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Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks
Scientists have long sought to understand how vascular networks supply blood and oxygen to cells throughout the body. Recent work focuses on principles that constrain how vessel size changes through branching generations from the aorta to capillaries and uses scaling exponents to quantify these chan...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4552567/ https://www.ncbi.nlm.nih.gov/pubmed/26317654 http://dx.doi.org/10.1371/journal.pcbi.1004455 |
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author | Newberry, Mitchell G Ennis, Daniel B Savage, Van M |
author_facet | Newberry, Mitchell G Ennis, Daniel B Savage, Van M |
author_sort | Newberry, Mitchell G |
collection | PubMed |
description | Scientists have long sought to understand how vascular networks supply blood and oxygen to cells throughout the body. Recent work focuses on principles that constrain how vessel size changes through branching generations from the aorta to capillaries and uses scaling exponents to quantify these changes. Prominent scaling theories predict that combinations of these exponents explain how metabolic, growth, and other biological rates vary with body size. Nevertheless, direct measurements of individual vessel segments have been limited because existing techniques for measuring vasculature are invasive, time consuming, and technically difficult. We developed software that extracts the length, radius, and connectivity of in vivo vessels from contrast-enhanced 3D Magnetic Resonance Angiography. Using data from 20 human subjects, we calculated scaling exponents by four methods—two derived from local properties of branching junctions and two from whole-network properties. Although these methods are often used interchangeably in the literature, we do not find general agreement between these methods, particularly for vessel lengths. Measurements for length of vessels also diverge from theoretical values, but those for radius show stronger agreement. Our results demonstrate that vascular network models cannot ignore certain complexities of real vascular systems and indicate the need to discover new principles regarding vessel lengths. |
format | Online Article Text |
id | pubmed-4552567 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45525672015-09-10 Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks Newberry, Mitchell G Ennis, Daniel B Savage, Van M PLoS Comput Biol Research Article Scientists have long sought to understand how vascular networks supply blood and oxygen to cells throughout the body. Recent work focuses on principles that constrain how vessel size changes through branching generations from the aorta to capillaries and uses scaling exponents to quantify these changes. Prominent scaling theories predict that combinations of these exponents explain how metabolic, growth, and other biological rates vary with body size. Nevertheless, direct measurements of individual vessel segments have been limited because existing techniques for measuring vasculature are invasive, time consuming, and technically difficult. We developed software that extracts the length, radius, and connectivity of in vivo vessels from contrast-enhanced 3D Magnetic Resonance Angiography. Using data from 20 human subjects, we calculated scaling exponents by four methods—two derived from local properties of branching junctions and two from whole-network properties. Although these methods are often used interchangeably in the literature, we do not find general agreement between these methods, particularly for vessel lengths. Measurements for length of vessels also diverge from theoretical values, but those for radius show stronger agreement. Our results demonstrate that vascular network models cannot ignore certain complexities of real vascular systems and indicate the need to discover new principles regarding vessel lengths. Public Library of Science 2015-08-28 /pmc/articles/PMC4552567/ /pubmed/26317654 http://dx.doi.org/10.1371/journal.pcbi.1004455 Text en © 2015 Newberry et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Newberry, Mitchell G Ennis, Daniel B Savage, Van M Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks |
title | Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks |
title_full | Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks |
title_fullStr | Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks |
title_full_unstemmed | Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks |
title_short | Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks |
title_sort | testing foundations of biological scaling theory using automated measurements of vascular networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4552567/ https://www.ncbi.nlm.nih.gov/pubmed/26317654 http://dx.doi.org/10.1371/journal.pcbi.1004455 |
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