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Background Ownership of patient information in the context of Big Data is a relatively new problem, apparently not yet fully understood. There are not enough publications on the subject. Since the topic is interdisciplinary, incorporating legal, ethical, medical and aspects of information and communication technologies, a slightly more sophisticated analysis of the issue is needed. Aim To determine how the medical academic community perceives the issue of ownership of patient information in the context of Big Data. Methods Literature search for full text publications, indexed in PubMed, Springer, ScienceDirect and Scopus identified only 27 appropriate articles authored by academicians and corresponding to three focus areas: problem (ownership); area (healthcare); context (Big Data). Three major aspects were studied: scientific area of publications, aspects and academicians' perception of ownership in the context of Big Data. Results Publications are in the period 2014 - 2019, 37% published in health and medical informatics journals, 30% in medicine and public health, 19% in law and ethics; 78% authored by American and British academicians, highly cited. The majority (63%) are in the area of scientific research - clinical studies, access and use of patient data for medical research, secondary use of medical data, ethical challenges to Big data in healthcare. The majority (70%) of the publications discuss ownership in ethical and legal aspects and 67% see ownership as a challenge mostly to medical research, access control, ethics, politics and business. Conclusions Ownership of medical data is seen first and foremost as a challenge. Addressing this challenge requires the combined efforts of politicians, lawyers, ethicists, computer and medical professionals, as well as academicians, sharing these efforts, experiences and suggestions. However, this issue is neglected in the scientific literature. Publishing may help in open debates and adequate policy solutions. Key messages Ownership of patient information in the context of Big Data is a problem that should not be marginalized but needs a comprehensive attitude, consideration and combined efforts from all stakeholders. Overcoming the challenge of ownership may help in improving healthcare services, medical and public health research and the health of the population as a whole.

The ownership of patient information in the context of big data is a relatively new problem, which is not yet fully recognized by the medical academic community. The problem is interdisciplinary, incorporating legal, ethical, medical, and aspects of information and communication technologies, requiring a sophisticated analysis. However, no previous scoping review has mapped existing studies on the subject. This study aims to map and assess published studies on patient data ownership in the context of big data as viewed by the academic community. A scoping review was conducted based on the 5-stage framework outlined by Arksey and O'Malley and further developed by Levac, Colquhoun, and O'Brien. The organization and reporting of results of the scoping review were conducted according to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses and its extensions for Scoping Reviews). A systematic and comprehensive search of 4 scientific information databases, PubMed, ScienceDirect, Scopus, and Springer, was performed for studies published between January 2000 and October 2019. Two authors independently assessed the eligibility of the studies and the extracted data. The review included 32 eligible articles authored by academicians that correspond to 3 focus areas: problem (ownership), area (health care), and context (big data). Five major aspects were studied: the scientific area of publications, aspects and academicians' perception of ownership in the context of big data, proposed solutions, and practical applications for data ownership issues in the context of big data. The aspects in which publications consider ownership of medical data are not clearly distinguished but can be summarized as ethical, legal, political, and managerial. The ownership of patient data is perceived primarily as a challenge fundamental to conducting medical research, including data sales and sharing, and to a lesser degree as a means of control, problem, threat, and opportunity also in view of medical research. Although numerous solutions falling into 3 categories, technology, law, and policy, were proposed, only 3 real applications were discussed. The issue of ownership of patient information in the context of big data is poorly researched; it is not addressed consistently and in its integrity, and there is no consensus on policy decisions and the necessary legal regulations. Future research should investigate the issue of ownership as a core research question and not as a minor fragment among other topics. More research is needed to increase the body of knowledge regarding the development of adequate policies and relevant legal frameworks in compliance with ethical standards. The combined efforts of multidisciplinary academic teams are needed to overcome existing gaps in the perception of ownership, the aspects of ownership, and the possible solutions to patient data ownership issues in the reality of big data.

