Glucose-Insulin regulator for type 1 diabetes using high order neural networks

In this paper a Glucose-Insulin regulator for Type 1 Diabetes using artificial neural networks (ANN) is proposed. This is done using a discrete recurrent high order neural network in order to identify and control a nonlinear dynamical system which represents the pancreas? beta-cells behavior of a virtual patient. The ANN which reproduces and identifies the dynamical behavior system, is configured as series parallel and trained on line using the extended Kalman filter algorithm to achieve a quickly convergence identification in silico. The control objective is to regulate the glucose-insulin level under different glucose inputs and is based on a nonlinear neural block control law. A safety block is included between the control output signal and the virtual patient with type 1 diabetes mellitus. Simulations include a period of three days. Simulation results are compared during the overnight fasting period in Open-Loop (OL) versus Closed- Loop (CL). Tests in Semi-Closed-Loop (SCL) are made feedforward in order to give information to the control algorithm. We conclude the controller is able to drive the glucose to target in overnight periods and the feedforward is necessary to control the postprandial period

Kalman Filter Bibliography: Agriculture, Biology, and Medicine

27 pages, 1 article*Kalman Filter Bibliography: Agriculture, Biology, and Medicine* (Federer, Walter T.; Murty, B. R.) 27 page

Diabetes Mellitus Glucose Prediction by Linear and Bayesian Ensemble Modeling

Diabetes Mellitus is a chronic disease of impaired blood glucose control due to degraded or absent bodily-specific insulin production, or utilization. To the affected, this in many cases implies relying on insulin injections and blood glucose measurements, in order to keep the blood glucose level within acceptable limits. Risks of developing short- and long-term complications, due to both too high and too low blood glucose concentrations are severalfold, and, generally, the glucose dynamics are not easy too fully comprehend for the affected individual—resulting in poor glucose control. To reduce the burden this implies to the patient and society, in terms of physiological and monetary costs, different technical solutions, based on closed or semi-closed loop blood glucose control, have been suggested. To this end, this thesis investigates simplified linear and merged models of glucose dynamics for the purpose of short-term prediction, developed within the EU FP7 DIAdvisor project. These models could, e.g., be used, in a decision support system, to alert the user of future low and high glucose levels, and, when implemented in a control framework, to suggest proactive actions. The simplified models were evaluated on 47 patient data records from the first DIAdvisor trial. Qualitatively physiological correct responses were imposed, and model-based prediction, up to two hours ahead, and specifically for low blood glucose detection, was evaluated. The glucose raising, and lowering effect of meals and insulin were estimated, together with the clinically relevant carbohydrate-to-insulin ratio. The model was further expanded to include the blood-to-interstitial lag, and tested for one patient data set. Finally, a novel algorithm for merging of multiple prediction models was developed and validated on both artificial data and 12 datasets from the second DIAdvisor trial

Sympathy for the Microbiota: How Changes in Gut Microbial Composition Influence the Immune System and Basic Physiology by Way of the Sympathetic Nervous System

