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20 results for “F-Actin”
Zellige example dataset: mouse embryonic cochlea stained for F-actin
<p><strong>Mouse embryonic cochlea stained for F-actin at embryonic stage E16.5. </strong></p> <p>The z-stack image encompasses an epithelial surface and a thick mesh of mesenchymal cells. It was acquired with a swept-field confocal microscope (Bruker OpterraII) equipped with a Nikon Plan-Apochromat 60x lens (NA=1.4). Pixel size 0.133 µm, z step <1 µm. This dataset contains both the ground-truth height map and the height map generated with Zellige, along with the parameters used to generate the latter one. The Zellige parameters used are:</p> <p><span class="math-tex">\(T_{A}=1, T_{otsu}=1, S_{min}=5, \sigma_{xy}=4, \sigma_{z}=1, T_{OSE1}=0.1, R_{1}=5, C_{1}=0.7, T_{OSE2}=0.1, R_{2}=10, C_{2}=0.8.\)</span></p> <p>Nota: to compare the ground truth height map with the Zellige height map, one first needs to substrat 1 to all values of the Zellige height map.</p> <p>See the accompanying paper: Extracting multiple surfaces from 3D microscopy images in complex biological tissues with the Zellige software tool. Trébeau <em>et al.</em> 2022: <a href="https://doi.org/10.1101/2022.04.05.485876">https://doi.org/10.1101/2022.04.05.485876</a></p> <p> </p>
Confocal and STED Live F-actin dataset
<p>Paired confocal and STED images of F-actin nanostructures in living neurons using the far-red fluorogenic dye SiR-Actin. This dataset was used to train and test the TA-GAN model for confocal-to-STED super-resolution of axonal and dendritic F-actin in living neurons (<a href="https://doi.org/10.1101/2021.07.19.452964">Resolution Enhancement with a Task-Assisted GAN to Guide Optical Nanoscopy Image Analysis and Acquisition</a>).</p> <p>All images : 20 nm/pixel.</p> <p>Folders:<br> - train : 753 pairs of confocal/STED images (varying sizes)<br> - valid : 47 pairs of confocal/STED images (varying sizes)<br> - test_initial & test_final : 84 confocal/STED pairs acquired before (initial) and 84 acquired after (final) control sequences where 15 confocal images of the full FOV (500 x 500 pixels = 10μm x 10μm) were acquired at 1 frame/minute. In addition to the confocal image, a sub-region (100 x 100 pixels = 2μm x 2μm) was selected outside the central ROI (300 x 300 pixels = 6μm x 6μm) and acquired with the STED modality at every time step; the signal decrease due to photobleaching effects can therefore be more prononced in the border region outside the central ROI.<br> - test_series : contains 149 series of images acquired with TA-GAN assistance using the change-based Dice coefficient threshold or the variability-based threshold. </p> <p>The test_series folder contains folders with names corresponding to "[date of acquisition]_cs[coverslip number]_ROI[selected region number]". Each folder contains three subfolders : input, full_STED, and initial_final_confocal. <br> - Input : this folder contains three-channel images for each of the 15 frames in the series. The first channel is the full FOV confocal image (10μm x 10μm), the second channel is the STED sub-region (2μm x 2μm) with zero-padding to match the shape of the FOV, and the third channel is a decision map of 0s and 1s, with the 1s indicating the position in the FOV of the STED sub-region.<br> - full_STED : this folder contains all the STED FOVs (10μm x 10μm) acquired when triggered by the TA-GAN assistance. The number of full_STED FOVs varies from 0 to 15 per region, with a mean of 2.8 STED images per series. The full FOV STED images acquired before (initialSTED.tif) and after (finalSTED.tif) the series of 15 frames are also included.<br> - initial_final_confocal : The full FOV confocal images acquired before (initialConfocal.tif) and after (finalConfocal.tif) the series of 15 frames.</p>
F-actin Imaging of Mechanically Compressed Pseudostratified Human Bronchial Epithelial Cells
