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523 results for “actin”
Partitioning of ribonucleoprotein complexes from the cellular actin cortex
<p>The cell cortex plays a crucial role in cell mechanics, signaling, and development. However, little is known about the influence of the cortical meshwork on the spatial distribution of cytoplasmic biomolecules. Here, we describe a new fluorescence microscopy method to infer the intracellular distribution of labeled biomolecules with sub-resolution accuracy. Unexpectedly, we find that RNA-binding proteins are partially excluded from the cytoplasmic volume adjacent to the plasma membrane that corresponds to the actin cortex. Complementary diffusion measurements of RNA-protein complexes suggest that a rudimentary model based on excluded volume interactions can explain this partitioning effect. Our results suggest the actin cortex meshwork may play a role in regulating the biomolecular content of the volume immediately adjacent to the plasma membrane.</p>
DNA sequences for: Synthetic control of actin polymerization and symmetry breaking in active protocells
<p>Non-linear biomolecular interactions on membranes drive membrane remodeling crucial for biological processes including chemotaxis, cytokinesis, and endocytosis. The complexity of biomolecular interactions, their redundancy, and the importance of spatiotemporal context in membrane organization impede understanding of the physical principles governing membrane mechanics. Developing a minimal in vitro system that mimics molecular signaling and mem- brane remodeling while maintaining physiological fidelity poses a significant challenge. Inspired by chemotaxis, we reconstructed chemically regulated actin polymerization inside vesicles, guiding membrane self-organization. An external, undirected chemical input induced directed actin polymerization and membrane deformation uncorrelated with upstream biochemical cues, suggesting symmetry breaking. A biophysical model incorporating actin dynamics and membrane mechanics proposes that uneven actin distributions cause non-linear membrane deformations, consistent with experimental findings. This protocellular system illuminates the interplay between actin dynamics and membrane shape during symmetry breaking, offering insights into chemotaxis and other cell biological processes.</p>
Zyxin, VASP, and profilin-G-actin force reconstitution assay dataset
<p>This dataset contains the raw TIRF microscopy data from single motor assays with zyxin, VASP, and profilin-G-actin, as well as the script used to analyze the data.</p>
Fluorescent images of actin and DAPI-labelled MCF10A, MCF7 and MDA-MB-231 cell lines
<p>This dataset of cell images was generated to understand the morphological changes between less and more metastic cancer cells and between normal and cancerous cells. They have been used in the linked publications.</p>
Other Supplementary Material for 'Myosin-I Synergizes with Arp2/3 Complex to Enhance Pushing Forces of Branched Actin Networks' by Xu et al.
<div> <p>Other Supplementary Material for "Myosin-I Synergizes with Arp2/3 Complex to Enhance Pushing Forces of Branched Actin Networks" by Xu, Rutkowski, Rebowski, Boczkowska, Pollard, Dominguez, Vavylonis, and Ostap, bioRxiv, <a href="https://doi.org/10.1101/2024.02.09.579714" rel="nofollow">https://doi.org/10.1101/2024.02.09.579714</a> </p> <p> </p> </div>
Videos: Computing on actin bundles network
<p>These are videos of experiments described in the paper </p> <p>Andrew Adamatzky, Florian Huber, Florian HuberJörg Schnauß. Computing on actin bundles network (March, 2019).</p> <p>Abstract </p> <p>Actin filaments are conductive to ionic currents, mechanical and voltage solitons. These travelling localisations can be utilised in making the actin network executing specific computing circuits. The propagation of localisations on a single actin filament is experimentally unfeasible, therefore we propose a `relaxed' version of the computing on actin networks by considering excitation waves propagating on actin bundles. We show that by using an arbitrary arrangement of electrodes it is possible to implement two-inputs-one-output circuits. Frequencies of the Boolean gates' detection in actin network match an overall distribution of gates discovered in living substrates.</p>
Supplementary videos for the paper ``Actin Droplet Machine''
<p>The actin droplet machine is a computer model of a three-dimensional network of actin bundles developed in a droplet of a physiological solution, which implements mappings of sets of binary strings. The actin bundle network is conductive to travelling excitations, .i.e. impulses. The machine is interfaced with an arbitrary selected set of k electrodes through which stimuli, binary strings of length k represented by impulses generated on the electrodes, are applied and responses are recorded. The responses are recorded in a form of impulses and then converted to binary strings. The machine's state is a binary string of length k: if there is an impulse recorded on the i-th electrode, there is a `1' in the i-th position of the string, and `0' otherwise. We present a design of the machine and analyse its state transition graphs. We envisage that actin droplet machines could form an elementary processor of future massive parallel computers made from biopolymers.</p>
Movie files: Actin dynamics and the Bmp pathway drive apical extrusion of proepicardial cells.
