Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/86094
Title: Composite mathematical modeling of calcium signaling behind neuronal cell death in Alzheimer’s disease
Authors: Ranjan, Bobby
Chong, Ket Hing
Zheng, Jie
Keywords: Calcium Signaling
Neuronal Cell Death
Issue Date: 2018
Source: Ranjan, B., Chong, K. H., & Zheng, J. (2018). Composite mathematical modeling of calcium signaling behind neuronal cell death in Alzheimer’s disease. BMC Systems Biology, 12(S1), 10-.
Series/Report no.: BMC Systems Biology
Abstract: Background: Alzheimer’s disease (AD) is a progressive neurological disorder, recognized as the most common cause of dementia affecting people aged 65 and above. AD is characterized by an increase in amyloid metabolism, and by the misfolding and deposition of β-amyloid oligomers in and around neurons in the brain. These processes remodel the calcium signaling mechanism in neurons, leading to cell death via apoptosis. Despite accumulating knowledge about the biological processes underlying AD, mathematical models to date are restricted to depicting only a small portion of the pathology. Results: Here, we integrated multiple mathematical models to analyze and understand the relationship among amyloid depositions, calcium signaling and mitochondrial permeability transition pore (PTP) related cell apoptosis in AD. The model was used to simulate calcium dynamics in the absence and presence of AD. In the absence of AD, i.e. without β-amyloid deposition, mitochondrial and cytosolic calcium level remains in the low resting concentration. However, our in silico simulation of the presence of AD with the β-amyloid deposition, shows an increase in the entry of calcium ions into the cell and dysregulation of Ca 2+ channel receptors on the Endoplasmic Reticulum. This composite model enabled us to make simulation that is not possible to measure experimentally. Conclusions: Our mathematical model depicting the mechanisms affecting calcium signaling in neurons can help understand AD at the systems level and has potential for diagnostic and therapeutic applications.
URI: https://hdl.handle.net/10356/86094
http://hdl.handle.net/10220/45259
DOI: 10.1186/s12918-018-0529-2
Rights: © 2018 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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