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A Preliminary Study for Estimating Postmortem Interval of Fabric Degradation in Central FloridaHumbert, Lorraine L. 01 December 2013 (has links)
Forensic anthropologists rely on forensic evidence to estimate the postmortem interval of a decedent. This may include the study of the degree of deterioration of the human body, the life stage of insects, and the degradation of associated material evidence. Material evidence comes in many forms, and certain taphonomic processes will affect the material and must be considered when making inferences about a PMI. These include variables such as the characteristics of the soil, microorganisms, and the presence of a decaying organic material. Previous research has undertaken studies in how fabric degrades over time; however, there is no standard methodology in use. The purpose of this research project is to establish a comprehensive scoring system and description standard after analyzing the degradation of four different fabric types. This will be useful for future studies in need of a standard methodology. In addition, the methods used in this project can be applied to actual forensic cases. After retrieval, the fabric type with the highest degradation was the cotton with about 1/3 of all cotton fabric swatches demonstrating more than 50% total degradation. For all fabric types, swatches that were positioned flat tended to degrade more than those that were positioned crumpled. Cotton fabric swatches degraded more in Trench 1 and Trench 2 than the Ground Surface, however, all other fabric types demonstrated slightly more degradation on the Ground Surface than the other two Areas. Soil moisture fluctuated the most on the Ground Surface while Trench 1 and Trench 2 were able to retain more water in the soil. Overall, cotton was the only fabric type to degrade significantly enough to show how it degrades over time, while the other fabric types have longer degradation intervals that must be studied further.
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Mechanical Properties Of The Intervertebral Disc As An Estimator Of Postmortem IntervalJackson, Jennifer Noelle 01 January 2005 (has links)
Currently, forensic scientists are only able to determine time since death (or postmortem interval) up to the first 60 hours. This is based largely on insect activity. Herein, it is proposed to use the degradation of the intervertebral disc (IVD) after death to determine a relationship between the mechanical properties of cadaveric tissue and time since death in order to extend the 60-hour window. To that end, 1 fresh human spine and 6 pig spines were each separated into sections (6 human and 48 pig), with each section having one intact disc. The sections were buried, unearthed, and cleaned, leaving only the disc and bone. To determine the mechanical properties, each disc underwent three different tests: cyclic conditioning, compression, and stress relaxation testing. The Schapery collocation method was used to create a theoretical curve from the data for the experimental curve. Observations were made involving the corresponding k values of the curve. Although there are trends in the data for k values that approximate the experimental stress relaxation curve, a correlation could not be determined.
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THE EFFECT OF ALTITUDE ON DECOMPOSITION: TOWARD AN UNDERSTANDING OF THE POSTMORTEM INTERVAL IN THE ROCKY MOUNTAIN REGION OF COLORADO.Baigent, Christiane Irene 01 May 2024 (has links) (PDF)
The estimation of postmortem interval (PMI) is a critical component of medicolegal death investigation. An accurate PMI estimate has the potential to influence the allocation of investigative resources, establish the probative value of associated biological and material evidence, shape the analytical framework applied to skeletal analysis, and inform cause and manner of death. Forensic anthropologists are often tasked with PMI estimation throughout all stages of decomposition and typically rely on categorical phases of soft tissue and skeletal change purported to correspond to broad estimates of elapsed time. In an attempt to improve precision, Megyesi et al. (2005) developed the Total Body Score model (TBS). This quantitative method relies on qualitative assessment of value-assigned categories of tissue change within three anatomical regions to estimate accumulated degree