A Brand-new Research Method of Neuroendocrine System

TL;DR

This paper investigates the neuroendocrine system using bipartite graphs, revealing structural characteristics and degree distributions that could aid in understanding and treating neuroendocrine diseases.

Contribution

It introduces a novel bipartite graph model for the neuroendocrine system, highlighting its structural properties and potential applications in medical research.

Findings

Act degree distribution follows shifted power law (SPL)

bFGF has the highest node act degree

Average act degree is 3.01, similarity is 0.14

Abstract

In this paper, we present the empirical investigation results on the neuroendocrine system by bipartite graphs. This neuroendocrine network model can describe the structural characteristic of neuroendocrine system. The act degree distribution and cumulate act degree distribution show so-called shifted power law-SPL function forms. In neuroendocrine network, the act degree stands for the number of the cells that secretes a single mediator, in which bFGF(basic fibroblast growth factor) is the largest node act degree. It is an important mitogenic cytokine, followed by TGF-beta, IL-6, IL1-beta, VEGF, IGF-1and so on. They are critical in neuroendocrine system to maintain bodily healthiness, emotional stabilization and endocrine harmony. The average act degree of neuroendocrine network is h = 3.01, It means each mediator is secreted by three cells on an average . The similarity that stand for the average probability of secreting the same mediators by all the neuroendocrine cells is s = 0.14. Our results may be used in the research of the medical treatment of neuroendocrine diseases.