Postmortem interval determination using 18S-rRNA and microRNA

A small RNA, microRNA as a potential biomolecular marker to estimate post mortem interval in forensic science: a systematic review

BACKGROUND

Post-mortem interval (PMI) is the cornerstone of the forensic field to investigate. The examination technique by seeing the changes in the body such as algor mortis, rigor mortis, and livor mortis is a traditional technique in which accuracy is influenced by many factors. A biomolecular technique that uses microRNA (miRNA) biomarkers is developing because miRNA has good stability than other RNA, so it meets the requirements to be used for PMI estimation.

METHOD

Following the PRISMA guidelines, journals were taken from 5 databases: Scopus, Science Direct, PubMed, Embase, and Springer. The review was carried out by two people. Inclusion criteria in this review are original research, published in the last 10 years, discussing miRNA as a biomarker for PMI estimation, and free full access. While exclusion criteria are not original research and not using English.

RESULT

Eighteen journals were reviewed in this study. The study was conducted using test animals (rats) and human samples with tissue sources taken from the liver, skeletal muscle, blood, bone, heart, skin, saliva, semen, brain, lung, vitreous humor, spleen, and kidney. miRNA expression levels after death showed different results based on miRNA target, tissue source, and others.

DISCUSSION

The results of each study are different due to the use of different types of miRNA targets and tissue sources. miRNA has great potential to estimate PMI in forensic science, but it is necessary to control the influencing factors to obtain an accurate conclusion.

The impact of RNA stability and degradation in different tissues to the determination of post-mortem interval: A systematic review

Postmortem interval (PMI) in legal medicine is extremely important for both criminal and civil cases, and several sorts of techniques have been recommended. This systematic review solely focuses on approaches linked to RNA analysis, instead of including all proposed methods for determining the PMI. The term PMI will be used in this review to indicate the time between a person's death and the postmortem examination of the body. We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Guidelines when conducting this systematic review. The majority of studies on various tissues at various time intervals at various temperatures are non-human, and just a small number are on humans. The results are then provided using various statistical approaches. To calculate the PMI, post-mortem RNA degradation was examined using several tissues. The result so obtained had an opposite polarity. While some studies show that RNA stability in various tissues remained constant for several days after death, the other group of studies showed evident RNA degradation over time post-mortem, which was significantly influenced by temperature and other agonal factors. These factors have an impact on the multi-parametric mathematical model of ante and post-mortem factors on RNA degradation, as well as its applicability and feasibility. The estimation of PMI using RNA degradation can prove to be highly objective and efficient after controlling for the various factors and challenges that pose the estimation of RNA in forensic samples difficult.

Post-mortem interval estimation using miRNAs of road traffic accident cases: A forensic molecular approach

In forensic examination accurate estimation of post-mortem interval (PMI) is a challenging task, particularly in the advanced stages of decomposition. The existing methods (algor mortis, livor mortis, rigor mortis, putrefaction etc) used for estimating PMI rely on analyzing the physical, biochemical, and metabolic changes that occur in the corpse after death. While these methods have shown some level of effectiveness in estimating PMI during the early stages of decomposition, accurate estimation becomes increasingly challenging during the later stages of putrefaction when the body undergoes significant changes. Recently, microRNA (miRNA) profiling due to its relatively small size and stability has emerged as a promising tool in several areas of forensics. This study demonstrates the potential of miRNA for PMI estimation in advanced stages of death. In this study, miRNA-195, miRNA-206, and miRNA-378 were selected as target miRNAs and miRNA-1 as reference miRNA. Left ventricle tissue (5 g) of the heart from 20 forensic autopsies of traffic accident victims (18-32 years) were collected and processed. The samples were held at room temperature for eight different time intervals (12, 24, 48, 72, 96, 120, 168 and 196 h), and RNA was extracted from all the samples using Trizol-based RNA isolation protocol, followed by cDNA synthesis and amplification with commercially available specific miRNA probes in Real-Time PCR (RT-PCR), Ct was calculated. The result showed that miRNAs were associated with PMI. Over time, there were substantial changes in the Ct values of all three miRNAs, with significant reductions observed at 196 h compared to 12 h. miRNA-206 demonstrated significant changes at multiple time intervals, while miRNA-1 remained stable for up to 196 h and thus holds caas an endogenous marker. In conclusion, miRNA has the potential to serve as a valuable tool for estimating PMI, especially during the advanced stages of decomposition, when used in conjunction with established techniques. However, further validation of the study is required to obtain more accurate estimates of PMI.