<p><strong>Overview</strong></p> <p>This dataset includes immunofluorescence microscopy of pseudostratified airway epithelial cells stained for F-actin. Each field of view consists of 3 images visualizing the apical cell boundaries, basal cell boundaries, and basal cell stress fibers.</p> <p><strong>Cell Culture and Treatment</strong></p> <p>Primary human bronchial epithelial cells (from a single donor) were grown on transwells in air-liquid interface culture for 14 days to model a well-differentiated, pseudostratified airway epithelium. Cells were then exposed to mechanical compression (30 cmH2O for 3 hours) mimicking asthmatic bronchoconstriction. Cells were fixed (4% PFA for 30 minutes) at 24, 48, or 72 hours after mechanical compression. Two transwells were collected per condition and timepoint.</p> <p><strong>Immunofluorescence Imaging</strong></p> <p>Fixed transwells were stained for F-actin (Alexa fluor 488-Phalloidin, ThermoFisher Scientific, diluted 1:40, 30 minutes). Transwell membranes were cut from the plastic support and mounted on glass slides. Slides were imaged using a Zeiss Axio Observer Z1 with an apotome module controlled using Zen Blue 2.0 software. Five random fields of view were imaged from each transwell membrane in a z-stack from substrate to apical cell surface. To visualize various planes through the pseudostratified epithelial layer (apical cell boundaries, basal cell boundaries, and basal cell stress fibers), maximum intensity projections were generated from regions of interest through the z-stack.</p> <p><strong>Dataset</strong></p> <p>Each image file contains</p> <ul> <li>Timepoint: <strong>24</strong>, <strong>48</strong>, or <strong>72 </strong>hours after treatment</li> <li>Condition & Well: control <strong>(C) </strong>or mechanical compression<strong> (P) </strong>followed by a number indicating the well (1 or 2)</li> <li>Unique Z-stack ID: <strong><em>3-digit number</em></strong></li> <li><em>Miscellaneous note: MIP or MIP_ROI</em></li> <li>Region of Interest: apical cell boundaries (<strong>ACB</strong>), basal cell boundaries (<strong>BCB</strong>), or basal stress fibers (<strong>SF</strong>)</li> </ul> <p>For example, these 3 maximum intensity projection images came from the<em> same z-stack/field of view. </em>They are from the 72 hour timepoint, mechanical compression, well #2, z-stack #147:</p> <ul> <li>72hr_P2_147_MIP_ACB.tif: <em>apical cell boundaries</em></li> <li>72hr_P2_147_MIP_ROI_BCB.tif: <em>basal cell boundaries</em></li> <li>72hr_P2_147_MIP_ROI_SF.tif: <em>basal stress fiber</em></li> </ul>
Phase Contrast Time-Lapse and F-actin Imaging of Mechanically Compressed or Irradiated Pseudostratified Human Bronchial Epithelial Cells
<p><strong>Overview</strong></p> <p>This dataset includes phase contrast time-lapse imaging of <em>in vitro</em> pseudostratified airway epithelial cells to visualize their collective cellular migration after exposure to mechanical compression (mimicking bronchoconstriction) or irradiation. Additionally, the cells were fixed and stained for F-actin to visualize the apical cell boundaries, basal cell boundaries, and basal cell stress fibers.</p> <p><strong>Cell Culture and Treatment</strong></p> <p>Primary human bronchial epithelial cells (from a single donor) were grown on transwells in air-liquid interface (ALI) culture for 14 days to model a well-differentiated, pseudostratified airway epithelium. Cells were then exposed to either mechanical compression (30 cmH2O for 3 hours) mimicking asthmatic bronchoconstriction or irradiation (1Gy of ionizing radiation using a RS 2000 Biological Research Irradiator (RadSource) on ALI days 7, 10, and 14).</p> <p><strong>Phase Contrast Time-Lapse Imaging</strong></p> <p>At 24 or 72 hours after final treatment, cells were imaged to visualize collective cellular migration. For each independent experimental replicate (2 transwells per treatment per timepoint), six fields of view per well were imaged every 6 minutes over 1.5 hours. The imaging chamber was supplied with 37°C, 5% CO2, humidified air on a Zeiss Axio Observer Z1 to collect phase contrast images. <em>The image resolution is 0.586 µm/pixel.</em></p> <p><strong>Immunofluorescence Imaging</strong></p> <p>Cells were fixed (4% PFA for 30 minutes) at 24 or 72 hours after final treatment (and after phase contrast time-lapse imaging). Fixed transwells were stained for F-actin (Alexa fluor 488-Phalloidin, ThermoFisher Scientific, diluted 1:40, 30 minutes). Transwell membranes were cut from the plastic support and mounted on glass slides. Slides were imaged using a Zeiss Axio Observer Z1 with an apotome module controlled using Zen Blue 2.0 software. Five random fields of view were imaged from each transwell membrane in a z-stack from substrate to apical cell surface. To visualize various planes through the pseudostratified epithelial layer (apical cell boundaries, basal cell boundaries, and basal cell stress fibers), maximum intensity projections were generated from regions of interest through the z-stack. <em>The image resolution is 0.293 µm/pixel.