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A minimal mathematical model to study insulin synthesis and secretion process.

Authors :
Paul, Abhijit
Kundu, Jayendrajyoti
Chatterjee, Samrat
Source :
Applied Mathematical Modelling. Oct2023, Vol. 122, p456-476. 21p.
Publication Year :
2023

Abstract

• A minimal model is proposed to study the insulin synthesis and secretion processes. • Identifies possible factors responsible for reduced insulin secretion. • Identifies potential factors responsible for elevated basal insulin secretion. • Compares the restoration capabilities between insulin synthesis and secretion. • Explores restoration strategies for compensating the beta-cells mass. Insulin, secreted from pancreatic β -cells, plays a vital role in maintaining glucose homeostasis in our body. In various pathophysiological conditions like diabetes, cancer, etc., this glucose-insulin relationship is altered. However, the underlying mechanisms behind the β -cell malfunctioning under these pathophysiological conditions remain a research topic. The current study aimed to explore the key factors responsible for impaired insulin secretion from β -cells. We studied insulin synthesis and secretion processes through a minimal mathematical model incorporating insulin mRNA, proinsulin pool, and insulin granules. Defects in the insulin granule trafficking and exocytosis processes hamper first- and second-phase insulin secretion and might be one of the main reasons for β -cell dysfunction in type 2 diabetes. The long-term effect of abnormal insulin synthesis could hamper insulin secretion and make the scenario more critical, causing complete insulin loss inside the β -cells. Besides, uncontrolled insulin synthesis could increase basal insulin secretion and drive toward fasting hypoglycemia. The present study also hypothesizes that regulation of insulin synthesis through targeting transcription and translation is a potential therapeutic strategy for controlling impaired insulin secretion. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0307904X
Volume :
122
Database :
Academic Search Index
Journal :
Applied Mathematical Modelling
Publication Type :
Academic Journal
Accession number :
169815460
Full Text :
https://doi.org/10.1016/j.apm.2023.06.012