A miRNome analysis at the early postmortem interval

The postmortem interval (PMI) is the time elapsing since the death of an individual until the body is examined. Different molecules have been analyzed to better estimate the PMI with variable results. The miRNAs draw attention in the forensic field to estimate the PMI as they can better support degradation. In the present work, we analyzed the miRNome at early PMI in rats' skeletal muscle using the Affymetrix GeneChip™ miRNA 4.0 microarrays. We found 156 dysregulated miRNAs in rats' skeletal muscle at 24 h of PMI, out of which 84 were downregulated, and 72 upregulated. The miRNA most significantly downregulated was miR-139-5p (FC = -160, p = 9.97 × 10^-11), while the most upregulated was rno-miR-92b-5p (FC = 241.18, p = 2.39 × 10^-6). Regarding the targets of these dysregulated miRNAs, the rno-miR-125b-5p and rno-miR-138-5p were the miRNAs with more mRNA targets. The mRNA targets that we found in the present study participate in several biological processes such as interleukin secretion regulation, translation regulation, cell growth, or low oxygen response. In addition, we found a downregulation of SIRT1 mRNA and an upregulation of TGFBR2 mRNA at 24 h of PMI. These results suggest there is an active participation of miRNAs at early PMI which could be further explored to identify potential biomarkers for PMI estimation.

Correlation between postmortem microbial signatures and substance abuse disorders

The microbiota gut-brain-axis is a bidirectional circuit that links the neural, endocrine, and immunological systems with gut microbial communities. The gut microbiome plays significant roles in human mind and behavior, specifically pain perception, learning capacity, memory, and temperament. Studies have shown that disruptions in the gut microbiota have been associated with substance use disorders. The interplay of gut microbiota in substance abuse disorders has not been elucidated; however, postmortem microbiome profiles may produce promising avenues for future forensic investigations. The goal of the current study was to determine gut microbiome composition in substance abuse disorder cases using transverse colon tissues of 21 drug overdose versus 19 non-overdose-related cases. We hypothesized that postmortem samples of the same cause of death will reveal similar microbial taxonomic relationships. We compared microbial diversity profiles using amplicon-based sequencing of the 16S rRNA gene V4 hypervariable region. The results demonstrated that the microbial abundance in younger-aged cases were found to have significantly more operational taxonomic units than older cases. Using weighted UniFrac analysis, the influence of substances in overdose cases was found to be a significant factor in determining microbiome similarity. The results also revealed that samples of the same cause of death cluster together, showing a high degree of similarity between samples and a low degree of similarity among samples of different causes of death. In conclusion, our examination of human transverse colon microflora in decomposing remains extends emerging literature on postmortem microbial communities, which will ultimately contribute to advanced knowledge of human putrefaction.

MicroRNAs in Various Body Fluids and its importance in Forensic Medicine

MicroRNAs (miRNAs) are a class of noncoding RNAs which regulate gene expression. miRNAs have tissue-specific expression and are also present in various extracellular body fluids, including blood, tears, semen, vaginal fluid and urine. Additionally, expression of miRNAs in body fluids is linked to various pathological diseases, including cancer and neurodegenerative diseases. Examination of body fluids is important in forensic medicine as they serve as a valuable form of evidence. Due to its stability, miRNA offers an advantage for body fluid identification, which can be detected even after several months or from compromised samples. Identification of unique miRNA profiles for different body fluids enable the identification of these body fluid. Furthermore, miRNAs profiling can be used to estimate post-mortem interval. Various biochemical and molecular methods have been used for identification of miRNAs have shown promising results. We discuss different miRNAs as specific biomarkers and their clinical importance regarding different pathological conditions, as well as their medico-legal importance.