days (ADD), and subsequently, PMI. However, the TBS model has failed to prove reliable in a diversity of region-specific validation studies, emphasizing the need for environment-specific research in taphonomy study. Toward that end, the rate, pattern, and trajectory of decomposition was assessed among a cohort of 12 human donors in the high-altitude Rocky Mountain region of Colorado. This research was performed at Colorado Mesa University’s Forensic Investigation Research Station high-altitude satellite facility, FIRS-TB40. The site lies at an elevation of 3000 meters/9840 feet above mean sea level (AMSL), in the Dfc (snow, fully humid, cool summer) climate region. With both significantly higher elevation and an unrepresented climate classification, FIRS-TB40 introduces a novel environment for the controlled study of human decomposition. This quadripartite study sought to (1) test the qualitative and quantitative aspects of the TBS model in a high-altitude environment to assess suitability of application in the estimation of local PMI; (2) test seven atmospheric variables to assess the utility of integrating atmospheric data beyond ADD into PMI estimation; (3) establish the rate and pattern of human decomposition, isolate and describe phasic patterns of soft tissue change throughout the trajectory of decomposition, and (4) develop a region specific bioecological profile with an emphasis on the integration of human behavior.Results: (1) Neither the qualitative or quantitative aspects of the TBS model tested well at high-altitude and are therefore not recommended for application within the study environment. The qualitative changes presented in the TBS model were not observed among the high-altitude cohort. While Megyesi et al. report that time and temperature - as measured by ADD - accounts for 84% of the variance observed throughout decomposition, ADD accounted for only 42% of the variance observed in decomposition within the high-altitude cohort. (2) Seven atmospheric variables were assessed using locally estimated scatterplot smoothing (LOESS) and multivariate regression. Two of these variables - accumulated solar radiation days (r2 = 0.67) and accumulated windspeed days (r2 = 0.65) – explained more variance in decomposition than ADD (r2 = 64). (3) Five categories of phasic, macroscopic soft tissue change, the suite of which is inferred unique to high-altitude, were identified. These include adipocere formation, trajectory of soft tissue color change, fluid bloat, tissue island formation, and skin sloughing. Patterns of slope roll and slope wash were also described to inform the local taphonomic profile. (4) A forensic bioecological profile was developed using empirically derived patterns of scavenger behavior, census and land use data, extant ethnographic data, and forensic case study. Analysis demonstrated that the data sources were cyclically informative and sufficient to develop an early phase foundational model that will benefit from future interdisciplinary research.Summarily, the high-altitude region of Colorado is culturally and environmentally distinct. The observed disparity in rate and pattern of human decomposition between the high-altitude cohort and the TBS model, and the inadequacy of ADD alone to predict PMI are demonstrative of the need for environment-specific model building in human taphonomy research.
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Differential decomposition patterns of human remains in variable environments of the MidwestPope, Melissa A 01 June 2010 (has links)
Where do people die alone when they remain undiscovered for extended periods of time? Estimation of the postmortem interval (PMI) is critical to reconstructing the events surrounding a person's death and this is an area in which forensic anthropologists have played a leading role. This thesis applied an anthropological framework that takes a comprehensive approach to analyzing the demography of unaccompanied deaths, the relationships and timing of decomposition in multiple depositional contexts, and created a model for the prediction of accumulated degree days (ADD) for bodies within enclosures. While there have been extensive experimental and case study reviews on decomposition in outdoor environments, very little data exist for enclosed spaces. A retrospective analysis of 2003-2008 Nebraskan autopsy records demonstrates that most people dying alone are within their homes.
