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337 results for “cell shape”
Text-fig. 7. Lusitanispermum choffatii gen. et sp. nov. seeds from the Early Cretaceous Famalicão locality (sample 025), Portugal; Synchrotron radiation X-ray tomographic microscopy (SRXTM, volume renderings). a) Holotype; seed in lateral view showing seed shape; note that the seed is broken near the lower surface of the hilum (S174345). b) Oblique apical view of micropylar-hilar region of holotype showing slightly ruptured micropylar slit (mi) in the outer integument and two bulging and abraded areas (arrow heads) close to hilum. c) Seed in oblique lateral-raphal view showing the two bulging structures (arrow heads) immediately adjacent to the lower edge of the hilum (S174472). d) Tangential, longitudinal cut (cut at yz0131) through the seed coat of seed in (7c) showing the undulate anticlinal cell walls of the exotesta cells that are thickest towards the outside and thinner towards the inside. Scale bars = 500 µm (a–c); 250 µm (d). in Extinct Taxa Of Exotestal Seeds Close To Austrobaileyales And Nymphaeales From The Early Cretaceous Of Portugal
Text-fig. 7. Lusitanispermum choffatii gen. et sp. nov. seeds from the Early Cretaceous Famalicão locality (sample 025), Portugal; Synchrotron radiation X-ray tomographic microscopy (SRXTM, volume renderings). a) Holotype; seed in lateral view showing seed shape; note that the seed is broken near the lower surface of the hilum (S174345). b) Oblique apical view of micropylar-hilar region of holotype showing slightly ruptured micropylar slit (mi) in the outer integument and two bulging and abraded areas (arrow heads) close to hilum. c) Seed in oblique lateral-raphal view showing the two bulging structures (arrow heads) immediately adjacent to the lower edge of the hilum (S174472). d) Tangential, longitudinal cut (cut at yz0131) through the seed coat of seed in (7c) showing the undulate anticlinal cell walls of the exotesta cells that are thickest towards the outside and thinner towards the inside. Scale bars = 500 µm (a–c); 250 µm (d).
Text-fig. 22. Scanning electron microscope (SEM, a–c) and synchrotron radiation X-ray tomographic microscopy (SRXTM, d) images of Ibericarpus cuneiformis gen. et sp. nov.; Catefica locality, Portugal. a) Fruiting axis bearing an elongated receptacle with numerous diamond-shaped scars from detached fruitlets; note the absence of scars from bracts, tepals or stamens at the transition to the fruitlet scars and the stalk (arrow); b) Group of ten fruitlets detached from fruiting axis in (a) showing apical stigmatic region and distinctive bulging isodiametric epidermal cells; c) Detached fruitlet showing apical stigmatic region; d) Volume rendering of three adhering fruits showing apical stigmatic region and distinctive bulging isodiametric epidermal cells. Specimens, Catefica MM75-P0477 (a, b), Catefica 49-S115852 (c), Catefica 50-S174907 (d). Scale bars = 300 Μm (a–d). in The Early Cretaceous Mesofossil Flora Of Catefica, Portugal: Angiosperms
Text-fig. 22. Scanning electron microscope (SEM, a–c) and synchrotron radiation X-ray tomographic microscopy (SRXTM, d) images of Ibericarpus cuneiformis gen. et sp. nov.; Catefica locality, Portugal. a) Fruiting axis bearing an elongated receptacle with numerous diamond-shaped scars from detached fruitlets; note the absence of scars from bracts, tepals or stamens at the transition to the fruitlet scars and the stalk (arrow); b) Group of ten fruitlets detached from fruiting axis in (a) showing apical stigmatic region and distinctive bulging isodiametric epidermal cells; c) Detached fruitlet showing apical stigmatic region; d) Volume rendering of three adhering fruits showing apical stigmatic region and distinctive bulging isodiametric epidermal cells. Specimens, Catefica MM75-P0477 (a, b), Catefica 49-S115852 (c), Catefica 50-S174907 (d). Scale bars = 300 Μm (a–d).