Innate immune stimulation prevents the development of anxiety-like behaviors in chronically stressed mice

Anxiety is a common psychological disease which can induce severe social burdens. Searching methods that prevent the onset of anxiety is of great significance for ameliorating the social and individual problems induced by this type of disease. In this study, we investigated how innate immune pre-stimulation influences the anxiety-like behaviors in chronically stressed mice. Our results showed that a single injection of an innate immune stimulant lipopolysaccharide (LPS) at the dose of 50, 100, and 500 μg/kg 1 day before stress exposure prevented chronic social defeat stress (CSDS)-induced anxiety-like behaviors in mice. A single injection of LPS (100 μg/kg) 5 days before stress exposure produced similar preventive effects on CSDS-induced anxiety-like behaviors, while similar effects were not observed at the condition of 10-days interval between LPS injection and stress exposure. A second LPS injection 10 days after the first LPS injection or a 4 × LPS injection 10 days before stress exposure also prevented CSDS-induced anxiety-like behaviors. Moreover, a single injection of LPS (100 μg/kg) 1 day before stress exposure prevented the production of pro-inflammatory cytokines in the hippocampus and prefrontal cortex of CSDS mice. Suppression of innate immune stimulation by minocycline pretreatment simultaneously abrogated the preventive effect of LPS pre-injection (100 μg/kg) on CSDS-induced anxiety-like behaviors and pro-inflammatory cytokine production in the brain. Our results demonstrated that the pre-stimulation of the innate immune system can prevent the development of anxiety-like behaviors and the progression of the neuroinflammatory responses in the brain in chronically stressed mice.

Dysregulation of miR-381-3p and miR-23b-3p in skeletal muscle could be a possible estimator of early post-mortem interval in rats

Background

The post-mortem interval (PMI) is the time elapsed since the dead of an individual until the body is found, which is relevant for forensic purposes. The miRNAs regulate the expression of some genes; and due to their small size, they can better support degradation, which makes them suitable for forensic analysis. In the present work, we evaluated the gene expression of miR-381-3p, miR-23b-3p, and miR-144-3p in skeletal muscle in a murine model at the early PMI.

Methods

We designed a rat model to evaluate the early PMI under controlled conditions. This model consisted in 25 rats divided into five groups of rats, that correspond to the 0, 3, 6, 12 and 24 hours of PMI. The 0 h-PMI was considered as the control group. Muscle samples were taken from each rat to analyze the expression of miR-381-3p, miR-23b-3p, and miR-144-3p by quantitative RT-PCR. The gene expression of each miRNA was expressed as Fold Change (FC) and compared among groups. To find the targets of these miRNAs and the pathways where they participate, we performed an in-silico analysis. From the gene targets of miR-381-3p identified in the silico analysis, the EPC1 gene was selected for gene expression analysis by quantitative RT-PCR in these samples. Also, to evaluate if miR-381-3p could predict the early PMI, a mixed effects model was calculated using its gene expression.

Results

An upregulation of miR-381-3p was found at 24 h-PMI compared with the control group of 0 h-PMI and (FC = 1.02 vs. FC = 1.96; p = 0.0079). This was the opposite for miR-23b-3p, which had a down-regulation at 24 h-PMI compared to 0 h-PMI (FC = 1.22 vs. FC = 0.13; p = 0.0079). Moreover, the gene expression of miR-381-3p increased throughout the first 24 h of PMI, contrary to miR-23b-3p. The targets of these two miRNAs, participate in biological pathways related to hypoxia, apoptosis, and RNA metabolism. The gene expression of EPC1 was found downregulated at 3 and 12 h of PMI, whereas it remained unchanged at 6 h and 24 h of PMI. Using a multivariate analysis, it was possible to predict the FC of miR-381-3p of all but 6 h-PMI analyzed PMIs.

Discussion

The present results suggest that miR-23b-3p and miR-381-3p participate at the early PMI, probably regulating the expression of some genes related to the autolysis process as EPC1 gene. Although the miR-381-3p gene expression is a potential estimator of PMI, further studies will be required to obtain better estimates.

