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Glucose Homeostasis: Pancreatic Islets and Insulin Secretion01:27

Glucose Homeostasis: Pancreatic Islets and Insulin Secretion

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The pancreatic islets comprising only 1%-2% of the volume are highly vascularized and innervated mini-organs. They contain five endocrine cell types, including β cells that secrete insulin, which is synthesized as a single polypeptide chain, preproinsulin, processed to proinsulin, and finally to insulin and C-peptide. This process is complex and regulated, involving the Golgi complex, the endoplasmic reticulum, and the secretory granules of the β cell.
Insulin and C-peptide are...
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Glucose Homeostasis: Regulation of Blood Glucose01:02

Glucose Homeostasis: Regulation of Blood Glucose

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Carbohydrates consumed through foods are converted into glucose, a crucial energy source for the body. In the prandial state, high blood glucose levels stimulate the secretion of insulin from the pancreas. Insulin inhibits hepatic glucose production and stimulates glucose uptake and metabolism by muscle and adipose tissue. The excess glucose is converted into glycogen and stored in the liver and muscles.
During fasting, when blood glucose levels are low, the pancreas secretes glucagon. it...
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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
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Hormones Regulating Blood Glucose01:16

Hormones Regulating Blood Glucose

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Insulin is released by beta cells of the pancreas when blood glucose levels are high. It facilitates glucose absorption and utilization in insulin-dependent cells with insulin receptors on their plasma membranes. Insulin promotes glucose uptake by increasing the number of glucose transport proteins in the cell membrane, allowing glucose to enter the cell. As a result, glucose utilization and ATP production are enhanced.
In addition to accelerating glucose uptake and utilization, insulin has...
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Insulin Secretory Vesicles01:05

Insulin Secretory Vesicles

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Insulin secretory vesicles release insulin to stimulate blood glucose uptake and regulate carbohydrate metabolism. When the blood glucose levels increase, glucose enters the pancreatic β-islet cells through glucose transporters. Once inside, glucose is metabolized through glycolysis, the citric acid cycle, and the electron transport chain, producing ATP. This increase in ATP concentration closes ATP-sensitive potassium channels, leading to depolarization of the membrane and the opening of...
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Insulin: The Receptor and Signaling Pathways01:28

Insulin: The Receptor and Signaling Pathways

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Insulin action is mediated through a receptor tyrosine kinase, akin to the IGF-1 receptor. The number of receptors per cell varies significantly, from 40 on erythrocytes to 300,000 on adipocytes and hepatocytes. The insulin receptor consists of linked α/β subunit dimers, forming a heterotetramer glycoprotein with two extracellular α subunits and two β subunits spanning the membrane. The α subunits inhibit the inherent tyrosine kinase activity of the β subunits, but...
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Related Experiment Video

Updated: Jul 22, 2025

An In Ovo Model for Testing Insulin-mimetic Compounds
06:09

An In Ovo Model for Testing Insulin-mimetic Compounds

Published on: April 23, 2018

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A simple modeling framework for prediction in the human glucose-insulin system.

Melike Sirlanci1, Matthew E Levine1, Cecilia C Low Wang2

  • 1Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, California 91125, USA.

Chaos (Woodbury, N.Y.)
|July 24, 2023
PubMed
Summary

Forecasting blood glucose (BG) levels is improved using a new linear stochastic model that handles sparse data effectively. This personalized approach enhances glycemic management by predicting BG mean and variation for type 2 diabetes mellitus and ICU patients.

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Area of Science:

  • Biomedical Engineering
  • Mathematical Modeling
  • Endocrinology

Background:

  • Accurate blood glucose (BG) forecasting is crucial for effective glycemic management.
  • Nonlinear dynamics of BG are complex and nonstationary, posing challenges for forecasting with sparse data.
  • High-fidelity nonlinear models struggle with parameter identifiability due to data sparsity, leading to inaccurate predictions.

Purpose of the Study:

  • To develop a robust and accurate forecasting model for blood glucose levels using routinely collected, sparse data.
  • To approximate complex nonlinear BG dynamics with a simplified linear stochastic differential equation.
  • To create personalized BG forecasting models for type 2 diabetes mellitus (T2DM) and intensive care unit (ICU) settings.

Main Methods:

  • Developed a linear stochastic differential equation model to represent BG dynamics.
  • Incorporated deterministic terms for glucose removal, nutrition, and insulin effects.
  • Included a stochastic term to capture BG oscillations and estimated parameters patient-specifically.
  • Specialized the model for T2DM and ICU contexts with appropriate functions.

Main Results:

  • The linear stochastic model demonstrated robust parameter estimation and forecasting capabilities with sparse data.
  • Personalized models provided BG mean and variation forecasts, quantifying potential high and low glucose levels.
  • Experimental results showed the model's predictive performance in T2DM and ICU settings.

Conclusions:

  • A linear stochastic model offers a viable solution for accurate BG forecasting with sparse, routinely collected data.
  • Patient-specific parameter estimation enables personalized glycemic management strategies.
  • The model's predictions of BG mean and variation can aid in preventing hypo- and hyperglycemia, particularly in T2DM and ICU patients.