Of the 87 forensic cases reviewed, 69 unaccompanied deaths occurred within enclosed environments. The value of retrospective studies in combination to experimental research is that the large number of variables that affect decompositional rates may be explored in a natural context. Multivariate models put emphasis on the dynamics of decompositional change and comprehensively address death and decomposition within an anthropological framework. For enclosed depositions, the PMI ranged from 1 - 66 days (n= 64, X¯=4.84, s.d.=9.1037) and the ADD ranged from 0 - 786 ADD (n=64, X¯=67.43, s.d.=120.275). Bass' (1997) model for outdoor surface decay was found to be an adequate predictor of the PMI for this sample (r=0.829, n=64, p
These results provided support for the prediction of ADD as a measure of the rate of decomposition. Relationships among ADD and multiple intrinsic, extrinsic and epidemiological variables were identified and considered for a multiple linear regression model. Variables selected by the model included: decomposition odor, use of air conditioning/heat, marbling, brain liquefaction, and mummification. The model was found to account for 95.2% of the variation in ADD (Adjusted R² =0.952; F=40.807, df=5, 5 and p
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Caractérisation de la diagénèse osseuse en anthropologie médico-légale : étude macroscopique, spectrométrique et histomorphologique / Characterization of bone diagenesis in forensic anthropology : a macroscopic, spectrometric and histomorphological studyDelannoy, Yann 15 December 2016 (has links)
Introduction : La détermination du délai postmortem dans les cas de découvertes de restes squelettisés est un élément clé de l’enquête judiciaire. Pour autant, face à la découverte de restes osseux, peu de méthodes sont applicables pour une estimation précise de ce délai. Cette étude taphonomique souhaitait s’inscrire dans une temporalité rejoignant les impératifs judiciaires appliqués en médecine légale. Ainsi, l’hypothèse principale de ce travail était constituée par une dégradation organique précoce de l’os en période postmortem, notamment sous la forme d’une dégradation collagénique. Celle ci a donc fait l’objet d’une évaluation prospective.Matériels et Méthodes : 6 dons de corps humains, sans pathologie osseuse connue ont été inclus et pour chaque sujet, le choix des os étudiés s’est orienté vers les côtes. Ces os ont été inclus dans un environnement de diagénèse et étudiés sur 2 ans. Une analyse macroscopique de perte de poids de l’os a été réalisée, et complétée par deux méthodes : l’une moléculaire (microspectrométrie Raman) et l’autre morphologique (histologie).Résultats : Ce travail, a permis de mettre en évidence certaines caractéristiques de l’altération temporelle des différentes phases osseuses via : une dessiccation mise en évidence par une perte de poids osseuse ; une diagénèse des fractions organiques et minérales. Ainsi, l’étude des paramètres physico-chimiques en microspectrométrie Raman a montré une tendance temporelle à la diminution des rapports phase minérale/phase organique ; la diminution de la carbonatation minérale ; l’augmentation de la cristallinité. L’analyse statistique multivariée des spectres Raman a permis : de distinguer des groupes temporels en les discriminant via leurs contributions organiques ; de construire l’ébauche d’un modèle statistique d’utilisation pratique. L’étude microscopique des prélèvements a montré l’absence de toute attaque microbienne en période postmortem précoce, mais un mécanisme d’altération organique collagénique de type hydrolyse chimique.Discussion : Notre travail, a permis d’identifier 3 paramètres fondamentaux du vieillissement osseux qui doivent être connus du praticien qualifié en anthropologie médico-légale, et cela même sur une période d’étude de 2 ans « courte » à l’échelle de l’anthropologie :- L’environnement influence fortement la diagénèse osseuse et doit être aussi bien étudié que l’os en lui même. En effet, l’étude de la perte de poids de l’os, a montré une altération de composition osseuse très précoce avec phénomène de dessiccation osseuse, comparable à la déshydratation globale du corps en période postmortem ;- La diagénèse osseuse est un phénomène global dans lequel les différentes altérations de phases minérales et organiques sont interdépendantes et peuvent être appréciées par la microspectrométrie Raman, qui outre son apport dans l’analyse de la dégradation chimique de l’os, permet par les outils statistiques qui y sont associés, d’identifier des classes temporelles de diagénèse. Ces classes, qui devront faire l’objet d’études supplémentaires, pourraient à terme être une aide pratique et servir de référence dans la datation précise d’un os ;- L’altération organique de l’os peut s’opérer selon des modes de dégradations chimiques ou bactériens en fonction de l’environnement et du délai postmortem. L’histologie peut permettre de faire ce distinguo. Sur ce délai d’étude, la dégradation collagénique de type chimique par hydrolyse est prédominante.Conclusion : Ces paramètres forment une unité