MicroRNAs as Useful Tools to Estimate Time Since Death. A Systematic Review of Current Literature

Estimating the time of death remains the most challenging question in forensic medicine, because post-mortem interval (PMI) estimation can be a remarkably difficult goal to achieve. The aim of this review is to analyze the potential of microRNAs (miRNAs) to evaluate PMI. MiRNAs have been studied as hallmarks and biomarkers in several pathologies and have also showed interesting applications in forensic science, such as high sensible biomarkers in body fluid and tissue, for wound age determination and PMI evaluation due to their low molecular weight and tissue-specific expression. The present systematic review was carried out according to the Preferred Reporting Items for Systematic Review (PRISMA) standards. We performed an electronic search of PubMed, Science Direct Scopus, and Excerpta Medica Database (EMBASE) from the inception of these databases to 12 August 2020. The search terms were (“PMI miRNA” or “PMI micro RNA”) and (“miRNA” and “time of death”) in the title, abstract and keywords. Through analysis of scientific literature regarding forensic uses of miRNAs, has emerged that the intrinsic characteristics of such molecules, and their subsequent resistance to degradation, make them suitable as endogenous markers in order to determine PMI. However, further and larger studies with human samples and standardized protocols are still needed.

Evaluating the use of hypoxia sensitive markers for body fluid stain age prediction

To augment DNA profiling and body fluid identification techniques efforts are being made to increase the amount of information available from a crime scene stain, which includes efforts to identify externally visible characteristics through phenotypic analysis. A key question surrounding crime scene stains is the length of time between deposition of the stain and its subsequent recovery, in that is the stain recovered related to the incident in question or from a previously deposited stain number of weeks earlier? The inability to answer this fundamental question has a detrimental effect upon the successful completion of a criminal investigation. Once a body fluid leaves the body, the oxygen concentration in the environment changes; therefore, it may be that this change could cause a change in the expression of hypoxia-sensitive biomarkers. Here, a range of bloodstains, liquid saliva and liquid semen samples were collected at 0 days, 7 days, 14 days, 21 days and 28 days of degrading at room temperature (19-22 °C), before undergoing total RNA extraction and cDNA synthesis. Blood was recovered from filter paper with 3 mm², with saliva and semen being left in their tubes and swabbed at the appropriate times. All samples then underwent quantitative PCR targeting Vascular Endothelial Growth Factor A (VEGFA) and Hypoxia-Inducible Factor 1 Alpha (HIF1A), with B-Actin (ACTB) as a reference gene. A range of linear and quadratic correlation values was obtained from the qPCR data and used to develop a predictive model with a mean absolute deviation (MAD) of 4.2, 2.1, and 5 days for blood, saliva, and semen respectively. Blind testing indicated that a stain age prediction model based upon VEGFA with ACTB as a reference gene could be used on samples up to four weeks old with a margin of error ranging from 2 days through to 5 days. While a sizeable potential time frame exists using this model; this represents a significant step towards the target of having an accurate stain age prediction model.

Postmortem expression of apoptosis-related genes in the liver of mice and their use for estimation of the time of death

PURPOSE

A major challenge in forensic medicine is to estimate the postmortem interval (PMI). Several approaches had been tried to determine the time of death, including physical and chemical changes. This study aims to explore the postmortem changes in the expression of apoptosis-related genes in the liver of mice and to use these changes for estimation of the PMI.

METHODS

Hepatic tissue was collected from sacrificed mice immediately after death (the control group) and at 3, 6, 9, 12, 18, and 24 hours after death. Four apoptosisrelated genes were selected as target genes, which are Caspase 3 (Casp3), B cell leukemia/ lymphoma 2 (Bcl2), BCL2-associated X protein (Bax), and Transformation related protein 53 (Trp53), and their relative expression was measured using quantitative PCR. miR-122 was used as a reference gene for normalization of the Ct (threshold cycle) values of the target genes.

