Forensic Sci Med Pathol
March 2017
In our previous study, a R code-based mathematical model using RNA degradation patterns was developed for PMI determination in rat brain specimens. However, the postmortem changes of RNA are much more complicated in real cases, and there is still a huge challenge in efficiently applying information in animal data to real cases. In the present study, different RNA markers in both rat and human tissues were collected to screen valid biomarkers and the corresponding mathematical models were established and validated.
View Article and Find Full Text PDFJ Forensic Leg Med
November 2016
The importance of determining postmortem interval (PMI) is crucial to criminal, civil and forensic cases. The precise estimation of PMI is a critical step in many death investigations. A technique exploiting the level of RNA, 18S rRNA and microRNA to estimate PMI was investigated.
View Article and Find Full Text PDFDetermining the postmortem interval (PMI) is important in criminal, civil, and forensic cases. We examined the feasibility of using the transcript abundances of mRNAs, 18S rRNA, U6 snRNA, and microRNAs as a means to estimate the PMI. We removed spleen tissues from rats at different PMIs under 4°C or 25°C and examined gene transcript abundances in these samples by RT-qPCR.
View Article and Find Full Text PDFPrecisely determining the postmortem interval (PMI), which is crucial to criminal and forensic cases, is a research in which quantitative RT-PCR (also known as qRT-PCR or real-time RT-PCR) has been used to analyse gene expression levels and data normalisation should be required to eliminate the differences among the samples. Therefore, it is quite necessary to find stable molecular biological markers in PMI determination research. In this study, we compared nine commonly used endogenous markers (containing ACTB, GAPDH, B2M, U6, 18S rRNA, hsa-mir-1, hsa-mir-9, hsa-mir-194-1 and hsa-mir-203) in the 109 human tissue samples obtained from autopsy at the aim of finding stable markers in human tissues with consideration of the impact of parameters (PMI and cause of death).
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