Time Lapse Observation Based Modeling and Identification of Cell Behaviors in Angiogenic Sprout Development
This paper presents a method for deriving dynamic equations for Endothelial Cell (EC) motion and estimating parameters based on time lapse imagery of angiogenic sprout development. Angiogenesis is the process whereby a collection of endothelial cells sprout out from an existing blood vessel, degrade...
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ASME International
2018
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Online Access: | http://hdl.handle.net/1721.1/118784 https://orcid.org/0000-0002-7232-304X https://orcid.org/0000-0003-3155-6223 |
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author | Wood, Levi Benjamin Kamm, Roger Dale Asada, Haruhiko |
author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Wood, Levi Benjamin Kamm, Roger Dale Asada, Haruhiko |
author_sort | Wood, Levi Benjamin |
collection | MIT |
description | This paper presents a method for deriving dynamic equations for Endothelial Cell (EC) motion and estimating parameters based on time lapse imagery of angiogenic sprout development. Angiogenesis is the process whereby a collection of endothelial cells sprout out from an existing blood vessel, degrade the surrounding scaffold and form a new blood vessel. Sprout formation requires that a collection of ECs all work together and coordinate their movements and behaviors. The process is initiated and guided by a collection of external growth factors. In addition, the individual cells communicate and respond to each other's movements to behave in a coordinated fashion. The mechanics of cell coordination are extremely complex and include both chemical and mechanical communication between cells and between cells and the matrix. Despite the complexity of the physical system, with many variables that cannot be measured in real time, the ECs behave in a predictable manner based on just a few quantities that can be measured in real time. This work presents a methodology for constructing a set of simple stochastic equations for cell motion dependent only on quantities obtained from time lapse data observed from in vitro experiments. Model parameters are identified from time lapse data using a Maximum Likelihood Estimator. Copyright © 2010 by ASME. |
first_indexed | 2024-09-23T15:08:47Z |
format | Article |
id | mit-1721.1/118784 |
institution | Massachusetts Institute of Technology |
last_indexed | 2024-09-23T15:08:47Z |
publishDate | 2018 |
publisher | ASME International |
record_format | dspace |
spelling | mit-1721.1/1187842022-09-29T13:00:52Z Time Lapse Observation Based Modeling and Identification of Cell Behaviors in Angiogenic Sprout Development Wood, Levi Benjamin Kamm, Roger Dale Asada, Haruhiko Massachusetts Institute of Technology. Department of Mechanical Engineering Wood, Levi Benjamin Kamm, Roger Dale Asada, Haruhiko This paper presents a method for deriving dynamic equations for Endothelial Cell (EC) motion and estimating parameters based on time lapse imagery of angiogenic sprout development. Angiogenesis is the process whereby a collection of endothelial cells sprout out from an existing blood vessel, degrade the surrounding scaffold and form a new blood vessel. Sprout formation requires that a collection of ECs all work together and coordinate their movements and behaviors. The process is initiated and guided by a collection of external growth factors. In addition, the individual cells communicate and respond to each other's movements to behave in a coordinated fashion. The mechanics of cell coordination are extremely complex and include both chemical and mechanical communication between cells and between cells and the matrix. Despite the complexity of the physical system, with many variables that cannot be measured in real time, the ECs behave in a predictable manner based on just a few quantities that can be measured in real time. This work presents a methodology for constructing a set of simple stochastic equations for cell motion dependent only on quantities obtained from time lapse data observed from in vitro experiments. Model parameters are identified from time lapse data using a Maximum Likelihood Estimator. Copyright © 2010 by ASME. 2018-10-25T18:53:29Z 2018-10-25T18:53:29Z 2010-09 2018-10-23T15:59:46Z Article http://purl.org/eprint/type/ConferencePaper 978-0-7918-4417-5 http://hdl.handle.net/1721.1/118784 Wood, Levi B., et al. “Time Lapse Observation Based Modeling and Identification of Cell Behaviors in Angiogenic Sprout Development.” ASME 2010 Dynamic Systems and Control Conference, Volume 1, 12-15 September, 2010, Cambridge, Massachusetts, ASME, 2010, pp. 357–64. https://orcid.org/0000-0002-7232-304X https://orcid.org/0000-0003-3155-6223 http://dx.doi.org/10.1115/DSCC2010-4139 ASME 2010 Dynamic Systems and Control Conference, Volume 1 Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf ASME International ASME |
spellingShingle | Wood, Levi Benjamin Kamm, Roger Dale Asada, Haruhiko Time Lapse Observation Based Modeling and Identification of Cell Behaviors in Angiogenic Sprout Development |
title | Time Lapse Observation Based Modeling and Identification of Cell Behaviors in Angiogenic Sprout Development |
title_full | Time Lapse Observation Based Modeling and Identification of Cell Behaviors in Angiogenic Sprout Development |
title_fullStr | Time Lapse Observation Based Modeling and Identification of Cell Behaviors in Angiogenic Sprout Development |
title_full_unstemmed | Time Lapse Observation Based Modeling and Identification of Cell Behaviors in Angiogenic Sprout Development |
title_short | Time Lapse Observation Based Modeling and Identification of Cell Behaviors in Angiogenic Sprout Development |
title_sort | time lapse observation based modeling and identification of cell behaviors in angiogenic sprout development |
url | http://hdl.handle.net/1721.1/118784 https://orcid.org/0000-0002-7232-304X https://orcid.org/0000-0003-3155-6223 |
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