<p>The epicardium, the outer mesothelial layer enclosing the myocardium, plays key roles in heart development and regeneration. During embryogenesis it arises from the proepicardium (PE), a cell cluster that appears in the dorsal pericardium (DP) close to the venous pole of the heart. Little is known about how the PE emerges from the pericardial mesothelium. Using the zebrafish model and a combination of genetic tools, pharmacological agents and quantitative <em>in vivo</em> imaging, we reveal that a coordinated collective movement of DP cells drives PE formation. We found that BMP signaling and the actomyosin cytoskeleton promote constriction of the DP, which enabled PE cells to extrude apically. We provide evidence that cell extrusion, which has been described in the elimination of unfit cells from epithelia and the emergence of hematopoietic stem cells, is also a mechanism for PE cells to exit an organized mesothelium and fulfil the developmental fate to form a new tissue layer, the epicardium.</p>
Numbers of Single-Cell β-Actins
<p>The dataset is an Excel composed of ten columns representing absolute numbers of single-cell β-actins from cell types of A549 (column A, N<sub>cell</sub> = 14,242), Hep G2 (column B, N<sub>cell</sub> = 35,932), MCF 10A (column C, N<sub>cell</sub> = 16,650), HeLa (column D, N<sub>cell</sub> = 26,151), PC3 (column E, N<sub>cell</sub> = 11,922), SACC-83 (column F, N<sub>cell</sub> = 13,616), CAL 27 (column G, N<sub>cell</sub> = 7,271), CAL 27-LN2 (column H, N<sub>cell</sub> = 6,222), Oral Tumour Patient I (column I, N<sub>cell</sub> = 359) and Oral Tumour Patient II (column J, N<sub>cell</sub> = 175), respectively.</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>
Calponin-Homology Domain mediated bending of membrane associated actin filaments
<p><span>This dataset contains data from experiments described in </span>'Palani S, Ghosh S, Ivorra-Molla E, Clarke S, Suchenko A, Balasubramanian MK, Köster DV. 2021. Calponin-homology domain mediated bending of membrane associated actin filaments. <i>Elife</i> <b>10</b>. doi:10.7554/eLife.61078'. This dataset consists of fluorescence microscopy images obtained by total internal reflection fluorescence (TIRF) microscopy. Using an <em>in vitro</em> approach, we studied the effect of the IQGAP protein fragment Rng2(1-189) on the geometry of actin filaments when tethered to supported lipid bilayers all reconstituted from purified proteins. The main findings are that Rng2(1-189) bends actin filaments into tight rings when tethered to supported lipid bilayers.</p>
Giant worm-shaped ESCRT-scaffolds surround actin-independent integrin clusters, data part 1
<p>Part one of the data used for the generation of the article <em>Giant worm-shaped ESCRT-scaffolds surround actin-independent integrin clusters.</em></p>
Giant worm-shaped ESCRT-scaffolds surround actin-independent integrin clusters, data part 2
<p>Part 2 of data for the article <em>Giant worm-shaped ESCRT-scaffolds surround actin-independent integrin clusters.</em></p>
Files associated with Purification of Human beta and gamma Actin from Budding Yeast
<p>Original imaging files, gels, and analyzed data associated with the paper</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>
Data from: The fat body cortical actin network regulates Drosophila inter-organ nutrient trafficking, signaling, and adipocyte cell size
<p>Defective nutrient storage and adipocyte enlargement (hypertrophy) are emerging features of metabolic syndrome and type 2 diabetes. How the cytoskeletal network contributes to nutrient uptake, fat storage, and adipocyte size remains poorly understood. Utilizing the <em>Drosophila</em> larval fat body (FB) as a model adipose tissue, we show that a specific actin isoform—Act5C—forms the cortical actin network necessary for inter-organ lipid trafficking. Act5C also promotes FB tissue expansion during larval development so larvae can store sufficient biomass for metamorphosis. We find FB-specific loss of Act5C, but not other <em>Drosophila</em> actins, perturbs FB triglyceride (TG) storage in lipid droplets (LDs), resulting in developmentally delayed larvae that fail to develop into flies. Act5C localizes to the FB cell surface where it intimately contacts peripheral LDs (pLDs), forming a cortical actin network together with spectrins for cell architectural support. While both the cortical actin and spectrin cytoskeletons maintain FB cell surface architecture, we find that only the actin network is required for fat storage. Mechanistically, we show that FBs lacking the Act5C cortical cytoskeleton exhibit a block in lipoprotein (Lpp) secretion from FB cells, and a subsequent disruption of gut:FB inter-organ lipid transport, resulting in mid-gut fat accumulation. Utilizing temporal RNAi-depletion approaches, we also reveal that Act5C is indispensable post-embryogenesis during larval feeding to promote FB cell expansion. Act5C-deficient FBs fail to expand cell sizes, leading to lipodystrophic larvae unable to accrue sufficient biomass for metamorphosis. Collectively, we propose that the Act5C-mediated cortical actin network of <em>Drosophila</em> adipose tissue plays an essential role in post-embryonic inter-organ nutrient transport and FB cell size determination for organismal energy homeostasis and development.</p>
Safety and Effectiveness Study of Imiquimod Creams for the Treatment of Actinic Keratoses (AKs)
ClinicalTrials.gov study NCT00603798. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Short Contact Protocols to Reduce Pain During 10% ALA Gel Red-light Photodynamic Therapy of Actinic Keratoses
ClinicalTrials.gov study NCT06027619. IPD Sharing: YES. Countries: 1. Publications: 1.
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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.