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No description available.

Since glucose is an essential nutrient for normal fetal growth and development, the impact of reduced maternal dietary glucose supply, on amniotic fluid (amf) amino acid composition was investigated. Furthermore, this study investigated whether any resulting changes in the concentrations of amf amino acids could be predictive of fetal growth and metabolic status. Pregnant rat dams were fed isocaloric diets containing graded levels of dietary glucose (0, 12, 24 and 60%) and the amf amino acid content was analysed on gestational days (gd) 18.5 to 21.5. Carbohydrate restriction produced significant increases in the concentrations of amf isoleucine (on gd 21.5), tryptophan (on gd 18.5 and 21.5) and 3-methylhistidine (on gd 20.5 and 21.5). An interaction between diet and day of gestation modified amf taurine levels such that dams fed low carbohydrate diets showed significant increases in amf taurine as pregnancy progressed. Specific amf amino acids correlated with fetal growth parameters and fetal tissue glycogen reserves indicating the ability of amf composition to reflect fetal distress under conditions of compromised maternal nutritional status. A greater statistical predictability of amf constituents was obtained with fetal growth parameters than with fetal tissue glycogen reserves. These results suggest that amf amino acids are better predictors of fetal growth status than of fetal metabolic status.

The peripheral and central mechanisms mediating the modulatory effects of glucose and acute stress in rats were investigated using two versions of an appetitive win-stay task. Post-training injections of glucose, but not fructose, enhanced retention on the closed maze task. Acquisition of this task was found to be impaired by lesions of the fimbria-fornix (FF). Further experiments showed that while the celiac ganglion and the FF normally participate in suppressing the memory-enhancing effect of an acute stressor, neither structure is involved in mediating the effect of glucose on memory. Post-training injections of glucose, but not fructose, enhanced retention on the open maze task. Although acquisition of this task was not affected by FF lesions, both the celiac ganglion and the FF participate in mediating the memory-enhancing effect of glucose. Together, the results suggest that the peripheral and central mechanisms studied here are both substance- and task-specific. The modulatory effects of different types of stress, and the issue of whether task acquisition and memory modulation are anatomically distinct are discussed.

Transient Receptor Potential Melastatin 7 (TRPM7) is a ubiquitously expressed divalent cation channel implicated as a key regulator of neuronal cell death in stroke. Our research group has previously shown that TRPM7 dependent cytoskeletal regulation particularly via cofilin mediates neuronal death in oxygen glucose deprivation (in vitro stroke model). LIMK1 phosphorylation was also shown to decrease downstream of TRPM7 activation during anoxia. In the present study we investigated the effects of TRPM7 activation during anoxia, on three regulators of LIMK and cofilin; Rho-associated kinase 2 (ROCK2), P-21 activated kinase 3 (PAK3) and Slingshot family phosphatase 1 (SSH1). Our findings suggest that PAK3 activity is downregulated during OGD through TRPM7 independent mechanisms. However, SSH1 activity appears to be regulated downstream of TRPM7 in a manner that is consistent with LIMK and cofilin regulation. Overall, our work suggests that SSH1 is a new link between anoxia-induced TRPM7activity and cofilin hyperactivation.

Transient Receptor Potential Melastatin 7 (TRPM7) is a ubiquitously expressed divalent cation channel implicated as a key regulator of neuronal cell death in stroke. Our research group has previously shown that TRPM7 dependent cytoskeletal regulation particularly via cofilin mediates neuronal death in oxygen glucose deprivation (in vitro stroke model). LIMK1 phosphorylation was also shown to decrease downstream of TRPM7 activation during anoxia. In the present study we investigated the effects of TRPM7 activation during anoxia, on three regulators of LIMK and cofilin; Rho-associated kinase 2 (ROCK2), P-21 activated kinase 3 (PAK3) and Slingshot family phosphatase 1 (SSH1). Our findings suggest that PAK3 activity is downregulated during OGD through TRPM7 independent mechanisms. However, SSH1 activity appears to be regulated downstream of TRPM7 in a manner that is consistent with LIMK and cofilin regulation. Overall, our work suggests that SSH1 is a new link between anoxia-induced TRPM7activity and cofilin hyperactivation.

