Forensic microbiology enables, among other applications, the estimation of the post-mortem interval (PMI), the identification of individuals, and the location of crime scenes through microbiome analysis and the geolocation of biological remains. Artificial intelligence (AI), together with new sequencing techniques, has revolutionized this field, markedly improving the accuracy and speed of forensic analyses. In this study, a systematic review was conducted following PRISMA guidelines. Databases such as PubMed, Scopus, Web of Science, and Google Scholar were searched using keywords related to forensic microbiology, IA, and PMI. Inclusion criteria included studies published in English or Spanish, regardless of the publication date. Exclusion criteria included duplicate studies or those that did not address the thanatomicrobiome analysis using AI tools. After the search and selection proces...

Objective: To determine the frequency of aggression and antisocial behavior in university students with mobile phone dependence. Materials and methods: Sixty-six (66) university students from 18 to 25 years old (54.5 % females) participated in the study. They completed the Mobile Phone Problematic Use Scale (MPPUS) to assess the mobile phone dependence, and the Minnesota Multiphasic Personality Inventory 2-RF (MMPI-2-RF) to assess the antisocial behavior and aggression. Results: Twenty-two point seven percent (22.7 %) of the sample showed mobile phone dependence (cutoff point: 80th percentile). Additionally, a statistical significance (p <0.01) was observed in eight scales of the MPPI-2-RF, including CR4, AG and AGGR-r, which are related to aggression and antisocial behavior. Conclusions: There is a relationship between mobile phone dependence and the scales assessing aggression...