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A computational model of urinary bladder smooth muscle syncytium

DSpace at IIT Bombay

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Title A computational model of urinary bladder smooth muscle syncytium
 
Creator APPUKUTTAN, S
BRAIN, KL
MANCHANDA, R
 
Subject PIG VAS-DEFERENS
EXCITATORY JUNCTION POTENTIALS
GUINEA-PIG
ELECTRICAL-PROPERTIES
SYNAPTIC POTENTIALS
GAP-JUNCTIONS
OUTLET OBSTRUCTION
CABLE PROPERTIES
FIBER MEMBRANE
ION CHANNELS
Electrical Syncytium
Detrusor
Gap Junction
Smooth Muscle
Compartmental Modeling
 
Description Certain smooth muscles, such as the detrusor of the urinary bladder, exhibit a variety of spikes that differ markedly in their amplitudes and time courses. The origin of this diversity is poorly understood but is often attributed to the syncytial nature of smooth muscle and its distributed innervation. In order to help clarify such issues, we present here a three-dimensional electrical model of syncytial smooth muscle developed using the compartmental modeling technique, with special reference to the bladder detrusor. Values of model parameters were sourced or derived from experimental data. The model was validated against various modes of stimulation employed experimentally and the results were found to accord with both theoretical predictions and experimental observations. Model outputs also satisfied criteria characteristic of electrical syncytia such as correlation between the spatial spread and temporal decay of electrotonic potentials as well as positively skewed amplitude frequency histogram for sub-threshold potentials, and lead to interesting conclusions. Based on analysis of syncytia of different sizes, it was found that a size of 21-cube may be considered the critical minimum size for an electrically infinite syncytium. Set against experimental results, we conjecture the existence of electrically sub-infinite bundles in the detrusor. Moreover, the absence of coincident activity between closely spaced cells potentially implies, counterintuitively, highly efficient electrical coupling between such cells. The model thus provides a heuristic platform for the interpretation of electrical activity in syncytial tissues.
 
Publisher SPRINGER
 
Date 2016-01-14T12:06:16Z
2016-01-14T12:06:16Z
2015
 
Type Article
 
Identifier JOURNAL OF COMPUTATIONAL NEUROSCIENCE, 38(1)167-187
0929-5313
1573-6873
http://dx.doi.org/10.1007/s10827-014-0532-6
http://dspace.library.iitb.ac.in/jspui/handle/100/17454
 
Language en