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2. Speed-Up of DNA Melting Algorithm with Complete Nearest Neighbor Properties

Author

Tostesen, E., Liu, F., Jenssen, T. -K., and Hovig, E.

Subjects
Quantitative Biology - Biomolecules
Abstract

We describe a faster and more accurate algorithm for computing the statistical mechanics of DNA denaturation according to the Poland-Scheraga type. Nearest neighbor thermodynamics is included in a complete and general way. The algorithm represents an optimization with respect to algorithmic complexity of the partition function algorithm of Yeramian et al.: We reduce the computation time for a base-pairing probability profile from O(N2) to O(N). This speed-up comes in addition to the speed-up due to a multiexponential approximation of the loop entropy factor as introduced by Fixman and Freire. The speed-up, however, is independent of the multiexponential approximation and reduces time from O(N3) to O(N2) in the exact case. In addition to calculating the standard base-pairing probability profiles, we propose to use the algorithm to calculate various other probabilities (loops, helices, tails) for a more direct view of the melting regions and their positions and sizes., Comment: 20 pages, 4 figures

Published
2004
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5. Plasma levels of marine n-3 fatty acids and cardiovascular risk markers in renal transplant recipients

Author

Eide, I.A., Dahle, D.O., Svensson, M., Hartmann, A., Asberg, A., Bjerve, K.S., Christensen, J.H., Schmidt, E.B., Lauritsen, M.E., Lund, K., and Jenssen, T.

Subjects
Kidneys -- Transplantation, Fatty acids -- Health aspects, Cardiovascular diseases -- Risk factors, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVES: Cardiovascular (CV) disease is the leading cause of death after renal transplantation. Marine n-3 polyunsaturated fatty acids (PUFAs) exert potential cardio-protective metabolic effects and might reduce CV morbidity and mortality in renal transplant recipients (RTRs). SUBJECTS/METHODS: In this cross-sectional study of 1990 Norwegian RTRs, transplanted between 1999 and 2011, associations between plasma phospholipid marine n-3 PUFA levels and various CV risk markers at 10 weeks after transplant were evaluated. RESULTS: Higher plasma marine n-3 PUFA levels were associated with lower resting heart rate (rHR), lower fasting plasma glucose (fPG) levels, lower plasma triglyceride levels and higher plasma high-density lipoprotein (HDL) cholesterol levels. Plasma levels of eicosapentaenoic acid, but not docosahexaenoic acid, showed a positive association with plasma HDL cholesterol levels. Plasma marine n-3 PUFA levels were not associated with plasma low-density lipoprotein cholesterol levels, pulse wave velocity or systolic and diastolic blood pressure. A negative association between plasma marine n-3 PUFA levels and CV mortality was weakened by additional adjustment for plasma triglyceride levels and rHR. The ratio of n-6 to n-3 PUFAs showed similar associations with CV risk markers as absolute plasma marine n-3 PUFA levels. CONCLUSIONS: This is the first study in RTRs showing that marine n-3 PUFAs are negatively associated with rHR and fPG in addition to beneficial effects on plasma HDL cholesterol and triglyceride levels. Especially, effects on autonomic nervous function and triglyceride metabolism might contribute to explain the lower CV mortality risk with higher plasma marine n-3 PUFA levels previously shown in this cohort. European Journal of Clinical Nutrition (2016) 70, 824-830; doi: 10.1038/ejcn.2016.14; published online 2 March 2016, INTRODUCTION Cardiovascular (CV) disease is the leading cause of death after renal transplantation, (1) and the CV mortality rate is twice that of the general population. (2) Traditional CV risk [...]

Published
2016
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12. Proceedings From an International Consensus Meeting on Posttransplantation Diabetes Mellitus: Recommendations and Future Directions

Author

Sharif, A., Hecking, M., de Vries, A. P. J., Porrini, E., Hornum, M., Rasoul-Rockenschaub, S., Berlakovich, G., Krebs, M., Kautzky-Willer, A., Schernthaner, G., Marchetti, P., Pacini, G., Ojo, A., Takahara, S., Larsen, J. L., Budde, K., Eller, K., Pascual, J., Jardine, A., Bakker, S. J. L., Valderhaug, T. G., Jenssen, T. G., Cohney, S., and Säemann, M. D.

