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Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events

BACKGROUND: Mechanotransduction in bone cells plays a pivotal role in osteoblast differentiation and bone remodelling. Mechanotransduction provides the link between modulation of the extracellular matrix by mechanical load and intracellular activity. By controlling the balance between the intracellu...

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Autores principales: Ascolani, Gianluca, Skerry, Timothy M., Lacroix, Damien, Dall’Ara, Enrico, Shuaib, Aban
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079370/
https://www.ncbi.nlm.nih.gov/pubmed/32183690
http://dx.doi.org/10.1186/s12859-020-3394-0
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author Ascolani, Gianluca
Skerry, Timothy M.
Lacroix, Damien
Dall’Ara, Enrico
Shuaib, Aban
author_facet Ascolani, Gianluca
Skerry, Timothy M.
Lacroix, Damien
Dall’Ara, Enrico
Shuaib, Aban
author_sort Ascolani, Gianluca
collection PubMed
description BACKGROUND: Mechanotransduction in bone cells plays a pivotal role in osteoblast differentiation and bone remodelling. Mechanotransduction provides the link between modulation of the extracellular matrix by mechanical load and intracellular activity. By controlling the balance between the intracellular and extracellular domains, mechanotransduction determines the optimum functionality of skeletal dynamics. Failure of this relationship was suggested to contribute to bone-related diseases such as osteoporosis. RESULTS: A hybrid mechanical and agent-based model (Mech-ABM), simulating mechanotransduction in a single osteoblast under external mechanical perturbations, was utilised to simulate and examine modulation of the activation dynamics of molecules within mechanotransduction on the cellular response to mechanical stimulation. The number of molecules and their fluctuations have been analysed in terms of recurrences of critical events. A numerical approach has been developed to invert subordination processes and to extract the direction processes from the molecular signals in order to derive the distribution of recurring events. These predict that there are large fluctuations enclosing information hidden in the noise which is beyond the dynamic variations of molecular baselines. Moreover, studying the system under different mechanical load regimes and altered dynamics of feedback loops, illustrate that the waiting time distributions of each molecule are a signature of the system’s state. CONCLUSIONS: The behaviours of the molecular waiting times change with the changing of mechanical load regimes and altered dynamics of feedback loops, presenting the same variation of patterns for similar interacting molecules and identifying specific alterations for key molecules in mechanotransduction. This methodology could be used to provide a new tool to identify potent molecular candidates to modulate mechanotransduction, hence accelerate drug discovery towards therapeutic targets for bone mass upregulation.
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spelling pubmed-70793702020-03-23 Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events Ascolani, Gianluca Skerry, Timothy M. Lacroix, Damien Dall’Ara, Enrico Shuaib, Aban BMC Bioinformatics Methodology Article BACKGROUND: Mechanotransduction in bone cells plays a pivotal role in osteoblast differentiation and bone remodelling. Mechanotransduction provides the link between modulation of the extracellular matrix by mechanical load and intracellular activity. By controlling the balance between the intracellular and extracellular domains, mechanotransduction determines the optimum functionality of skeletal dynamics. Failure of this relationship was suggested to contribute to bone-related diseases such as osteoporosis. RESULTS: A hybrid mechanical and agent-based model (Mech-ABM), simulating mechanotransduction in a single osteoblast under external mechanical perturbations, was utilised to simulate and examine modulation of the activation dynamics of molecules within mechanotransduction on the cellular response to mechanical stimulation. The number of molecules and their fluctuations have been analysed in terms of recurrences of critical events. A numerical approach has been developed to invert subordination processes and to extract the direction processes from the molecular signals in order to derive the distribution of recurring events. These predict that there are large fluctuations enclosing information hidden in the noise which is beyond the dynamic variations of molecular baselines. Moreover, studying the system under different mechanical load regimes and altered dynamics of feedback loops, illustrate that the waiting time distributions of each molecule are a signature of the system’s state. CONCLUSIONS: The behaviours of the molecular waiting times change with the changing of mechanical load regimes and altered dynamics of feedback loops, presenting the same variation of patterns for similar interacting molecules and identifying specific alterations for key molecules in mechanotransduction. This methodology could be used to provide a new tool to identify potent molecular candidates to modulate mechanotransduction, hence accelerate drug discovery towards therapeutic targets for bone mass upregulation. BioMed Central 2020-03-18 /pmc/articles/PMC7079370/ /pubmed/32183690 http://dx.doi.org/10.1186/s12859-020-3394-0 Text en © The Author(s). 2020 Open AccessThis 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.
spellingShingle Methodology Article
Ascolani, Gianluca
Skerry, Timothy M.
Lacroix, Damien
Dall’Ara, Enrico
Shuaib, Aban
Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events
title Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events
title_full Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events
title_fullStr Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events
title_full_unstemmed Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events
title_short Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events
title_sort revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079370/
https://www.ncbi.nlm.nih.gov/pubmed/32183690
http://dx.doi.org/10.1186/s12859-020-3394-0
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