Gupta, I and Cassará, A M and Tarotin, I and Donega, M and Miranda, J A and Sokal, D M and Ouchouche, S and Dopson, W and Matteucci, P and Neufeld, E and Schiefer, M A and Rowles, A and McGill, P and Perkins, J and Dolezalova, N and Saeb-Parsy, K and Kuster, N and Yazicioglu, R F and Witherington, J and Chew, D J (2020) Quantification of clinically applicable stimulation parameters for precision near-organ neuromodulation of human splenic nerves. Communications Biology, 3 (1). p. 577. ISSN 2399-3642
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Abstract
Abstract: Neuromodulation is a new therapeutic pathway to treat inflammatory conditions by modulating the electrical signalling pattern of the autonomic connections to the spleen. However, targeting this sub-division of the nervous system presents specific challenges in translating nerve stimulation parameters. Firstly, autonomic nerves are typically embedded non-uniformly among visceral and connective tissues with complex interfacing requirements. Secondly, these nerves contain axons with populations of varying phenotypes leading to complexities for axon engagement and activation. Thirdly, clinical translational of methodologies attained using preclinical animal models are limited due to heterogeneity of the intra- and inter-species comparative anatomy and physiology. Here we demonstrate how this can be accomplished by the use of in silico modelling of target anatomy, and validation of these estimations through ex vivo human tissue electrophysiology studies. Neuroelectrical models are developed to address the challenges in translation of parameters, which provides strong input criteria for device design and dose selection prior to a first-in-human trial.
| Item Type: | Article |
|---|---|
| RVC Publication Type: | Original research article |
| Uncontrolled Keywords: | Article, /631/1647/1453, /692/308/575, /631/114/2397, /14/28, /9/30, article |
| Departments: | Clinical Sciences and Services |
| SWORD Depositor: | Publications Repository |
| Depositing User: | Publications Repository |
| Last Modified: | 20 Nov 2020 20:19 |
| URI: | https://researchonline.rvc.ac.uk/id/eprint/13137 |
| Date Deposited: | 29 October 2020 |
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