An application of queueing theory to the relationship between insulin level and number of insulin receptors


Kandemir Çavaş Ç., Çavaş L.

TURKISH JOURNAL OF BIOCHEMISTRY-TURK BIYOKIMYA DERGISI, vol.32, no.1, pp.32-38, 2007 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 32 Issue: 1
  • Publication Date: 2007
  • Journal Name: TURKISH JOURNAL OF BIOCHEMISTRY-TURK BIYOKIMYA DERGISI
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), TR DİZİN (ULAKBİM)
  • Page Numbers: pp.32-38
  • Keywords: arrival rate, insulin, number of insulin receptors, queueing, service rate, human metabolism, GLUCOSE-TOLERANCE TEST, MONTE-CARLO-SIMULATION, HYPERTENSION, SENSITIVITY
  • Dokuz Eylül University Affiliated: Yes

Abstract

Insulin is a hormone that regulates blood glucose levels. Its deficiency or over secretion cause many disorders including polyurea, polydipsia, and weight loss in metabolism. Publications to date show strict relationships between insulin level and number of insulin receptors in a cell. In this respect a mathematical estimation on insulin level and number of insulin receptors may be important in order to understand some diseases related to insulin level and number of insulin receptors. In the present study, a queueing theory originated model is applied to insulin level and number of insulin receptors. Based on real data, some parameters such as optimum insulin level, number of insulin receptor and minimum required energy spent were calculated by using queueing theory. Our results show an indirect correlation between insulin level and receptor. The total energy spent is also decreased up to optimum number of insulin receptors and then it is increased. From the results, it could be said that queuing theory predicts the optimal number of insulin receptors. In conclusion, the data reveals that queueing theory can be applied to insulin level and number of insulin receptors. Estimation of insulin levels in insulin-insulin receptor complex and number of insulin receptors obtained through queueing analysis may identify etiological origins of some insulin-based metabolic disorders.