Per- and polyfluoroalkyl substances (PFAS) hepatotoxicity is well documented, especially for legacy compounds such as PFHxS, PFOA, PFOS, and PFNA. However, the mechanism(s) involved are yet to be fully understood. The present study aims to investigate the origin of PFAS-induced formation of reactive oxygen species (ROS) and their relevance for the decrease of cell viability of HepG2 cells after exposure to PFASs. Moreover, a structure–activity relationship was assessed using PFASs with different headgroups (carboxylic, sulfonic, and alcoholic) and variable carbon-chain lengths (4–10 C). The link between ROS generation and cell viability was assessed using two antioxidants: quercetin, a generic antioxidant, and mito-tempo, a mitochondria-targeted antioxidant. Both antioxidants were demonstrated to be effective in reducing PFAS-induced ROS generation. The mechanism behind PFAS-induced ROS might be headgroup-dependent, as quercetin increased cell viability after both perfluoroalkyl carboxylic acids (PFCA) and perfluorosulfonic acids (PFSA) exposure, while mito-tempo only improved cell viability after PFCAs exposure. The two major sources of ROS generation in HepG2 cells are the peroxisomes and mitochondria. However, exposure to PFASs did not impact peroxisomal or mitochondrial activity after 24 h. Uncommon sources of ROS generation, such as lysosomal leakage or lipid peroxidation, have been demonstrated to result from previously generated ROS and not from PFASs exposure. Indeed, lysosomal leakage caused by PFASs exposure is negated by either quercetin or mito-tempo treatment, while lipid peroxidation only occurs after 24 h of exposure, long after the initial ROS generation by PFASs. This indicates that both events are a result of previously generated ROS. However, exposure to both PFOA and PFOS was demonstrated to reduce catalase activity in HepG2. In conclusion, the present study demonstrates that ROS generation after PFASs exposure might be due to inhibition of HepG2 endogenous antioxidants. Moreover, a headgroup-dependent mechanism of action has been observed, indicating that PFCAs and PFSAs exposure might lead to hepatotoxicity through different pathways.

SARS-CoV-2 vaccination is effective in preventing severe Covid-19, but efficacy in reducing viral load and transmission wanes over time. In addition, the emergence of novel SARS-CoV-2 variants increases the threat of uncontrolled dissemination and additional antiviral therapies are urgently needed for effective containment. In previous in vitro studies Echinacea purpurea demonstrated strong antiviral activity against enveloped viruses, including SARS-CoV-2. In this study, we examined the potential of Echinacea purpurea in preventing and treating respiratory tract infections (RTIs) and in particular, SARS-CoV-2 infections. 120 healthy volunteers (m,f, 18—75 years) were randomly assigned to Echinacea prevention or control group without any intervention. After a run-in week, participants went through 3 prevention cycles of 2, 2 and 1 month with daily 2,400 mg Echinacea purpurea extract (Echinaforce ® , EF). The prevention cycles were interrupted by breaks of 1 week. Acute respiratory symptoms were treated with 4,000 mg EF for up to 10 days, and their severity assessed via a diary. Naso/oropharyngeal swabs and venous blood samples were routinely collected every month and during acute illnesses for detection and identification of respiratory viruses, including SARS-CoV-2 via RT-qPCR and serology. Summarized over all phases of prevention, 21 and 29 samples tested positive for any virus in the EF and control group, of which 5 and 14 samples tested SARS-CoV-2 positive (RR = 0.37, Chi-square test, p = 0.03). Overall, 10 and 14 symptomatic episodes occurred, of which 5 and 8 were Covid-19 (RR = 0.70, Chi-square test, p > 0.05). EF treatment when applied during acute episodes significantly reduced the overall virus load by at least 2.12 log 10 or approx. 99% ( t -test, p < 0.05), the time to virus clearance by 8.0 days for all viruses (Wilcoxon test, p = 0.02) and by 4.8 days for SARS-CoV-2 ( p > 0.05) in comparison to control. Finally, EF treatment significantly reduced fever days (1 day vs 11 days, Chi-square test, p = 0.003) but not the overall symptom severity. There were fewer Covid-19 related hospitalizations in the EF treatment group ( N = 0 vs N = 2). EF exhibited antiviral effects and reduced the risk of viral RTIs, including SARS-CoV-2. By substantially reducing virus loads in infected subjects, EF offers a supportive addition to existing mandated treatments like vaccinations. Future confirmatory studies are warranted.

