Modeling the physiological glucose-insulin system on normal and diabetic subjects

Area of Science:

• * Mathematical modeling
• * Biomedical engineering
• * Endocrinology

Background:

• * Understanding daily glucose and insulin variations is crucial for managing diabetes.
• * Existing models may not fully capture the complex dynamics in both healthy and diabetic states.

Purpose of the Study:

• * To develop a novel mathematical model for simulating plasma glucose and insulin daily variations.
• * To characterize the distinct physiological dynamics and oscillation behaviors in normal and diabetic subjects.
• * To assess the model's practicality in representing real-world glucose dynamics.

Main Methods:

• * Development of a mathematical model comprising two delay differential equations (DDEs).
• * Incorporation of five adjustable parameters to define subject-specific dynamics.
• * Validation of the model using clinical data from normal, Type 1, and Type 2 diabetic subjects.

Main Results:

• * The proposed DDE model accurately describes daily glucose dynamics across different subject groups.
• * The model's parameters effectively differentiate between normal, Type 1, and Type 2 diabetes.
• * Clinical data tests confirm the model's practical applicability.

Conclusions:

• * The developed mathematical model provides a robust tool for analyzing glucose-insulin dynamics.
• * The model aids in distinguishing physiological functions in normal and diabetic individuals.
• * This approach offers potential for improved patient condition identification and management.