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

Hormones Regulating Blood Glucose01:16

Hormones Regulating Blood Glucose

3.3K
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...
3.3K
Oral Hypoglycemic Agents: Glinides01:06

Oral Hypoglycemic Agents: Glinides

154
Repaglinide (Prandin) and Nateglinide (Starlix), known as glinides, are oral insulin secretagogues that stimulate insulin release from pancreatic β cells by closing the ATP-sensitive potassium channels (KATP channel). Repaglinide controls insulin release from pancreatic β cells by managing potassium efflux. It shares two binding sites with sulfonylureas and also has a unique site, indicating overlapping mechanisms of action. With a rapid onset and a 4-7 hour duration, it effectively...
154
Glucose Homeostasis: Pancreatic Islets and Insulin Secretion01:27

Glucose Homeostasis: Pancreatic Islets and Insulin Secretion

1.2K
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...
1.2K
Insulin: Dosing Regimen and Adverse Effects01:16

Insulin: Dosing Regimen and Adverse Effects

169
Insulin-replacement therapy usually includes both long-acting insulin (basal) and short-acting insulin (to cater to postprandial needs). In a diverse group of type 1 diabetes patients, the average daily insulin dose is typically 0.5-0.7 units/kg body weight. However, obese patients and pubertal adolescents may need more due to insulin resistance.
The basal dose constitutes about 40%-50% of the total daily dose, with the rest as premeal insulin. The mealtime insulin dose should mirror...
169
Diabetes Mellitus: Type 2 and Gestational01:22

Diabetes Mellitus: Type 2 and Gestational

2.3K
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...
2.3K
Hypoglycemia and Glucagon01:15

Hypoglycemia and Glucagon

257
Without prolonged fasting, healthy individuals maintain blood glucose levels above 3.5 mM due to a well-adapted neuroendocrine counterregulatory system that effectively prevents acute hypoglycemia, a potentially life-threatening condition. The primary clinical scenarios for hypoglycemia encompass diabetes treatment, inappropriate production of endogenous insulin or insulin-like substances by tumors, and the use of glucose-lowering agents in non-diabetic individuals. Notably, hypoglycemia in the...
257

You might also read

Related Articles

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

Sort by
Same author

Comparing Automated Lyumjev® Delivery with Carbohydrate Counting, Qualitative Meal-Size Estimation, and Fully Closed-Loop in Type 1 Diabetes: A Pilot, Randomized, Crossover Trial.

Diabetes technology & therapeutics·2026
Same author

Design and Evaluation of a Novel Clinical Decision Support Algorithm for Weekly Insulin Efsitora Alfa.

Journal of diabetes science and technology·2026
Same author

A hierarchical network model for the estimate of the energy expenditure in individuals with type 1 diabetes.

Engineering applications of artificial intelligence·2026
Same author

Integrating the Glycemia Risk Index Into Clinical Practice and Research: A Consensus Report.

Journal of diabetes science and technology·2026
Same author

Autoregressive With Exogenous Input (ARX) Decision Support for Blood Pressure Maintenance During Cesarean Delivery Under Spinal Anesthesia: A Prospective Pilot Study With Matched Nonconcurrent Controls.

medRxiv : the preprint server for health sciences·2026
Same author

Research Code Sharing in Support of Gold Standard Science.

Journal of diabetes science and technology·2026

Related Experiment Video

Updated: Jun 29, 2025

Quantitative and Temporal Control of Oxygen Microenvironment at the Single Islet Level
11:49

Quantitative and Temporal Control of Oxygen Microenvironment at the Single Islet Level

Published on: November 17, 2013

9.2K

Glucose Rate-of-Change and Insulin-on-Board Jointly Weighted Zone Model Predictive Control.

Sunil Deshpande1, Francis J Doyle1, Eyal Dassau1

  • 1Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA.

IEEE Transactions on Control Systems Technology : a Publication of the IEEE Control Systems Society
|March 25, 2024
PubMed
Summary

This study introduces an adaptive zone model predictive control (MPC) for closed-loop insulin delivery. The novel system effectively manages blood glucose levels, reducing hyperglycemia without increasing hypoglycemia risk.

Keywords:
adaptive algorithmsclosed-loop insulin deliverydiabetesmedical control systemsmodel predictive control

More Related Videos

Improving IV Insulin Administration in a Community Hospital
12:08

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

18.8K
Glucose Uptake Measurement and Response to Insulin Stimulation in In Vitro Cultured Human Primary Myotubes
08:03

Glucose Uptake Measurement and Response to Insulin Stimulation in In Vitro Cultured Human Primary Myotubes

Published on: June 25, 2017

20.0K

Related Experiment Videos

Last Updated: Jun 29, 2025

Quantitative and Temporal Control of Oxygen Microenvironment at the Single Islet Level
11:49

Quantitative and Temporal Control of Oxygen Microenvironment at the Single Islet Level

Published on: November 17, 2013

9.2K
Improving IV Insulin Administration in a Community Hospital
12:08

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

18.8K
Glucose Uptake Measurement and Response to Insulin Stimulation in In Vitro Cultured Human Primary Myotubes
08:03

Glucose Uptake Measurement and Response to Insulin Stimulation in In Vitro Cultured Human Primary Myotubes

Published on: June 25, 2017

20.0K

Area of Science:

  • Biomedical Engineering
  • Control Systems Engineering
  • Endocrinology

Background:

  • Closed-loop insulin delivery systems aim to automate blood glucose management for diabetes.
  • Existing systems face challenges with variable insulin sensitivity, underdelivery, and meal composition, leading to prolonged hyperglycemia.
  • Model predictive control (MPC) offers a promising framework for advanced glycemic control.

Purpose of the Study:

  • To design and evaluate an adaptive zone model predictive control (MPC) for closed-loop insulin delivery.
  • To address prolonged hyperglycemia by incorporating an adaptive weighting scheme into the MPC cost function.
  • To improve glucose control by considering glucose rate-of-change (ROC) and insulin-on-board (IOB) for personalized adjustments.

Main Methods:

  • Developed a zone MPC with an adaptive weighting scheme in the cost function.
  • The weighting scheme jointly considers predicted glucose ROC and IOB to modulate glycemic control.
  • Evaluated the controller using simulation scenarios (induced resistance, nominal) and clinical validation in outpatient studies.

Main Results:

  • The adaptive zone MPC demonstrated consistent improvement across the glucose range without increasing hypoglycemia risk.
  • In an induced resistance scenario without a feedforward bolus, time in the 70-180 mg/dL range improved (53.5% vs. 48.9%, p<0.001).
  • Overnight time in the tighter 70-140 mg/dL range significantly improved (70.9% vs. 52.9%, p<0.001).

Conclusions:

  • The proposed adaptive zone MPC is effective in managing prolonged hyperglycemia in closed-loop insulin delivery.
  • The adaptive weighting scheme enhances glucose control by responding to glucose ROC and IOB dynamics.
  • Clinical validation supports the utility and safety of this advanced glycemic control strategy.