Computational modeling and analysis of the impacts of sleep deprivation on glucose stimulated insulin secretion

The impact of postoperative pain interventions on circadian rhythm disruptions: mechanisms and clinical implications

Postoperative pain is a prevalent clinical issue that significantly impacts patient recovery, making its management crucial for rehabilitation. Recent studies have shown that postoperative pain not only affects the physiological state of patients but may also disrupt their circadian rhythms, leading to decreased sleep quality and physiological dysfunctions. This review aims to explore the effects of postoperative pain interventions on circadian rhythm disturbances, analyze the underlying mechanisms, and summarize the effective strategies currently used in clinical practice. Through a comprehensive analysis of the relevant literature, we will highlight the importance of pain management during the recovery process and emphasize its potential role in regulating circadian rhythms. Pharmacological treatments like NSAIDs and melatonin have shown efficacy in regulating circadian rhythms and improving sleep quality in postoperative patients. Multimodal analgesia combining pharmacological and non-pharmacological methods (e.g., CBT, acupuncture) can optimize pain relief while minimizing side effects. However, further research is needed to clarify the bidirectional relationship between pain perception and circadian rhythms and translate these findings into clinical practice.

Mathematical modeling informs the impact of changes in circadian rhythms and meal patterns on insulin secretion

Disruption of circadian rhythms has been associated with metabolic syndromes, including obesity and diabetes. A variety of metabolic activities are under circadian modulation, as local and global clock gene knockouts result in glucose imbalance and increased risk of metabolic diseases. Insulin release from the pancreatic β cells exhibits daily variation, and recent studies have found that insulin secretion, not production, is under circadian modulation. As consideration of daily variation in insulin secretion is necessary to accurately describe glucose-stimulated insulin secretion, we describe a mathematical model that incorporates the circadian modulation via insulin granule trafficking. We use this model to understand the effect of oscillatory characteristics on insulin secretion at different times of the day. Furthermore, we integrate the dynamics of clock genes under the influence of competing environmental signals (light/dark cycle and feeding/fasting cycle) and demonstrate how circadian disruption and meal size distribution change the insulin secretion pattern over a 24-h day.