RESULTS

The results revealed that the postmortem expression of Casp3 increased in a time-dependent manner; the expression of Bax increased from 3 to 18 hours followed by a decrease at 24 hours after death; the expression of Bcl2 decreased in a time-dependent manner after death; the expression of Trp53 increased from 3 to 6 hours and then started to decrease from 9 to 24 hours after death.

CONCLUSION

Based on the observed changes in the expression level of these genes, mathematical models were established to estimate the PMI. Further research is needed to investigate these markers and mathematical models in human tissues.

Estimation of the post-mortem interval using microRNA in the bones

MicroRNAs (miRNAs) can be useful in forensic science because of their numerous characteristics, especially stability. Post-mortem interval (PMI) is crucial for death scene investigations. However, estimating PMI is challenging in cases involving significantly decomposed or destroyed bodies, such as those involving skeletonized remains. In this study, 71 bones (patella) were collected from the bodies during autopsies (PMI ranging from 1 day to 2 years). As the let-7e and miR-16 miRNAs were used as internal controls for the bone tissue in previous studies, these miRNAs were selected as targets to estimate PMI. The miRNA Ce_miR-39_1 was used as a spike-in internal control to normalize the target miRNA levels. Real-time quantitative reverse transcription polymerase chain reaction was performed to correlate the expression levels of let-7e and miR-16 with increasing PMI. A negative correlation was observed between miRNA expression and increasing PMI. The expression of both let-7e and miR-16 was observed to be significantly different between group A and the other PMI groups (group A < 1 month; 1 month < group B < 3 months; 3 months < group C < 6 months; group D > 6 months). In conclusion, these data suggest that the expression level of specific miRNAs (let-7e and miR-16) in the bone tissue could be used to estimate PMI. However, more studies using long-term PMI samples are required to further corroborate these findings.

Predicting postmortem interval based on microbial community sequences and machine learning algorithms

Microbes play an essential role in the decomposition process but were poorly understood in their succession and behaviour. Previous researches have shown that microbes show predictable behaviour that starts at death and changes during the decomposition process. Research of such behaviour enhances the understanding of decomposition and benefits estimating the postmortem interval (PMI) in forensic investigations, which is critical but faces multiple challenges. In this study, we combined microbial community characterization, microbiome sequencing from different organs (i.e. brain, heart and cecum) and machine learning algorithms [random forest (RF), support vector machine (SVM) and artificial neural network (ANN)] to investigate microbial succession pattern during corpse decomposition and estimate PMI in a mouse corpse system. Microbial communities exhibited significant differences between the death point and advanced decay stages. Enterococcus faecalis, Anaerosalibacter bizertensis, Lactobacillus reuteri, and so forth were identified as the most informative species in the decomposition process. Furthermore, the ANN model combined with the postmortem microbial data set from the cecum, which was the best combination among all candidates, yielded a mean absolute error of 1.5 ± 0.8 h within 24-h decomposition and 14.5 ± 4.4 h within 15-day decomposition. This integrated model can serve as a reliable and accurate technology in PMI estimation.

Postmortem interval determination using mRNA markers and DNA normalization

Postmortem interval (PMI) determination is an important part of criminal investigations, but it is still subject to uncertainty. Degradation of mRNA in PMI determination has been studied in decays; however, some studies have reported no correlation between PMI and RNA degradation. Thus, we aimed to determine whether RNA quantity was correlated with PMI. Heart and brain tissues were separated from a mouse model of a 0-48 h PMI with 29 time points. We then coextracted the DNA and RNA in one tube with Bioteke coextraction kits and selected some mRNA markers associated with cell oxygen deprivation and apoptosis as target genes, such as hypoxia-associated factor (HAF), apoptosis-inducing factor (AIF), hypoxia-inducible factor 2 alpha (HIF2a), and factor inhibiting HIF (FIH). We measured the quantity of these markers using real-time quantitative PCR (qPCR), and Caspase-3 DNA and 18S were each used for normalization. The results showed that in the heart tissue, the degradation of HIF2a, AIF, and FIH was correlated with PMI, as was the degradation of HIF2a, FIH, and AIF in brain tissue when normalized with Caspase-3 DNA. However, when normalized with 18S, only the degradation of HIF2a in brain tissue was correlated with PMI. Interestingly, the quantity of HAF in brain tissue was found to increase after death with either 18S or Caspase-3 DNA normalization, and it was significantly correlated with 0-48 h PMI. These results indicated that mRNA quantity can be used to determine PMI and that Caspase-3 DNA is feasible for PMI estimation. In summary, we established mathematical models for PMI determination using multiple mRNA markers and multiple tissues and further studies are needed to validate and investigate these markers and mathematical models in human tissues.Duo Peng and Meili Lv contributed equally to this work.

