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.

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.

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.

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.

Human microbiome and microbiota identification for preventing and controlling healthcare-associated infections: A systematic review.

Objective: This systematic review describes the role of the human microbiome and microbiota in healthcare-associated infections (HAIs). Studies on the microbiota of patients, healthcare environment (HE), medical equipment, or healthcare workers (HCW) and how it could be transmitted among the different subjects will be described in order to define alarming risk factors for HAIs spreading and to identify strategies for HAIs control or prevention. Methods: This review was performed in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. After retrieval in databases, identification, and screening of available records, 36 published studies were considered eligible and included in the review. Results: A multifaceted approach is required and the analyses of the many factors related to human microbiota, which can influence HAIs onset, could be of paramount importance in their prevention and control. In this review, we will focus mainly on the localization, transmission, and prevention of ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) bacteria and Clostridium difficile which are the most common pathogens causing HAIs. Conclusions: Healthcare workers' microbiota, patient's microbiota, environmental and medical equipment microbiota, ecosystem characteristics, ways of transmission, cleaning strategies, and the microbial resistome should be taken into account for future studies on more effective preventive and therapeutic strategies against HAIs.

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.

Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review.

The determination of the Post-Mortem Interval (PMI) is an issue that has always represented a challenge in the field of forensic science. Different innovative approaches, compared to the more traditional ones, have been tried over the years, without succeeding in being validated as successful methods for PMI estimation. In the last two decades, innovations in sequencing technologies have made it possible to generate large volumes of data, allowing all members of a bacterial community to be sequenced. The aim of this manuscript is to provide a review regarding new advances in PMI estimation through cadaveric microbiota identification using 16S rRNA sequencing, in order to correlate specific microbiome profiles obtained from different body sites to PMI. The systematic review was performed according to PRISMA guidelines. For this purpose, 800 studies were identified through database searching (Pubmed). Articles that dealt with PMI estimation in correlation with microbiome composition and contained data about species, body site of sampling, monitoring time and sequencing method were selected and ultimately a total of 25 studies were considered. The selected studies evaluated the contribution of the various body sites to determine PMI, based on microbiome sequencing, in human and animal models. The results of this systematic review highlighted that studies conducted on both animals and humans yielded results that were promising. In order to fully exploit the potential of the microbiome in the estimation of PMI, it would be desirable to identify standardized body sampling sites and specific sampling methods in order to align data obtained by different research groups.

Skin Microbial Changes during Space Flights: A Systematic Review.

Background. Sixty years after the launch of the first human into space, different studies on the physiological changes that humans undergo during dynamic flight phases and prolonged weightlessness have been undertaken. Understanding these changes is important for the creation of the preventative measures that are essential to ensuring astronaut health. Among these changes, those of the skin are frequent, despite being rarely treated during missions. The skin is a physical barrier that protects the body from pathogen invasion and environmental changes, and it harbors diverse microbial communities that form the skin microbiota. Methods. A systematic literature review of skin microbiome changes during space flight was conducted using public electronic databases (PubMed and Scopus) selecting studies published from 2015 to 2022. The systematic review was performed according to 2020 PRISMA guidelines. Results. A total of 17 studies were collected and, after screening for inclusion and exclusion criteria, eight studies were included in this review. According to the examined literature, some skin microbiota changes seems to be only temporary, in particular Gamma- and Betaproteobacteria abundance tends to decrease, while the occurrence of the Malassezia species and Firmicutes, including Staphylococcus and Streptococcus, tends to increase. At the same time, there seems to be an exchange of microorganisms between astronauts and between the confined environment and a single astronaut, with alterations in the proportion of microorganisms maintained during the flight, in particular for species such as Corynebacterium spp., Staphylococcus spp., Streptococcus spp. and Cloacibacterium spp. Given that skin contributes both to protecting the body from pathogen invasion and environmental changes and to maintaining human homeostasis, changes in the skin microbiota of astronauts might result in skin diseases. Discussion. The skin microbiota of astronauts seems to influence the microbial composition of the International Space Station, but further studies should be performed to better understand skin microbiota dynamics and to prevent the development of dermatologic conditions during space flight.

