HUMAN RIGHTS AND ETHICS IN THE COVID-19 PANDEMIC. THE PHENOMENON OF "VACCINATION AT THE SINK" IN ROMANIA

The increase in the number of confirmed coronavirus cases (Covid-19) at various stages of the pandemic, as well as the success of several waves, have highlighted the need to take action to ensure the safety of human health and to adapt the strategies so that the measures taken are as effective as possible. This paper aims to address key issues regarding the ethical challenges generated by the distribution and administration of the anti-Covid vaccine and from the perspective of fundamental human rights, considering the right to health. The work ends with a case study from the Romanian space regarding the violation of ethical and legal norms in the administration of the vaccine by "vaccination at the sink"

Education, Neurotechnologies, and Ethics. An overview

The progress made in recent decades in neuroscience and new technologies have also influenced the educational environment from the perspective of the didactic methods used and the integration of modern methods. Educational neurotechnologies increasingly present in educational systems are also more challenging for both students, teachers, and parents. In the present article we provide an overview of educational neurotechnologies, with an analysis of the benefits and ethical-legal issues raised by their use. We bring to attention the need to train teachers, in the sense of developing specific skills for using neurotechnologies in the classroom, through training courses. Only in this way is it possible to prevent errors and possible unwanted effects. We sustain the need to integrate the use of educational neurotechnologies in an ethical-legal framework for ensuring personal neurobiological data and respecting confidentiality. The methods used are the analysis of the data provided by specialized works, especially recent ones, the extraction of relevant information for the researched topic and then their synthesis for a better understanding of the problems and the identification of possible solutions

Hope and human longevity, an actual challenging topic

This paper represents an attempt to correlate the concept of hope with the notion of human longevity and reflects the actual debates around the problem of life extension. Our analysis combines ideas from philosophy, sociology, bioethics, and religion to illustrate the problem of longevity in the context of biomedical and technological progress, and - at the same time - to show the (possible) consequences of prolonging life over the human body limits. Extending human life through emerging technologies is much closer to us than we might think and is a particularly challenging topic

GLP-1 Receptor Agonists and Coronary Arteries: From Mechanisms to Events.

Objective: Glucagon-like peptide 1 receptor agonists (GLP-1 RAs) lower plasma glucose through effects on insulin and glucagon secretion and by decelerating gastric emptying. GLP-1 RAs have many beneficial effects beyond glycemic control, including a protective role on the cardiovascular system. However, underlying mechanisms linking GLP-1 RAs with coronary artery disease are complex and not fully elucidated. In this mini-review, we discuss these mechanisms and subsequent clinical events. Data Sources: We searched PubMed and Google Scholar for evidence on GLP-1 RAs and coronary events. We did not apply restrictions on article type. We reviewed publications for clinical relevance. Synopsis of Content: In the first part, we review the current evidence concerning the role of GLP-1 RAs on potential mechanisms underlying the development of coronary events. Specifically, we discuss the role of GLP-1 RAs on atherosclerosis and vasospasms of epicardial coronary arteries, as well as structural/functional changes of coronary microvasculature. In the second part, we summarize the clinical evidence on the impact of GLP-1 RAs in the prevention of acute and chronic coronary syndromes and coronary revascularization. We conclude by discussing existing gaps in the literature and proposing directions for future research

Effect of placenta previa on umbilical cord hematocrit value

Objective Placenta previa is one of the causes of neonatal anemia. This condition is mainly explained by antenatal hemorrhage and incision of the anteriorly located placenta during cesarean section. However, the mechanism of neonatal anemia in placenta previa has not been extensively studied or well elucidated. This study investigates whether placenta previa is associated with lower hematocrit levels in newborns with no antenatal hemorrhage and placental incision. Key findings This prospective study investigated 47 patients with previa and 43 control patients who gave birth with a cesarean section at 34-38 weeks of gestation. Blood samples were obtained from the fetal end of the umbilical vein. The mean umbilical cord hematocrit value was 49.3% in the control patients and 46.7% in the patients with previa, and the difference was statistically significant (p = .029). No significant association was observed between hematocrit value and birth weight, gestational age, newborn gender, placenta position, or preoperative maternal hemoglobin level. Conclusion The study findings reveal that even if not complicated by antepartum or intrapartum hemorrhage, placenta previa may be associated with lower hematocrit values in newborns. Although in none of the cases, the umbilical cord hematocrit value was not as low as to be defined as anemia, this effect of previa on newborns should be considered because of the importance of iron status

From Raw Data to FAIR Data: The FAIRification Workflow for Health Research

BackgroundFAIR (findability, accessibility, interoperability, and reusability) guidingprinciples seek the reuse of data and other digital research input, output, and objects(algorithms, tools, and workflows that led to that data) making themfindable, accessible,interoperable, and reusable. GO FAIR - a bottom-up, stakeholder driven and self-governedinitiative-defined a seven-step FAIRificationprocessfocusingondata,butalsoindicatingtherequired work for metadata. This FAIRification process aims at addressing the translation ofraw datasets into FAIR datasets in a general way, without considering specific requirementsand challenges that may arise when dealing with some particular types of data.This work was performed in the scope of FAIR4Healthproject. FAIR4Health has received funding from the European Union’s Horizon 2020 research and innovationprogramme under grant agreement number 824666

Postmarketing Safety Study Tool: A Web Based, Dynamic, and Interoperable System for Postmarketing Drug Surveillance Studies

