Forensic aspects of gene expression signatures for age determination in bruises as evaluated in an experimental porcine model

The time-dependent expression of FPR2 and ANXA1 in murine deep vein thrombosis model and its relation to thrombus age

Thrombus age determination in fatal venous thromboembolism cases is an important task for forensic pathologists. In this study, we investigated the time-dependent expressions of formyl peptide receptor 2 (FPR2) and Annexin A1 (ANXA1) in a stasis-induced deep vein thrombosis (DVT) murine model, with the aim of obtaining useful information for thrombus age timing. A total of 75 ICR mice were randomly classified into thrombosis group and control group. In thrombosis group, a DVT model was established by ligating the inferior vena cava (IVC) of mice, and thrombosed IVCs were harvested at 1, 3, 5, 7, 10, 14, and 21 days after modeling. In control group, IVCs without thrombosis were taken as control samples. The expressions of FPR2 and ANXA1 during thrombosis were detected using immunohistochemistry and double immunofluorescence staining. Their protein and mRNA levels in the samples were determined by Western blotting and quantitative real-time PCR. The results reveal that FPR2 was predominantly expressed by intrathrombotic neutrophils and macrophages. ANXA1 expression in the thrombi was mainly distributed in neutrophils, endothelial cells of neovessels, and fibroblastic cells. After thrombosis, the expressions of FPR2 and ANXA1 were time-dependently up-regulated. The percentage of FPR2-positive cells and the level of FPR2 protein significantly elevated at 1, 3, 5 and 7 days after IVC ligation as compared to those at 10, 14 and 21 days after ligation (p < 0.05). Moreover, the mRNA level of FPR2 were significantly higher at 5 days than that at the other post-ligation intervals (p < 0.05). Besides, the levels of ANXA1 mRNA and protein peaked at 10 and 14 days after ligation, respectively. A significant increase in the mRNA level of ANXA1 was found at 10 and 14 days as compared with that at the other post-ligation intervals (p < 0.01). Our findings suggest that FPR2 and ANXA1 are promising as useful markers for age estimation of venous thrombi.

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.

Artificial intelligence in forensic medicine and related sciences - selected issues

Aim

The aim of the work is to provide an overview of the potential application of artificial intelligence in forensic medicine and related sciences, and to identify concerns related to providing medico-legal opinions and legal liability in cases in which possible harm in terms of diagnosis and/or treatment is likely to occur when using an advanced system of computer-based information processing and analysis.

Material and methods

The material for the study comprised scientific literature related to the issue of artificial intelligence in forensic medicine and related sciences. For this purpose, Google Scholar, PubMed and ScienceDirect databases were searched. To identify useful articles, such terms as "artificial intelligence," "deep learning," "machine learning," "forensic medicine," "legal medicine," "forensic pathology" and "medicine" were used. In some cases, articles were identified based on the semantic proximity of the introduced terms.

Conclusions

Dynamic development of the computing power and the ability of artificial intelligence to analyze vast data volumes made it possible to transfer artificial intelligence methods to forensic medicine and related sciences. Artificial intelligence has numerous applications in forensic medicine and related sciences and can be helpful in thanatology, forensic traumatology, post-mortem identification examinations, as well as post-mortem microscopic and toxicological diagnostics. Analyzing the legal and medico-legal aspects, artificial intelligence in medicine should be treated as an auxiliary tool, whereas the final diagnostic and therapeutic decisions and the extent to which they are implemented should be the responsibility of humans.

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.

