| 1. |
- Bossart, Martin, et al.
(författare)
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Effects on weight loss and glycemic control with SAR441255, a potent unimolecular peptide GLP-1/GIP/GCG receptor triagonist
- 2022
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Ingår i: Cell Metabolism. - : CELL PRESS. - 1550-4131 .- 1932-7420. ; 34:1, s. 59-
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Tidskriftsartikel (refereegranskat)abstract
- Unimolecular triple incretins, combining the activity of glucagon-like peptide-1 (GLP-1), glucose -dependent insulinotropic polypeptide (GIP), and glucagon (GCG), have demonstrated reduction in body weight and improved glucose control in rodent models. We developed SAR441255, a synthetic peptide agonist of the GLP-1, GCG, and GIP receptors, structurally based on the exendin-4 sequence. SAR441255 displays high potency with balanced activation of all three target receptors. In animal models, metabolic outcomes were superior to results with a dual GLP-1/GCG receptor agonist. Preclinical in vivo positron emission tomography imaging demonstrated SAR441255 binding to GLP-1 and GCG receptors. In healthy subjects, SAR441255 improved glycemic control during a mixed-meal tolerance test and impacted biomarkers for GCG and GIP receptor activation. Single doses of SAR441255 were well tolerated. The results demonstrate that integrating GIP activity into dual GLP-1 and GCG receptor agonism provides improved effects on weight loss and glycemic control while buffering the diabetogenic risk of chronic GCG receptor agonism.
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| 2. |
- Kissner, Carolin, et al.
(författare)
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ACAT1 Benchmark of RANS-Informed Analytical Methods for Fan Broadband Noise Prediction-Part I-Influence of the RANS Simulation
- 2020
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Ingår i: Acoustics. - : MDPI AG. - 2624-599X. ; 2:3, s. 539-578
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Tidskriftsartikel (refereegranskat)abstract
- A benchmark of Reynolds-Averaged Navier-Stokes (RANS)-informed analytical methods, which are attractive for predicting fan broadband noise, was conducted within the framework of the European project TurboNoiseBB. This paper discusses the first part of the benchmark, which investigates the influence of the RANS inputs. Its companion paper focuses on the influence of the applied acoustic models on predicted fan broadband noise levels. While similar benchmarking activities were conducted in the past, this benchmark is unique due to its large and diverse data set involving members from more than ten institutions. In this work, the authors analyze RANS solutions performed at approach conditions for the ACAT1 fan. The RANS solutions were obtained using different CFD codes, mesh resolutions, and computational settings. The flow, turbulence, and resulting fan broadband noise predictions are analyzed to pinpoint critical influencing parameters related to the RANS inputs. Experimental data are used for comparison. It is shown that when turbomachinery experts perform RANS simulations using the same geometry and the same operating conditions, the most crucial choices in terms of predicted fan broadband noise are the type of turbulence model and applied turbulence model extensions. Chosen mesh resolutions, CFD solvers, and other computational settings are less critical.
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