The University of Manchester (UoM) bid for phase 5 of MRC Confidence in Concept (CiC) funding
Lead Research Organisation:
University of Manchester
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Technical Summary
The Confidence in Concept scheme is a key part of MRC’s translational research strategy and provides annual awards to institutions, to be used flexibly to support the earliest stages of multiple translational research projects. The award can be used by the institution to support a number of preliminary-stage translational projects. The projects supported should aim to provide sufficient preliminary data to establish the viability of an approach –– before seeking more substantive funding. It is intended to accelerate the transition from discovery research to translational development projects by supporting preliminary work or feasibility studies to establish the viability of an approach.
Publications
Arendsen LJ
(2020)
Entraining Alpha Activity Using Visual Stimulation in Patients With Chronic Musculoskeletal Pain: A Feasibility Study.
in Frontiers in neuroscience
Arno MC
(2020)
Exploiting the role of nanoparticle shape in enhancing hydrogel adhesive and mechanical properties.
in Nature communications
Bahri R
(2018)
Mast cell activation test in the diagnosis of allergic disease and anaphylaxis.
in The Journal of allergy and clinical immunology
Conroy P
(2018)
Report on a novel treatment approach to aphasia: time for a quick word?
in British Journal of Neuroscience Nursing
Conroy P
(2018)
Time for a quick word? The striking benefits of training speed and accuracy of word retrieval in post-stroke aphasia.
in Brain : a journal of neurology
Heald A
(2020)
Application of SWATH mass spectrometry in the identification of circulating proteins does not predict future weight gain in early psychosis.
in Clinical proteomics
Murray PG
(2018)
Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency.
in JCI insight
| Description | Gene Expression Data and Diagnosis of GHD - Presentations at British Society for Paediatric Endocrinology |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Presentations at British Society for Paediatric Endocrinology - won best clinical abstract award. Data presented at NovoNordisk meeting on GH in Copenhagan and we will be including an element of our transcriptomic research into two upcoming industry studies on long acting growth hormone (REAL4 and REAL5). |
| Year(s) Of Engagement Activity | 2018 |