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Clinical guidelines dictate that frequent blood glucose monitoring in diabetic patients is critical towards proper management of the disease. Although, several different types of glucose monitors are now commercially available, most of these devices are invasive, thereby adversely affecting patient compliance. To this end, optical polarimetric glucose sensing through the eye has been proposed as a potential noninvasive means to aid in the control of diabetes. Arguably, the most critical and limiting factor towards successful application of such a technique is the time varying corneal birefringence due to eye motion artifact. In the first part of this research, we describe a birefringent ocular model along with a geometric ray tracing scheme to serve as a tool towards better understanding of the cornea’s birefringence properties. The simulations show that index-unmatched coupling of light is spatially limited to a smaller range when compared to index-matched situation. Polarimetric measurements on rabbits’ eyes indicate relative agreement between the modeled and experimental values of corneal birefringence. In addition, the observed rotation in the plane of polarized light for multiple wavelengths demonstrates the potential for using a dual-wavelength polarimetric approach to overcome the noise due to time-varying corneal birefringence. These results will ultimately aid in the development of an appropriate eye coupling mechanism for in vivo polarimetric glucose measurements. The latter part of the dissertation focuses on design and development of a dual wavelength optical polarimeter. The described system utilizes real-time closed-loop feedback based on proportional-integral-derivative (PID) control, which effectively reduced the time taken by the system to stabilize while minimizing the effect of motion artifact, which appears as common noise source for both the wavelengths. Glucose measurements performed in both in vitro and ex vivo conditions demonstrate the sensitivity of the current system. Finally, in vivo results in rabbits indicate that dual-wavelength polarimetry has the potential to noninvasively probe glucose through the anterior chamber of the eye.

<p>As an increasingly prevalent chronic disease, diabetes represents one of the fastest growing health burdens to both the developed and developing world. In an effort to improve the management and treatment of diabetes, implantable sensors that continuously monitor glucose levels have become popular alternatives to patient-administered finger prick measurements of blood glucose. However, following implantation, the performance of these implants suffers from inaccurate and erratic readings that compromise their useful lives. As a result, implantable glucose sensors remain limited as a platform for the reliable management of diabetes. While the interaction between the sensor and its surrounding tissue has been posited as a culprit for erroneous in vivo sensor performance, there remains little evidence to support that theory.</p><p>This dissertation describes the effects that implant-associated tissue reactions have on implantable sensor function. Since tissue response to an implant changes over time, the overall effect of these tissue reactions is broken into two temporal phases: (1) the phase of weeks to months following implantation when a mature foreign body capsule is present around the sensor and (2) the phase of days to weeks immediately following sensor implantation when a provisional matrix of proteins and inflammatory cells envelops the sensor.</p><p>Late stage sensor responses to implantation are marked by both an attenuated sensor signal and a significant time lag relative to blood glucose readings. For this later stage of sensor response, a computational model of glucose transport through the interstitial space and foreign body capsule was derived and implemented. Utilizing physiologically relevant parameters, the model was used to mechanistically study how each constituent part of the capsular tissue could affect sensor response with respect to signal attenuation and lag. Each parameter was then analyzed using logarithmic sensitivity analysis to study the effects of different transport variables on both lag and attenuation. Results identified capsule thickness as the strongest determinant of sensor time lag, while subcutaneous vessel density and capsule porosity had the largest effects on attenuation of the sensor signal.</p><p>For the phase of early stage tissue response, human whole blood was used as a simple ex vivo experimental system. The impacts of protein accumulation at the sensor surface (biofouling effects) and cellular consumption of glucose in both the biofouling layer and in the bulk (metabolic effects) on sensor response were assessed. Medtronic Minimed SofSensor glucose sensors were incubated in whole blood, plasma diluted whole blood, and cell-free platelet poor plasma (PPP) to analyze the effects of different blood constituents on sensor function. Experimental conditions were then simulated using MATLAB to predict the relative impacts of biofouling and metabolic effects on the observed sensor responses. It was found that the physical barrier to glucose transport presented by protein biofouling did not hinder glucose movement to the sensor surface. Instead, glucose consumption by inflammatory cells was identified as the major culprit for generating poor sensor performance immediately following implantation.</p><p>Lastly, a novel, biomimetic construct was designed to mimic the in vivo 3D cellular setting around the sensor for the focused in vitro investigation of early stage effects of implantation on glucose sensor performance. Results with this construct demonstrate similar trends in sensor signal decline to the ex vivo cases described above, suggesting this construct could be used as an in vitro platform for assessing implantable glucose sensor performance.</p><p>In total, it may be concluded from this dissertation that instead of sensors "failing" in vivo, as is often reported, that different physiological factors mediate long term sensor function by altering the environment around the implant. For times immediately following implantation, sensor signals are mediated by the presence of inflammatory macrophages adhered on the surface. However, at longer times post-implantation, sensor signals are mediated not by the consumptive capacity of macrophages, but instead by the subcutaneous vessel density surrounding the sensor as well as the porosity and thickness of the foreign body capsule itself. Taken in concert, the results of this dissertation provide a temporal framework for outlining the effects of tissue response on sensor performance, hopefully informing more biocompatible glucose sensor designs in the future.</p> / Dissertation