Aberrant basal cell clonal dynamics shape early lung carcinogenesis
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Data from: Shape matters: The relationship between cell geometry and diversity in phytoplankton
<p>We compiled the most comprehensive data set of phytoplankton and other marine protists in terms of sizes, shapes, genus, and species names. Samples were obtained from seven globally distributed marine areas: Baltic Sea, North Atlantic (Scotland), Mediterranean Sea (Greece and Turkey), Indo-Pacific (the Maldives), South-western Pacific (Australia), Southern Atlantic (Brazil).</p> <p>See details in Ryabov et al Ecology Letters <em>'Shape matters: the relationship between cell geometry and diversity in phytoplankton</em>'</p>
The cell adhesion molecule Sdk1 shapes assembly of a retinal circuit that detects localized edges
<p>Nearly 50 different mouse retinal ganglion cell (RGC) types sample the visual scene for distinct features. RGC feature selectivity arises from its synapses with a specific subset of amacrine (AC) and bipolar cell (BC) types, but how RGC dendrites arborize and collect input from these specific subsets remains poorly understood. Here we examine the hypothesis that RGCs employ molecular recognition systems to meet this challenge. By combining calcium imaging and type-specific histological stains we define a family of circuits that express the recognition molecule Sidekick 1 (Sdk1) which include a novel RGC type (S1-RGC) that responds to local edges. Genetic and physiological studies revealed that Sdk1 loss selectively disrupts S1-RGC visual responses which result from a loss of excitatory and inhibitory inputs and selective dendritic deficits on this neuron. We conclude that Sdk1 shapes dendrite growth and wiring to help S1-RGCs become feature selective.</p>
Data from: Of puzzles and pavements: a quantitative exploration of leaf epidermal cell shape
Epidermal cells of leaves are diverse: tabular pavement cells, trichomes, and stomatal complexes. Pavement cells from the monocot Zea mays (maize) and the eudicot Arabidopsis thaliana (Arabidopsis) have highly undulate anticlinal walls. The molecular basis for generating these undulating margins has been extensively investigated in these species. This has led to two assumptions: first, that particular plant lineages are characterized by particular pavement cell shapes; and second, that undulatory cell shapes are common enough to be model shapes. To test these assumptions, we quantified pavement cell shape in epidermides from the leaves of 278 vascular plant taxa. We found that monocot pavement cells tended to have weakly undulating margins, fern cells had strongly undulating margins, and eudicot cells showed no particular undulation degree. Cells with highly undulating margins, like those of Arabidopsis and maize, were in the minority. We also found a trend towards more undulating cell margins on abaxial leaf surfaces; and that highly elongated leaves in ferns, monocots and gymnosperms tended to have highly elongated cells. Our results reveal the diversity of pavement cell shapes, and lays the quantitative groundwork for testing hypotheses about pavement cell form and function within a phylogenetic context.
Identification of structural and regulatory cell-shape determinants in Haloferax volcanii
<p>Archaea are key players in various processes, yet little is known about their cell biology, including cell-shape determination. <em>Haloferax volcanii</em> is a haloarchaeon that can form both rod- and disk-shaped cells, depending on growth conditions. In this study, we used proteomics, genetics, and live-cell imaging to identify mutants that are defective in rod or disk formation. Diverse proteins were implicated to be important for cell-shape determination, including predicted transporters, transducers, signaling molecules, and transcriptional regulators. We identified and phenotypically characterized two deletion strains, strains missing rod-determining factor A (RdfA) and disk-determining factor A (DdfA), which are required for rod and disk formation, respectively. We also identified an actin homolog, volactin, which we characterized with live-cell imaging and determined to be dynamic and important for disk-shape determination.