The known challenge of underutilization of data and biological material from biorepositories as potential resources for medical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability-entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)-are likely to address only parts of the problem. In this article, we argue that biological material and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks. We propose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently.

• MeSH
• Biological Specimen Banks * organization & administration   standards   MeSH
• Databases, Factual standards   MeSH
• Confidentiality standards   MeSH
• Humans MeSH
• Information Dissemination methods   MeSH
• Guidelines as Topic MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Review MeSH

• MeSH
• Documentation MeSH
• Health Services Accessibility MeSH
• Confidentiality MeSH
• Health Care Economics and Organizations MeSH
• Delivery of Health Care, Integrated MeSH
• Personally Identifiable Information MeSH
• Public Health Informatics MeSH
• Health Policy MeSH
• Health Information Systems MeSH

• Conspectus
• Veřejné zdraví a hygiena
• NML Fields
• veřejné zdravotnictví
• ekonomie, ekonomika, ekonomika zdravotnictví
• NML Publication type
• studie

There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body.

• MeSH
• Neurosciences * MeSH
• Reproducibility of Results MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Research Support, N.I.H., Extramural MeSH

Electronic Health Record (EHR) systems currently in use are not designed for widely interoperable longitudinal health data. Therefore, EHR data cannot be properly shared, managed and analyzed. In this article, we propose two approaches to making EHR data more comprehensive and FAIR (Findable, Accessible, Interoperable, and Reusable) and thus more useful for diagnosis and clinical research. Firstly, the data modeling based on the LinkML framework makes the data interoperability more realistic in diverse environments with various experts involved. We show the first results of how diverse health data can be integrated based on an easy-to-understand data model and without loss of available clinical knowledge. Secondly, decentralizing EHRs contributes to the higher availability of comprehensive and consistent EHR data. We propose a technology stack for decentralized EHRs and the reasons behind this proposal. Moreover, the two proposed approaches empower patients because their EHR data can become more available, understandable, and usable for them, and they can share their data according to their needs and preferences. Finally, we explore how the users of the proposed solution could be involved in the process of its validation and adoption.

• MeSH
• Data Management MeSH
• Electronic Health Records * MeSH
• Humans MeSH
• Semantic Web * MeSH
• Software MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

We argue that statistical practice in the social and behavioural sciences benefits from transparency, a fair acknowledgement of uncertainty and openness to alternative interpretations. Here, to promote such a practice, we recommend seven concrete statistical procedures: (1) visualizing data; (2) quantifying inferential uncertainty; (3) assessing data preprocessing choices; (4) reporting multiple models; (5) involving multiple analysts; (6) interpreting results modestly; and (7) sharing data and code. We discuss their benefits and limitations, and provide guidelines for adoption. Each of the seven procedures finds inspiration in Merton's ethos of science as reflected in the norms of communalism, universalism, disinterestedness and organized scepticism. We believe that these ethical considerations-as well as their statistical consequences-establish common ground among data analysts, despite continuing disagreements about the foundations of statistical inference.

• MeSH
• Data Interpretation, Statistical MeSH
• Humans MeSH
• Uncertainty MeSH
• Information Dissemination MeSH
• Models, Statistical MeSH
• Statistics as Topic * methods   standards   MeSH
• Research Design standards   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH

IMPORTANCE: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. OBJECTIVE: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. MAIN OUTCOMES AND MEASURES: Interregional profiles of group difference in cortical thickness between cases and controls. RESULTS: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders. CONCLUSIONS AND RELEVANCE: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

• MeSH
• Principal Component Analysis MeSH
• Bipolar Disorder diagnostic imaging   pathology   MeSH
• Depressive Disorder, Major diagnostic imaging   pathology   MeSH
• Child MeSH
• Adult MeSH
• Gene Expression physiology   MeSH
• Attention Deficit Disorder with Hyperactivity diagnostic imaging   pathology   MeSH
• Cohort Studies MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging MeSH
• Adolescent MeSH
• Young Adult MeSH
• Cerebral Cortex cytology   diagnostic imaging   growth & development   pathology   MeSH
• Obsessive-Compulsive Disorder diagnostic imaging   pathology   MeSH
• Autism Spectrum Disorder diagnostic imaging   pathology   MeSH
• Child, Preschool MeSH
• Schizophrenia diagnostic imaging   pathology   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Case-Control Studies MeSH
• Computational Biology MeSH
• Human Development physiology   MeSH
• Fetal Development physiology   MeSH
• Check Tag
• Child MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Male MeSH
• Child, Preschool MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

