The Eggers Lab in the UArizona Departments of Physiology and Biomedical Engineering is seeking highly motivated candidates for the full-time position of Postdoctoral Research Associate I. Dr. Eggers’s NIH-funded research incorporates physiological light stimulation, electrophysiology, immunohistochemical and optogenetic approaches to identify cellular, synaptic and molecular mechanisms that underlie changes in retinal neurons in diabetes. The goal of current studies is to determine how retinal calcium and dopamine signaling are altered in multiple levels of the rod pathway during early stages of diabetes and to identify potential targets for treatment. More information on our current research interests can be found at: http://eggerslab.sites.arizona.edu/.

Changes in ocular hemodynamics may be indicative of pathological conditions in the eye (e.g. glaucoma, age-related macular degeneration), but also elsewhere in the body (e.g. systemic hypertension, diabetes, neurodegenerative disorders). Thanks to its transparent fluids and structures that allow the light to go through, the eye offers a unique window on the circulation from large to small vessels, and from arteries to veins. Deciphering the causes that lead to changes in ocular hemodynamics in a specific individual could help prevent vision loss as well as aid in the diagnosis and management of diseases beyond the eye. In this talk, we will discuss how mathematical and computational modelling can help in this regard. We will focus on two main factors, namely blood pressure (BP), which drives the blood flow through the vessels, and intraocular pressure (IOP), which compresses the vessels and may impede the flow. Mechanism-driven models translates fundamental principles of physics and physiology into computable equations that allow for identification of cause-to-effect relationships among interplaying factors (e.g. BP, IOP, blood flow). While invaluable for causality, mechanism-driven models are often based on simplifying assumptions to make them tractable for analysis and simulation; however, this often brings into question their relevance beyond theoretical explorations. Data-driven models offer a natural remedy to address these short-comings. Data-driven methods may be supervised (based on labelled training data) or unsupervised (clustering and other data analytics) and they include models based on statistics, machine learning, deep learning and neural networks. Data-driven models naturally thrive on large datasets, making them scalable to a plethora of applications. While invaluable for scalability, data-driven models are often perceived as black- boxes, as their outcomes are difficult to explain in terms of fundamental principles of physics and physiology and this limits the delivery of actionable insights. The combination of mechanism-driven and data-driven models allows us to harness the advantages of both, as mechanism-driven models excel at interpretability but suffer from a lack of scalability, while data-driven models are excellent at scale but suffer in terms of generalizability and insights for hypothesis generation. This combined, integrative approach represents the pillar of the interdisciplinary approach to data science that will be discussed in this talk, with application to ocular hemodynamics and specific examples in glaucoma research.

The increasing prevalence of obesity and type 2 diabetes (T2D) and associated morbidity and mortality emphasizes the need for a more complete understanding of the mechanisms mediating energy homeostasis to accelerate the identification of new medications. Recent reports indicate that obesity medication, 5-hydroxytryptamine (5-HT, serotonin)2C receptor (5-HT2CR) agonist lorcaserin improves glycemic control in association with weight loss in obese patients with T2D. We examined whether lorcaserin has a direct effect on insulin sensitivity and how this effect is achieved. We clarify that lorcaserin dose-dependently improves glycemic control in a mouse model of T2D without altering body weight. Examining the mechanism of this effect, we reveal a necessary and sufficient neurochemical mediator of lorcaserin’s glucoregulatory effects, via activation of brain pro-opiomelanocortin (POMC) peptides. We observed that lorcaserin reduces hepatic glucose production and improves insulin sensitivity. These data suggest that lorcaserin’s action within the brain represents a mechanistically novel treatment for T2D: findings of significance to a prevalent global disease.

A single person can be the source of billions of data points, whether these are generated from everyday internet use, healthcare records, wearable sensors or participation in experimental research. This vast amount of data can be used to make predictions about people and systems: what is the probability this person will develop diabetes in the next year? Will commit a crime? Will be a good employee? Is of a particular ethnicity? Predictions are simply represented by a number, produced by an algorithm. A single number in itself is not biased. How that number was generated, interpreted and subsequently used are all processes deeply susceptible to human bias and prejudices. This session will explore a philosophical perspective of data ethics and discuss practical steps to reducing statistical bias. There will be opportunity in the last section of the session for attendees to discuss and troubleshoot ethical questions from their own analyses in a ‘Data Clinic’.

The hippocampal formation has been implicated in both cognitive functions as well as the sensing and control of endocrine states. To identify a candidate activity pattern which may link such disparate functions, we simultaneously measured electrophysiological activity from the hippocampus and interstitial glucose concentrations in the body of freely behaving rats. We found that clusters of sharp wave-ripples (SPW-Rs) recorded from both dorsal and ventral hippocampus reliably predicted a decrease in peripheral glucose concentrations within ~10 minutes. This correlation was less dependent on circadian, ultradian, and meal-triggered fluctuations, it could be mimicked with optogenetically induced ripples, and was attenuated by pharmacogenetically suppressing activity of the lateral septum, the major conduit between the hippocampus and subcortical structures. Our findings demonstrate that a novel function of the SPW-R is to modulate peripheral glucose homeostasis and offer a mechanism for the link between sleep disruption and blood glucose dysregulation seen in type 2 diabetes and obesity.