Postmarketing drug surveillance is a crucial aspect of the clinical research activities in pharmacovigilance and pharmacoepidemiology. Successful utilization of available Electronic Health Record (EHR) data can complement and strengthen postmarketing safety studies. In terms of the secondary use of EHRs, access and analysis of patient data across different domains are a critical factor; we address this data interoperability problem between EHR systems and clinical research systems in this paper. We demonstrate that this problem can be solved in an upper level with the use of common data elements in a standardized fashion so that clinical researchers can work with different EHR systems independently of the underlying information model. Postmarketing Safety Study Tool lets the clinical researchers extract data from different EHR systems by designing data collection set schemas through common data elements. The tool interacts with a semantic metadata registry through IHE data element exchange profile. Postmarketing Safety Study Tool and its supporting components have been implemented and deployed on the central data warehouse of the Lombardy region, Italy, which contains anonymized records of about 16 million patients with over 10-year longitudinal data on average. Clinical researchers in Roche validate the tool with real life use cases.Publisher's Versio

An Interoperability Platform Enabling Reuse of Electronic Health Records for Signal Verification Studies

Depending mostly on voluntarily sent spontaneous reports, pharmacovigilance studies are hampered by low quantity and quality of patient data. Our objective is to improve postmarket safety studies by enabling safety analysts to seamlessly access a wide range of EHR sources for collecting deidentified medical data sets of selected patient populations and tracing the reported incidents back to original EHRs. We have developed an ontological framework where EHR sources and target clinical research systems can continue using their own local data models, interfaces, and terminology systems, while structural interoperability and Semantic Interoperability are handled through rule-based reasoning on formal representations of different models and terminology systems maintained in the SALUS Semantic Resource Set. SALUS Common Information Model at the core of this set acts as the common mediator. We demonstrate the capabilities of our framework through one of the SALUS safety analysis tools, namely, the Case Series Characterization Tool, which have been deployed on top of regional EHR Data Warehouse of the Lombardy Region containing about 1 billion records from 16 million patients and validated by several pharmacovigilance researchers with real-life cases. The results confirm significant improvements in signal detection and evaluation compared to traditional methods with the missing background information

Applying the FAIR4Health Solution to Identify Multimorbidity Patterns and Their Association with Mortality through a Frequent Pattern Growth Association Algorithm

This article belongs to the Special Issue Addressing the Growing Burden of Chronic Diseases and Multimorbidity: Characterization and InterventionsThe current availability of electronic health records represents an excellent research opportunity on multimorbidity, one of the most relevant public health problems nowadays. However, it also poses a methodological challenge due to the current lack of tools to access, harmonize and reuse research datasets. In FAIR4Health, a European Horizon 2020 project, a workflow to implement the FAIR (findability, accessibility, interoperability and reusability) principles on health datasets was developed, as well as two tools aimed at facilitating the transformation of raw datasets into FAIR ones and the preservation of data privacy. As part of this project, we conducted a multicentric retrospective observational study to apply the aforementioned FAIR implementation workflow and tools to five European health datasets for research on multimorbidity. We applied a federated frequent pattern growth association algorithm to identify the most frequent combinations of chronic diseases and their association with mortality risk. We identified several multimorbidity patterns clinically plausible and consistent with the bibliography, some of which were strongly associated with mortality. Our results show the usefulness of the solution developed in FAIR4Health to overcome the difficulties in data management and highlight the importance of implementing a FAIR data policy to accelerate responsible health research.This study was performed in the framework of FAIR4Health, a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 824666. Also, this research has been co-supported by the Carlos III National Institute of Health, through the IMPaCT Data project (code IMP/00019), and through the Platform for Dynamization and Innovation of the Spanish National Health System industrial capacities and their effective transfer to the productive sector (code PT20/00088), both co-funded by European Regional Development Fund (FEDER) ‘A way of making Europe’, and by REDISSEC (RD16/0001/0005) and RICAPPS (RD21/0016/0019) from Carlos III National Institute of Health. This work was also supported by Instituto de Investigación Sanitaria Aragón and Carlos III National Institute of Health [Río Hortega Program, grant number CM19/00164].Peer reviewe

FAIR4Health: Findable, Accessible, Interoperable and Reusable data to foster Health Research

Due to the nature of health data, its sharing and reuse for research are limited by ethical, legal and technical barriers. The FAIR4Health project facilitated and promoted the application of FAIR principles in health research data, derived from the publicly funded health research initiatives to make them Findable, Accessible, Interoperable, and Reusable (FAIR). To confirm the feasibility of the FAIR4Health solution, we performed two pathfinder case studies to carry out federated machine learning algorithms on FAIRified datasets from five health research organizations. The case studies demonstrated the potential impact of the developed FAIR4Health solution on health outcomes and social care research. Finally, we promoted the FAIRified data to share and reuse in the European Union Health Research community, defining an effective EU-wide strategy for the use of FAIR principles in health research and preparing the ground for a roadmap for health research institutions. This scientific report presents a general overview of the FAIR4Health solution: from the FAIRification workflow design to translate raw data/metadata to FAIR data/metadata in the health research domain to the FAIR4Health demonstrators' performance.This research was financially supported by the European Union’s Horizon 2020 research and innovation programme under the grant agreement No 824666 (project FAIR4Health). Also, this research has been co-supported by the Carlos III National Institute of Health, through the IMPaCT Data project (code IMP/00019), and through the Platform for Dynamization and Innovation of the Spanish National Health System industrial capacities and their effective transfer to the productive sector (code PT20/00088), both co-funded by European Regional Development Fund (FEDER) ‘A way of making Europe’.Peer reviewe