Dental dimorphism can be used for discriminating sex in forensic contexts. Geometric morphometric analysis (GMA) allows the evaluation of the shape and size, separately, of uneven 3D objects. This study presents experiments using a novel combination of GMA and an artificial neural network (ANN) for sex classification, applied to premolars of Caucasian Italian adults (50 females and 50 males). General Procrustes superimposition (GPS) and the partial least square (PLS) method were performed, respectively, to study the shape variance between sexes and to eliminate landmark variations. The “set-aside” approach was used to assess the accuracy of the proposed neural networks. As the main findings of the pilot study, the proposed method applied to the first upper premolar correctly classified 90% of females and 73% of males of the test sample. The accuracy was 0.84 and 0.80 for the training and test samples, respectively. The sexual dimorphism resulting from GMA was low, although statistically significant. GMA combined with the ANN demonstrated better sex classification ability than previous odontometric or dental morphometric methods. Future research could overcome some limitations by considering a larger sample of subjects and other kinds of teeth and experimenting with the use of computer vision for automatic landmark positioning.

Forensic entomology is a branch of forensic science in which insects are used as evidence in legal investigations relating to humans, domestic animals and wildlife. One of the theoretical pillars on which the discipline is based concerns the fact that flies colonize a body after death. However in cases of myiasis, maggots are present before death, with consequences in the correct estimation of the minimum postmortem interval (mPMI). We report here the case of a woman, largely colonized by fly larvae, who has lain alive in her garden for four days prior to being rescued. Larvae were found on the conjunctivae, the bronchi, the rectum and vagina. The woman's death, two months later, was caused by tetanus. The consequences of myiasis on mPMI estimation are here discussed. In fact, despite she was still alive larvae, indicated and estimated age of 1.5–2.5 days, based on environmental and body temperature.

Teeth have proven to be a reliable source of DNA for forensic analysis as the pulp is rich in cells and protected from damaging factors and contamination by dental hard tissues. The pilot study aims to evaluate the feasibility of Next-Generation sequencing analysis on dental pulp to detect genetic mutations in DNA caused by post-mortem cell necrosis. We used a 56-gene oncopanel kit on a sample of 17 teeth extracted from living patients. Time of the tooth avulsion was assumed as death of the individual and Post-mortem Interval (PMI) was the time elapse since the DNA extraction and analysis. Days and Accumulated Degree Days (ADD) were assumed as measures of PMI that ranged between 0 to 34 days. Only 38 of the 56 considered genes proved to be affected by mutations (101), thus being of forensic interest. More specifically, 14 mutations occurred only in a specific range of PMIs/ADD; 67 were detected (alone or as clusters of the same gene) at specific PMI/ADD; 22 occurred at every PMI/ADD, except for some specific intervals. Since dental pulp was not targeted by any oncological diseases and all teeth were intact, vital, and from patients with unremarkable medical history, it could be assumed that mutations were due to post-mortem DNA changes induced by pulp death and the increasing time elapse since death. This pilot study found encouraging results in the application of NGS analysis on dental DNA, especially for PMIs of several days for which the traditional tools for PMI estimation have limitations. Further research on a larger sample of PMI and validation research on a larger sample of PMI and validation of the results are indeed necessary.

The European Council of Legal Medicine (ECLM) on-site inspection form allows the collection of data relevant to the identification, collection, sampling and preservation of all elements that, during the on-site inspection, may be useful as forensic evidence. The aim of this study is to assess the completeness of the information collected in a large number of on-site inspections, the records of which were drawn up without the use of the ECLM on-site inspection form, in order to verify the usefulness and the application of this form. The authors present a multicentre study involving 20 Italian forensic medicine institutes. For each institute, the reports of on-site inspections carried out without the use of the ECLM on-site inspection form were collected and a forensic pathologist was asked to analyse the individual cases and to identify, for each case, the presence or absence of information regarding all the points examined by the ECLM on-site inspection form. A practical database was prepared and sent to each institute for this analysis. Data were collected and analysed from a total of 1721 on-site inspection reports. Our results document that certain items on the ECLM on-site inspection form are not always investigated in reports written without the use of this tool. The use of the ECLM on-site inspection form proves to be a valid tool to assist the forensic pathologist during the on-site inspection. We therefore hope that the forms developed by the ECLM will be systematically adopted in the forensic practice of the forensic pathologist.

Teeth are known to be reliable substrates for human identification and are endowed with significant sexual dimorphism not only in the size but also in the shape of the crowns. In the preliminary phase of our study (already published in 2021), a novel sex estimation method based on dental morphometric geometric (GMA) analysis combined with the artificial neural network (ANN) was developed and validated on a single dental element (first upper premolar) with an accuracy rate of 80%. This study aims to experiment and validate the combination of GMA–ANN on the upper first and second left premolars and the upper left first molar to obtain a reliable classification model based on the sexual dimorphic traits of multiple maxillary teeth of Caucasian Italian adults (115 males and 115 females). A general procrustes superimposition (GPS) and principal component analysis (PCA) were performed to study the shape variance between the sexes and to reduce the data variations. The “set-aside” approach was used to validate the accuracy of the proposed ANN. As the main findings, the proposed method correctly classified 94% of females and 68% of males from the test sample and the overall accuracy gained was 82%, higher than the odontometric methods that similarly consider multiple teeth. The shape variation between male and female premolars represents the best dimorphic feature compared with the first upper molar. Future research could overcome some limitations by considering a larger sample of subjects and experimenting with the use of computer vision for automatic landmark positioning and should verify the present evidence in samples with different ancestry.