Early postmortem interval (EPMI) estimation using differentially expressed gene transcripts

Genes differentially expressed after death were selected to construct a mathematical model for early postmortem interval estimation. Sprague Dawley rats were sacrificed and placed at temperatures of 4 °C, 15 °C, 25 °C, and 35 °C. Brain tissues were collected at 0, 6, 12, 18, and 24 h after death and total RNA was extracted. Changes in gene transcript levels after death were detected using microarray expression profiling and differentially expressed genes was screened. Expanded experiments were performed to validate gene transcript levels at different temperatures using the reverse transcription real-time quantitative polymerase chain reaction. Six genes with high coefficients of determination were chosen for construction of mathematical models. Optimal ternary cubic equations were built using R software with temperature, postmortem interval and ΔCq defined as the independent variable x, y and z, respectively. Equations were converted into a three-dimensional visual statistical model using MATLAB. Animal samples were used to validate the mathematical models. Results showed that the 5srRNA showed best stability at four temperatures. The genes Ninj2, Grifin, Arpp19, and Hopx showed high coefficients of determination (>80%) and low error (<3h) in verification experiments which indicate that they are potential markers for early postmortem interval estimation.

Using miRNAs and circRNAs to estimate PMI in advanced stage

In our previous study, we evaluated the stability of multi-RNA markers in heart, liver and skeletal muscle tissues of mice within 8 days after death and concluded that microRNAs (miRNAs) and circular (circRNAs) were more stable as reference genes in dead bodies than other kinds of RNAs. Based on their tissue-specific expression, we obtained reference genes for three kinds of tissues: miR-122, miR-133a and 18S in heart tissues; LC-Ogdh, circ-AFF1 and miR-122 in liver tissues; and miR-133a, circ-AFF1 in skeletal muscle tissues. For the estimation of post mortem interval (PMI), we also selected suitable biomarkers, which exhibited the best correlation coefficient with PMI. In our stability analysis of multi-RNA markers, Gapdh, Rps18, U6 and β-actin were unstable and selected as candidate target biomarkers. By analyzing the correlation between the expression levels of candidate target biomarkers and PMI, we obtained suitable target biomarkers for the three kinds of tissues, respectively. Finally, we established mathematical models of PMI estimation using the above selected reference genes and target biomarkers. The low estimated error in the validated samples demonstrated that PMI in advanced stage could be accurately predicted by real-time quantitative polymerase chain reaction (qPCR) through systematically selected effective reference genes and target biomarkers. Besides, combining the estimated results of various tissues and multi-biomarkers could improve the accuracy of PMI estimation.

Early postmortem interval estimation based on Cdc25b mRNA in rat cardiac tissue

PURPOSE

The postmortem interval (PMI) is the amount of time that has elapsed since the time of death. Over the years, many approaches have been developed to assess PMI, but their time frame of applicability has been only days to weeks. Our present pilot study aimed to find the sensitive mRNA marker if the degradation of mRNA could be used to estimate the early postmortem interval (up to 24 h).

METHODS

In our study, we use the microarray to screen 217 mRNAs markers of rat cardiac tissue. Then, real-time fluorescent quantitative PCR (qPCR) was used to validate of the candidate markers at 7 time points within 24 h and at temperatures of 25 °C and 35 °C. Another 27 rats were then used to verify the model.

