INTRODUCTION:Modelling of kidney physiology can add to comprehension of its work by formalizing existing information into numerical conditions and computational methods. The study evaluates the mathematical models that have been created to comprehend kidney physiology and pathophysiology.OBJECTIVE: Kidneys play a critical role in maintaining the body's water balance, electrolyte equilibrium, and acidbase balance, Through current knowledge with numerical models and computational methods, kidney physiology modeling will improve understanding of kidney function. METHOD:A L-System fractal system is designed to develop symmetrical branching tree systems that can fuse the physiological concepts of arterial tree branching to find the efficiency of blood flow in the renal arterial tree. Hopf Bifurcation analysis is also performed on mathematical models of autoregulation mechanisms that evaluate kidney physiology and glomerular filtration.RESULT: Because of the fractal structure of arterial branching, the flow rate is reduced in line with Strahler's order, so that work required (energy loss) is minimized to the cube root of flow rate. According to bifurcation analysis, mean arterial pressures between 70 and 100 mmHg can cause glomerulosclerosis, and a high gain in TGF signal can cause Limit cycle oscillations. CONCLUSION:The study concludes that nature has developed an optimal way of transferring blood from the Aorta to the Capillary bed by an evolutionary process such that the energy loss along the pathway is progressively reduced. Bifurcation analysis concludes that long and sustained oscillations due to underlying conditions such as diabetes, hypertension can lead to kidney damage.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.