Early immune responses in skin and lymph node after skin delivery of Toll-like receptor agonists in neonatal and adult pigs

The skin is potentially an important vaccine delivery route facilitated by a high number of resident antigen presenting cells (APCs), which are known to be stimulated by different Toll-like receptor agonists (TLRa). In this study, neonatal and adult pigs were vaccinated in the skin using dissolving microneedle patches to investigate the immuno-stimulatory potential of different TLRa and possible age-dependent differences early after vaccination. These patches contained TLR1/2a (Pam3Cys), TLR7/8a (R848) or TLR9a (CpG ODN) combined with inactivated porcine reproductive and respiratory syndrome virus (PRRSV) or with an oil-in-water stable emulsion. Vaccinated skin and draining lymph nodes were analysed for immune response genes using microfluidic high-throughput qPCR to evaluate the early immune response and activation of APCs. Skin pathology and immunohistochemistry were used to evaluate the local immune responses and APCs in the vaccinated skin, respectively. In both neonatal and adult pigs, skin vaccination with TLR7/8a induced the most prominent early inflammatory and immune cell responses, particularly in the skin. Skin histopathology and immunohistochemistry of APCs showed comparable results for neonatal and adult pigs after vaccination with the different TLRa vaccines. However, in vaccinated neonatal pigs in the skin and draining lymph node more immune response related genes were upregulated compared to adult pigs. We showed that both neonatal and adult skin could be stimulated to develop an immune response, particularly after TLR7/8a vaccination, with age-dependent differences in regulation of immune genes. Therefore, age-dependent differences in local early immune responses should be considered when developing skin vaccines.

Insight into molecular profile changes after skeletal muscle contusion using microarray and bioinformatics analyses

Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. The present study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process. A total of 33 rats were divided randomly into control (n=3), mild contusion (n=15), and severe contusion (n=15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n=3 per subgroup). A total of 2844 and 2298 differentially expressed genes (DEGs) were identified using microarray analyses in the mild and severe contusions, respectively. From the analysis of the 1620 coexpressed genes in mildly and severely contused muscle, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. The functional analyses of genes in the functional modules and temporal clusters were performed, and the hub genes in each module-cluster pair were identified. Interestingly, we found that genes down-regulated at 24-48 h were largely associated with metabolic processes, especially of the oxidative phosphorylation (OXPHOS), which has been rarely reported. These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

Bruise dating using deep learning

The bruise dating can have important medicolegal implications in family violence and violence against women cases. However, studies show that the medical specialist has 50% accuracy in classifying a bruise by age, mainly due to the variability of the images and the color of the bruise. This research proposes a model, based on deep convolutional neural networks, for bruise dating using only images, by age ranges, ranging from 0-2 days to 17-30 days, and images of healthy skin. A 2140 experimental bruise photograph dataset was constructed, for which a data capture protocol and a preprocessing procedure are proposed. Similarly, 20 classification models were trained with the Inception V3, Resnet50, MobileNet, and MnasNet architectures, where combinations of learning transfer, cross-validation, and data augmentation were used. Numerical experiments show that classification models based on MnasNet have better results, reaching 97.00% precision and sensitivity, and 99.50% specificity, exceeding 40% precision reported in the literature. Also, it was observed that the precision of the model decreases with the age of the bruise.

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.

Optimising the sampling procedure for forensic investigation of bruises on pigs

BACKGROUND

Human-inflicted bruises on pigs are a violation of the law and affected tissue is regularly sent for forensic investigation. The authors aimed to evaluate the variation in inflammation within and between human-inflicted porcine bruises in order to determine the optimal sampling procedure.

METHODS

Skin and muscle tissues from the centre and ends of 21 bruises were evaluated histologically. Moreover, RNA was extracted from the subcutaneous fat tissue. The bruises were detected during meat inspection at the slaughter line, and all carcases were kept at 5°C for 12-24 hours before sampling.

RESULTS

The sampling site with the most infiltration of neutrophils and macrophages differed between bruises inflicted on the same pig and between bruises inflicted on more pigs within the same delivery. The extracted RNA had RIN (RNA integrity number) values from 3 to 6.5.

