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Applied Sciences
Special Issues
Data Driven Modelling of Disease and Therapy Mechanisms
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Data Driven Modelling of Disease and Therapy Mechanisms

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: closed (10 January 2022) | Viewed by 2398

Special Issue Editor

Dr. Sanjay Kharche

E-Mail Website
Guest Editor
Computational Medicine Laboratory, Department of Medicine, The University of Western Ontario, London, ON, Canada
Interests: blood flow modelling; cardiac electrophysiology modelling; cerebral modelling; clinical imaging; device development; device testing; large data; high performance computing; decision making; machine learning; biomedical engineering

Special Issue Information

Dear Colleagues,

Introduction: Electrical signaling underlies communication and information exchange in all organs of all mammals, including humans. Mathematical–computational modelling of electrical activity has led to deeper insights into disease mechanisms and is increasingly being used in pre-clinical drug and device testing. A significant effort has been dedicated to developing the methods and scientific platforms (software) used in modelling. This Special Issue is designed to catalyze inter-research group interactions, thus enhancing our collective approaches.

Scope of call: This Special Issue invites contributions that use scientific platforms (software) to uncover disease mechanisms and assess treatment efficacy. We welcome contributions on the topics listed below, and other manuscripts will be considered as well.

  • multi-scale cardiac electrophysiology
  • multi-scale cerebral electrophysiology
  • electrical modelling in other organs
  • electrical activity in neuronal networks and vascular networks
  • device and drug testing using modelling
  • data driven simulations
  • open source software and data repository announcements
  • review articles
  • clinical review of technology

Dr. Sanjay Kharche
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cardiac electrophysiology
  • cerebral electrophysiology
  • gut
  • skeletal muscle
  • kidney
  • fluid flow
  • multi-physics modelling
  • scientific platforms
  • large data

Published Papers (1 paper)

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Research

18 pages, 3604 KiB  
Article
Using a Human Circulation Mathematical Model to Simulate the Effects of Hemodialysis and Therapeutic Hypothermia
by Jermiah J. Joseph, Timothy J. Hunter, Clara Sun, Daniel Goldman, Sanjay R. Kharche and Christopher W. McIntyre
Appl. Sci. 2022, 12(1), 307; https://doi.org/10.3390/app12010307 - 29 Dec 2021
Cited by 3 | Viewed by 1949
Abstract
Background: We developed a hemodynamic mathematical model of human circulation coupled to a virtual hemodialyzer. The model was used to explore mechanisms underlying our clinical observations involving hemodialysis. Methods: The model consists of whole body human circulation, baroreflex feedback control, and a hemodialyzer. [...] Read more.
Background: We developed a hemodynamic mathematical model of human circulation coupled to a virtual hemodialyzer. The model was used to explore mechanisms underlying our clinical observations involving hemodialysis. Methods: The model consists of whole body human circulation, baroreflex feedback control, and a hemodialyzer. Four model populations encompassing baseline, dialysed, therapeutic hypothermia treated, and simultaneous dialysed with hypothermia were generated. In all populations atrial fibrillation and renal failure as co-morbidities, and exercise as a treatment were simulated. Clinically relevant measurables were used to quantify the effects of each in silico experiment. Sensitivity analysis was used to uncover the most relevant parameters. Results: Relative to baseline, the modelled dialysis increased the population mean diastolic blood pressure by 5%, large vessel wall shear stress by 6%, and heart rate by 20%. Therapeutic hypothermia increased systolic blood pressure by 3%, reduced large vessel shear stress by 15%, and did not affect heart rate. Therapeutic hypothermia reduced wall shear stress by 15% in the aorta and 6% in the kidneys, suggesting a potential anti-inflammatory benefit. Therapeutic hypothermia reduced cardiac output under atrial fibrillation by 12% and under renal failure by 20%. Therapeutic hypothermia and exercise did not affect dialyser function, but increased water removal by approximately 40%. Conclusions: This study illuminates some mechanisms of the action of therapeutic hypothermia. It also suggests clinical measurables that may be used as surrogates to diagnose underlying diseases such as atrial fibrillation. Full article
(This article belongs to the Special Issue Data Driven Modelling of Disease and Therapy Mechanisms)
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