Estimation of Human Chronological Age from Buccal Swab Samples through a DNA Methylation Analysis Approach of a Five-Locus Multiple Regression Model.

Recent advancements in forensic genetics have facilitated the extraction of additional characteristics from unidentified samples. This study delves into the predictive potential of a five-gene (ELOVL2, FHL2, KLF14, C1orf132, and TRIM59) methylation rate analysis for human age estimation using buccal swabs collected from 60 Italian volunteers. The methylation levels of specific CpG sites in the five genes were analyzed through bisulfite conversion, single-base extension, and capillary electrophoresis. A multivariate linear regression model was crafted on the training set, then the test set was employed to validate the predictive model. The multivariate predictive model revealed a mean absolute deviation of 3.49 years in the test set of our sample. While limitations include a modest sample size, the study provides valuable insights into the potential of buccal swab-based age prediction, aiding in criminal investigations where accurate age determination is crucial. Our results also highlight that it is necessary to investigate the effectiveness of predictive models specific to biological tissues and individual populations, since models already proven effective for other populations or different tissues did not show the same effectiveness in our study.

Forensic Age Estimation through a DNA Methylation-Based Age Prediction Model in the Italian Population: A Pilot Study.

DNA methylation is one of the epigenetic marks which has been studied intensively in recent years for age predicting purposes in the forensic area. In order to integrate age prediction into routine forensic workflow, the purpose of this study was to standardize and optimize a DNA methylation-based protocol tailored to the Italian context. A previously published protocol and age-predictive method was implemented for the analysis of 84 blood samples originating from Central Italy. The study here presented is based on the Single Base Extension method, considering five genes: ELOVL2, FHL2, KLF14, C1orf132, now identified as MIR29B2C, and TRIM59. The precise and specific steps consist of DNA extraction and quantification, bisulfite conversion, amplification of converted DNA, first purification, single base extension, second purification, capillary electrophoresis, and analysis of the results to train and test the tool. The prediction error obtained, expressed as mean absolute deviation, showed a value of 3.12 years in the training set and 3.01 years in the test set. Given that population-based differences in DNA methylation patterns have been previously reported in the literature, it would be useful to further improve the study implementing additional samples representative of the entire Italian population.

Touch DNA Sampling Methods: Efficacy Evaluation and Systematic Review.

Collection and interpretation of "touch DNA" from crime scenes represent crucial steps during criminal investigations, with clear consequences in courtrooms. Although the main aspects of this type of evidence have been extensively studied, some controversial issues remain. For instance, there is no conclusive evidence indicating which sampling method results in the highest rate of biological material recovery. Thus, this study aimed to describe the actual considerations on touch DNA and to compare three different sampling procedures, which were "single-swab", "double-swab", and "other methods" (i.e., cutting out, adhesive tape, FTA® paper scraping), based on the experimental results published in the recent literature. The data analysis performed shows the higher efficiency of the single-swab method in DNA recovery in a wide variety of experimental settings. On the contrary, the double-swab technique and other methods do not seem to improve recovery rates. Despite the apparent discrepancy with previous research, these results underline certain limitations inherent to the sampling procedures investigated. The application of this information to forensic investigations and laboratories could improve operative standard procedures and enhance this almost fundamental investigative tool's probative value.

Digital Biobanking and Big Data as a New Research Tool: A Position Paper.

Big data analytics in medicine is driving significant change, as it offers vital information for improving functions, developing cutting-edge solutions and overcoming inefficiencies. With the right archiving and analysis tools, all players in the healthcare system, from hospitals to patients and from medical personnel to the pharmaceutical industry, can yield numerous benefits. Therefore, to analyze and interpret these analytics effectively, so that they can be useful for the advancement of scientific knowledge, we require information sharing, specific skills, training, integration between all system players, unique infrastructures and security. All these characteristics will make it possible to establish and harmonize real big data biobanks, for which it will be appropriate to consider new forms of governance compared to those traditionally conceived for large-sample biobanks.

Defining medical liability when artificial intelligence is applied on diagnostic algorithms: a systematic review.

Artificial intelligence (AI) in medicine is an increasingly studied and widespread phenomenon, applied in multiple clinical settings. Alongside its many potential advantages, such as easing clinicians' workload and improving diagnostic accuracy, the use of AI raises ethical and legal concerns, to which there is still no unanimous response. A systematic literature review on medical professional liability related to the use of AI-based diagnostic algorithms was conducted using the public electronic database PubMed selecting studies published from 2020 to 2023. The systematic review was performed according to 2020 PRISMA guidelines. The literature review highlights how the issue of liability in case of AI-related error and patient's damage has received growing attention in recent years. The application of AI and diagnostic algorithm moreover raises questions about the risks of using unrepresentative populations during the development and about the completeness of information given to the patient. Concerns about the impact on the fiduciary relationship between physician and patient and on the subject of empathy have also been raised. The use of AI in medical field and the application of diagnostic algorithms introduced a revolution in the doctor-patient relationship resulting in multiple possible medico-legal consequences. The regulatory framework on medical liability when AI is applied is therefore inadequate and requires urgent intervention, as there is no single and specific regulation governing the liability of various parties involved in the AI supply chain, nor on end-users. Greater attention should be paid to inherent risk in AI and the consequent need for regulations regarding product safety as well as the maintenance of minimum safety standards through appropriate updates.

Lessons Learned from the COVID-19 Pandemic: A Survey-Based Study on a Sample of Italian Physicians' Opinions on Telemedicine.

Telemedicine was born out of the need to ensure clinical evaluation and personal care regardless of the physical presence of the healthcare professional nearby. Information technologies have been vital during the COVID-19 pandemic to ensure medical care and avoid the contagion between patients and clinicians. Accordingly, telecare services multiplied worldwide and gained paramount importance. The present work aims to collect field-based opinions about Telemedicine and ethics among Italian physicians. We developed a web-based questionnaire that was administered to Italian physicians from 1 May to 15 June 2022. The questionnaire was distributed as a link to Google Forms via social networks/instant messaging applications to groups of graduated and qualified physicians. A total of 180 physicians answered the questionnaire (with an age range from 25 to 68 years old). Physicians belonging to the medical area of expertise appear to more frequently use new technologies in comparison to other specialties. The vast majority believe that it is appropriate to use Telemedicine for monitoring and follow-up but not for evaluating a new patient. Concerns about changes in the physician-patient relationship, informed consent, digital barrier, and privacy and data protection also emerged. Finally, telehealth is thought to be a potential useful tool for the future by the majority of respondents but proper training for physicians is therefore needed.