Profiling of RNA Degradation for Estimation of <em>Post Morterm</em> Interval

<div><p>An estimation of the <i>post mortem</i> 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 <i>algor</i>, <i>rigor</i> and <i>livor mortis</i>. 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 <i>post mortem</i> 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 (<i>Actb</i>, <i>Gapdh</i>, <i>Ppia</i> and <i>Srp72</i>) 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.</p> </div

Six genes (<i>Alb</i>, <i>Actb</i>, <i>Gapdh</i>, <i>Ppia</i>, <i>Cyp2E1</i> and <i>Srp72</i>) in two tissues (femoral quadriceps and liver) identified to significantly correlate with the <i>post mortem</i> interval.

<p>The normalized expression levels of these genes analyzed by quantitative real time PCR is plotted against the PMI in the femoral quadriceps (A) and liver (B). One representative experiment out of 15 is depicted.</p

A mathematical model for the accurate estimation of the PMI.

<p>The two equations represent the formula to calculate the PMI with a confidence interval of 95% (A) and the standard deviation (B), where () is the average signal for our sample, <i>K</i> is the number of replicate samples used to establish , <i>n</i> is the number of measured endpoint times, is the average signal for each endpoint time, is the summation of (individual <i>x</i>−)².</p

Murine genes targeted for quantitative analysis.

<p>Murine genes targeted for quantitative analysis.</p

Loss of RNA integrity from heart, femoral quadriceps and liver tissue samples significantly correlate with the <i>post mortem</i> interval.

<p>The degradation profile of total RNA recovered from heart (A), femoral quadriceps (B) and liver (C) tissue samples was evaluated at different time periods <i>post mortem</i> (0–11 h) by RNA electrophoresis (Experion®). For each tissue, the RNA quality indicator (RQI) is plotted against the <i>post mortem</i> interval (L – single strand RNA ladder). Pearson correlation (r) and <i>p</i> value are depicted for each organ. One representative experiment out of 15 is shown.</p

Pearson correlation (r) and <i>p</i> values of linear regression for each gene in the tested organs.

<p>Bold highlights Pearson correlations between gene decay and PMI higher than 0.900 and found to be statistically significant.</p

Representative histological images of renal cell carcinoma.

<p>(A) Clear cell renal cell carcinoma, and (B) chromophobe renal cell carcinoma.</p

Schematic representation of the isolation procedure for HPTEC and HRTC.

<p>Schematic representation of the isolation procedure for HPTEC and HRTC.</p

Representative morphology of confluent monolayers.

<p>(A) Primary HPTEC, (B) HK-2 cell line, (C) primary clear cell RCC, and (D) primary chromophobe RCC. Magnification: 400x.</p

Study of the potential toxicity of adrenaline to neurons, using the SH-SY5Y human cellular model

Abstract Prolonged overexposure to catecholamines causes toxicity, usually credited to continuous adrenoceptor stimulation, autoxidation, and the formation of reactive pro-oxidant species. Non-differentiated SH-SY5Y cells were used to study the possible contribution of oxidative stress in adrenaline (ADR)-induced neurotoxicity, as a model to predict the toxicity of this catecholamine to peripheral nerves. Cells were exposed to several concentrations of ADR (0.1, 0.25, 0.5 and 1mM) and two cytotoxicity assays [lactate dehydrogenase (LDH) release and 3-(4,5-dimethylthiazol-2yl)-2,5-diphenyl tetrazolium bromide (MTT) reduction] were performed at several time-points (24, 48, and 96h). The cytotoxicity of ADR was concentration- and time-dependent in both assays, since the lowest concentration tested (0.1mM) also caused significant cytotoxicity at 96h. N-acetyl-cysteine (1mM), a precursor of glutathione synthesis, prevented ADR-induced toxicity elicited by 0.5mM and 0.25mM ADR following a 96-h exposure, while the antioxidant Tiron (100µM) was non-protective. In conclusion, ADR led to mitochondrial distress and ultimately cell death in non-differentiated SH-SY5Y cells, possibly because of ADR oxidation products. The involvement of such processes in the catecholamine-induced peripheral neuropathy requires further analysis.</div