Who Benefits Most from a University Degree?: A Cross-National Comparison of Selection and Wage Returns in the US, UK, and Germany

Recent research on economic returns to higher education in the United States suggests that those with the highest wage returns to a college degree are least likely to obtain one. We extend the study of heterogeneous returns to tertiary education across multiple institutional contexts, investigating how the relationship between wage returns and the propensity to complete a degree varies by the level of expansion, differentiation, and cost of higher education. Drawing on panel data and matching techniques, we compare findings from the US with selection into degree completion in Germany and the UK. Contrary to previous studies, we find little evidence for population level heterogeneity in economic returns to higher education

Observer-Based State Feedback for Enhanced Insulin Control of Type ‘I’ Diabetic Patients

During the past few decades, biomedical modeling techniques have been applied to improve performance of a wide variety of medical systems that require monitoring and control. Diabetes is one of the most important medical problems. This paper focuses on designing a state feedback controller with observer to improve the performance of the insulin control for type ‘I’ diabetic patients. The dynamic model of glucose levels in diabetic patients is a nonlinear model. The system is a typical fourth-order single-input-single-output state space model. Using a linear time invariant controller based on an operating condition is a common method to simplify control design. On the other hand, adaptive control can potentially improve system performance. But it increases control complexity and may create further stability issues. This paper investigates patient models and presents a simplified control scheme using observer-based feedback controllers. By comparing different control schemes, it shows that a properly designed state feedback controller with observer can eliminate the adaptation strategy that the Proportional-Integral-Derivative (PID) controllers need to improve the control performance. Control strategies are simulated and their performance is evaluated in MATLAB and Simulink

Measurement of the Absolute Magnitude and Time Courses of Mitochondrial Membrane Potential in Primary and Clonal Pancreatic Beta-Cells

The aim of this study was to simplify, improve and validate quantitative measurement of the mitochondrial membrane potential (ΔψM) in pancreatic β-cells. This built on our previously introduced calculation of the absolute magnitude of ΔψM in intact cells, using time-lapse imaging of the non-quench mode fluorescence of tetramethylrhodamine methyl ester and a bis-oxonol plasma membrane potential (ΔψP) indicator. ΔψM is a central mediator of glucose-stimulated insulin secretion in pancreatic β-cells. ΔψM is at the crossroads of cellular energy production and demand, therefore precise assay of its magnitude is a valuable tool to study how these processes interplay in insulin secretion. Dispersed islet cell cultures allowed cell type-specific, single-cell observations of cell-to-cell heterogeneity of ΔψM and ΔψP. Glucose addition caused hyperpolarization of ΔψM and depolarization of ΔψP. The hyperpolarization was a monophasic step increase, even in cells where the ΔψP depolarization was biphasic. The biphasic response of ΔψP was associated with a larger hyperpolarization of ΔψM than the monophasic response. Analysis of the relationships between ΔψP and ΔψM revealed that primary dispersed β-cells responded to glucose heterogeneously, driven by variable activation of energy metabolism. Sensitivity analysis of the calibration was consistent with β-cells having substantial cell-to-cell variations in amounts of mitochondria, and this was predicted not to impair the accuracy of determinations of relative changes in ΔψM and ΔψP. Finally, we demonstrate a significant problem with using an alternative ΔψM probe, rhodamine 123. In glucose-stimulated and oligomycin-inhibited β-cells the principles of the rhodamine 123 assay were breached, resulting in misleading conclusion

A local glucose-and oxygen concentration-based insulin secretion model for pancreatic islets

<p>Abstract</p> <p>Background</p> <p>Because insulin is the main regulator of glucose homeostasis, quantitative models describing the dynamics of glucose-induced insulin secretion are of obvious interest. Here, a computational model is introduced that focuses not on organism-level concentrations, but on the quantitative modeling of local, cellular-level glucose-insulin dynamics by incorporating the detailed spatial distribution of the concentrations of interest within isolated avascular pancreatic islets.</p> <p>Methods</p> <p>All nutrient consumption and hormone release rates were assumed to follow Hill-type sigmoid dependences on local concentrations. Insulin secretion rates depend on both the glucose concentration and its time-gradient, resulting in second-and first-phase responses, respectively. Since hypoxia may also be an important limiting factor in avascular islets, oxygen and cell viability considerations were also built in by incorporating and extending our previous islet cell oxygen consumption model. A finite element method (FEM) framework is used to combine reactive rates with mass transport by convection and diffusion as well as fluid-mechanics.</p> <p>Results</p> <p>The model was calibrated using experimental results from dynamic glucose-stimulated insulin release (GSIR) perifusion studies with isolated islets. Further optimization is still needed, but calculated insulin responses to stepwise increments in the incoming glucose concentration are in good agreement with existing experimental insulin release data characterizing glucose and oxygen dependence. The model makes possible the detailed description of the intraislet spatial distributions of insulin, glucose, and oxygen levels. In agreement with recent observations, modeling also suggests that smaller islets perform better when transplanted and/or encapsulated.</p> <p>Conclusions</p> <p>An insulin secretion model was implemented by coupling local consumption and release rates to calculations of the spatial distributions of all species of interest. The resulting glucose-insulin control system fits in the general framework of a sigmoid proportional-integral-derivative controller, a generalized PID controller, more suitable for biological systems, which are always nonlinear due to the maximum response being limited. Because of the general framework of the implementation, simulations can be carried out for arbitrary geometries including cultured, perifused, transplanted, and encapsulated islets.</p