</em></p> <p><strong>Dataset</strong></p> <p>Phase contrast time-lapse movies are provided as *.avi files. Immunofluorescence images are provided as *.tif files. For an individual transwell, the imaging dataset includes:</p> <ul> <li>6 phase contrast time-lapse movies</li> <li>5 immunofluorescence images of apical cell boundaries</li> <li>5 immunofluorescence images of basal cell boundaries</li> <li>5 immunofluorescence images of basal cell stress fibers</li> </ul> <p>Phase contrast time-lapse filenames contain</p> <ul> <li>Donor: U13</li> <li>Timepoint: 24 or 72 hours</li> <li>Treatment & Well: control (C), mechanical compression (P), or irradiation (R); well 1 or 2</li> <li>Field of View: (1) – (6)</li> </ul> <p>Immunofluorescence image filenames contain:</p> <ul> <li>Donor: <strong>U13</strong></li> <li>Timepoint: <strong>24</strong> or <strong>72</strong> hours</li> <li>Treatment & Well: control (<strong>C</strong>), mechanical compression (<strong>P</strong>), or irradiation (<strong>R</strong>); well <strong>1</strong> or <strong>2</strong></li> <li>Field of View: <strong>1-5</strong></li> <li>Region of Interest: apical cell boundaries (<strong>ACB</strong>), basal cell boundaries (<strong>BCB</strong>), or basal stress fibers (<strong>SF</strong>)</li> </ul> <p>Phase contrast time-lapse and immunofluorescence from the same transwell will all start with the same “Donor_Timepoint_Treatment/Well...” (i.e. U13_24_C1…). <strong>Note that the images from phase contrast and immunofluorescence are not necessarily from matched locations within the transwell and are at different spatial scales.</strong></p> <p>Immunofluorescence images from the same z-stack field of view will start with the same “Donor_Timepoint_Treatment/Well_FieldofView…” (i.e. U13_24_C1_1…).</p>
Models and maps from cryoDRGN results of cadherin-catenin-afadin complex bound to F-actin
<p>This dataset contains the inputs and outputs of cryoDRGN variability analysis for F-actin with bound afadin-catenin-cadherin complex. Within cryoDRGN.zip are the maps and models used for bending analysis as well as the input data and trained neural networks to reproduce these results.</p>
BioTISR: F-actin (3D WF)
<p>3D F-actin data of BioTISR dataset.</p> <p>BioTISR is a biological image dataset for super-resolution microscopy, currently including 2D and 3D time-lapse image pairs of low-and-high resolution images of a variety of biology structures, aiming to provide a high-quality dataset of time-lapse biological SR images for the community to spark more developments of computational SR methods.</p> <p>At present, 2D dataset includes five specimens (clathrin-coated pits, lysosomes, outer mitochondrial membrane, microtubules, and F-actin) acquired with the GI/TIRF-SIM mode and nonlinear SIM mode of our Multi-SIM system, and 3D data includes three specimens (outer mitochondrial membrane, microtubules, and F-actin) acquired with 3D-SIM mode of the Multi-SIM system. For each type of specimen and each imaging modality, we acquired the raw data from at least 50 distinct regions-of-interest (ROI). For each ROI, we acquired two (3D data) or three (2D data) groups of N-phase × M-orientation × T-timepoint raw images with a constant exposure time but increasing the excitation light intensity, where (N, M, T) are (3, 3, 20) for TIRF-SIM and GI-SIM, (5, 5, 10) for nonlinear SIM, and (3, 5, 10) for 3D-SIM.</p> <p>The BioTISR dataset is related to the following paper:<a href="https://doi.org/10.1101/2024.05.04.592503">Chang Qiao, Shuran Liu, Yuwang Wang, Wencong Xu, et al. "Time-lapse Image Super-resolution Neural Network with Reliable Confidence Evaluation for Optical Microscopy." bioRxiv 2024.05.04.592503 (2024)</a>, which is an extension of our previously published <a href="https://doi.org/10.6084/m9.figshare.13264793.v9">BioSR dataset</a> (https://www.nature.com/articles/s41592-020-01048-5).</p>
BioTISR: F-actin (3D)
<p><strong><span>3D F-actin</span><span><span> data of BioTISR dataset</span></span></strong></p> <p><span>BioTISR is a biological image dataset for super-resolution microscopy, currently including 2D and 3D time-lapse image pairs of low-and-high resolution images of a variety of biology structures, aiming to provide a high-quality dataset of time-lapse biological SR images for the community to spark more developments of computational SR methods.