Published
2014
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31. Updated risk factors should be used to predict development of diabetes

Author

Bethel, M, Hyland, K, Chacra, A, Deedwania, P, Fulcher, G, Holman, R, Jenssen, T, Levitt, N, McMurray, J, Boutati, E, Thomas, L, Sun, J, Haffner, S, and Group, NAVIGATOR Study

Subjects
Blood Glucose, Male, Diabetic Cardiomyopathies, Endocrinology, Diabetes and Metabolism, Type 2 diabetes, 030204 cardiovascular system & hematology, Nateglinide, Global Health, Impaired glucose tolerance, 0302 clinical medicine, Endocrinology, Health Transition, Risk Factors, fasting plasma glucose, 030212 general & internal medicine, Randomized Controlled Trials as Topic, post-prandial glucose, Incidence, Combined Modality Therapy, Cardiovascular Diseases, Practice Guidelines as Topic, Disease Progression, Female, type 2 diabetes, medicine.drug, medicine.medical_specialty, diabetes risk prediction, Diabetes risk, Population health, Models, Biological, Prediabetic State, 03 medical and health sciences, Internal medicine, Diabetes mellitus, Internal Medicine, medicine, Humans, Healthy Lifestyle, Time point, Proportional Hazards Models, business.industry, Glucose Tolerance Test, medicine.disease, impaired glucose tolerance, Diabetes Mellitus, Type 2, Emergency medicine, Outcomes research, business, Diabetic Angiopathies, Follow-Up Studies
Abstract

Aims Predicting incident diabetes could inform treatment strategies for diabetes prevention, but the incremental benefit of recalculating risk using updated risk factors is unknown. We used baseline and 1-year data from the Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) Trial to compare diabetes risk prediction using historical or updated clinical information. Methods Among non-diabetic participants reaching 1 year of follow-up in NAVIGATOR, we compared the performance of the published baseline diabetes risk model with a “landmark” model incorporating risk factors updated at the 1-year time point. The C-statistic was used to compare model discrimination and reclassification analyses to demonstrate the relative accuracy of diabetes prediction. Results A total of 7527 participants remained non-diabetic at 1 year, and 2375 developed diabetes during a median of 4 years of follow-up. The C-statistic for the landmark model was higher (0.73 [95% CI 0.72–0.74]) than for the baseline model (0.67 [95% CI 0.66–0.68]). The landmark model improved classification to modest (40%) 4-year risk, with a net reclassification index of 0.14 (95% CI 0.10–0.16) and an integrated discrimination index of 0.01 (95% CI 0.003–0.013). Conclusions Using historical clinical values to calculate diabetes risk reduces the accuracy of prediction. Diabetes risk calculations should be routinely updated to inform discussions about diabetes prevention at both the patient and population health levels.

Published
2017

41. Estimation of glucose-alanine-lactate-glutamine cycles in postabsorptive humans: role of skeletal muscle

Author

Perriello, G., Jorde, R., Nurjhan, N., Stumvoll, M., Dailey, G., Jenssen, T., Bier, D.M., and Gerich, J.E.

Subjects
Gluconeogenesis -- Regulation, Glutamine -- Analysis, Lactic acid -- Analysis, Biological sciences
Abstract

A glucose-glutamine cycle is present in postabsorptive humans ensuring an actual transfer of new carbon to the glucose pool, in contrast to the Cori and glucose-alanine cycles. Glutamine and lactate add carbon to the glucose pool about 1.5 times of that of alanine. The skeletal muscle participates in the glucose-alanine and Cori-cycle, but the formation of half of plasma alanine and two-thirds of plasma lactate are caused in other tissues.

Published
1995

50. Updated risk factors should be used to predict development of diabetes

Author

Bethel, M.A. Hyland, K.A. Chacra, A.R. Deedwania, P. Fulcher, G.R. Holman, R.R. Jenssen, T. Levitt, N.S. McMurray, J.J.V. Boutati, E. Thomas, L. Sun, J.-L. Haffner, S.M. NAVIGATOR Study Group

Abstract

Aims Predicting incident diabetes could inform treatment strategies for diabetes prevention, but the incremental benefit of recalculating risk using updated risk factors is unknown. We used baseline and 1-year data from the Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) Trial to compare diabetes risk prediction using historical or updated clinical information. Methods Among non-diabetic participants reaching 1 year of follow-up in NAVIGATOR, we compared the performance of the published baseline diabetes risk model with a “landmark” model incorporating risk factors updated at the 1-year time point. The C-statistic was used to compare model discrimination and reclassification analyses to demonstrate the relative accuracy of diabetes prediction. Results A total of 7527 participants remained non-diabetic at 1 year, and 2375 developed diabetes during a median of 4 years of follow-up. The C-statistic for the landmark model was higher (0.73 [95% CI 0.72–0.74]) than for the baseline model (0.67 [95% CI 0.66–0.68]). The landmark model improved classification to modest ( 40%) 4-year risk, with a net reclassification index of 0.14 (95% CI 0.10–0.16) and an integrated discrimination index of 0.01 (95% CI 0.003–0.013). Conclusions Using historical clinical values to calculate diabetes risk reduces the accuracy of prediction. Diabetes risk calculations should be routinely updated to inform discussions about diabetes prevention at both the patient and population health levels. © 2017 Elsevier Inc.

Published
2017

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