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Connectomics of Bone to Brain—Probing Physical Renderings of Cellular Experience

“Brainless” cells, the living constituents inhabiting all biological materials, exhibit remarkably smart, i.e., stimuli-responsive and adaptive, behavior. The emergent spatial and temporal patterns of adaptation, observed as changes in cellular connectivity and tissue remodeling by cells, underpin n...

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Autores principales: Knothe Tate, Melissa L., Srikantha, Abhilash, Wojek, Christian, Zeidler, Dirk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8313296/
https://www.ncbi.nlm.nih.gov/pubmed/34322033
http://dx.doi.org/10.3389/fphys.2021.647603
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author Knothe Tate, Melissa L.
Srikantha, Abhilash
Wojek, Christian
Zeidler, Dirk
author_facet Knothe Tate, Melissa L.
Srikantha, Abhilash
Wojek, Christian
Zeidler, Dirk
author_sort Knothe Tate, Melissa L.
collection PubMed
description “Brainless” cells, the living constituents inhabiting all biological materials, exhibit remarkably smart, i.e., stimuli-responsive and adaptive, behavior. The emergent spatial and temporal patterns of adaptation, observed as changes in cellular connectivity and tissue remodeling by cells, underpin neuroplasticity, muscle memory, immunological imprinting, and sentience itself, in diverse physiological systems from brain to bone. Connectomics addresses the direct connectivity of cells and cells’ adaptation to dynamic environments through manufacture of extracellular matrix, forming tissues and architectures comprising interacting organs and systems of organisms. There is imperative to understand the physical renderings of cellular experience throughout life, from the time of emergence, to growth, adaptation and aging-associated degeneration of tissues. Here we address this need through development of technological approaches that incorporate cross length scale (nm to m) structural data, acquired via multibeam scanning electron microscopy, with machine learning and information transfer using network modeling approaches. This pilot case study uses cutting edge imaging methods for nano- to meso-scale study of cellular inhabitants within human hip tissue resected during the normal course of hip replacement surgery. We discuss the technical approach and workflow and identify the resulting opportunities as well as pitfalls to avoid, delineating a path for cellular connectomics studies in diverse tissue/organ environments and their interactions within organisms and across species. Finally, we discuss the implications of the outlined approach for neuromechanics and the control of physical behavior and neuromuscular training.
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spelling pubmed-83132962021-07-27 Connectomics of Bone to Brain—Probing Physical Renderings of Cellular Experience Knothe Tate, Melissa L. Srikantha, Abhilash Wojek, Christian Zeidler, Dirk Front Physiol Physiology “Brainless” cells, the living constituents inhabiting all biological materials, exhibit remarkably smart, i.e., stimuli-responsive and adaptive, behavior. The emergent spatial and temporal patterns of adaptation, observed as changes in cellular connectivity and tissue remodeling by cells, underpin neuroplasticity, muscle memory, immunological imprinting, and sentience itself, in diverse physiological systems from brain to bone. Connectomics addresses the direct connectivity of cells and cells’ adaptation to dynamic environments through manufacture of extracellular matrix, forming tissues and architectures comprising interacting organs and systems of organisms. There is imperative to understand the physical renderings of cellular experience throughout life, from the time of emergence, to growth, adaptation and aging-associated degeneration of tissues. Here we address this need through development of technological approaches that incorporate cross length scale (nm to m) structural data, acquired via multibeam scanning electron microscopy, with machine learning and information transfer using network modeling approaches. This pilot case study uses cutting edge imaging methods for nano- to meso-scale study of cellular inhabitants within human hip tissue resected during the normal course of hip replacement surgery. We discuss the technical approach and workflow and identify the resulting opportunities as well as pitfalls to avoid, delineating a path for cellular connectomics studies in diverse tissue/organ environments and their interactions within organisms and across species. Finally, we discuss the implications of the outlined approach for neuromechanics and the control of physical behavior and neuromuscular training. Frontiers Media S.A. 2021-07-12 /pmc/articles/PMC8313296/ /pubmed/34322033 http://dx.doi.org/10.3389/fphys.2021.647603 Text en Copyright © 2021 Knothe Tate, Srikantha, Wojek and Zeidler. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Knothe Tate, Melissa L.
Srikantha, Abhilash
Wojek, Christian
Zeidler, Dirk
Connectomics of Bone to Brain—Probing Physical Renderings of Cellular Experience
title Connectomics of Bone to Brain—Probing Physical Renderings of Cellular Experience
title_full Connectomics of Bone to Brain—Probing Physical Renderings of Cellular Experience
title_fullStr Connectomics of Bone to Brain—Probing Physical Renderings of Cellular Experience
title_full_unstemmed Connectomics of Bone to Brain—Probing Physical Renderings of Cellular Experience
title_short Connectomics of Bone to Brain—Probing Physical Renderings of Cellular Experience
title_sort connectomics of bone to brain—probing physical renderings of cellular experience
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8313296/
https://www.ncbi.nlm.nih.gov/pubmed/34322033
http://dx.doi.org/10.3389/fphys.2021.647603
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