<br><br>This Zenodo project includes the CellProfiler pipeline (.cpproj file) used for analyzing and quantifying cell-shape images. Additionally, the cell-shape images taken during the proteomics sample collection (comparing H53, ∆<em>rdfA</em>, and ∆<em>ddfA </em>at early- and late-log growth phases) are provided. This project also includes whole genome sequencing Illumina files for H53, ∆<em>rdfA</em>, ∆<em>sph3</em>, ∆<em>ddfA</em>, JK3, and JK5.<br><br>These data accompany:<br>Schiller, H., Hong, Y., Kouassi, J., Rados, T., Kwak, J., DiLucido, A., Safer, D., Marchfelder, A., Pfeiffer, F., Bisson, A., Schulze, S., and Pohlschroder, M. 2024. Identification of structural and regulatory cell-shape determinants in Haloferax volcanii. Nat Commun 15(1):1414. https://doi.org/10.1038/s41467-024-45196-0.</p>
Dataset and Code for Manuscript "Cell sorting based on pulse shapes from angle resolved detection of scattered light"
<p>Dataset and code for the cell cycle analysis and cluster selection for sorting:</p> <ul> <li>ReadMe file with explanations of the data set and analysis</li> <li>Python scripts for converting the data and to reproduce the sort cluster selection</li> <li>binary data files containing pulse shapes and wavelet transform coefficients</li> <li>FSC data files containing the respective common flow cytometry parameters</li> <li>text files with event indices that represent the gating</li> </ul>
SARS-CoV-2 antigen exposure history shapes phenotypes and specificity of memory CD8 T cells
<p>This dataset contains aggregated CellRanger output for six 10x Genomics (5'GEX+abTCR+Feature barcoding) experiments from the study by Minervina, Pogorelyy et al (<a href="https://www.medrxiv.org/content/10.1101/2021.07.12.21260227v3">medrxiv</a>). <br> The scripts to process it further are available at github (<a href="https://github.com/pogorely/COVID_vax_CD8">repository</a>). <br> Raw sequencing data is available at SRA (acc. PRJNA744851)</p>
Characterizing multidimensional cellular physiological states with quantitative three-dimensional shape descriptors for cell membranes
<h3>Supplementary dataset and code for the article "<em>Characterizing Cellular Physiological States with Three-Dimensional Shape Descriptors for Cell Membranes</em>"</h3> <p>CShaper Dataset.zip: The 3D cell regions reused from the previously published article <a href="https://doi.org/10.1038/s41467-020-19863-x">https://doi.org/10.1038/s41467-020-19863-x</a>.</p> <p>Cell Shape Descriptors - Code & Data.zip: The code (exemplifed by embryo Sample04) and data (including embryo Sample04-Sample20) of 12 3D shape descriptors for all 3D cell regions in the <em>CShaper</em> dataset.</p> <p>GUI.zip: The user-friendly software <em>Shape Descriptor Tool</em> is a Graphical User Interface based on <em>Matlab</em> for calculating 12 shape descriptors for a 3D cell region (exemplified by embryo Sample20, time point 14, ABpl cell in the <em>CShaper</em> dataset). The instruction guidebook is included in the Supplementary Material of the article.</p>
Code and data for "Cell shape and orientation control galvanotactic accuracy"
<p>This is the code and the data required to reproduce the results from "Cell shape and orientation control galvanotactic accuracy" Ifunanya Nwogbaga and Brian A. Camley, arXiv:2407.17420 2024, in press in Soft Matter, DOI https://doi.org/10.1039/D4SM00952E</p>
Data and code for "Cell shape characterization, alignment and comparison using FlowShape"
<p><strong>Code</strong></p> <p>This folder contains a snapshot of the FlowShape Python package at the time of paper submission. The latest version is available at: <a href="https://bitbucket.org/pgmsembryogenesis/flowshape/src/main/">https://bitbucket.org/pgmsembryogenesis/flowshape/src/main/</a></p> <p><strong>Data</strong></p> <p>Contain 3D meshes of <em>C. elegans</em> early embryo cells, in Wavefront .obj format. Each filename has three parts sepparated by underscores</p> <ul> <li>Embryo identifier</li> <li>Cell name</li> <li>Timestep For example: <code>wt13_ABar_18</code> Embryo = wt13 Cell = ABar Timestep = 18</li> </ul> <p>The timesteps are frames from the original timelapse, where one frame corresponds to 90 seconds. The starting point is arbitrary, so time is aligned by EMS division.</p> <p>Embryo labels:</p> <ul> <li><code>7cell01-7cell07</code>: 7 wild-type embryos imaged only around the seven-cell stage.