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

Insulin Secretory Vesicles01:05

Insulin Secretory Vesicles

6.1K
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...
6.1K
Variability: Analysis01:11

Variability: Analysis

280
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
280
One-Compartment Open Model for IV Bolus Administration: Estimation of Clearance00:56

One-Compartment Open Model for IV Bolus Administration: Estimation of Clearance

197
Clearance is a key pharmacokinetic parameter that quantifies the volume of body fluid from which a drug is entirely removed within a specific time frame. It is crucial in assessing how a drug is eliminated from the body and has critical clinical applications.
In the one-compartment open model for intravenous (IV) bolus administration, clearance is estimated by dividing the elimination rate by the plasma drug concentration. This equation leverages the elimination rate constant and the apparent...
197
Glucose Homeostasis: Pancreatic Islets and Insulin Secretion01:27

Glucose Homeostasis: Pancreatic Islets and Insulin Secretion

1.7K
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...
1.7K
One-Compartment Open Model for IV Bolus Administration: Estimation of Elimination Rate Constant, Half-Life and Volume of Distribution01:09

One-Compartment Open Model for IV Bolus Administration: Estimation of Elimination Rate Constant, Half-Life and Volume of Distribution

653
The one-compartment open model is a simplified approach used in pharmacokinetics to understand the distribution and elimination of a drug administered through an intravenous bolus. This model assumes rapid drug dispersal throughout the body and elimination using a first-order process. Key pharmacokinetic parameters, such as the elimination rate constant (k), half-life (t1/2), and the apparent volume of distribution (Vd), can be estimated from this model. The elimination rate is calculated...
653
Insulin: Dosing Regimen and Adverse Effects01:16

Insulin: Dosing Regimen and Adverse Effects

403
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...
403

You might also read

Related Articles

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

Sort by
Same author

Respiratory and oxygen saturation data for improved modelling and detection of obstructive sleep apnoea.

Data in brief·2026
Same author

'Impossible' Insulin to C-Peptide Ratios are Common in Insulin-Free Pre-term NICU Infants: Antibodies Act as a Storage Medium.

Journal of diabetes science and technology·2026
Same author

Demand-Side Management for a Decentralised and Equitable Energy Transition in Aotearoa New Zealand.

Journal of the Royal Society of New Zealand·2026
Same author

Quantifying the recollection of discomfort and emotional suffering during a stay in intensive care: development and validation of the EXPRIM questionnaire : EXPRIM: quantification of discomfort experienced during an ICU stay.

Journal of patient-reported outcomes·2026
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 journal

A Pilot Study on Disposal Practices and Environmental Awareness of Insulin-Related Devices Among People With Diabetes.

Journal of diabetes science and technology·2026
Same journal

Quality of In-Use Insulin Under Real-World Storage Conditions in Mwanza, Tanzania.

Journal of diabetes science and technology·2026
Same journal

Continuous Glucose Monitoring Metrics for Predicting Adverse Neonatal Outcomes in Individuals Undergoing Gestational Diabetes Screening.

Journal of diabetes science and technology·2026
Same journal

Diabetes Technologist: Optimal Use of Technology in Everyday Practice.

Journal of diabetes science and technology·2026
Same journal

AI-Driven Diabetes Care and Its Relevance in the Philippine Context: Opportunities and Persistent Digital Barriers.

Journal of diabetes science and technology·2026
Same journal

Ease of Use, Ease of Learning, and Convenience of the CagriSema Dual-Chamber Pen: Results From a Usability Study in Adults With Overweight, Obesity, or Type 2 Diabetes.

Journal of diabetes science and technology·2026
See all related articles

Related Experiment Video

Updated: Nov 17, 2025

Homogeneous Time-resolved Förster Resonance Energy Transfer-based Assay for Detection of Insulin Secretion
07:30

Homogeneous Time-resolved Förster Resonance Energy Transfer-based Assay for Detection of Insulin Secretion

Published on: May 10, 2018

9.5K

Variability in Estimated Modelled Insulin Secretion.

Jennifer J Ormsbee1, Hannah J Burden2, Jennifer L Knopp1

  • 1Department of Mechanical Engineering, Centre for Bioengineering, University of Canterbury, Christchurch, New Zealand.

Journal of Diabetes Science and Technology
|February 16, 2021
PubMed
Summary
This summary is machine-generated.

Understanding insulin secretion variability is key for diabetes management. This study quantifies expected model-based variation in C-peptide measurements, aiding accurate glucose-insulin physiology monitoring.

Keywords:
glycemic controlinsulin secretioninsulin sensitivitymathematical modelvariability

More Related Videos

Measuring Relative Insulin Secretion using a Co-Secreted Luciferase Surrogate
05:58

Measuring Relative Insulin Secretion using a Co-Secreted Luciferase Surrogate

Published on: June 25, 2019

7.7K
Hyperinsulinemic-euglycemic Clamps in Conscious, Unrestrained Mice
11:10

Hyperinsulinemic-euglycemic Clamps in Conscious, Unrestrained Mice

Published on: November 16, 2011

95.3K

Related Experiment Videos

Last Updated: Nov 17, 2025

Homogeneous Time-resolved Förster Resonance Energy Transfer-based Assay for Detection of Insulin Secretion
07:30

Homogeneous Time-resolved Förster Resonance Energy Transfer-based Assay for Detection of Insulin Secretion

Published on: May 10, 2018

9.5K
Measuring Relative Insulin Secretion using a Co-Secreted Luciferase Surrogate
05:58

Measuring Relative Insulin Secretion using a Co-Secreted Luciferase Surrogate

Published on: June 25, 2019

7.7K
Hyperinsulinemic-euglycemic Clamps in Conscious, Unrestrained Mice
11:10

Hyperinsulinemic-euglycemic Clamps in Conscious, Unrestrained Mice

Published on: November 16, 2011

95.3K

Area of Science:

  • Endocrinology
  • Metabolic Physiology
  • Biomedical Modeling

Background:

  • Accurate measurement of insulin secretion from pancreatic beta cells is crucial for monitoring glucose-insulin physiology.
  • C-peptide serves as a reliable surrogate for plasma insulin concentration.
  • Quantifying variability in modelled insulin secretion enhances confidence in model estimates.

Purpose of the Study:

  • To quantify the expected variability of modelled insulin secretion using C-peptide measurements.
  • To improve confidence in model estimates for insulin secretion.
  • To assess the impact of Body Mass Index (BMI) on insulin secretion variability.

Main Methods:

  • Employed a frequently sampled, intravenous glucose tolerance test (FS-IVGTT) in 43 healthy adult males.
  • Utilized a 2-compartment model with standardized kinetic parameters to estimate insulin secretion from C-peptide.
  • Applied Monte Carlo analysis (N=10,000) to determine the range of expected insulin secretion variability.

Main Results:

  • Modelled insulin secretion estimates show approximately ±15% variation.
  • Higher variability (34.3% IQR) observed in subjects with BMI > 30 kg/m² compared to those with BMI ≤ 30 kg/m² (24.7% IQR).

Conclusions:

  • C-peptide measurements with a 2-compartment model provide ~±15% variation in insulin secretion estimates.
  • This variability must be considered for clinical diagnostic thresholds and model-based analyses like insulin sensitivity.
  • The findings aid in more precise interpretation of insulin secretion dynamics.