Rationale About 50% of hospitalized coronavirus disease 2019 (COVID-19) patients with diabetes mellitus (DM) developed myocardial damage. The mechanisms of direct SARS-CoV-2 cardiomyocyte infection include viral invasion via ACE2-Spike glycoprotein-binding. In DM patients, the impact of glycation of ACE2 on cardiomyocyte invasion by SARS-CoV-2 can be of high importance. Objective To evaluate the presence of SARS-CoV-2 in cardiomyocytes from heart autopsy of DM cases compared to Non-DM; to investigate the role of DM in SARS-COV-2 entry in cardiomyocytes. Methods and results We evaluated consecutive autopsy cases, deceased for COVID-19, from Italy between Apr 30, 2020 and Jan 18, 2021. We evaluated SARS-CoV-2 in cardiomyocytes, expression of ACE2 (total and glycosylated form), and transmembrane protease serine protease-2 (TMPRSS2) protein. In order to study the role of diabetes on cardiomyocyte alterations, independently of COVID-19, we investigated ACE2, glycosylated ACE2, and TMPRSS2 proteins in cardiomyocytes from DM and Non-DM explanted-hearts. Finally, to investigate the effects of DM on ACE2 protein modification, an in vitro glycation study of recombinant human ACE2 (hACE2) was performed to evaluate the effects on binding to SARS-CoV-2 Spike protein. The authors included cardiac tissue from 97 autopsies. DM was diagnosed in 37 patients (38%). Fourth-seven out of 97 autopsies (48%) had SARS-CoV-2 RNA in cardiomyocytes. Thirty out of 37 DM autopsy cases (81%) and 17 out of 60 Non-DM autopsy cases (28%) had SARS-CoV-2 RNA in cardiomyocytes. Total ACE2, glycosylated ACE2, and TMPRSS2 protein expressions were higher in cardiomyocytes from autopsied and explanted hearts of DM than Non-DM. In vitro exposure of monomeric hACE2 to 120 mM glucose for 12 days led to non-enzymatic glycation of four lysine residues in the neck domain affecting the protein oligomerization. Conclusions The upregulation of ACE2 expression (total and glycosylated forms) in DM cardiomyocytes, along with non-enzymatic glycation, could increase the susceptibility to COVID-19 infection in DM patients by favouring the cellular entry of SARS-CoV2.

According to international regulations, unaccompanied minor status determination implies a different set of rights, needs and entitlements than migrant adults. In forensic scenarios, the age assessment of refugee and asylum seekers who do not have reliable documentation is based on the application of different medical and non-medical methods. A multidisciplinary and holistic approach based on a gradual implementation of these methods is recommended worldwide. Many healthcare professionals consider medical age assessment, especially when performed through radiology, highly intrusive and ethically questionable because it is conducted without medical or therapeutic benefits. About dental examination, the evaluation of the third molar development can provide very useful information on the crucial age limit of 18 years. Demirjian's scoring system and the third molar maturity index (I 3 M) developed by Cameriere et al. (2008) are the two most common quantitative methods for dental age estimation. An ethical evaluation of the dental age estimation performed by these radiological methods through the four principles of biomedical ethics (autonomy, beneficence, non-maleficence and justice) is discussed here.

The syndemic framework proposed by the 2021–2030 World Health Organization (WHO) action plan for patient safety and the introduction of enabling technologies in health services involve a more effective interpretation of the data to understand causation. Based on the Systemic Theory, this communication proposes the “Systemic Clinical Risk Management” (SCRM) to improve the Quality of Care and Patient Safety. This is a new Clinical Risk Management model capable of developing the ability to observe and synthesize different elements in ways that lead to in-depth interventions to achieve solutions aligned with the sustainable development of health services. In order to avoid uncontrolled decision-making related to the use of enabling technologies, we devised an internal Learning Algorithm Risk Management (LARM) level based on a Bayesian approach. Moreover, according to the ethics of Job Well Done, the SCRM, instead of giving an opinion on events that have already occurred, proposes a bioethical co-working because it suggests the best way to act from a scientific point of view.

During the Covid-19 health emergency, telemedicine was an essential asset through which health systems strengthened their response during the critical phase of the pandemic. According to the post-pandemic economic reform plans of many countries, telemedicine will not be limited to a tool for responding to an emergency condition but it will become a structural resource that will contribute to the reorganization of Healthcare Systems and enable the transfer of part of health care from the hospital to the home-based care. However, scientific evidences have shown that health care delivered through telemedicine can be burdened by numerous ethical and legal issues. Although there is an emerging discussion on patient safety issues related to the use of telemedicine, there is a lack of reseraches specifically designed to investigate patient safety. On the contrary, it would be necessary to determine standards and specific application rules in order to ensure safety. This paper examines the telemedicine-risk profiles and proposes a position statement for clinical risk management to support continuous improvement in the safety of health care delivered through telemedicine.

Recent evolution in the field of data science has revealed the potential utility of machine learning (ML) applied to criminal justice. Hence, the literature focused on finding better techniques to predict criminal recidivism risk is rapidly flourishing. However, it is difficult to make a state of the art for the application of ML in recidivism prediction. In this systematic review, out of 79 studies from Scopus and PubMed online databases we selected, 12 studies that guarantee the replicability of the models across different datasets and their applicability to recidivism prediction. The different datasets and ML techniques used in each of the 12 studies have been compared using the two selected metrics. This study shows how each method applied achieves good performance, with an average score of 0.81 for ACC and 0.74 for AUC. This systematic review highlights key points that could allow criminal justice professionals to routinely exploit predictions of recidivism risk based on ML techniques. These include the presence of performance metrics, the use of transparent algorithms or explainable artificial intelligence (XAI) techniques, as well as the high quality of input data.

No abstract

No abstract

AbstractTo overcome kidney donation, the pool of potentially eligible donors has been widened by using suboptimal organs harvested from living donors or cadavers. These organs may engender health complications as age, risk factors, and pathologies of donors fail to meet the standard donor criteria.After examining a wide array of literature on suboptimal kidney transplants, we evidenced two major issues: the lack of standardized terminology and the lack of longterm data on the health outcomes of both suboptimal living donors and recipients. Consequently, surgeons are still unable to provide patients with thorough information to obtain a well-informed consent. Suboptimal kidney transplantation still remains in its experimental stage, thereby raising many ethical and medico-legal concerns.We suggest that one possible solution to overcome some of the ethical shortcomings of suboptimal kidney donations is to provide living donors and recipients honest, accurate, and thorough information about its health risks. To this aim, we advocate adopting a widely standardized terminology that would embrace the whole concept of suboptimal kidney transplantation, increasing the number of future publications on the health outcomes of living donors and recipients, spurring ethical reflection to improve the experience of suboptimal kidney transplantation and reduce the waiting-list for kidney transplantation.