Inferring Insulin Secretion Rate from Sparse Patient Glucose and Insulin Measures.

The insulin secretion rate (ISR) contains information that can provide a personal, quantitative understanding of endocrine function. If the ISR can be reliably inferred from measurements, it could be used for understanding and clinically diagnosing problems with the glucose regulation system. Objective: This study aims to develop a model-based method for inferring a parametrization of the ISR and related physiological information among people with different glycemic conditions in a robust manner. The developed algorithm is applicable for both dense or sparsely sampled plasma glucose/insulin measurements, where sparseness is defined in terms of sampling time with respect to the fastest time scale of the dynamics. Methods: An algorithm for parametrizing and validating a functional form of the ISR for different compartmental models with unknown but estimable ISR function and absorption/decay rates describing the dynamics of insulin accumulation was developed. The method and modeling applies equally to c-peptide secretion rate (CSR) when c-peptide is measured. Accuracy of fit is reliant on reconstruction error of the measured trajectories, and when c-peptide is measured the relationship between CSR and ISR. The algorithm was applied to data from 17 subjects with normal glucose regulatory systems and 9 subjects with cystic fibrosis related diabetes (CFRD) in which glucose, insulin and c-peptide were measured in course of oral glucose tolerance tests (OGTT). Results: This model-based algorithm inferred parametrization of the ISR and CSR functional with relatively low reconstruction error for 12 of 17 control and 7 of 9 CFRD subjects. We demonstrate that when there are suspect measurements points, the validity of excluding them may be interrogated with this method. Significance: A new estimation method is available to infer the ISR and CSR functional profile along with plasma insulin and c-peptide absorption rates from sparse measurements of insulin, c-peptide, and plasma glucose concentrations. We propose a method to interrogate and exclude potentially erroneous OGTT measurement points based on reconstruction errors.

Insulator semiconductor structures coated with biodegradable latexes as encapsulation matrix for urease.

A new urea biosensor for clinical applications was obtained by immobilization of urease within different latex polymers functionalized by hydroxy, acetate and lactobionate groups. Responses of these biosensors based on pH-ion-selective field effect insulator-semiconductor (IS) systems to urea additions were evaluated by capacitance measurements. UV-visible spectroscopy was used to check the urease activity in various matrixes. A good retention of the catalytic urease activity in the case of the cationic polymers was observed. In addition, rotating disk electrode experiments were carried out to determine the matrix permeability characteristics. Under optimal conditions, i.e. buffer capacity corresponding to 5 mM phosphate buffer, the urea enzyme insulator semiconductor (ENIS) sensors showed a linear response for urea concentrations in the range 10(-1.5) to 10(-4)M. Furthermore, kinetic parameters for the immobilized urease were obtained from Lineweaver-Burk plot. Clearly, a fast response and a good adhesion for the urease-acetate polymer composite films, prepared without using glutaraldehyde as cross-linking agent was observed.