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

Obesity01:24

Obesity

1.1K
The Body Mass Index (BMI) is a numerical value derived from a person's weight and height, used to categorize individuals into weight ranges. It is calculated using the formula: weight in kilograms divided by height in meters squared. Obesity is a health condition characterized by excessive accumulation of adipose tissue that poses health risks, often diagnosed with a BMI ≥ 30. This excess fat storage occurs when surplus dietary calories are converted into triglycerides and stored in...
1.1K
Insulin: The Receptor and Signaling Pathways01:28

Insulin: The Receptor and Signaling Pathways

2.7K
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...
2.7K

You might also read

Related Articles

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

Sort by
Same author

Effects of garlic supplementation on glycemic indices in adults: a GRADE-assessed systematic review and dose-response meta-analysis of randomized controlled trials.

Diabetes research and clinical practice·2026
Same author

Dietary supplement consumption among active individuals in Saudi Arabia.

PloS one·2026
Same author

Comparative evaluation of antioxidant, cytoprotective, and anti-arthritic activities of pomegranate peel powder and coarse powdered date seeds: implications for functional nutrition.

Journal, genetic engineering & biotechnology·2026
Same author

Correlation of vitamin D levels with TNF-α and IL-6 expression in insulin-resistant type 2 diabetes mellitus patients.

Scientific reports·2026
Same author

Erucin Targets Oncogenic Signaling Pathways in Triple-Negative Breast Cancer: An Integrated Network Pharmacology and In Vitro Study.

Life (Basel, Switzerland)·2026
Same author

Integrative Pharmacological and Computational Analysis of <i>Abelmoschus esculentus</i> Phytochemicals: Enzyme Inhibition, Molecular Docking, and Dynamics Simulation Against Key Antidiabetic Targets.

Life (Basel, Switzerland)·2026

Related Experiment Video

Updated: Jan 10, 2026

A Buoyancy-based Method of Determining Fat Levels in Drosophila
08:00

A Buoyancy-based Method of Determining Fat Levels in Drosophila

Published on: November 1, 2016

9.0K

Examining the interplay between sdLDL, resistin, and BMI.

Fauzia Ashfaq1, Mohammad Idreesh Khan2, Abdulrahman A Alsayegh1

  • 1Department of Clinical Nutrition, College of Nursing and Health Sciences, Jazan University, Jazan, 45142, Saudi Arabia.

Scientific Reports
|November 29, 2025
PubMed
Summary

Obesity is linked to higher levels of small dense low-density lipoprotein (sdLDL) and resistin, which are key indicators of dyslipidemia and metabolic issues. These biomarkers can help predict obesity and guide early interventions for cardiovascular risk.

Keywords:
Body mass indexObesityPrognostic markerResistinSmall dense LDL

More Related Videos

Author Spotlight: Semi-Automated Isolation of the Stromal Vascular Fraction from Murine White Adipose Tissue Using a Tissue Dissociator
06:08

Author Spotlight: Semi-Automated Isolation of the Stromal Vascular Fraction from Murine White Adipose Tissue Using a Tissue Dissociator

Published on: May 19, 2023

2.8K
An Adipocyte Cell Culture Model to Study the Impact of Protein and Micro-RNA Modulation on Adipocyte Function
09:20

An Adipocyte Cell Culture Model to Study the Impact of Protein and Micro-RNA Modulation on Adipocyte Function

Published on: May 4, 2021

4.2K

Related Experiment Videos

Last Updated: Jan 10, 2026

A Buoyancy-based Method of Determining Fat Levels in Drosophila
08:00

A Buoyancy-based Method of Determining Fat Levels in Drosophila

Published on: November 1, 2016

9.0K
Author Spotlight: Semi-Automated Isolation of the Stromal Vascular Fraction from Murine White Adipose Tissue Using a Tissue Dissociator
06:08

Author Spotlight: Semi-Automated Isolation of the Stromal Vascular Fraction from Murine White Adipose Tissue Using a Tissue Dissociator

Published on: May 19, 2023

2.8K
An Adipocyte Cell Culture Model to Study the Impact of Protein and Micro-RNA Modulation on Adipocyte Function
09:20

An Adipocyte Cell Culture Model to Study the Impact of Protein and Micro-RNA Modulation on Adipocyte Function

Published on: May 4, 2021

4.2K

Area of Science:

  • Endocrinology
  • Cardiovascular Science
  • Metabolic Health

Background:

  • Obesity is a global health concern, increasing the risk of chronic diseases.
  • Poor health outcomes correlate with body mass index (BMI).
  • Obesity alters lipid profiles, potentially increasing small dense low-density lipoprotein (sdLDL) and resistin levels, contributing to atherosclerosis and metabolic dysfunction.

Purpose of the Study:

  • To investigate the relationship between BMI, sdLDL, and resistin levels.
  • To evaluate the potential of sdLDL and resistin as biomarkers for obesity-related metabolic and cardiovascular risks.

Main Methods:

  • A study involving 300 participants with varying BMI levels.
  • Measurement of sdLDL and resistin using ELISA.
  • Analysis of lipid parameters, HbA1c, and correlation with BMI, blood pressure, and lifestyle factors (smoking, hypertension).
  • Receiver Operating Characteristic (ROC) curve analysis to determine biomarker cutoffs.

Main Results:

  • Obese participants exhibited significantly higher HbA1c, LDL, triglycerides, cholesterol, and VLDL compared to normal and overweight groups.
  • Smokers and hypertensive individuals showed elevated sdLDL and resistin levels.
  • Both sdLDL and resistin levels increased with BMI, showing positive correlations with each other and with adverse lipid profiles.
  • ROC analysis identified specific cutoffs for sdLDL (18.55 mg/dL) and resistin (750 pg/mL) as prognostic markers for overweight and obesity.

Conclusions:

  • Resistin and sdLDL are primary contributors to dyslipidemia and metabolic dysregulation in obesity.
  • Both biomarkers effectively predict higher BMI categories, with resistin as a universal risk factor and sdLDL showing a male-specific correlation.
  • sdLDL and resistin demonstrate high predictive accuracy, validating their use in early risk assessment and guiding interventions for obesity-related metabolic and cardiovascular risks.