Hyperglycemia is prevalent in critical care, as patients experience stress-induced hyperglycemia, even with no history of diabetes. Hyperglycemia has a significant impact on patient mortality, outcome and health care cost. Tight regulation can significantly reduce these negative outcomes, but achieving it remains clinically elusive, particularly with regard to what constitutes tight control and what protocols are optimal in terms of results and clinical effort. Hyperglycemia in critical care is not largely benign, as once thought, and has a deleterious effect on outcome. Recent studies have shown that tight glucose regulation to average levels from 6.1–7.75 mmol/L can reduce mortality 17–45%, while also significantly reducing other negative clinical outcomes. However, clinical results are highly variable and there is little agreement on what levels of performance can be achieved and how to achieve them. A typical clinical solution is to use ad-hoc protocols based primarily on experience, where large amounts of insulin, up to 50 U/hr, are titrated against glucose measurements variably taken every 1–4 hours. When combined with the unpredictable and sudden metabolic changes that characterise this aspect of critical illness and/or clinical changes in nutritional support, this approach results in highly variable blood glucose levels. The overall result is sustained periods of hyper- or hypo- glycemia, characterised by oscillations between these states, which can adversely affect clinical outcomes and mortality. The situation is exacerbated by exogenous nutritional support regimes with high dextrose content. Model-based predictive control can deliver patient specific and adaptive control, ideal for such a highly dynamic problem. A simple, effective physiological model is presented in this thesis, focusing strongly on clinical control feasibility. This model has three compartments for glucose utilisation, interstitial insulin and its transport, and insulin kinetics in blood plasma. There are two patient specific parameters, the endogenous glucose removal and insulin sensitivity. A novel integral-based parameter identification enables fast and accurate real-time model adaptation to individual patients and patient condition. Three stages of control algorithm developments were trialed clinically in the Christchurch Hospital Department of Intensive Care Medicine. These control protocols are adaptive and patient specific. It is found that glycemic control utilising both insulin and nutrition interventions is most effective. The third stage of protocol development, SPRINT, achieved 61% of patient blood glucose measurements within the 4–6.1 mmol/L desirable glycemic control range in 165 patients. In addition, 89% were within the 4–7.75 mmol/L clinical acceptable range. These values are percentages of the total number of measurements, of which 47% are two-hourly, and the rest are hourly. These results showed unprecedented tight glycemic control in the critical care, but still struggle with patient variability and dynamics. Two stochastic models of insulin sensitivity for the critically ill population are derived and presented in this thesis. These models reveal the highly dynamic variation in insulin sensitivity under critical illness. The stochastic models can deliver probability intervals to support clinical control interventions. Hypoglycemia can thus be further avoided with the probability interval guided intervention assessments. This stochastic approach brings glycemic control to a more knowledge and intelligible level. In “virtual patient” simulation studies, 72% of glycemic levels were within the 4–6.1 mmol/L desirable glycemic control range. The incidence level of hypoglycemia was reduced to practically zero. These results suggest the clinical advances the stochastic model can bring. In addition, the stochastic models reflect the critical patients’ insulin sensitivity driven dynamics. Consequently, the models can create virtual patients to simulated clinical conditions. Thus, protocol developments can be optimised with guaranteed patient safety. Finally, the work presented in this thesis can act as a starting point for many other glycemic control problems in other environments. These areas include the cardiac critical care and neonatal critical care that share the most similarities to the environment studied in this thesis, to general diabetes where the population is growing exponentially world wide. Furthermore, the same pharmacodynamic modelling and control concept can be applied to other human pharmacodynamic control problems. In particular, stochastic modelling can bring added knowledge to these control systems. Eventually, this added knowledge can lead clinical developments from protocol simulations to better clinical decision making.