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Profiling of RNA Degradation for Estimation of Post Morterm Interval

An estimation of the post mortem interval (PMI) is frequently touted as the Holy Grail of forensic pathology. During the first hours after death, PMI estimation is dependent on the rate of physical observable modifications including algor, rigor and livor mortis. However, these assessment methods ar...

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Autores principales: Sampaio-Silva, Fernanda, Magalhães, Teresa, Carvalho, Félix, Dinis-Oliveira, Ricardo Jorge, Silvestre, Ricardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3577908/
https://www.ncbi.nlm.nih.gov/pubmed/23437149
http://dx.doi.org/10.1371/journal.pone.0056507
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author Sampaio-Silva, Fernanda
Magalhães, Teresa
Carvalho, Félix
Dinis-Oliveira, Ricardo Jorge
Silvestre, Ricardo
author_facet Sampaio-Silva, Fernanda
Magalhães, Teresa
Carvalho, Félix
Dinis-Oliveira, Ricardo Jorge
Silvestre, Ricardo
author_sort Sampaio-Silva, Fernanda
collection PubMed
description An estimation of the post mortem interval (PMI) is frequently touted as the Holy Grail of forensic pathology. During the first hours after death, PMI estimation is dependent on the rate of physical observable modifications including algor, rigor and livor mortis. However, these assessment methods are still largely unreliable and inaccurate. Alternatively, RNA has been put forward as a valuable tool in forensic pathology, namely to identify body fluids, estimate the age of biological stains and to study the mechanism of death. Nevertheless, the attempts to find correlation between RNA degradation and PMI have been unsuccessful. The aim of this study was to characterize the RNA degradation in different post mortem tissues in order to develop a mathematical model that can be used as coadjuvant method for a more accurate PMI determination. For this purpose, we performed an eleven-hour kinetic analysis of total extracted RNA from murine's visceral and muscle tissues. The degradation profile of total RNA and the expression levels of several reference genes were analyzed by quantitative real-time PCR. A quantitative analysis of normalized transcript levels on the former tissues allowed the identification of four quadriceps muscle genes (Actb, Gapdh, Ppia and Srp72) that were found to significantly correlate with PMI. These results allowed us to develop a mathematical model with predictive value for estimation of the PMI (confidence interval of ±51 minutes at 95%) that can become an important complementary tool for traditional methods.
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spelling pubmed-35779082013-02-22 Profiling of RNA Degradation for Estimation of Post Morterm Interval Sampaio-Silva, Fernanda Magalhães, Teresa Carvalho, Félix Dinis-Oliveira, Ricardo Jorge Silvestre, Ricardo PLoS One Research Article An estimation of the post mortem interval (PMI) is frequently touted as the Holy Grail of forensic pathology. During the first hours after death, PMI estimation is dependent on the rate of physical observable modifications including algor, rigor and livor mortis. However, these assessment methods are still largely unreliable and inaccurate. Alternatively, RNA has been put forward as a valuable tool in forensic pathology, namely to identify body fluids, estimate the age of biological stains and to study the mechanism of death. Nevertheless, the attempts to find correlation between RNA degradation and PMI have been unsuccessful. The aim of this study was to characterize the RNA degradation in different post mortem tissues in order to develop a mathematical model that can be used as coadjuvant method for a more accurate PMI determination. For this purpose, we performed an eleven-hour kinetic analysis of total extracted RNA from murine's visceral and muscle tissues. The degradation profile of total RNA and the expression levels of several reference genes were analyzed by quantitative real-time PCR. A quantitative analysis of normalized transcript levels on the former tissues allowed the identification of four quadriceps muscle genes (Actb, Gapdh, Ppia and Srp72) that were found to significantly correlate with PMI. These results allowed us to develop a mathematical model with predictive value for estimation of the PMI (confidence interval of ±51 minutes at 95%) that can become an important complementary tool for traditional methods. Public Library of Science 2013-02-20 /pmc/articles/PMC3577908/ /pubmed/23437149 http://dx.doi.org/10.1371/journal.pone.0056507 Text en © 2013 Sampaio-Silva et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Sampaio-Silva, Fernanda
Magalhães, Teresa
Carvalho, Félix
Dinis-Oliveira, Ricardo Jorge
Silvestre, Ricardo
Profiling of RNA Degradation for Estimation of Post Morterm Interval
title Profiling of RNA Degradation for Estimation of Post Morterm Interval
title_full Profiling of RNA Degradation for Estimation of Post Morterm Interval
title_fullStr Profiling of RNA Degradation for Estimation of Post Morterm Interval
title_full_unstemmed Profiling of RNA Degradation for Estimation of Post Morterm Interval
title_short Profiling of RNA Degradation for Estimation of Post Morterm Interval
title_sort profiling of rna degradation for estimation of post morterm interval
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3577908/
https://www.ncbi.nlm.nih.gov/pubmed/23437149
http://dx.doi.org/10.1371/journal.pone.0056507
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