The gastro-intestinal tract is the most extensive mucosal surface in mammals and harbors the most numerous immune cell reservoir as well as a complex and autonomous nervous system. The GI tract is continuously exposed to foreign antigen and potentially toxic chemicals through the ingestion of food. In addition, the lumen of the human GI tract is populated with approximately 1013 bacteria, which is equivalent to the number of cells in the entire human body (Sender et al., 2016). The intestinal microbiome, which aids in host metabolism, represents a diverse population of microorganisms separated from the inside of the body by only a single layer of epithelial cells. Thus, in this highly inflammatory and ever-changing environment, the intestine must be able to balance tolerance to dietary antigens and microbes, while remaining vigilant when exposed to potentially toxic substances or pathogens. Sensing of the microbiota has been previously shown to impact the intestinal immune and nervous systems, including crosstalk between the two. However, how microbes influence the enteric associated nervous system and whether these effects play a role in mediating host physiology, inclusive of immune responses, remains unanswered. We previously uncovered neuro-immune cross-talk in the intestine (Muller et al., 2014), whereby muscularis macrophages (MM) that reside in the muscle layers of the intestine express bone morphogenetic protein 2 (BMP2) that can directly impact intrinsic enteric associated neurons (iEAN) and intestinal motility. Reciprocally, iEAN express colony-stimulating factor 1 (CSF1), which may play a role in the local maintenance and differentiation of MM. Both axes of this crosstalk occur during normal, steady-state conditions and are dependent upon the commensal microbiota. To determine whether these macrophages played a role during the course of an intestinal infection, we first aimed to better characterize how MM differed from their counterparts that reside in the intestinal lamina propria, in close proximity to the microbialrich lumen. Through two-photon intravital microscopy, cleared tissue light-sheet imaging, and RNA-sequencing of purified macrophage populations, we found that MM are morphologically, anatomically, dynamically, and transcriptionally distinct from LpM. These MM were skewed towards a more anti-inflammatory transcriptional profile and were in close apposition to actively firing iEAN. Utilizing an attenuated form of Salmonella typhimurium, spiB, we found that although MM are not in direct contact with luminal contents, they were rapidly polarized towards an enhanced anti-inflammatory profile in response to pathogenic infection. Furthermore, polarization was dependent upon sympathetic neuronal activation in the celiac-superior mesenteric ganglion (CG-SMG), which enabled communication from the lumen to MM through adrenergic receptor beta 2 (ADBR2) engagement (Gabanyi & Muller et al., 2016). Together, these results established that neurotransmitter signaling can swiftly coordinate a response to infection through anatomically-associated immune cells. To gain insights into how sympathetic neurons, and more broadly, all extrinsic enteric associated neurons (eEAN) might detect and/or be influenced by changes in the microbiota, we performed unbiased RNA translational profiling comparing eEAN sensory and effector nodes from germ free and specific pathogen free mice. RNA sequencing revealed changes in activity-dependent transcripts in afferent sensory neurons in the nodose ganglion and efferent sympathetic neurons in the CG-SMG. These results served as an entry point to identify which microbial signals and neuronal populations transmit microbial information to the central nervous system (CNS), and which CNS populations integrate this information to control gut physiology. We identified a subset of distal intestine-projecting vagal neurons positioned to play an afferent role in luminal detection through chemogenetic manipulation, translational profiling and anterograde tracing. Using retrograde polysynaptic neuronal tracing from the intestinal wall, we identified brainstem sensory nuclei activated by specific bacterial metabolites, including short chain fatty acids. Finally, chemogenetic modulation demonstrated that activation of sympathetic premotor glutamatergic neurons is sufficient to regulate gastrointestinal transit. In sum, we established an anatomical, molecular, and functional framework for the complex circuit(s) monitoring microbial content (Muller et al., 2019a). Equipped with a more complete understanding of how the gut sympathetic nervous system functions, we then asked whether pathogen-induced adrenergic changes in MM are important for a proper tissue-protective response. Infection with multiple pathogens, including spiB, led to a significant and persistent loss in iEAN numbers and chronic dysmotility. Intersectional genetics, pharmacological intervention, and chemogenetic sympathetic activation was used to demonstrate that MM-specific Β2AR signaling is required to confer neuronal protection during the course of infection and prevent further pathogen-induced damage. Furthermore, translational profiling of iEAN led to the discovery that these neurons express a unique combination of inflammasome pathway components as compared to other peripheral neuronal sub-populations. These inflammasome components are activated in iEAN during infection, and neuron-specific gene targeting was sufficient to prevent pathogen-induced neuronal loss. Thus, we found that MM-adrenergic signaling can mitigate EAN inflammasome-dependent cell-death during enteric infection (Matheis & Muller et al., 2019). Based upon our discovery of iEAN dysbiosis detection via the inflammasome, we next probed how changes in the microbiota might further impact these neurons. Using translational profiling, we found that distinct regions of the intestine have unique gene expression programs in the presence of the microbiome. By comparing this profile to germ free mice, we found that the microbiota is a principal driving force in establishing these regional differences and that specific neuropeptides populations are decreased in the distal intestine in the absence of a microbiota. Chemogenetic characterization of microbiota-influenced iEAN identified a subset of viscerofugal CART+ neurons that modulate feeding behavior through insulin-glucose levels independent of the central nervous system. We discovered that CART+ iEAN numbers decrease in the absence of the microbiota through the same iEAN inflammasome pathway we previously identified. Finally, genetic ablation of this inflammasome pathway was sufficient to prevent insulinglucose level changes normally seen in antibiotic-treated conditions (Muller et al., 2019b). Through these studies we found that multiple signals generated by changes in the gut microbial composition are integrated by the sympathetic nervous system to control gastrointestinal motility, enteric immunity, and blood glucose. Cumulatively, these findings have increased our understanding of how the enteric associated nervous system responds to changes in the microbiota and consequently regulates local tissue and overall mammalian homeostasis

Peptide Corrination for the Mitigation of Nausea and Emesis in the Treatment of Type 2 Diabetes

This thesis addresses several questions focused on the activation of receptors expressed withinthe area postrema (AP) and the nucleus tractus solitarius (NTS), regions known to influence nausea and emesis. Prevention of such effects were achieved via corrination, covalent attachment to vitamin B12 (B12) or other corrin constructs, of GLP glucagon-like peptide-one (GLP-1) receptor (GLP-1R) agonists or via the use of GRASP a growth differentiation factor 15 (GDF15) glial derived neurotropic family receptor α-like (GFRAL) complex antagonist

Novel Mechanisms In The Sorting Of Proglucagon To The Secretory Granules Of The Regulated Secretory Pathway

The prohormone proglucagon encodes for multiple peptide hormones, including glucagon, glucagon-like peptide-1 (GLP-1), and GLP-2, produced through tissue-specific processing by prohormone convertase (PC) 1/3 and PC2. In alpha cells, PC2 yields glucagon, the major counter-regulatory hormone to insulin, which together, control glucose homeostasis. In contrast, GLP-1 and GLP2 are mainly produced in intestinal L-cells by PC1/3. GLP-1 stimulates insulin secretion following a meal, and therefore has opposing function to glucagon regulating glucose homeostasis; in contrast, GLP-2 enhances gut nutrient absorption. Efficient sorting of proglucagon to secretory granules is required for nutrient-regulated secretion. The aim of this thesis is to discover the molecular mechanisms by which proglucagon is targeted to secretory granules, which ensures that proglucagon is correctly processed to mature hormones, and is necessary for prompt physiologic response to nutrient status. In this thesis, we identify several sorting signals within the hormone domains of proglucagon that encode targeting information. Using quantitative immunofluorescence microscopy and co-localization analyses, I was able to determine the molecular nature by which glucagon and GLP-1 enter granules. Despite these two hormones sharing a large degree of structural homology, it is their particular alpha-helix structures that enable the sorting of proglucagon. Further, I provide evidence that proglucagon is first sorted to granules prior to being processed to active hormones. Furthermore, I have identified carboxypeptidase E in the mechanism by which glucagon sorts within alpha cells. Together, each hormone carries with it a unique sorting “signature” to efficiently reach its destination, and allows alpha and L-cells to tightly regulate nutrient homeostasis