|
1000
|
Abstract/Summary
|
-
<jats:title>Abstract</jats:title><jats:p>The delimitation of the postmortem interval (PMI) is of utmost importance in forensic science. It is especially difficult to determine the PMI in advanced decomposition stages and/or when dead bodies are found under uncommon circumstances, such as tents, or other (semi-) enclosed environments. In such cases, especially when insect access is restricted, morphological assessment of body decomposition is one of the remaining approaches for delimitation of the PMI. However, as this method allows only vague statements/indications about the PMI, it is required to develop new and more reliable methods. One of the most important candidates is the biochemical analysis of protein degradation. In this regard, it has been demonstrated that specific skeletal muscle protein degradation patterns characterize certain time points postmortem and thus can be used as markers for PMI estimation. In order to test this method in different micro-environments, a pilot study using ten pig carcasses was conducted in summer in Northern Germany. The cadavers were openly placed outside (freely accessible for insects), as well as enclosed in tents nearby, and left to decompose to investigate decomposition processes over a time course of 10 days. Muscle samples of the <jats:italic>M. biceps femoris</jats:italic> were collected on a regular basis and processed via SDS-PAGE and degradation patterns of selected proteins identified by Western blotting. In addition, morphological changes of the cadavers during decomposition were assessed using the total body score (TBS). Results showed that postmortem protein degradation patterns are largely consistent between treatment groups (open field versus tents) despite major morphological differences in the decomposition rate. This field study provides evidence that muscle protein degradation is mostly unaffected by different levels of exposure, making it a sufficient candidate for PMI delimitation under various circumstances.</jats:p>
|
|
1000
|
Hinweis
|
-
DeepGreen-ID: 3cad3b8fed15461097034b145143b6fc ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
|
