGROUND

The timing of wounds production is a significant issue in forensic pathology. Although various methods have been evaluated, obtaining an accurate dating of lesions is still a challenge. The pathologist uses many parameters to value wound age, such as histological and immunohistochemical. In recent years, there have been many studies regarding the use of miRNAs in wound-age estimation; indeed, miRNAs have multiple potential uses in forensic pathology.

SCOPE

This review aims to verify the efficacy and feasibility of miRNAs as a tool for determining the timing of lesions.

MATERIALS AND METHODS

The authors conducted the systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. PubMed was used as a search engine to find articles published between January, 1st 2016 and October, 1st 2021, to evaluate the current state of the art regarding wound-age estimation.

RESULTS

A total of 256 articles were collected; after screening according to PRISMA guidelines, the systematic review included 8 articles. The studies included in this review were all Original articles evaluating the use of biomarkers for wound-age determination.

DISCUSSION AND CONCLUSION

The literature review showed that analysis of miRNA is an innovative field of study with significant potentiality in forensic pathology. There are few studies, and almost all of them are at an early stage. The challenge is to understand how to standardize the samples' selection to obtain reliable experimental data. This observation represents a necessary prerequisite to planning further clinical trials.

Estimating the time of skeletal muscle contusion based on the spatial distribution of neutrophils: a practical approach to forensic problems

The study aimed to explore the neutrophil's spatial distributions used to estimate the histological age of contused skeletal muscle, and assessed the accuracy of various indicators, such as the proportion of neutrophils, "neutrophil mean distance," and distribution of neutrophils in areas of "contiguous contour lines." Fifty-five Sprague-Dawley rats were divided randomly into a control group and contusion groups at 1, 1.5, 2, 3, 4, and 6 h, as well as 1, 3, 5, and 15 days, post-injury (n = 5 per group). Nuclei and neutrophils were detected by hematoxylin and eosin (HE) staining and immunohistochemical (IHC) staining. At 0-24 h after injury, the distribution of neutrophils at distances of 100, 200, 300, 400, 500, and 600 µm from adjacent blood vessels was determined, and the best samples were screened to estimate wound age. To estimate wound age as accurately as possible, Fisher discriminant analysis (FDA) of the proportion of neutrophils, neutrophil mean distance, and distribution of neutrophils was performed, and 100.0% and 95.0% of the original and cross-validated cases were correctly classified, respectively. The spatial distribution of neutrophils at different distances from adjacent blood vessels showed a strong correlation with the histological age of contusion skeletal muscle, and the combination of the proportion of neutrophils, neutrophil mean distance, and distribution of neutrophils could be used to accurately estimate wound age.

Novel insights into wound age estimation: combined with "up, no change, or down" system and cosine similarity in python environment

Wound age estimation is a complex, multifactorial issue. It is considered to have great practical significance that combining multi-biomarkers and multi-methods for injury time estimation. We optimized our earlier "up, no change, or down" model by adding data on the expression levels of mRNAs encoding ABHD2, MAD2L2, and ARID5A, and we converted the relative quantitative expression levels of seven genes into a vector rather than a color model. We used Python to derive the cosine similarity (CS) between a test set and the vector matrix; the highest similarity most accurately reflected the injury time. For the optimized model, the internal and external verifications were approximately 0.71 and 0.66, respectively. The good double-blinded results indicated that the model was stable and reliable. In summary, we used a vector matrix and cosine similarities derived by Python to mine the levels of genes expressed in contused skeletal muscle. We are the first to combine several biomarkers and methods for wound age estimation.

Analysis of sensitivity and specificity: precise recognition of neutrophils during regeneration of contused skeletal muscle in rats

In this report, we applied the TissueFAXS 200 digital pathological analysis system to rapidly and accurately identify neutrophils during regeneration of contused skeletal muscle, and to provide information for follow-up studies on neutrophils to estimate wound age. Rat injury model was established, and skeletal muscle samples were obtained from the control group and contusion groups at 1, 1.5, 2, 3, 4, and 6 h, as well as at 1, 3, 5, and 15 d post-injury (n = 5 per group). The expression of nuclei and neutrophils was detected by hematoxylin and eosin (HE) staining and immunohistochemical (IHC) staining. A total of 20 injury site areas of 0.25 mm² (0.5 mm × 0.5 mm) were then randomly selected at all time points. A TissueFAXS 200 digital pathological analysis system was used to identify the positive and negative numbers. Knowledge of five professional medical workers were considered the gold standard to measure the false positive rate (FPR), false negative rate (FNR), sensitivity, specificity, and area under the curve (AUC) of receiver operating characteristic (ROC) curves. As a result, with a staining area of neutrophils from 8 µm² to 15 µm², the FPR was 4.28%–12.14%, the FNR was 12.42%–64.08%, the sensitivity was 35.92%–87.58%, the specificity was 87.86%–95.72%, the Youden index was 0.316–0.754, the accuracy was 82.80%–88.30%, and the AUC was 0.771–0.826. The AUC was largest when the cut-off value of the staining area was 12 µm². Our results show that this software-based method is more accurate than the human eye in evaluating neutrophil infiltration. Based on the sensitivity and specificity, neutrophils can be accurately identified during regeneration of contused skeletal muscle. The TissueFAXS 200 digital pathological analysis system can also be used to optimize conditions for different cell types under various injury conditions to determine the optimal cut-off value of the staining area and provide optimal conditions for further study. Furthermore, it will provide evidence for forensic pathology cases.

Temporal expression of wound healing-related genes inform wound age estimation in rats after a skeletal muscle contusion: a multivariate statistical model analysis

Although many time-dependent parameters involved in wound healing have been exhaustively investigated, establishing an objective and reliable means for estimating wound age remains a challenge. In this study, 78 Sprague-Dawley rats were divided randomly into a control group and contusion groups at 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, and 48 h post-injury (n = 6 per group). The expression of 35 wound healing-related genes was explored in contused skeletal muscle by real-time polymerase chain reaction. Differences between the groups were assessed by partial least squares discriminant analysis (PLS-DA). The results show that the samples were classified into three groups by wound age (4-12, 16-24, and 28-48 h). A Fisher discriminant analysis model of 14 selected genes was constructed, and 94.9% cross-validated grouped cases were correctly classified. A PLS regression analysis using 14 genes showed reasonable internal predictive validity, with a root mean squared error of cross-validation of approximately 8 h. To examine whether the prediction models were capable of analyzing new (ungrouped) cases, an external validation was carried out using the expression data from an additional 30 rats. Approximately 76.7% of ungrouped cases were correctly classified, which was a lower proportion than that for cross-validation. Similarly, the prediction results of the PLS model showed lower relatively external predictive validity (root mean squared error of prediction = 11 h) than internal predictive validity. Although the prediction results were less accurate than expected, the gene expression modeling and multivariate analyses showed great potential for estimating injury time. These multivariate methods may be valuable when devising future wound time estimation strategies.

Vitality and wound-age estimation in forensic pathology: review and future prospects

Determining the age of a wound is challenging in forensic pathology, but it can contribute to the reconstruction of crime scenes and lead to arrest of suspects. Forensic scholars have tended to focus on evaluating wound vitality and determining the time elapsed since the wound was sustained. Recent progress in forensic techniques, particularly high-throughput analyses, has enabled evaluation of materials at the cellular and molecular levels, as well as simultaneous assessment of multiple markers. This paper provides an update on wound-age estimation in forensic pathology, summarizes the recent literature, and considers useful additional information provided by each marker. Finally, the future prospects for estimating wound age in forensic practise are discussed with the hope of providing something useful for further study.