</li> <li><code>wt01-wt19</code>: 19 wild-type embryos imaged for a longer time.</li> <li><code>dshmig01-dshmig05</code>: 5 dsh-2 / mig-5 RNAi knockdown embryos, imaged around seven-cell stage.</li> </ul> <p><code>cell_filters.csv</code> is a CSV file containing identifiers of embryos left out of the analysis because of automatically detected errors. Further, wt06 was also left out because of problems with labeling the cells.</p> <p><strong>Images</strong></p> <p>Contains raw microscopy data that was used to generate the meshes. <code>resolution.csv</code> contains a list of Z, Y and X resolutions (micron / pixel).</p> <p><strong>Changelog</strong></p> <p>0.1.0</p> <ul> <li>Initial upload</li> </ul> <p>0.2.0</p> <ul> <li>Added microscopy images.</li> <li>Removed cells 6 and 7 from dsh-2 / mig-5 dataset, which were not supposed to be included there.</li> <li>Removed Python cache files.</li> </ul>
The cell adhesion molecule Sdk1 shapes assembly of a retinal circuit that detects localized edges
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Cell-sheet shape transformation by internally-driven, oriented forces
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Data from: Optimizing gelation time for cell shape control through active learning
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Data from: Of puzzles and pavements: a quantitative exploration of leaf epidermal cell shape
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Shape matters: The relationship between cell geometry and diversity in phytoplankton
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Class-A penicillin binding proteins do not contribute to cell shape but repair cell-wall defects
Cell shape and cell-envelope integrity of bacteria are determined by the peptidoglycan cell wall. In rod-shaped Escherichia coli, two conserved sets of machinery are essential for cell-wall insertion in the cylindrical part of the cell: the Rod complex and the class-A penicillin-binding proteins (aPBPs). While the Rod complex governs rod-like cell shape, aPBP function is less well understood. aPBPs were previously hypothesized to either work in concert with the Rod complex or to independently repair cell-wall defects. First, we demonstrate through modulation of enzyme levels that aPBPs do not contribute to rod-like cell shape but are required for mechanical stability, supporting their independent activity. By combining measurements of cell-wall stiffness, cell-wall insertion, and PBP1b motion at the single-molecule level, we then present evidence that PBP1b, the major aPBP, contributes to cell-wall integrity by repairing cell wall defects.
Modelling Cell Shape in 3D Structured Environments: A Quantitative Comparison with Experiments
<p>This repository contains experimental data and computer scripts for the following publication: Link R, Jaggy M, Bastmeyer M, Schwarz US (2024) Modelling cell shape in 3D structured environments: A quantitative comparison with experiments. PLoS Comput Biol 20(4): e1011412. https://doi.org/10.1371/journal.pcbi.1011412</p> <p>There are two directories, “data” and “scripts”.</p> <p> <strong>1) </strong><strong>Directory data</strong></p> <p> WRL-files for experimental data generated with Imaris from Zeiss image files.</p> <p>The WRL-files can be converted to STL-files with MeshLab (<a href="https://www.meshlab.net/">https://www.meshlab.net</a>).</p> <p>The STL-files can be converted to FE-files for the SurfaceEvolver with our script CreateFeFile.py.</p> <p> The WRL-files are named according to the scaffolds:</p> <p>L*.wrl cells in L-shaped scaffolds (n=6).</p> <p>V*.wrl cells in V-shaped scaffolds (n=7).</p> <p>TRight*.wrl cells in right-triangle scaffolds (n=3).</p> <p>TEqui*.wrl cells in equilateral-triangle scaffolds (n=4).</p> <p><strong>2) </strong><strong>Directory scripts</strong></p> <p>ClusterSurfaceLinearPlugin: New CompuCell3D plugin needed to calculate linear surface energy functional for cells with nucleus (using the cluster concept).</p> <p>CompuCell3DScript: Hamiltonian_Comparison.cc3d is the main script for our simulations, uses the directory “Simulation”.</p> <p>CreateFeFile.py: generates surface evolver FE-file from STL-file. A STL-file can be generated from a WRL-file e.g. with MeshLab (<a href="https://www.meshlab.net/">https://www.meshlab.net</a>). </p> <p>SphericalHarmonicsAnalysis.ipynb: Python notebook that calculates the Fourier spectrum and Delta_30, needs WRL-file as input.</p> <p> </p>