structurelle indissociable qui est connue de longue date en anthropologie archéologique, et qui est parfaitement transposable en pratique médico-légale si des méthodologies adaptées sont développées. Les voies de recherche sur cette thématique ont un rôle essentiel à jouer pour que la médecine légale puisse répondre aux légitimes demandes exprimées par les victimes et leurs ayants-droits auprès de la justice. / Introduction: Determining the postmortem interval in cases of skeletonized remains is a key element of the judicial investigation. However, few methods are applicable for an accurate estimate of this period. This taphonomic study wanted to be performed in a temporality joining the legal requirements applied in forensics. Thus, the main hypothesis of this study was an early organic postmortem bone degradation, particularly a collagen degradation. The latter has been studied prospectively.Materials and Methods: 6 human bodies without known bone disease were included, and for each subject, the ribs were chosen. The bones were included in a diagenetic environment and studied over 2 years. Macroscopic analysis of bone weight loss was performed, and completed by two methods: one molecular (Raman microspectrometry) and the other morphological (histology).Results: This work has highlighted certain features of the temporary bone alteration on its different phases via: a desiccation highlighted by bone mass loss; a diagenesis of organic and mineral phases. Thus, the study of physicochemical parameters by Raman microspectrometry revealed a temporary trend of declining mineral / organic ratios; decreasing carbonation; increasing crystallinity. Multivariate analysis of Raman spectra allowed: to distinguish temporal groups by discriminating via their organic contributions; to design a statistical model of practical use. The microscopic study of the samples revealed no microbial attack in the early postmortem period, but an alteration of collagen by chemical hydrolysis.Discussion: Our study identified three basic parameters of bone diagenesis that must be known to the forensic anthropologist, even over a period of 2 years which is \\\"short\\\" on the scale of anthropology:- The environment strongly influences bone diagenesis and should be studied as well as the bone itself. Indeed, the study of weight loss of the bone, revealed a phenomenon of bone drying, similar to the overall dehydration of the body in the postmortem period;- Bone diagenesis is a global phenomenon in which the various alterations of inorganic and organic phases are interdependent and can be evaluated by Raman microspectrometry. Also its contribution in the analysis of the chemical degradation of the bone, Raman spectroscopy and statistical tools associated with it, allows the identification of diagenesis classes. These classes will require additional studies, eventually to be a practical support in dating a bone;- The organic alteration of the bone may be due to chemical or bacterial degradation, according to the environment and the postmortem period. Histology can make this distinction. On this period of study, the collagen degradation by chemical hydrolysis is predominant.Conclusion: These parameters form a structural unit, which is well known in archaeological anthropology, and is absolutely transposable in forensic practice if appropriate methodologies are developed. Research on this topic has an essential role as forensics can respond to legitimate requests from victims and their relatives towards justice.
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Estimating Postmortem Interval Using VNIR Spectroscopy on Human Cortical BoneServello, John A. 05 1900 (has links)
Postmortem interval (PMI) estimation is a necessary but often difficult task that must completed during a death investigation. The level of difficulty rises as time since death increases, especially with the case of skeletonized remains (long PMI). While challenging, a reliable PMI estimate may be of great importance for investigative direction and cost-savings (e.g. suspect identification, tailoring missing persons searches, non-forensic remains exclusion). Long PMI can be estimated by assessing changes in the organic content of bone (i.e. collagen), which degrades and is lost as the PMI lengthens. Visible-near infrared (VNIR) spectroscopy is one method that can be used for analyzing organic constituents, including proteins, in solid specimens. A 2013 preliminary investigation using a limited number of human cortical bone samples suggested that VNIR spectroscopy could provide a fast, reliable technique for assessing PMI in human skeletal remains. Clear separation was noted between "forensic" and "archaeological" specimen spectra within the near-infrared (NIR) bands. The goal of this research was to develop reliable multivariate classification models that could assign skeletal remains to appropriate PMI classes (e.g. "forensic" and "non-forensic"), based on NIR spectra collected from human cortical bone. Working with a large set of cortical samples (n=341), absorbance spectra were collected with an