Taynnan Barros, Michael and Dey, Subhrakanti
(2018)
Feed-forward and Feedback Control in Astrocytes for Ca2+-based Molecular Communications Nanonetworks.
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 6.
pp. 78904-78917.
ISSN 1545-5963
Abstract
Synaptic plasticity depends on the gliotransmitters’ concentration in the synaptic channel. And, an abnormal concentration of gliotransmitters is linked to neurodegenerative diseases, including Alzheimer’s, Parkinson’s, and epilepsy. In this paper, a theoretical investigation of the cause of the abnormal concentration of gliotransmitters and how to achieve its control is presented through a Ca2+-signalling-based molecular communications framework. A feed-forward and feedback control technique is used to manipulate IP3 values to stabilise the concentration of Ca2+ inside the astrocytes. The theoretical analysis of the given model aims i) to stabilize the Ca2+ concentration around a particular desired level in order to prevent abnormal gliotransmitters’ concentration (extremely high or low concentration can result in neurodegeneration), ii) to improve the molecular communication performance that utilises Ca2+ signalling, and maintain gliotransmitters’ regulation remotely. It shows that the refractory periods from Ca2+ can be maintained to lower the noise propagation resulting in smaller time-slots for bit transmission, which can also improve the delay and gain performances. The proposed approach can potentially lead to novel nanomedicine solutions for the treatment of neurodegenerative diseases, where a combination of nanotechnology and gene therapy approaches can be used to elicit the regulated Ca2+ signalling in astrocytes, ultimately improving neuronal activity.
| Item Type: |
Article
|
| Keywords: |
Synapses;
Neurons;
Mathematical model;
Molecular communication;
Diseases; Molecular Communication;
Tripartite Synapses;
Ca2+ Signalling;
Astrocytes;
Control Theory;
Oscillators;
Feedback control; |
| Academic Unit: |
Faculty of Science and Engineering > Electronic Engineering |
| Item ID: |
12697 |
| Identification Number: |
https://doi.org/10.1109/TCBB.2018.288722 |
| Depositing User: |
Subhrakanti Dey
|
| Date Deposited: |
02 Apr 2020 11:00 |
| Journal or Publication Title: |
IEEE/ACM Transactions on Computational Biology and Bioinformatics |
| Publisher: |
IEEE |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
Repository Staff Only(login required)
 |
Item control page |
Downloads per month over past year
Origin of downloads
Altmetric
Altmetric