Hypoglycemia in children and young adults with cystic fibrosis during oral glucose tolerance testing vs. continuous glucose monitoring.

BACKGROUND: Hypoglycemia is common in people with cystic fibrosis (pwCF) during oral glucose tolerance tests (OGTTs) and in the free-living setting, yet its pathophysiology remains unclear. OBJECTIVE: To evaluate hypoglycemia in children and young adults with CF by OGTT and continuous glucose monitoring (CGM). METHODS: A 3-h OGTT was performed in children and young adults with CF and healthy controls (HC). Individuals were classified as experiencing hypoglycemia on OGTT (glucose <70 mg/dL) or not. Insulin, C-peptide, glucose, glucagon, and incretins were measured. CGM was performed for 7 days in the free-living setting. Measures of insulin sensitivity, beta cell function accounting for insulin sensitivity, and insulin clearance were calculated. RESULTS: A total of 57 participants (40 CF and 17 HC) underwent assessment. Rates of hypoglycemia by OGTT were similar in pwCF (53%, 21/40) compared to HC (35%, 6/17), p = 0.23. PwCF compared to HC had higher A1c; on OGTT higher and later glucose peaks, later insulin peaks; and on CGM more glucose variability. CF Hypo+ versus CF Hypo- had higher lung function, higher insulin sensitivity, higher beta cell function accounting for insulin sensitivity, and decreased CGM variability. When comparing CF Hypo+ to HC Hypo+, although rates of hypoglycemia are similar, pwCF had blunted glucagon responses to hypoglycemia. OGTT hypoglycemia was not associated with CGM hypoglycemia in any group. CONCLUSION: Youth with CF have increased insulin sensitivity and impaired glucagon response to hypoglycemia on OGTT. Hypoglycemia on OGTT did not associate with free-living hypoglycemia.

Dynamic interactions between orexin and dynorphin may delay onset of functional orexin effects: a modeling study.

Orexin (also known as hypocretin) neurons play a key role in regulating sleep-wake behavior, but the links between orexin neuron electrophysiology and function have not been explored. Orexin neurons are wake-active, and spiking activity in orexin neurons may anticipate transitions to wakefulness by several seconds. However, it is suggested that while the orexin system is necessary to maintain sustained wake bouts, orexin has little effect on brief wake bouts. In vitro experiments investigating the actions of orexin and dynorphin, a colocalized neuropeptide, on orexin neurons indicate that the dynamics of desensitization to dynorphin may represent a mechanism for modulating local network activity and resolving the apparent discrepancy between the onset of firing in orexin neurons and the onset of functional orexin effects. To investigate the role of dynorphin on orexin neuron activity, a Hodgkin-Huxley-type model orexin neuron was developed in which baseline electrophysiology, orexin/dynorphin action, and dynorphin desensitization were closely tied to experimental data. In this model framework, model orexin neuron responses to orexin/dynorphin action were calibrated by simulating the physiologic effects of static orexin and dynorphin bath application on orexin neurons. Then behavior in a small network of model orexin neurons was simulated with pure orexin, pure dynorphin, or combined orexin and dynorphin coupling based on the mechanisms established in the static case. It was found that the dynamics of desensitization to dynorphin can mediate a clear shift from a network in which firing is suppressed by dynorphin-mediated inhibition to a network of neurons with high firing rates sustained by orexin-mediated excitation. The findings suggest that dynamic interactions between orexin and dynorphin at transitions from sleep to wake may delay onset of functional orexin effects.

Mathematical model of network dynamics governing mouse sleep-wake behavior.

Recent work in experimental neurophysiology has identified distinct neuronal populations in the rodent brain stem and hypothalamus that selectively promote wake and sleep. Mutual inhibition between these cell groups has suggested the conceptual model of a sleep-wake switch that controls transitions between wake and sleep while minimizing time spent in intermediate states. By combining wake- and sleep-active populations with populations governing transitions between different stages of sleep, a "sleep-wake network" of neuronal populations may be defined. To better understand the dynamics inherent in this network, we created a model sleep-wake network composed of coupled relaxation oscillation equations. Mathematical analysis of the deterministic model provides insight into the dynamics underlying state transitions and predicts mechanisms for each transition type. With the addition of noise, the simulated sleep-wake behavior generated by the model reproduces many qualitative and quantitative features of mouse sleep-wake behavior. In particular, the existence of simulated brief awakenings is a unique feature of the model. In addition to capturing the experimentally observed qualitative difference between brief and sustained wake bouts, the model suggests distinct network mechanisms for the two types of wakefulness. Because circadian and other factors alter the fine architecture of sleep-wake behavior, this model provides a novel framework to explore dynamical principles that may underlie normal and pathologic sleep-wake physiology.