Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Glucose Homeostasis: Regulation of Blood Glucose01:02

Glucose Homeostasis: Regulation of Blood Glucose

3.7K
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...
3.7K
Glucose Homeostasis: Pancreatic Islets and Insulin Secretion01:27

Glucose Homeostasis: Pancreatic Islets and Insulin Secretion

2.1K
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...
2.1K
Diabetes Mellitus: Type 2 and Gestational01:22

Diabetes Mellitus: Type 2 and Gestational

4.2K
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...
4.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Tight Glycemic Control Can Be Achieved in Adult ICU Patients Safely: Results From a 5-Year Single-Center Observational Study Using the STAR Glycemic Control Framework.

Journal of diabetes science and technology·2026
Same author

Incorporating patient history into the insulin sensitivity prediction in intensive care by feedforward neural network models.

International journal of medical informatics·2026
Same author

Monitoring Airway Resistance for Obstructive Sleep Apnea Using a Leak-Based BiPAP System.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

A novel clinical data acquisition device: Towards real time cardiovascular modelling in the ICU.

HardwareX·2025
Same author

Evaluation of insulin sensitivity temporal prediction by using quantile regression combined with neural network model.

International journal of medical informatics·2025
Same author

Detection of spontaneous breathing during an apnea test in a patient with suspected brain death using electrical impedance tomography: a case report.

BMC pulmonary medicine·2024

Related Experiment Video

Updated: Jan 5, 2026

Computational Reconstruction of Pancreatic Islets as a Tool for Structural and Functional Analysis
07:58

Computational Reconstruction of Pancreatic Islets as a Tool for Structural and Functional Analysis

Published on: March 9, 2022

1.9K

3D kernel-density stochastic model for more personalized glycaemic control: development and in-silico validation.

Vincent Uyttendaele1,2, Jennifer L Knopp3, Shaun Davidson3

  • 1Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand. vincent.uyttendaele@pg.canterbury.ac.nz.

Biomedical Engineering Online
|October 24, 2019
PubMed
Summary

A new 3D stochastic model for the Stochastic-Targeted (STAR) glycaemic control framework offers improved personalization for critically ill patients. This advanced model better captures metabolic variability, leading to tighter glucose predictions and enhanced control outcomes without compromising safety.

Keywords:
Blood glucoseGlycaemic controlHyperglycaemiaInsulinInsulin sensitivityKernel density

More Related Videos

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

11.1K
Modeling the Endothelial Glycocalyx Post-Pneumonectomy in a 3D Fluidic Chip - An Approach to Fabricating a Vascular-based Organ-on-Chip System
06:12

Modeling the Endothelial Glycocalyx Post-Pneumonectomy in a 3D Fluidic Chip - An Approach to Fabricating a Vascular-based Organ-on-Chip System

Published on: September 16, 2025

548

Related Experiment Videos

Last Updated: Jan 5, 2026

Computational Reconstruction of Pancreatic Islets as a Tool for Structural and Functional Analysis
07:58

Computational Reconstruction of Pancreatic Islets as a Tool for Structural and Functional Analysis

Published on: March 9, 2022

1.9K
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

11.1K
Modeling the Endothelial Glycocalyx Post-Pneumonectomy in a 3D Fluidic Chip - An Approach to Fabricating a Vascular-based Organ-on-Chip System
06:12

Modeling the Endothelial Glycocalyx Post-Pneumonectomy in a 3D Fluidic Chip - An Approach to Fabricating a Vascular-based Organ-on-Chip System

Published on: September 16, 2025

548

Area of Science:

  • Critical Care Medicine
  • Biomedical Engineering
  • Endocrinology

Background:

  • Glycaemic control in critically ill patients is challenging due to metabolic variability, increasing morbidity and mortality.
  • Current guidelines recommend higher glucose targets, fearing hypoglycemia and variability.
  • Computerized, model-based methods offer personalized insulin/nutrition titration, improving safety and efficacy.

Purpose of the Study:

  • To compare a novel 3D stochastic model with the existing 2D model within the STAR glycaemic control framework.
  • To assess the 3D model's ability to capture metabolic variability and improve glycaemic outcomes.
  • To evaluate the enhanced personalization and safety of the 3D model.

Main Methods:

  • Development of a 3D stochastic model using kernel-density estimation, building upon the 2D STAR model.
  • Fivefold cross-validation using 681 retrospective patient glycaemic control episodes (>65,000 hours).
  • Validated virtual trials to assess glycaemic outcome gains and safety.

Main Results:

  • The 3D model demonstrated similar predictive power but significantly tighter, patient-specific prediction ranges compared to the 2D model.
  • The 2D model was found to be over-conservative in over 70% of cases.
  • Virtual trials showed similar safety and performance, with the 3D model reducing median blood glucose and increasing time within the target range (4.4-6.5 mmol/L).

Conclusions:

  • The 3D stochastic model better characterizes patient-specific insulin sensitivity dynamics, leading to improved simulated glycaemic outcomes.
  • Enhanced personalization in glucose control was achieved with higher insulin rates and carbohydrate intake, maintaining safety.
  • The study supports the integration of the 3D STAR model into clinical practice for improved glycaemic management.