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.

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

BACKGROUND: FAIR (findability, accessibility, interoperability, and reusability) guiding principles seek the reuse of data and other digital research input, output, and objects (algorithms, tools, and workflows that led to that data) making them findable, accessible, interoperable, and reusable. GO FAIR - a bottom-up, stakeholder driven and self-governed initiative - defined a seven-step FAIRification process focusing on data, but also indicating the required work for metadata. This FAIRification process aims at addressing the translation of raw datasets into FAIR datasets in a general way, without considering specific requirements and challenges that may arise when dealing with some particular types of data. OBJECTIVES: This scientific contribution addresses the architecture design of an open technological solution built upon the FAIRification process proposed by "GO FAIR" which addresses the identified gaps that such process has when dealing with health datasets. METHODS: A common FAIRification workflow was developed by applying restrictions on existing steps and introducing new steps for specific requirements of health data. These requirements have been elicited after analyzing the FAIRification workflow from different perspectives: technical barriers, ethical implications, and legal framework. This analysis identified gaps when applying the FAIRification process proposed by GO FAIR to health research data management in terms of data curation, validation, deidentification, versioning, and indexing. RESULTS: A technological architecture based on the use of Health Level Seven International (HL7) FHIR (fast health care interoperability resources) resources is proposed to support the revised FAIRification workflow. DISCUSSION: Research funding agencies all over the world increasingly demand the application of the FAIR guiding principles to health research output. Existing tools do not fully address the identified needs for health data management. Therefore, researchers may benefit in the coming years from a common framework that supports the proposed FAIRification workflow applied to health datasets. CONCLUSION: Routine health care datasets or data resulting from health research can be FAIRified, shared and reused within the health research community following the proposed FAIRification workflow and implementing technical architecture.

ABA is an essential signal for plant resistance to pathogens affecting JA biosynthesis and the activation of defenses in Arabidopsis.

Analyses of Arabidopsis thaliana defense response to the damping-off oomycete pathogen Pythium irregulare show that resistance to P. irregulare requires a multicomponent defense strategy. Penetration represents a first layer, as indicated by the susceptibility of pen2 mutants, followed by recognition, likely mediated by ERECTA receptor-like kinases. Subsequent signaling of inducible defenses is predominantly mediated by jasmonic acid (JA), with insensitive coi1 mutants showing extreme susceptibility. In contrast with the generally accepted roles of ethylene and salicylic acid cooperating with or antagonizing, respectively, JA in the activation of defenses against necrotrophs, both are required to prevent disease progression, although much less so than JA. Meta-analysis of transcriptome profiles confirmed the predominant role of JA in activation of P. irregulare-induced defenses and uncovered abscisic acid (ABA) as an important regulator of defense gene expression. Analysis of cis-regulatory sequences also revealed an unexpected overrepresentation of ABA response elements in promoters of P. irregulare-responsive genes. Subsequent infections of ABA-related and callose-deficient mutants confirmed the importance of ABA in defense, acting partly through an undescribed mechanism. The results support a model for ABA affecting JA biosynthesis in the activation of defenses against this oomycete.

Growth phase-dependent expression of the Pseudomonas putida KT2440 transcriptional machinery analysed with a genome-wide DNA microarray.

Bacterial transcriptional networks are built on a hierarchy of regulators, on top of which lie the components of the RNA polymerase (in particular the sigma factors) and the global control elements, which play a pivotal role. We have designed a genome-wide oligonucleotide-based DNA microarray for Pseudomonas putida KT2440. In combination with real-time reverse transcription polymerase chain reaction (RT-PCR), we have used it to analyse the expression pattern of the genes encoding the RNA polymerase subunits (the core enzyme and the 24 sigma factors), and various proteins involved in global regulation (Crc, Lrp, Fur, Anr, Fis, CsrA, IHF, HupA, HupB, HupN, BipA and several MvaT-like proteins), during the shift from exponential growth in rich medium into starvation and stress brought about by the entry into stationary phase. Expression of the genes encoding the RNA polymerase core and the vegetative sigma factor decreased in stationary phase, while that of sigma(S) increased. Data obtained for sigma(N), sigma(H), FliA and for the 19 extracytoplasmic function (ECF)-like sigma factors suggested that their mRNA levels change little upon entry into stationary phase. Expression of Crc, BipA, Fis, HupB, HupN and the MvaT-like protein PP3693 decreased in stationary phase, while that of HupA and the MvaT-like protein PP3765 increased significantly. Expression of IHF was indicative of post-transcriptional control. These results provide the first global study of the expression of the transcriptional machinery through the exponential stationary-phase shift in P. putida.

p73beta-Mediated apoptosis requires p57kip2 induction and IEX-1 inhibition.

Similarly to p53, p73alpha and p73beta induce growth arrest and/or apoptosis in response to DNA damage or when exogenously expressed. However, how they trigger apoptosis remains unresolved. After stable transduction of either p73alpha or p73beta, a greater apoptotic response was observed for p73beta in both primary and tumor cells. Consistently, blocking ectopic and endogenous p73beta expression by specific shRNA significantly decreased apoptotic levels after DNA damage. We found that p73beta targets the apoptotic program at multiple levels: (i) facilitating caspase activation through p53-dependent signals and (ii) inducing p57KIP2, while down-regulating c-IPA1 and IEX1 through a p53-independent mechanism. p73beta-mediated apoptosis was considerably reduced after inhibition of p57(KIP2) by small interfering RNA, IEX-1 overexpression, and in mouse embryo fibroblasts derived from p57-/- mice. Data from this study offer evidence for the apoptotic activity exclusive of p73beta. In the clinical context, these results might have potential therapeutic implications, because p73beta could induce alternative apoptotic responses in tumors harboring p53 mutations.