The UMN has witnessed unprecedented growth in biomedical research. To improve human health, our clinical and translational science institute (CTSI) will: (1) create a flexible academic infrastructure to coordinate and integrate clinical translational science (CTS) research; (2) foster transparent interactions between UMN and the community; and (3) train and reward CTS interdisciplinary UMN and community teams. Integrated functions and UMN-wide cores include the: (1) Education, Training and Research Career Development Program, supporting CTS research trainees and junior faculty with learner-tailored curricula; (2) Office of Discovery and Translation, accelerating bench-to-bedside translation and commercialization; and (3) Office of Community Engagement for Health, partnering statewide communities and UMN research. Our Biomedical Informatics Function integrates and networks clinical data and bio-specimen resources and cross-CTSI informatics infrastructure, provides training for future informatics scholars, and engages the CTS research community. Our CTSI operates on a platform accessed by an easy access entry (Front Door). Junior investigators will be vigorously supported by: (1) basic science, Tl and T2/T3 Project Development Teams; (2) rapid allocation of junior investigator-dedicated and general pilot funds; and (3) no cost access to (a) all research project managers with preferential assignment to a junior faculty specialist, (b) consultations from the service platform and (c) a junior investigator-dedicated biostatistics advisory team. All CTS mentors will be incentivized, investigators can access general pilot funds, and 3 champions will be supported. For the first time, the Community University Board will engage the UMN and community to discuss high impact health issues. By leveraging CTSA funds, strategic UMN and State investments, our community and major statewide healthcare partner support, electronic networks, special and rural community populations, MN Department of Health, the Mayo Clinic and CTSA collaborators, our CTSI will have a statewide impact on workforce training, healthcare outcomes, and policy. With award of CTSA funds, our innovative CTSI is poised to achieve our long-term goal of better health for individuals, communities, our state, and the world.
The UMN CTSI will improve the health of Minnesotans through CTS research by transforming the relationships among UMN, the community, and the State. Concrete partnerships will facilitate CTS discovery, translation, and knowledge dissemination. Interdisciplinary CTS research teams will be trained using new educational programs and rewarded to meet UMN and identified community needs to impact people's health.
| Lin, Lucy Q; Kazmirczak, Felipe; Chen, Ko-Hsuan Amy et al. (2018) Impact of Cardiovascular Magnetic Resonance Imaging on Identifying the Etiology of Cardiomyopathy in Patients Undergoing Cardiac Transplantation. Sci Rep 8:16212 |
| Clark, Christopher R; Maile, Makayla; Blaney, Patrick et al. (2018) Transposon mutagenesis screen in mice identifies TM9SF2 as a novel colorectal cancer oncogene. Sci Rep 8:15327 |
| Misono, Stephanie; Haut, Caroline; Meredith, Liza et al. (2018) Dysphonia, Perceived Control, and Psychosocial Distress: A Qualitative Study. J Voice : |
| Reddy, Prajwal; Birkenbach, Mark; Shenoy, Chetan (2018) Chest Pain and a Very Abnormal Stress Echocardiogram. Circulation 138:1899-1903 |
| Lock, Eric F (2018) Tensor-on-tensor regression. J Comput Graph Stat 27:638-647 |
| Lock, Eric F; Li, Gen (2018) Supervised multiway factorization. Electron J Stat 12:1150-1180 |
| Shivappa, Nitin; Blair, Cindy K; Prizment, Anna E et al. (2018) Dietary inflammatory index and risk of renal cancer in the Iowa Women's Health Study. Eur J Nutr 57:1207-1213 |
| Hart, A; Smith, J M; Skeans, M A et al. (2018) OPTN/SRTR 2016 Annual Data Report: Kidney. Am J Transplant 18 Suppl 1:18-113 |
| Bedna?ík, Petr; Tká?, Ivan; Giove, Federico et al. (2018) Neurochemical responses to chromatic and achromatic stimuli in the human visual cortex. J Cereb Blood Flow Metab 38:347-359 |
| Lock, Eric F; Kohli, Nidhi; Bose, Maitreyee (2018) Detecting Multiple Random Changepoints in Bayesian Piecewise Growth Mixture Models. Psychometrika 83:733-750 |
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