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A method to generate the surface cell layer of the 3D virtual shoot apex from apical initials

Overview of attention for article published in Plant Methods, December 2017
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Title
A method to generate the surface cell layer of the 3D virtual shoot apex from apical initials
Published in
Plant Methods, December 2017
DOI 10.1186/s13007-017-0262-7
Pubmed ID
Authors

Krzysztof Kucypera, Marcin Lipowczan, Anna Piekarska-Stachowiak, Jerzy Nakielski

Abstract

The development of cell pattern in the surface cell layer of the shoot apex can be investigated in vivo by use of a time-lapse confocal images, showing naked meristem in 3D in successive times. However, how this layer is originated from apical initials and develops as a result of growth and divisions of their descendants, remains unknown. This is an open area for computer modelling. A method to generate the surface cell layer is presented on the example of the 3D paraboloidal shoot apical dome. In the used model the layer originates from three apical initials that meet at the dome summit and develops through growth and cell divisions under the isotropic surface growth, defined by the growth tensor. The cells, which are described by polyhedrons, divide anticlinally with the smallest division plane that passes depending on the used mode through the cell center, or the point found randomly near this center. The formation of the surface cell pattern is described with the attention being paid to activity of the apical initials and fates of their descendants. The computer generated surface layer that included about 350 cells required about 1200 divisions of the apical initials and their derivatives. The derivatives were arranged into three more or less equal clonal sectors composed of cellular clones at different age. Each apical initial renewed itself 7-8 times to produce the sector. In the shape and location and the cellular clones the following divisions of the initial were manifested. The application of the random factor resulted in more realistic cell pattern in comparison to the pure mode. The cell divisions were analyzed statistically on the top view. When all of the division walls were considered, their angular distribution was uniform, whereas in the distribution that was limited to apical initials only, some preferences related to their arrangement at the dome summit were observed. The realistic surface cell pattern was obtained. The present method is a useful tool to generate surface cell layer, study activity of initial cells and their derivatives, and how cell expansion and division are coordinated during growth. We expect its further application to clarify the question of a number and permanence or impermanence of initial cells, and possible relationship between their shape and oriented divisions, both on the ground of the growth tensor approach.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Student > Doctoral Student 2 25%
Student > Postgraduate 1 13%
Student > Bachelor 1 13%
Unknown 2 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 25%
Computer Science 1 13%
Physics and Astronomy 1 13%
Materials Science 1 13%
Engineering 1 13%
Other 0 0%
Unknown 2 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 December 2017.
All research outputs
#18,320,524
of 22,685,926 outputs
Outputs from Plant Methods
#950
of 1,072 outputs
Outputs of similar age
#325,795
of 438,072 outputs
Outputs of similar age from Plant Methods
#37
of 41 outputs
Altmetric has tracked 22,685,926 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,072 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 3rd percentile – i.e., 3% of its peers scored the same or lower than it.
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