Application of Innovative TGA/Chemometric Approach for Forensic Purposes: The Estimation of the Time since Death in Contaminated Specimens

Zapico S. Partners in Postmortem Interval Estimation: X-ray Diffraction and Fourier Transform Spectroscopy

The postmortem interval (PMI) is difficult to estimate in later stages of decomposition. There is therefore a need to develop reliable methodologies to estimate late PMI. This study aims to assess whether there is a correlation between changes in the mineral composition of human teeth and the estimation of PMI. X-ray diffraction (XRD) and attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy techniques were performed to address this challenge. Forty healthy human teeth obtained from odontological clinics were stored at different times (0, 10, 25, 50 years; N = 10/group). XRD and ATR-FTIR parameters related to the structure and composition of teeth were studied. Our results showed that the crystallinity index, crystal size index, mineral-to-organic matrix ratio (M/M) and carbonate/phosphate ratio (C/P) had the strongest association with PMI. For larger PMIs, there was a significant increase in crystallinity, crystal size and M/M ratio, while the C/P ratio showed a specific decrease with increasing PMI. According to our results, the parameters of crystallinity, crystal size, M/M ratio and C/P ratio can be considered highly accurate in determining a PMI of 10 years of data; crystallinity and mineral maturity can be considered useful in determining a PMI of 25 years; and crystallinity and mineral maturity can be considered highly accurate in determining a PMI of 50 years. A particular XRD index was identified as the most suitable parameter to estimate PMI: crystallinity. The joint use of XRD and ATR-FTIR analyses could be a promising alternative for dating human teeth.

Combined metabolomics and tandem machine-learning models for wound age estimation: a novel analytical strategy

Wound age estimation is one of the most challenging and indispensable issues for forensic pathologists. Although many methods based on physical findings and biochemical tests can be used to estimate wound age, an objective and reliable method for inferring the time interval after injury remains difficult. In the present study, endogenous metabolites of contused skeletal muscle were investigated to estimate the time interval after injury. Animal model of skeletal muscle injury was established using Sprague-Dawley rat, and the contused muscles were sampled at 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, and 48 h postcontusion (n = 9). Then, the samples were analysed using ultraperformance liquid chromatography coupled with high-resolution mass spectrometry. A total of 43 differential metabolites in contused muscle were determined by metabolomics method. They were applied to construct a two-level tandem prediction model for wound age estimation based on multilayer perceptron algorithm. As a result, all muscle samples were eventually divided into the following subgroups: 4, 8, 12, 16-20, 24-32, 36-40, and 44-48 h. The tandem model exhibited a robust performance and achieved a prediction accuracy of 92.6%, which was much higher than that of the single model. In summary, the multilayer perceptron-multilayer perceptron tandem machine-learning model based on metabolomics data can be used as a novel strategy for wound age estimation in future forensic casework.

Key Points

The changes of metabolite profile were correlated with the time interval after injury in contused skeletal muscle.A panel of 43 endogenous metabolites screened by ultraperformance liquid chromatography coupled with high-resolution mass spectrometry could distinguish the wound ages.The multilayer perceptron (MLP) algorithm exhibited a robust performance in wound age estimation using metabolites.The combination of matabolomics and MLP-MLP tandem model could improve the accuracy of inferring the time interval after injury.

On-Line Thermally Induced Evolved Gas Analysis: An Update-Part 2: EGA-FTIR

The on-line thermally induced evolved gas analysis (OLTI-EGA) is widely applied in many different fields. Aimed to update the applications, our group has systematically collected and published examples of EGA characterizations. Following the recently published review on EGA-MS applications, this second part reviews the latest applications of Evolved Gas Analysis performed by on-line coupling heating devices to infrared spectrometers (EGA-FTIR). The selected 2019, 2020, 2021 and early 2022 references are collected and briefly described in this review; these are useful to help researchers to easily find applications that are sometimes difficult to locate.

On-Line Thermally Induced Evolved Gas Analysis: An Update-Part 1: EGA-MS

Advances in on-line thermally induced evolved gas analysis (OLTI-EGA) have been systematically reported by our group to update their applications in several different fields and to provide useful starting references. The importance of an accurate interpretation of the thermally-induced reaction mechanism which involves the formation of gaseous species is necessary to obtain the characterization of the evolved products. In this review, applications of Evolved Gas Analysis (EGA) performed by on-line coupling heating devices to mass spectrometry (EGA-MS), are reported. Reported references clearly demonstrate that the characterization of the nature of volatile products released by a substance subjected to a controlled temperature program allows us to prove a supposed reaction or composition, either under isothermal or under heating conditions. Selected 2019, 2020, and 2021 references are collected and briefly described in this review.