BackgroundResearch into rare diseases is becoming more common, with recognition of the significant diagnostic and therapeutic care gaps. Registries are considered a key research methodology to address rare diseases. This report describes the structure of the Rare UK Diseases Study (RUDY) platform that aims to improve research processes and address many of the challenges of carrying out rare musculoskeletal disease research.RUDY is an internet-based platform with online registration, initial verbal consent, online capture of patient reported outcome measures and events within a dynamic consent framework. The database structure, security and governance framework are described.ResultsThere have been 380 participants recruited into RUDY with completed questionnaire rates in excess of 50 %. There has been one withdrawal and two participants have amended their consent options.ConclusionsThe strengths of RUDY include low burden for the clinical team, low research administration costs with high participant recruitment and ease of data collection and access. This platform has the potential to be used as the model for other rare diseases globally.

BackgroundHealth-related quality of life of adults with osteogenesis imperfecta (OI), fibrous dysplasia (FD) and X-linked hypophosphatemia (XLH) remains poorly described. The aim of this study was to describe the HRQoL of adults with osteogenesis imperfecta, fibrous dysplasia and X-linked hypophophataemia and perform a cost-utility simulation to calculate the maximum cost that a health care system would be willing to pay for a hypothetical treatment of a rare bone disease.ResultsParticipants completed the EQ-5D-5 L questionnaire between September 2014 and March 2016. For the economic simulation, we considered a hypothetical treatment that would be applied to OI participants in the lower tertile of the health utility score.A total of 109 study participants fully completed the EQ-5D-5 L questionnaire (response rate 63%). Pain/discomfort was the most problematic domain for participants with all three diseases (FD 31%, XLH 25%, OI 16%).The economic simulation identified an expected treatment impact of +2.5 QALYs gained per person during the 10-year period, which led to a willing to pay of £14,355 annually for a health care system willing to pay up to £50,000 for each additional QALY gained by an intervention.ConclusionsThis is the first study to quantitatively measure and compare the HRQoL of adults with OI, FD and XLH and the first to use such data to conduct an economic simulation leading to healthcare system willingness-to-pay estimates for treatment of musculoskeletal rare diseases at various cost-effectiveness thresholds.Electronic supplementary materialThe online version of this article (doi:10.1186/s13023-016-0538-4) contains supplementary material, which is available to authorized users.

Selectfluor, one of the most reactive and commonly used electrophilic fluorinating N–F reagents, has been radiolabeled with 18F. The resulting new [18F]‐labeled N–F reagent is safe, nontoxic, and easy to handle. The combined use of [18F]Selectfluor bis(triflate) and AgOTf allows for the preparation of electron‐rich 18F‐aromatic compounds through a simple “shake and mix” protocol at room temperature (see scheme; SA=specific activtiy).

Genome-Wide Association Study (GWAS) Higher Blood pressure Arthritides Neuropsychiatric conditions Malignancies Lower Anaemias Lipidaemias Ischaemic heart disease Genetically higher central obesity Highlights Variants in HFE and TMPRSS6 are associated with higher liver iron. There is genetic evidence that higher central obesity causes higher liver iron. Liver iron variants are not organ specific and associate with multiple diseases.

Dynamic consent has been discussed in theory as a way to show user preferences being taken into account when data is accessed and shared for research purposes. The mechanism is grounded in principles of revocation and engagement-participants may withdraw or edit their permissions at any time, and they receive feedback on the project they are contributing to if they have chosen to do so. The level of granular control offered by dynamic consent means that individuals have informational control over what they are sharing with the study, and to what extent that data can be used further. Rather than attempt to redefine privacy, this paper takes the position that data controllers have certain obligations to protect a data subject's information and must show trustworthy behaviour to encourage research participation. Our model of privacy is grounded in normative, transaction-based requirements. We argue that dynamic consent is a mechanism that offers data controllers a way to evidence compliance with individual privacy preferences, and data subjects with control as and when they require it. The key difference between dynamic consent and a "rich" database consisting of a dataset with the ability for a subject to revoke access is human engagement, or relations of trust. We must rethink how consent is implemented from the top-down (policy-based) and bottom up (technical architecture) to develop useful privacy controls.