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Karl Thomaseth

Researcher at National Research Council

Publications -  93
Citations -  2782

Karl Thomaseth is an academic researcher from National Research Council. The author has contributed to research in topics: Insulin & Heart rate. The author has an hindex of 29, co-authored 93 publications receiving 2601 citations. Previous affiliations of Karl Thomaseth include University of Padua & University of Bologna.

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Pronounced insulin resistance and inadequate beta-cell secretion characterize lean gestational diabetes during and after pregnancy.

TL;DR: Defective insulin secretion seems to be a predominant defect in lean GDM subjects, indicating that it might represent a specific prediabetic condition during pregnancy and after delivery.
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Power Spectral Analysis of Heart-Rate Variations Improves Assessment of Diabetic Cardiac Autonomic Neuropathy

TL;DR: PSA appears to be a powerful tool in the determination of autonomic tone in diabetic CAN and offers a picture of overall autonomic activity that can be explored only partially by traditional cardiovascular autonomic tests and can reveal parasympathetic versus sympathetic dyssynergia.
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Insulin sensitivity, fat distribution, and adipocytokine response to different diets in lean and obese cats before and after weight loss

TL;DR: Diet HP is beneficial through maintenance of normal insulin sensitivity of fat metabolism in obese cats, facilitating the loss of fat during weight loss, and increasing heat production in lean cats, and shows that insulinensitivity of glucose and fat metabolism can be differentially regulated in cats.
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Insulin and C-peptide secretion and kinetics in humans: direct and model-based measurements during OGTT

TL;DR: Good correspondence between experimental data and model estimates for prehepatic insulin secretion is found, whereas estimation of hepatic insulin extraction and insulin clearance needs further investigation for improvement.
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Generalized sensitivity functions in physiological system identification.

TL;DR: A new set of sensitivity functions, called the generalized sensitivity functions (GSF), are proposed, based on information theoretical criteria, for the analysis of input–output identification experiments and provide a more accurate picture on the information content of measured outputs on individual model parameters at different times.