Mummification in a forensic context: an observational study of taphonomic changes and the post-mortem interval in an indoor setting.

The objective of this study was to evaluate the presence of mummification in an indoor setting, with an emphasis on the forensic perspective. A dataset of 102 forensic autopsy cases was assessed for distribution of desiccation of skin and soft tissue (i.e., subcutaneous fat and musculature) and for moist decompositional (i.e., putrefactive) changes. Further, possible correlation with the post-mortem interval (PMI) was evaluated, as well as the effects of clothing coverage of the body. The results indicated that yellow to orange parchment-like desiccated skin was found at significantly shorter PMIs than reddish brown to black leathery desiccated skin, even when soft tissue desiccation was included in the comparative analysis. Clothing appeared to have a significant decelerating effect on the extent of desiccation on the legs, but findings in regard to whole body or torso/arms were inconclusive. A large variation in PMIs was evident as regards fully desiccated skin (PMI 18-217 days), indicating difficulties in PMI estimation due to a variable repressive effect on the decompositional process per se in an indoor setting. For the specific case in forensic practice, no definite conclusion can be drawn from the observed desiccation changes to the PMI. One way forward might be creating a systematic and standardized method for describing different desiccation types, as well as other cooccurring decompositional changes and how they relate to the PMI, as a foundation for a future quantification model.

Microbial neoformation of volatiles: implications for the estimation of post-mortem interval in decomposed human remains in an indoor setting.

The objective of this study was to determine if a relationship between microbial neoformation of volatiles and the post-mortem interval (PMI) exists, and if the volatiles could be used as a tool to improve the precision of PMI estimation in decomposed human remains found in an indoor setting. Chromatograms from alcohol analysis (femoral vein blood) of 412 cases were retrospectively assessed for the presence of ethanol, N-propanol, 1-butanol, and acetaldehyde. The most common finding was acetaldehyde (83% of the cases), followed by ethanol (37%), N-propanol (21%), and 1-butanol (4%). A direct link between the volatiles and the PMI or the degree of decomposition was not observed. However, the decomposition had progressed faster in cases with microbial neoformation than in cases without signs of neoformation. Microbial neoformation may therefore act as an indicator of the decomposition rate within the early decomposition to bloating stages. This may be used in PMI estimation based on the total body score (TBS) and accumulated degree days (ADD) model, to potentially improve the model's precision.

Histological quantification of decomposed human livers: a potential aid for estimation of the post-mortem interval?

The objective of this study was to determine if a novel scoring-based model for histological quantification of decomposed human livers could improve the precision of post-mortem interval (PMI) estimation for bodies from an indoor setting. The hepatic decomposition score (HDS) system created consists of five liver scores (HDS markers): cell nuclei and cell structure of hepatocytes, bile ducts, portal triad, and architecture. A total of 236 forensic autopsy cases were divided into a training dataset (n = 158) and a validation dataset (n = 78). All cases were also scored using the total body score (TBS) method. We specified a stochastic relationship between the log-transformed accumulated degree-days (log10ADD) and the taphonomic findings, using a multivariate regression model to compute the likelihood function. Three models were applied, based on (i) five HDS markers, (ii) three partial body scores (head, trunk, limbs), or (iii) a combination of the two. The predicted log10ADD was compared with the true log10ADD for each case. The fitted models performed equally well in the training dataset and the validation dataset. The model comprising both scoring methods had somewhat better precision than either method separately. Our results indicated that the HDS system was statistically robust. Combining the HDS markers with the partial body scores resulted in a better representation of the decomposition process and might improve PMI estimation of decomposed human remains.

Application of the Bayesian framework for forensic interpretation to casework involving postmortem interval estimates of decomposed human remains.

We demonstrate how the Bayesian framework for forensic interpretation can be adapted for casework involving postmortem intervals (PMI) utilizing taphonomic data as well as how to overcome some of the limitations of current approaches for estimating and communicating uncertainty. A model is implemented for indoor cases based on partial body scores from three different anatomical regions as correlated functions of accumulated temperature (AT). The multivariate model enables estimation of PMI for human remains also when one or two local body scores are missing or undetermined, e.g. as a result of burns, scars or covered body parts. The model was trained using the expectation maximization algorithm, enabling us to account for uncertainty of PMI and/or ambient temperature in the training data. Alternative approaches reporting the results are presented, including the likelihood curve, likelihood ratios for competing hypotheses and posterior probability distributions and credibility intervals for PMI. The applicability or the approaches in different forensic scenarios is discussed.

Quantifying human decomposition in an indoor setting and implications for postmortem interval estimation.

This study's objective is to obtain accuracy and precision in estimating the postmortem interval (PMI) for decomposing human remains discovered in indoor settings. Data were collected prospectively from 140 forensic cases with a known date of death, scored according to the Total Body Score (TBS) scale at the post-mortem examination. In our model setting, it is estimated that, in cases with or without the presence of blowfly larvae, approximately 45% or 66% respectively, of the variance in TBS can be derived from Accumulated Degree-Days (ADD). The precision in estimating ADD/PMI from TBS is, in our setting, moderate to low. However, dividing the cases into defined subgroups suggests the possibility to increase the precision of the model. Our findings also suggest a significant seasonal difference with concomitant influence on TBS in the complete data set, possibly initiated by the presence of insect activity mainly during summer. PMI may be underestimated in cases with presence of desiccation. Likewise, there is a need for evaluating the effect of insect activity, to avoid overestimating the PMI. Our data sample indicates that the scoring method might need to be slightly modified to better reflect indoor decomposition, especially in cases with insect infestations or/and extensive desiccation. When applying TBS in an indoor setting, the model requires distinct inclusion criteria and a defined population.