External visible characteristics prediction through SNPs analysis in the forensic setting: a review.

Numerous major advances have been made in forensic genetics over the past decade. One recent field of research has been focused on the analysis of External Visible Characteristics (EVC) such as eye colour, hair colour (including hair greying), hair morphology, skin colour, freckles, facial morphology, high myopia, obesity, and adult height, with important repercussions in the forensic field. Its use could be especially useful in investigative cases where there are no potential suspects and no match between the evidence DNA sample under investigation and any genetic profiles entered into criminal databases. The present review represents the current state of knowledge of SNPs (Single Nucleotide Polymorphisms) regarding visible characteristics, including the latest research progress in identifying new genetic markers, their most promising applications in the forensic field and the implications for police investigations. The applicability of these techniques to concrete cases has stoked a heated debate in the literature on the ethical implications of using these predictive tools for visible traits.

Chimerism Monitoring Techniques after Hematopoietic Stem Cell Transplantation: An Overview of the Last 15 Years of Innovations.

Chimerism analysis is a well-established method for monitoring the state of hematopoietic stem cell transplantation (HSCT) over time by analyzing peripheral blood or bone marrow samples of the recipient in several malignant and non-malignant hematologic diseases. From a clinical point of view, a continuous monitoring is fundamental for an effective early therapeutic intervention. This paper provides a comparative overview of the main molecular biology techniques which can be used to study chimerism after bone marrow transplantation, focusing on their advantages and disadvantages. According to the examined literature, short tandem repeats (STR) analysis through simple PCR coupled with capillary electrophoresis (STR-PCR) is the most powerful method which guarantees a high power of differentiation between different individuals. However, other methods such as real-time quantitative PCR (qPCR), digital PCR (dPCR), and next-generation sequencing (NGS) technology were developed to overcome the technical limits of STR-PCR. In particular, these other techniques guarantee a higher sensitivity, which allows for the detection of chimerism at an earlier stage, hence expanding the window for therapeutic intervention. After a comparative evaluation of the various techniques, it seems clear that STR-PCR still remains the gold standard option for chimerism study, even if it is likely that both dPCR and NGS could supplement or even replace the common methods of STR analysis.

Comparison of the Allelic Alterations between InDel and STR Markers in Tumoral Tissues Used for Forensic Purposes.

Background and objectives: Over the last two decades, human DNA identification and kinship tests have been conducted mainly through the analysis of short tandem repeats (STRs). However, other types of markers, such as insertion/deletion polymorphisms (InDels), may be required when DNA is highly degraded. In forensic genetics, tumor samples may sometimes be used in some cases of human DNA identification and in paternity tests. Nevertheless, tumor genomic instability related to forensic DNA markers should be considered in forensic analyses since it can compromise genotype attribution. Therefore, it is useful to know what impact tumor transformation may have on the forensic interpretation of the results obtained from the analysis of these polymorphisms. Materials and Methods: The aim of this study was to investigate the genomic instability of InDels and STRs through the analysis of 55 markers in healthy tissue and tumor samples (hepatic, gastric, breast, and colorectal cancer) in 66 patients. The evaluation of genomic instability was performed comparing InDel and STR genotypes of tumor samples with those of their healthy counterparts. Results: With regard to STRs, colorectal cancer was found to be the tumor type affected by the highest number of mutations, whereas in the case of InDels the amount of genetic mutations turned out to be independent of the tumor type. However, the phenomena of genomic instability, such as loss of heterozygosity (LOH) and microsatellite instability (MSI), seem to affect InDels more than STRs hampering genotype attribution. Conclusion: We suggest that the use of STRs rather than InDels could be more suitable in forensic genotyping analyses given that InDels seem to be more affected than STRs by mutation events capable of compromising genotype attribution.