ObjectivesWe examined major issues associated with sharing of individual clinical trial data and developed a consensus document on providing access to individual participant data from clinical trials, using a broad interdisciplinary approach.Design and methodsThis was a consensus-building process among the members of a multistakeholder task force, involving a wide range of experts (researchers, patient representatives, methodologists, information technology experts, and representatives from funders, infrastructures and standards development organisations). An independent facilitator supported the process using the nominal group technique. The consensus was reached in a series of three workshops held over 1 year, supported by exchange of documents and teleconferences within focused subgroups when needed. This work was set within the Horizon 2020-funded project CORBEL (Coordinated Research Infrastructures Building Enduring Life-science Services) and coordinated by the European Clinical Research Infrastructure Network. Thus, the focus was on non-commercial trials and the perspective mainly European.OutcomeWe developed principles and practical recommendations on how to share data from clinical trials.ResultsThe task force reached consensus on 10 principles and 50 recommendations, representing the fundamental requirements of any framework used for the sharing of clinical trials data. The document covers the following main areas: making data sharing a reality (eg, cultural change, academic incentives, funding), consent for data sharing, protection of trial participants (eg, de-identification), data standards, rights, types and management of access (eg, data request and access models), data management and repositories, discoverability, and metadata.ConclusionsThe adoption of the recommendations in this document would help to promote and support data sharing and reuse among researchers, adequately inform trial participants and protect their rights, and provide effective and efficient systems for preparing, storing and accessing data. The recommendations now need to be implemented and tested in practice. Further work needs to be done to integrate these proposals with those from other geographical areas and other academic domains.
Messenger RNA transcripts of the highly pigmented murine melanoma B16-F1 cells were compared with those from their weakly pigmented derivative B16-F1O cells by differential display. A novel gene called msgl (melanocyte-specific gene) was found to be expressed at high levels in B16-F1 cells but at low levels in B16-F1O cells. Expression of msgl was undetectable in the amelanotic K1735 murine melanoma cells. The pigmented murine melanocyte cell line melan-a expressed msgl, as did pigmented primary cultures of murine and human melanocytes; however, seven amelanotic or very weakly pigmented human melanoma cell lines were negative. Transformation of murine melanocytes by transfection with v-Ha-ras orEla was accompanied by depigmentation and led to complete loss ofmsgl expression. The normal tissue distribution of msgl mRNA transcripts in adult mice was confined to melanocytes and testis. Murine msgl and human MSG] genes encode a predicted protein of 27 kDa with 75% overall amino acid identity and 96% identity within the C-terminal acidic domain of 54 amino acids. This C-terminal domain was conserved with 76% amino acid identity in another protein product of a novel human gene, MRGI (msgl-related gene), isolated from normal human melanocyte cDNA by 5'-rapid amplification of cDNA ends based on the homology to msgl. The msgl protein was localized to the melanocyte nucleus by immunofluorescence cytochemistry. We conclude that msgl encodes a nuclear protein, is melanocyte-specific, and appears to be lost in depigmented melanoma cells.
This article presents a practical roadmap for scholarly data repositories to implement data citation in accordance with the Joint Declaration of Data Citation Principles, a synopsis and harmonization of the recommendations of major science policy bodies. The roadmap was developed by the Repositories Expert Group, as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of FORCE11.org and the NIH-funded BioCADDIE ( https://biocaddie.org ) project. The roadmap makes 11 specific recommendations, grouped into three phases of implementation: a) required steps needed to support the Joint Declaration of Data Citation Principles, b) recommended steps that facilitate article/data publication workflows, and c) optional steps that further improve data citation support provided by data repositories. We describe the early adoption of these recommendations 18 months after they have first been published, looking specifically at implementations of machine-readable metadata on dataset landing pages.
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