CONCLUSIONS

Tissue samples should always be taken from both skin and underlying muscle tissue. Samples should be collected from several sites along each bruise, and all bruises should be sampled in order to include the site of maximum tissue damage and inflammation. Moreover, RNA of sufficient quality for quantitative PCR and subsequent age estimation cannot be obtained from carcases kept for 12-24 hours at 5°C.

Prenatal Intra-Amniotic Endotoxin Induces Fetal Gut and Lung Immune Responses and Postnatal Systemic Inflammation in Preterm Pigs

Prenatal inflammation is a major risk for preterm birth and neonatal morbidity, but its effects on postnatal immunity and organ functions remain unclear. Using preterm pigs as a model for preterm infants, we investigated whether prenatal intra-amniotic (IA) inflammation modulates postnatal systemic immune status and organ functions. Preterm pigs exposed to IA lipopolysaccharide (LPS) for 3 days were compared with controls at birth and postnatal day 5 after formula feeding. IA LPS induced mild chorioamnionitis but extensive intra-amniotic inflammation. There were minor systemic effects at birth (increased blood neutrophil counts), but a few days later, prenatal LPS induced delayed neonatal arousal, systemic inflammation (increased blood leukocytes, plasma cytokines, and splenic bacterial counts), altered serum biochemistry (lower albumin and cholesterol and higher iron and glucose values), and increased urinary protein and sodium excretion. In the gut and lungs, IA LPS-induced inflammatory responses were observed mainly at birth (increased LPS, CXCL8, and IL-1β levels and myeloperoxidase-positive cell density, multiple increases in innate immune gene expressions, and reduced villus heights), but not on postnatal day 5 (except elevated lung CXCL8 and diarrhea symptoms). Finally, IA LPS did not affect postnatal gut brush-border enzymes, hexose absorption, permeability, or sensitivity to necrotizing enterocolitis on day 5. Short-term IA LPS exposure predisposes preterm pigs to postnatal systemic inflammation after acute fetal gut and lung inflammatory responses.

The intensity of the inflammatory response in experimental porcine bruises depends on time, anatomical location and sampling site

The assessment of the age of bruises inflicted on livestock is an important component of veterinary forensic pathology investigations. However, the sampling site within a bruise, the anatomical location and the mass and speed of the object inflicting the blunt trauma might influence the intensity of the inflammatory reaction. In the present study, the variation of the inflammatory reaction within and along experimental porcine bruises was evaluated in order to determine the optimal sampling site. Moreover, we evaluated if a combination of histological characteristics and gene expression signatures was able to differentiate bruises according to anatomical location, age of bruises and the speed and mass of the object used to cause the impact. Twelve experimental slaughter pigs were anesthetized, and on each animal four blunt traumas were inflicted on the back using either a plastic tube or an iron bar, respectively. The pigs were euthanized at 2, 5 or 8 h after infliction. Following gross examination, skin and underlying muscle tissue were sampled from the center and both ends of bruises and evaluated histologically. Subcutaneous fat tissue from the center of the bruises was sampled for quantitative real-time polymerase chain reaction to evaluate mRNA expression of 13 selected genes. Uninjured tissue was sampled from the right thigh of all pigs and served as control tissue. The amount of tissue damage and the intensity of the inflammatory reaction in bruises depended on the sampling site within and along a bruise, the anatomical location and the age of the bruise. The optimal site for sampling, i.e. the most pronounced inflammatory reaction, was at the center of the bruises where the plastic tube or iron bar first struck the skin. Moreover, bruises inflicted in areas with a thin layer of subcutaneous fat tissue showed more damage and inflammation in the underlying muscle tissue compared to bruises inflicted in areas with a thicker layer of subcutaneous fat tissue. In addition, hemorrhage in the muscle tissue was more likely present when bruises were inflicted with an iron bar compared to a plastic tube. Combining histology and mRNA expression of the 13 genes showed that the age of bruises could be determined with a precision of ±2.04 h. Moreover, the age of bruises could be determined with a precision of ±1.84 h based solely on mRNA expression of a selection of four genes.