ASD/PANalytical LabSpec® 4 full range spectrometer. Sample spectra were then randomly assigned to training and test sets, where training set spectra were used to build internally cross-validated models in Camo Unscrambler® X 10.4; external validations of the models were then performed on test set spectra. Selected model algorithms included soft independent modeling of class analogy (SIMCA), linear discriminant analysis on principal components (LDA-PCA), and partial least squares discriminant analysis (PLSDA); an application of support vector machines on principal components (SVM-PCA) was attempted as well. Multivariate classification models were built using both raw and transformed spectra (standard normal variate, Savitzky-Golay) that were collected from the longitudinally cut cortical surfaces (Set A models) and the superficial cortical surface following light grinding (Set B models). SIMCA models were consistently the poorest performers, as were many of the SVM-PCA models; LDA-PCA models were generally the best performers for these data. Transformed-spectra model classification accuracies were generally the same or lower than corresponding raw spectral models. Set A models out-performed Set B counterparts in most cases; Set B models often yielded lower classification accuracy for older forensic and non-forensic spectra. A limited number of Set B transformed-spectra models out-performed the raw model counterparts, suggesting that these transformations may be removing scattering-related noise, leading to improvements in model accuracy. This study suggests that NIR spectroscopy may represent a reliable technique for assessing the PMI of unknown human skeletal remains. Future work will require identifying new sources of remains with established extended PMI values. Broadening the number of spectra collected from older forensic samples would allow for the determination of how many narrower potential PMI classes can be discriminated within the forensic time-frame.
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Applied Machine Learning Predicts the Postmortem Interval from the Metabolomic FingerprintArpe, Jenny January 2024 (has links)
In forensic autopsies, accurately estimating the postmortem interval (PMI) is crucial. Traditional methods, relying on physical parameters and police data, often lack precision, particularly after approximately two days have passed since the person's death. New methods are increasingly focusing on analyzing postmortem metabolomics in biological systems, acting as a 'fingerprint' of ongoing processes influenced by internal and external molecules. By carefully analyzing these metabolomic profiles, which span a diverse range of information from events preceding death to postmortem changes, there is potential to provide more accurate estimates of the PMI. The limitation of available real human data has hindered comprehensive investigation until recently. Large-scale metabolomic data collected by the National Board of Forensic Medicine (RMV, Rättsmedicinalverket) presents a unique opportunity for predictive analysis in forensic science, enabling innovative approaches for improving PMI estimation. However, the metabolomic data appears to be large, complex, and potentially nonlinear, making it difficult to interpret. This underscores the importance of effectively employing machine learning algorithms to manage metabolomic data for the purpose of PMI predictions, the primary focus of this project. In this study, a dataset consisting of 4,866 human samples and 2,304 metabolites from the RMV was utilized to train a model capable of predicting the PMI. Random Forest (RF) and Artificial Neural Network (ANN) models were then employed for PMI prediction. Furthermore, feature selection and incorporating sex and age into the model were explored to improve the neural network's performance. This master's thesis shows that ANN consistently outperforms RF in PMI estimation, achieving an R2 of 0.68 and an MAE of 1.51 days compared to RF's R2 of 0.43 and MAE of 2.0 days across the entire PMI-interval. Additionally, feature selection indicates that only 35% of total metabolites are necessary for comparable results with maintained predictive accuracy. Furthermore, Principal Component Analysis (PCA) reveals that these informative metabolites are primarily located within a specific cluster on the first and second principal components (PC), suggesting a need for further research into the biological context of these metabolites. In conclusion, the dataset has proven valuable for predicting PMI. This indicates significant potential for employing machine learning models in PMI estimation, thereby assisting forensic pathologists in determining the time of death. Notably, the model shows promise in surpassing current methods and filling crucial gaps in the field, representing an important step towards achieving accurate PMI estimations in forensic practice. This project suggests that machine learning will play a central role in assisting with determining time since death in the future.
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