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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.
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Hormones Regulating Blood Glucose01:16

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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.
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Diabetes Mellitus: Type 2 and Gestational01:22

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Type 2 diabetes, characterized by insulin resistance, arises when the insulin receptors on cells lose responsiveness to insulin, diminishing the cell's capacity to take up glucose, resulting in elevated blood glucose levels. To receive a diagnosis of Type 2 diabetes, a series of blood glucose tests are necessary to assess whether the blood glucose falls within normal parameters. If the result is out of the normal range, a patient may be diagnosed as prediabetic or diabetic, depending on the...
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Neural Regulation of Blood Pressure01:18

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The neural regulation of blood pressure involves intricate interactions between the autonomic nervous system (ANS) and cardiovascular system, ensuring adequate perfusion of tissues. This regulation primarily occurs through baroreceptor and chemoreceptor reflexes, involving both short-term and long-term mechanisms.
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Glucose Homeostasis: Pancreatic Islets and Insulin Secretion01:27

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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.
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Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

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Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
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Updated: Jul 24, 2025

A Method for Manipulating Blood Glucose and Measuring Resulting Changes in Cognitive Accessibility of Target Stimuli
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A 2-dimensional model framework for blood glucose prediction based on iterative learning control architecture.

Shuang Wen1, Hongru Li2, Rui Tao1

  • 1College of Information Sciences and Engineering, Northeastern University, No. 11 St. 3, Wenhua Road, Heping District, Shenyang, 110819, People's Republic of China.

Medical & Biological Engineering & Computing
|July 3, 2023
PubMed
Summary

Predicting future blood glucose (BG) levels is crucial for diabetes management. A new 2-D model framework using neural networks improves BG prediction accuracy and reduces delay by considering daily and inter-day glycemic dynamics.

Keywords:
2-dimensional modelBlood glucose predictionIterative learning controlType 1 diabetes

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Area of Science:

  • Biomedical Engineering
  • Artificial Intelligence in Healthcare
  • Diabetes Technology

Background:

  • Accurate, personalized blood glucose (BG) prediction is essential for advancing diabetes management.
  • Human circadian rhythms and lifestyle influence daily glycemic dynamics, offering potential for predictive modeling.

Purpose of the Study:

  • To develop an advanced model framework for accurate and timely prediction of future blood glucose levels.
  • To leverage both intra-day and inter-day glycemic data for enhanced prediction accuracy.

Main Methods:

  • A 2-dimensional (2-D) model framework inspired by iterative learning control (ILC) was developed.
  • Radial basis function neural networks were employed to capture nonlinearities in glycemic metabolism.
  • Patient-specific models were built and validated on in silico datasets across various prediction horizons (PHs).

Main Results:

  • The 2-D framework demonstrated increased prediction accuracy for blood glucose levels.
  • The model successfully reduced the delay in predicting future glycemic trends.
  • The approach effectively integrated short-range (intra-day) and long-range (inter-day) glycemic information.

Conclusions:

  • The proposed 2-D modeling framework offers a novel approach to blood glucose prediction.
  • This method enhances personalized glucose management, including applications in hypoglycemia warning and glycemic control.
  • The findings contribute to the development of more sophisticated diabetes management technologies.