RESULTS

Among all of the candidate markers, △Cq (cell division cycle 25 homolog B(Cdc25b)) had the best correlation coefficient with early postmortem interval and was used to build a new model using the R software. The results of verification testing demonstrated that the error rate was less than 15%, demonstrating the high predictive power of our mathematical model.

CONCLUSION

In this study, Cdc25b was found to be the sensitive marker to estimate early postmortem interval, and Rpl27 was found to be suitable for use as the endogenous control. Our work provided new leads for molecular approaches to early postmortem interval estimation using the significant mRNA markers established here.

Bias in recent miRBase annotations potentially associated with RNA quality issues

Although microRNAs are supposed to be stable in-vivo, degradation processes potentially blur our knowledge on the small oligonucleotides. We set to quantify the effect of degradation on microRNAs in mouse to identify causes for distorted microRNAs patterns. In liver, we found 298, 99 and 8 microRNAs whose expression significantly correlated to RNA integrity, storage time at room temperature and storage time at 4 °C, respectively. Expression levels of 226 microRNAs significantly differed between liver samples with high RNA integrity compared to liver samples with low RNA integrity by more than two-fold. Especially the 157 microRNAs with increased expression in tissue samples with low RNA integrity were most recently added to miRBase. Testing potentially confounding sources, e.g. in-vitro degraded RNA depleted of small RNAs, we detected signals for 350 microRNAs, suggesting cross-hybridization of fragmented RNAs. Therefore, we conclude that especially microRNAs added in the latest miRBase versions might be artefacts due to RNA degradation. The results facilitate differentiation between degradation-resilient microRNAs, degradation-sensitive microRNAs, and likely erroneously annotated microRNAs. The latter were largely identified by NGS but not experimentally validated and can severely bias microRNA biomarker research and impact the value of microRNAs as diagnostic, prognostic or therapeutic tools.

Cell Death-Associated Ribosomal RNA Cleavage in Postmortem Tissues and Its Forensic Applications

Estimation of postmortem interval (PMI) is a key issue in the field of forensic pathology. With the availability of quantitative analysis of RNA levels in postmortem tissues, several studies have assessed the postmortem degradation of constitutively expressed RNA species to estimate PMI. However, conventional RNA quantification as well as biochemical and physiological changes employed thus far have limitations related to standardization or normalization. The present study focuses on an interesting feature of the subdomains of certain RNA species, in which they are site-specifically cleaved during apoptotic cell death. We found that the D8 divergent domain of ribosomal RNA (rRNA) bearing cell death-related cleavage sites was rapidly removed during postmortem RNA degradation. In contrast to the fragile domain, the 5' terminal region of 28S rRNA was remarkably stable during the postmortem period. Importantly, the differences in the degradation rates between the two domains in mammalian 28S rRNA were highly proportional to increasing PMI with a significant linear correlation observed in mice as well as human autopsy tissues. In conclusion, we demonstrate that comparison of the degradation rates between domains of a single RNA species provides quantitative information on postmortem degradation states, which can be applied for the estimation of PMI.

Characterization of postmortem biochemical changes in rabbit plasma using ATR-FTIR combined with chemometrics: A preliminary study

Postmortem interval (PMI) determination is one of the most challenging tasks in forensic medicine due to a lack of accurate and reliable methods. It is especially difficult for late PMI determination. Although many attempts with various types of body fluids based on chemical methods have been made to solve this problem, few investigations are focused on blood samples. In this study, we employed an attenuated total reflection (ATR)-Fourier transform infrared (FTIR) technique coupled with principle component analysis (PCA) to monitor biochemical changes in rabbit plasma with increasing PMI. Partial least square (PLS) model was used based on the spectral data for PMI prediction in an independent sample set. Our results revealed that postmortem chemical changes in compositions of the plasma were time-dependent, and various components including proteins, lipids and nucleic acids contributed to the discrimination of the samples at different time points. A satisfactory prediction within 48h postmortem was performed by the combined PLS model with a good fitting between actual and predicted PMI of 0.984 and with an error of ±1.92h. In consideration of the simplicity and portability of ATR-FTIR, our preliminary study provides an experimental and theoretical basis for application of this technique in forensic practice.