There are global movements aiming to promote reform of the traditional research evaluation and reward systems. However, a comprehensive picture of the existing best practices and efforts across various institutions to integrate Open Science into these frameworks remains underdeveloped and not fully known. The aim of this study was to identify perceptions and expectations of various research communities worldwide regarding how Open Science activities are (or should be) formally recognised and rewarded. To achieve this, a global survey was conducted in the framework of the Research Data Alliance, recruiting 230 participants from five continents and 37 countries. Despite most participants reporting that their organisation had one form or another of formal Open Science policies, the majority indicated that their organisation lacks any initiative or tool that provides specific credits or rewards for Open Science activities. However, researchers from France, the United States, the Netherlands and Finland affirmed having such mechanisms in place. The study found that, among various Open Science activities, Open or FAIR data management and sharing stood out as especially deserving of explicit recognition and credit. Open Science indicators in research evaluation and/or career progression processes emerged as the most preferred type of reward.

• MeSH
• Internationality * MeSH
• Humans MeSH
• Surveys and Questionnaires MeSH
• Research Personnel psychology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

• MeSH
• Health Status Disparities MeSH
• Health Services Accessibility MeSH
• Health Care Economics and Organizations MeSH
• Socioeconomic Factors MeSH
• Public Health MeSH
• Health Policy MeSH
• Health Planning MeSH
• Publication type
• News MeSH
• Geographicals
• Europe MeSH

• Conspectus
• Veřejné zdraví a hygiena
• NML Fields
• veřejné zdravotnictví
• NML Publication type
• publikace WHO

BACKGROUND: The European Reference Networks, ERNs, are virtual networks for healthcare providers across Europe to collaborate and share expertise on complex or rare diseases and conditions. As part of the ERNs, the Clinical Patient Management System, CPMS, a secure digital platform, was developed to allow and facilitate web-based, clinical consultations between submitting clinicians and relevant international experts. The European Reference Network on Intellectual Disability, TeleHealth and Congenital Anomalies, ERN ITHACA, was formed to harness the clinical and diagnostic expertise in the sector of rare, multiple anomaly and/or intellectual disability syndromes, chromosome disorders and undiagnosed syndromic disorders. We present the first year results of CPMS use by ERN ITHACA as an example of a telemedicine strategy for the diagnosis and management of patients with rare developmental disorders. RESULTS: ERN ITHACA ranked third in telemedicine activity amongst 24 European networks after 12 months of using the CPMS. Information about 28 very rare cases from 13 different centres across 7 countries was shared on the platform, with diagnostic or other management queries. Early interaction with patient support groups identified data protection as of primary importance in adopting digital platforms for patient diagnosis and care. The first launch of the CPMS was built to accommodate the needs of all ERNs. The ERN ITHACA telemedicine process highlighted a need to customise the CPMS with network-specific requirements. The results of this effort should enhance the CPMS utility for telemedicine services and ERN-specific care outcomes. CONCLUSIONS: We present the results of a long and fruitful process of interaction between the ERN ITHACA network lead team and EU officials, software developers and members of 38 EU clinical genetics centres to organise and coordinate direct e-healthcare through a secure, digital platform. The variability of the queries in just the first 28 cases submitted to the ERN ITHACA CPMS is a fair representation of the complexity and rarity of the patients referred, but also proof of the sophisticated and variable service that could be provided through a structured telemedicine approach for patients and families with rare developmental disorders. Web-based approaches are likely to result in increased accessibility to clinical genomic services.

• MeSH
• Child MeSH
• Humans MeSH
• Delivery of Health Care MeSH
• Telemedicine * MeSH
• Developmental Disabilities MeSH
• Rare Diseases * diagnosis   therapy   MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Europe MeSH

• MeSH
• Long-Term Care statistics & numerical data   MeSH
• Home Nursing trends   MeSH
• Costs and Cost Analysis MeSH
• Respite Care MeSH
• Aged MeSH
• Socioeconomic Factors MeSH
• Aging MeSH
• Check Tag
• Aged MeSH

• Conspectus
• Veřejné zdraví a hygiena
• NML Fields
• ekonomie, ekonomika, ekonomika zdravotnictví
• demografie
• veřejné zdravotnictví
• NML Publication type
• studie