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Throughout the years an increase has been observed in research output on biochemical markers for determining the postmortem interval (PMI). However, to date, a complete overview is missing on the results of postmortem biochemical markers (PBM''s) for PMI estimation. In this paper, literature was reviewed in order to identify the knowledge lacunae of PBM research from a practical point of view. A three-step approach was undertaken in order to achieve the set goal. Literature was collected, the PBM''s were evaluated for completeness by means of a scorings index based on set criteria, and PBM''s were subsequently evaluated in light of the Daubert & Frye criteria for scientific evidence in court. Seven PBM''s were found to be well investigated, from which potassium had the highest completion score. However, none of these PBM''s could be qualified as suitable for court evidence. Further, this study revealed that the majority of PBM''s (94%) is not well investigated. Consequently, these PBM''s did not meet Daubert & Frye criteria. In order to improve the assessment for use of PBM''s as evidence in court regarding PMI estimation, PBM''s should be investigated more thoroughly and data should be made readily available.

We present here a novel surface mass spectrometry strategy to perform untargeted metabolite profiling of formalin-fixed paraffin-embedded pediatric ependymoma archives. Sequential Orbitrap secondary ion mass spectrometry (3D OrbiSIMS) and liquid extraction surface analysis-tandem mass spectrometry (LESA-MS/MS) permitted the detection of 887 metabolites (163 chemical classes) from pediatric ependymoma tumor tissue microarrays (diameter

Purpose The aim is of this study was to show the poor statistical power of postmortem studies. Further, this study aimed to find an estimate of the effect size for postmortem studies in order to show the importance of this parameter. This can be an aid in performing power analysis to determine a minimal sample size. Methods GPower was used to perform calculations on sample size, effect size, and statistical power. The minimal significance (α) and statistical power (1 − β) were set at 0.05 and 0.80 respectively. Calculations were performed for two groups (Student’s t-distribution) and multiple groups (one-way ANOVA; F-distribution). Results In this study, an average effect size of 0.46 was found (n = 22; SD = 0.30). Using this value to calculate the statistical power of another group of postmortem studies (n = 5) revealed that the average statistical power of these studies was poor (1 − β

Recently, Costa et al. published an article about promising biomarkers for estimating the postmortem interval., Recently, Costa et al. published an article about promising biomarkers for estimating the postmortem interval. Instead of postmortem blood, antemortem blood was putrefied in vitro by exposing the blood to a temperature gradient. However, in this way several other influencing factors were excluded, hence, the accuracy of the proposed model is doubtful. Therefore, the aim of this comment is to discuss the methodology, results and shortcomings of the study of Costa et al.