Research progress in the estimation of the postmortem interval by Chinese forensic scholars

The determination of time since death or the postmortem interval (PMI) is one of the most important and frequently asked questions in forensic medicine. Medicolegal scholars and forensic pathologists around the world have studied the estimation of PMI extensively in the past, and many novel methods and advanced technologies have now been applied in the field. For several centuries, Chinese forensic examiners have also worked on the estimation of the PMI, and there are a large number of excellent studies published in Chinese rather than in English, and these are not easily accessible or known internationally. Therefore we have conducted a review of relevant studies published by Chinese forensic scholars in the last few decades. The scope of this review is to provide a concise summary of the current progress in the estimation of PMI by Chinese forensic researchers using molecular biology, spectroscopic technology, entomological methods, energy changes, thanatochemistry and other methods.

Integrated microRNA and messenger RNA analysis in aortic stenosis

Aortic valve stenosis (AS) is a major cause of morbidity and mortality, with no effective medical therapies. Investigation into the underlying biology of AS in humans is limited by difficulties in obtaining healthy valvular tissue for use as a control group. However, micro-ribonucleic acids (miRNAs) are stable in post-mortem tissue. We compared valve specimens from patients undergoing aortic valve replacement for AS to non-diseased cadaveric valves. We found 106 differentially expressed miRNAs (p < 0.05, adjusted for multiple comparisons) on microarray analysis, with highly correlated expression among up- and down-regulated miRNAs. Integrated miRNA/gene expression analysis validated the microarray results as a whole, while quantitative polymerase chain reaction confirmed downregulation of miR-122-5p, miR-625-5p, miR-30e-5p and upregulation of miR-21-5p and miR-221-3p. Pathway analysis of the integrated miRNA/mRNA network identified pathways predominantly involved in extracellular matrix function. A number of currently available therapies target products of upregulated genes in the integrated miRNA/mRNA network, with these genes being predominantly more peripheral members of the network. The identification of a group of tissue miRNA associated with AS may contribute to the development of new therapeutic approaches to AS. This study highlights the importance of systems biology-based approaches to complex diseases.

Exploration of the R code-based mathematical model for PMI estimation using profiling of RNA degradation in rat brain tissue at different temperatures

Precise estimation of postmortem interval (PMI) is crucial in some criminal cases. This study aims to find some optimal markers for PMI estimation and build a mathematical model that could be used in various temperature conditions. Different mRNA and microRNA markers in rat brain samples were detected using real-time fluorescent quantitative PCR at 12 time points within 144 h postmortem and at temperatures of 4, 15, 25, and 35 °C. Samples from 36 other rats were used to verify the animal mathematical model. Brain-specific mir-9 and mir-125b are effective endogenous control markers that are not affected by PMI up to 144 h postmortem under these temperatures, whereas the commonly used U6 is not a suitable endogenous control in this study. Among all the candidate markers, ΔCt (β-actin) has the best correlation coefficient with PMI and was used to build a new model using R software which can simultaneously manage both PMI and temperature parameters. This animal mathematical model is verified using samples from 36 other rats and shows increased accuracy for higher temperatures and longer PMI. In this study, β-actin was found to be an optimal marker to estimate PMI and some other markers were found to be suitable to act as endogenous controls. Additionally, we have used R code software to build a model of PMI estimation that could be used in various temperature conditions.

The complete mitochondria genome of Parasarcophaga similis (Diptera: Sarcophagidae)

The complete mitochondrial genome of Parasarcophaga similis collected from China was determined using PCR reactions. The mitogenome was 15,158 bp in length with a total A + T content of 76.4%, consisting of 22 transfer RNA genes, 13 protein-coding genes, 2 ribosomal RNA genes and a control region. The gene contents of the mitogenome were identical to those observed in other insects. The overall base compositions of A, G, C and T were 39.54%, 9.43%, 14.20% and 36.83%, respectively. This paper aimed to improve and perfect dipteran mitochondrial genomes and provided the first complete mitochondrial genome of Parasarcophaga similis for entomologists as a potential tool for application of phylogenetic analysis and forensic entomology.