</span></p> <p><span>At present, 2D dataset includes five specimens (clathrin-coated pits, lysosomes, outer mitochondrial membrane, microtubules, and F-actin) acquired with the GI/TIRF-SIM mode and nonlinear SIM mode of our Multi-SIM system, and 3D data includes three specimens (outer mitochondrial membrane, microtubules, and F-actin) acquired with 3D-SIM mode of the Multi-SIM system. For each type of specimen and each imaging modality, we acquired the raw data from at least 50 distinct regions-of-interest (ROI). For each ROI, we acquired two (3D data) or three (2D data) groups of N-phase × M-orientation × T-timepoint raw images with a constant exposure time but increasing the excitation light intensity, where (N, M, T) are (3, 3, 20) for TIRF-SIM and GI-SIM, (5, 5, 10) for nonlinear SIM, and (3, 5, 10) for 3D-SIM.</span></p> <p><span>The BioTISR dataset is related to the following paper:</span><span><a href="https://doi.org/10.1101/2024.05.04.592503"><span>Chang Qiao, Shuran Liu, Yuwang Wang, Wencong Xu, et al. "Time-lapse Image Super-resolution Neural Network with Reliable Confidence Evaluation for Optical Microscopy." bioRxiv 2024.05.04.592503 (2024)</span></a></span><span>, which is an extension of our previously published </span><span><a href="https://doi.org/10.6084/m9.figshare.13264793.v9"><span>BioSR dataset</span></a></span><span> (https://www.nature.com/articles/s41592-020-01048-5).</span></p>
Nanoscale chemical characterization of secondary protein structure of F-Actin using mid-infrared photoinduced force microscopy (PiF-IR)
<p>Raw data for manuscript for special issue in Spectrochimica Acta related to ECSBM 2022</p> <p> </p>
Single particle analysis supplemental files for F-actin under myosin directed forces
<p>This dataset contains supplemental files associated with the single particle analysis for F-actin under myosin directed forces. Included are neural networks used to pick particles from 2D micrographs, flexibly fit atomic models and associated maps, and variability analysis-generated maps and associated models.</p>
Denoised tomograms and filament traces for F-actin under myosin directed forces
<p>This dataset contains the neural networks used to denoise cryo-electron tomograms of F-actin filaments under myosin directed forces as well as the denoised tomograms and filament traces.</p>
Drosophila Imp iCLIP identifies an RNA assemblage co-ordinating F-actin formation
GEO Series GSE62997. Drosophila melanogaster. 16 samples. Type: Expression profiling by high throughput sequencing.
Ground-state pluripotent stem cells are characterized by Rac1-dependent cadherin-enriched F-actin complexes
GEO Series GSE290766. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome analysis after disruption of nuclear F-actin in mouse embryos
GEO Series GSE126317. Mus musculus. 15 samples. Type: Expression profiling by high throughput sequencing.
Mitochondrial dysfunction, disruption of F-actin polymerization, and transcriptomic alterations in zebrafish larvae exposed to trichloroethylene
GEO Series GSE72918. Danio rerio. 8 samples. Type: Expression profiling by array.
Myocardin-related transcription factors regulate F-actin organization during gastrulation and neural tube closure in Xenopus embryos
GEO Series GSE243351. Xenopus laevis. 4 samples. Type: Expression profiling by high throughput sequencing.
F-actin dynamics regulates mammalian organ growth and cell fate maintenance
GEO Series GSE116993. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
F-actin cryoDRGN bending maps and models
<p>This dataset contains the inputs and outputs of cryoDRGN variability analysis for ADP-F-actin and ADP-Pi-F-actin. Within cryoDRGN.zip are the maps and models used for bending analysis as well as the input data and trained neural networks to reproduce these results. In bin1_particles_aligned.zip are the stacks of aligned polished, bin1 particles that were binned by 2 and used as input for cryoDRGN training. Lastly, curvature_measurements.zip contains the curvature measurements used to generate curvature distribution histograms.</p>
Investigation of the potential mechanisms underlying nuclear F-actin organization in ovarian cancer cells by high-throughput screening in combination with deep learning
GEO Series GSE199915. Homo sapiens. 15 samples. Type: Expression profiling by high throughput sequencing.
The regulatory effect and mechanism of F-actin gene on the response of cadmium toxicity in farmland Pardosa pseudoannulata
GEO Series GSE284523. Pardosa pseudoannulata. 6 samples. Type: Expression profiling by high throughput sequencing.
Coactosin-like F-actin Binding Protein (Cotl1) Plays a Key Role in Adipocyte Differentiation and Obesity
GEO Series GSE293445. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
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International Brain Laboratory public data
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OpenNeuro
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