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Cilia density and flow velocity affect alignment of motile cilia from brain cells

Authors: Nicola Pellicciotta; Pietro Cicuta; Jurij Kotar; Debasish Das; Eric Lauga; Marion Faucourt; Nathalie Spassky;

Cilia density and flow velocity affect alignment of motile cilia from brain cells

Abstract

Here we store the supplementary Materials and Methods for the publication Cilia density and flow velocity affect alignment of motile cilia from brain cells. In the Supplementary methods we included additional information on the hydrodynamic simulations. Video1 and Video2 are videos referenced in the main text of the paper In the archive 'raw data and code.tar' , we provide raw images and codes to support the article.The complete dataset of raw images is more than 1 Tb. Here we are limited to 50Gb. The full dataset is available upon request. We choose to provide a full dataset of two culture at DIV 16, one treated with shear flow and a control without flow. For each of the two cultures, the videos with propelled particles are in the directory FL, The bright field images without particles are stored in BF. Unfortunately we uploaded only few videos because of their large size. The results of the analysis of this dataset is reported in the directory analysis (available for each culture). Moreover we provide the code to analyse these data. The analysis routine: Step 1: for each field of view (fov) getting the cilia beating direction from the FL images. This is done with PIV. The code is Step1_PIVanalysis.mat Step 2: for each fov getting ciliated cell position and CBF from the BF movies. Gather the cilia beating direction and cilia posion and frequency in a unique figure and matlab class (Res.mat). This is done in Step2_gatherResults.mat The results of these analysis are stored in the analysis folder for each culture. These routines are repeated for each experiment and results are then plotted to get trends. In the folder code4figures we report the code that we used to make the figures in the papers starting from a matlab file "all_results*.mat", where are gathered all the analysis. The code may improve in the future with more comments. please check Nicola's github page for the latest update. Please contact us for any problem. https://github.com/NicolaPellicciotta/Code4-Cilia-density-and-flow-velocity-affect-alignment-of-motile-cilia-from-brain-cells All the raw videos and code are in the archive.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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