Fibrillar organization in tendons: A pattern revealed by percolation characteristics of the respective geometric network

Since the tendon is composed by collagen fibrils of various sizes connected between them through molecular cross-links, it sounds logical to model it via a heterogeneous network of fibrils. Using cross sectional images, that network is operatively inferred from the respective Gabriel graph of the fi...

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Main Authors: Daniel Andres Dos Santos, Maria Laura Ponssa, Maria Jose Tulli, et al.
Format: Article
Language:English
Published: International Academy of Ecology and Environmental Sciences 2014-06-01
Series:Network Biology
Subjects:
Online Access:http://www.iaees.org/publications/journals/nb/articles/2014-4(2)/fibrillar-organization-in-tendons.pdf
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author Daniel Andres Dos Santos
Maria Laura Ponssa
Maria Jose Tulli, et al.
author_facet Daniel Andres Dos Santos
Maria Laura Ponssa
Maria Jose Tulli, et al.
author_sort Daniel Andres Dos Santos
collection DOAJ
description Since the tendon is composed by collagen fibrils of various sizes connected between them through molecular cross-links, it sounds logical to model it via a heterogeneous network of fibrils. Using cross sectional images, that network is operatively inferred from the respective Gabriel graph of the fibril mass centers. We focus on network percolation characteristics under an ordered activation of fibrils (progressive recruitment going from the smallest to the largest fibril). Analyses of percolation were carried out on a repository of images of digital flexor tendons obtained from samples of lizards and frogs. Observed percolation thresholds were compared against values derived from hypothetical scenarios of random activation of nodes. Strikingly, we found a significant delay for the occurrence of percolation in actual data. We interpret this finding as the consequence of some non-random packing of fibrillar units into a size-constrained geometric pattern. We erect an ideal geometric model of balanced interspersion of polymorphic units that accounts for the delayed percolating instance. We also address the circumstance of being percolation curves mirrored by the empirical curves of stress-strain obtained from the same studied tendons. By virtue of this isomorphism, we hypothesize that the inflection points of both curves are different quantitative manifestations of a common transitional process during mechanical load transference.
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spelling doaj.art-0521574296e546be83e9671a5174fd6c2022-12-21T20:40:33ZengInternational Academy of Ecology and Environmental SciencesNetwork Biology2220-88792220-88792014-06-01423146Fibrillar organization in tendons: A pattern revealed by percolation characteristics of the respective geometric networkDaniel Andres Dos Santos0Maria Laura Ponssa1Maria Jose Tulli, et al.2Instituto de Biodiversidad Neotropical, Facultad de Ciencias Naturales e Instituto Miguel Lillo, Universidad Nacional de Tucuman - CONICET. Horco Molle S/N, Yerba Buena, Tucuman, ArgentinaInstituto de Herpetologia, Fundacion Miguel Lillo-CONICET. Miguel Lillo 251, San Miguel de Tucuman, Tucuman, ArgentinaInstituto de Herpetologia, Fundacion Miguel Lillo-CONICET. Miguel Lillo 251, San Miguel de Tucuman, Tucuman, ArgentinaSince the tendon is composed by collagen fibrils of various sizes connected between them through molecular cross-links, it sounds logical to model it via a heterogeneous network of fibrils. Using cross sectional images, that network is operatively inferred from the respective Gabriel graph of the fibril mass centers. We focus on network percolation characteristics under an ordered activation of fibrils (progressive recruitment going from the smallest to the largest fibril). Analyses of percolation were carried out on a repository of images of digital flexor tendons obtained from samples of lizards and frogs. Observed percolation thresholds were compared against values derived from hypothetical scenarios of random activation of nodes. Strikingly, we found a significant delay for the occurrence of percolation in actual data. We interpret this finding as the consequence of some non-random packing of fibrillar units into a size-constrained geometric pattern. We erect an ideal geometric model of balanced interspersion of polymorphic units that accounts for the delayed percolating instance. We also address the circumstance of being percolation curves mirrored by the empirical curves of stress-strain obtained from the same studied tendons. By virtue of this isomorphism, we hypothesize that the inflection points of both curves are different quantitative manifestations of a common transitional process during mechanical load transference.http://www.iaees.org/publications/journals/nb/articles/2014-4(2)/fibrillar-organization-in-tendons.pdfpercolationcollagenfibril networkinterspersionpattern recognition
spellingShingle Daniel Andres Dos Santos
Maria Laura Ponssa
Maria Jose Tulli, et al.
Fibrillar organization in tendons: A pattern revealed by percolation characteristics of the respective geometric network
Network Biology
percolation
collagen
fibril network
interspersion
pattern recognition
title Fibrillar organization in tendons: A pattern revealed by percolation characteristics of the respective geometric network
title_full Fibrillar organization in tendons: A pattern revealed by percolation characteristics of the respective geometric network
title_fullStr Fibrillar organization in tendons: A pattern revealed by percolation characteristics of the respective geometric network
title_full_unstemmed Fibrillar organization in tendons: A pattern revealed by percolation characteristics of the respective geometric network
title_short Fibrillar organization in tendons: A pattern revealed by percolation characteristics of the respective geometric network
title_sort fibrillar organization in tendons a pattern revealed by percolation characteristics of the respective geometric network
topic percolation
collagen
fibril network
interspersion
pattern recognition
url http://www.iaees.org/publications/journals/nb/articles/2014-4(2)/fibrillar-organization-in-tendons.pdf
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AT marialauraponssa fibrillarorganizationintendonsapatternrevealedbypercolationcharacteristicsoftherespectivegeometricnetwork
AT mariajosetullietal fibrillarorganizationintendonsapatternrevealedbypercolationcharacteristicsoftherespectivegeometricnetwork