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dc.contributor.author
Uriu, Koichiro  
dc.contributor.author
Morelli, Luis Guillermo  
dc.date.available
2018-06-19T19:20:03Z  
dc.date.issued
2017-06  
dc.identifier.citation
Uriu, Koichiro; Morelli, Luis Guillermo; Determining the impact of cell mixing on signaling during development; Wiley Blackwell Publishing, Inc; Development Growth & Differentiation; 59; 5; 6-2017; 351-368  
dc.identifier.issn
0012-1592  
dc.identifier.uri
http://hdl.handle.net/11336/49417  
dc.description.abstract
Cell movement and intercellular signaling occur simultaneously to organize morphogenesis during embryonic development. Cell movement can cause relative positional changes between neighboring cells. When intercellular signals are local such cell mixing may affect signaling, changing the flow of information in developing tissues. Little is known about the effect of cell mixing on intercellular signaling in collective cellular behaviors and methods to quantify its impact are lacking. Here we discuss how to determine the impact of cell mixing on cell signaling drawing an example from vertebrate embryogenesis: the segmentation clock, a collective rhythm of interacting genetic oscillators. We argue that comparing cell mixing and signaling timescales is key to determining the influence of mixing. A signaling timescale can be estimated by combining theoretical models with cell signaling perturbation experiments. A mixing timescale can be obtained by analysis of cell trajectories from live imaging. After comparing cell movement analyses in different experimental settings, we highlight challenges in quantifying cell mixing from embryonic timelapse experiments, especially a reference frame problem due to embryonic motions and shape changes. We propose statistical observables characterizing cell mixing that do not depend on the choice of reference frames. Finally, we consider situations in which both cell mixing and signaling involve multiple timescales, precluding a direct comparison between single characteristic timescales. In such situations, physical models based on observables of cell mixing and signaling can simulate the flow of information in tissues and reveal the impact of observed cell mixing on signaling.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Wiley Blackwell Publishing, Inc  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Cell Movement  
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Coupled Oscillators  
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Delta-Notch Signal  
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Mean Squared Displacement  
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Synchronization  
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Otras Ciencias Biológicas  
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Ciencias Biológicas  
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CIENCIAS NATURALES Y EXACTAS  
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Astronomía  
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Ciencias Físicas  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
Determining the impact of cell mixing on signaling during development  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-06-19T15:55:37Z  
dc.journal.volume
59  
dc.journal.number
5  
dc.journal.pagination
351-368  
dc.journal.pais
Reino Unido  
dc.journal.ciudad
Londres  
dc.description.fil
Fil: Uriu, Koichiro. Kanazawa University; Japón  
dc.description.fil
Fil: Morelli, Luis Guillermo. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina. Institut Max Planck fur Molekulare Physiologie; Alemania  
dc.journal.title
Development Growth & Differentiation  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1111/dgd.12366