Related Experiment Video
Updated: Feb 7, 2026

Fast Micro-iontophoresis of Glutamate and GABA: A Useful Tool to Investigate Synaptic Integration
Published on: July 31, 2013
Hyper-insulinemia increases the glutamate-excitotoxicity in cortical neurons: A mechanistic study
Ashok Kumar Datusalia1, Piyush Agarwal1, Jitendra Narain Singh1
1Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER), Sector-67, S.A.S. Nagar 160062 Punjab, India.
Abstract:
Insulin resistance in type-2 diabetic condition increases the risk of stroke and cognitive deficits in which involvement of glutamate has been postulated. It has been hypothesized that hyper-insulinemia in cortical neurons increases the vulnerability towards glutamate-induced excitotoxicity. To mimic insulin resistance, cortical neurons were incubated with high insulin (1 µM) and high glucose (50 mM final concentration) in in-vitro condition for 24 h. Pre-treatment of cortical neurons with high insulin blocked acute insulin-induced activation of Akt and GSK-3β but not in the case of high glucose. Our results demonstrate that chronic high insulin exposure increases glutamate-induced excitotoxity, which was blocked by insulin receptor antagonist (S961) and GSK-3β inhibitor (SB216763). These inhibitors also ameliorated pAkt (Ser473) and pGSK-3β(Ser9) levels after chronic insulin exposure. Increase in glutamate-excitotoxicity in insulin-resistant cortical neurons was found to be associated with increased expression of PICK1. However, GluR2 did not get altered in hyper-insulinemia condition. This study demonstrates that hyper-insulinemia increases glutamate excitotoxicity which could be attributed to activation of GSK-3β and increased expression of PICK1.
Related Concept Videos
Increasing Function
Antiepileptic Drugs: Glutamate Antagonists
Increased Body Temperature
Increased pulse rate
Many factors can elevate the risk of developing tachycardia. These include advanced age, a family history of arrhythmias, and an...
Mechanistic Models: Overview of Compartment Models
Mechanistic Models: Compartment Models in Individual and Population Analysis