Cell shape analysis
<p>Cell shape analysis<br> ---------------------------------------------<br> This package contains custom-written code associated with the paper "Direct observation of a crescent-shape chromosome in Bacillus subtilis" By Tišma et al. 2023</p> <p>See README's in subdirectories for specific content description </p> <p>Notes:<br> ----------------------------------------------<br> ## general<br> * code for extended cell analysis as used in the Cees Dekker Lab, 2017-onwards</p> <p>## associated publications<br> 1. [current submission] 'Direct observation of a crescent-shape chromosome in Bacillus subtilis'<br> Authors Miloš Tišma, Florian Patrick Bock, Jacob Kerssemakers, Aleksandre Japaridze, Stephan Gruber, Cees Dekker, submitted (2023).</p> <p>2. MukBEF-dependent chromosomal organization in widened Escherichia coli<br> Authors Aleksandre Japaridze, Raman van Wee, Christos Gogou, Jacob WJ Kerssemakers, Cees Dekker; (2022)<br> 3. Direct observation of independently moving replisomes in Escherichia coli<br> Authors Aleksandre Japaridze, Christos Gogou, Jacob WJ Kerssemakers, Huyen My Nguyen, Cees Dekker, Nat.Com (2020)<br> 4. Direct imaging of the circular chromosome in a live bacterium<br> Authors Fabai Wu, Aleksandre Japaridze, Xuan Zheng, Jakub Wiktor, Jacob WJ Kerssemakers, Cees Dekker, Nat.Com (2019)</p> <p>## package description<br> This package collects code to analyze multi-channel microscope images of cells. Patterns of interest may be extended, such as a fully labeled chromosome, or compact, as one or multiple labeled spots. The code is used to select and screen individual cells and to quantify locations of above labels. </p> <p>## package contents<br> * custom-written source code [Matlab] <br> * test data to demonstrate the software code</p> <p>## system requirements and used software<br> * Windows 10, 64bits <br> * Matlab Version 2021 [custom source code]<br> * Oufti Version .... <br> * Fiji(ImageJ) Version 1.52a<br> * Dip_image analysis software Version 2.9</p> <p>## installation guide<br> * please follow the installation instructions provided by above package distributors<br> * installation of all platforms should take less than a day on a standard PC</p> <p>## demo and instructions for use<br> * the code is divided in three main subsections (that are to be used in this order) and one extra:<br> * 'crop': works on microsocopic data, outputs data organized per cells<br> * 'donut': in-depth analysis on chromosome patterns and other labels ('spots')<br> * 'repli': follow-up analysis on spots<br> * 'topical subjects': shorter code platforms for various analyses<br> * see 'README.md' in each subdirectory for a detailed step-by-step descriptions, in order of appearance or importance in the analysis pipeline<br> * see 'README_code_annotations.md' in each subdirectory for a full collection of all custom function descriptions<br> * demo data for two cells is provided to illustrate workings and settings. Running this demo data typically only takes a few minutes<br> * for new data, follow the setup as described via the demo data <br> <br> ## contributions<br> ---------------------------------------------- <br> * F. Wu and X. Zheng originally wrote and assembled the original code package<br> * J.Kerssemakers organized, re-edited and expanded the 'crop' code package<br> * J.Kerssemakers wrote the 'donut' and 'repli' code packages<br> * A. Japaridze, Raman van Wee, Christos Gogou and M.Tisma contributed to analysis design<br> * J.Kerssemakers and M.Tisma contributed to 'topical subjects'</p> <p>## disclaimer<br> ---------------------------------------------<br> This code was custom written and shared to illustrate used algorithms, analysis pathways etc. in relation to published results. The code was regularly used and tested. However, small bugs, not relevant for the data analysis as present in publications may still be around. Interested users are expected to have a sufficient knowledge of Matlab code to understand and adapt the code to their own wishes.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.