This thematic section focuses on health as a multilayered political, economic, and cultural phenomenon. Based on case studies from Southeastern Europe, the four articles in the section pose research questions that are important for understanding the interplay between personal experiences of using healthcare services, trust in the healthcare system, and the governance of healthcare service provision in the region. The articles build on complementary perspectives on individual experiences of interacting with healthcare providers, social issues, and public health strategies, drawing a multidimensional “health map” with interrelated but sometimes diverging arguments. This allows a better understanding of the issues of health and illness in turbulent times of social crises and provides a conceptual basis for healthcare policies in Southeastern Europe.

Drug-induced liver injury (DILI) is associated with high mortality risk. However, no biomarker can reliably predict outcome. In order to identify baseline parameters that are associated with mortality the data of 268 prospectively collected DILI patients were analyzed. Multivariate logistic regression and receiver operating characteristic curves were used to identify the parameters being most predictive for a fatal outcome, as defined by orthotopic liver transplantation (OLT) or death. 10.4% of patients had a fatal outcome, which was associated with higher levels of transaminases, total bilirubin, INR and model for end-stage liver disease (MELD) scores (25 vs. 12, p  < 0.001). Multivariate analysis revealed that only MELD and aspartate aminotransferase (AST) were independently associated with a poor outcome, the MELD score in particular had an extraordinarily high c-statistic of 0.93 (95% CI: 0.87–0.97). At a cut-off of ≥ 20, MELD could predict a fatal outcome with a sensitivity and specificity of 88% and 81%. The predictive performance of the MELD score could even be enhanced by combing it with AST elevation: At a cut-off of ≥ 20 and ≥ 29.6xULN, respectively, positive and negative predictive values of 44% and 96% were observed, which were higher than for any other baseline parameter.

Climate models' outputs are affected by biases that need to be detected and adjusted to model climate impacts. Many climate hazards and climate-related impacts are associated with the interaction between multiple drivers, i.e. by compound events. So far climate model biases are typically assessed based on the hazard of interest, and it is unclear how much a potential bias in the dependence of the hazard drivers contributes to the overall bias and how the biases in the drivers interact. Here, based on copula theory, we develop a multivariate bias-assessment framework, which allows for disentangling the biases in hazard indicators in terms of the underlying univariate drivers and their statistical dependence. Based on this framework, we dissect biases in fire and heat stress hazards in a suite of global climate models by considering two simplified hazard indicators: the wet-bulb globe temperature (WBGT) and the Chandler burning index (CBI). Both indices solely rely on temperature and relative humidity. The spatial pattern of the hazard indicators is well represented by climate models. However, substantial biases exist in the representation of extreme conditions, especially in the CBI (spatial average of absolute bias: 21 ∘C) due to the biases driven by relative humidity (20 ∘C). Biases in WBGT (1.1 ∘C) are small compared to the biases driven by temperature (1.9 ∘C) and relative humidity (1.4 ∘C), as the two biases compensate for each other. In many regions, also biases related to the statistical dependence (0.85 ∘C) are important for WBGT, which indicates that well-designed physically based multivariate bias adjustment procedures should be considered for hazards and impacts that depend on multiple drivers. The proposed compound-event-oriented evaluation of climate model biases is easily applicable to other hazard types. Furthermore, it can contribute to improved present and future risk assessments through increasing our understanding of the biases' sources in the simulation of climate impacts.

Cancerous and precancerous skin conditions occupy one of the leading places in oncology. Early detection of suspects and temporary referrals to a specialist are critical to successful treatment. Numerous optical techniques are used for obtaining a new data from cutaneous neoplasia. Diffuse–reflectance spectroscopy is one of these techniques due to its high sensitivity in detecting subtle tissue alterations. Light scattering events inside the skin tissues change significantly in the development stage of skin lesions. These changes in the tissue scattering properties affect the diffuse reflectance spectrum and provide classification of different skin lesions based on diffuse reflectance measurements. We have investigated diffuse–reflectance spectroscopy for diagnostic of skin lesions and as a result, an optical device for clinical application was developed. The current study shows the obtained results by the prototype device for the reflective ability of pigmented and non-pigmented skin benign, dysplastic, and malignant cutaneous lesions in vivo.