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111,247 results for “cells”
Mitochondria morphology quantification datasheet of different MIGA2 expressing cells
<p>Mitochondria morphology quantification datasheet of different MIGA2 constructs expressing Hela cells: WT, MIGA2 KO, MIGA2 KO cells transfected with WT MIGA2, MIGA2 KO cells transfected with MIGA2 mutants (M1, M2, M3).</p>
Lipid droplet quantification datasheet of different MIGA2 constructs expressing cells
<p>Lipid droplet quantification datasheet of different MIGA2 constructs expressing Hela cells: WT, MIGA2 KO, MIGA2 KO cells transfected with WT MIGA2, MIGA2 KO cells transfected with MIGA2 mutants.</p>
THOR progress presentation 2022: Targeting Smooth Muscle Cells for Atherosclerosis Therapy
<p>This is a recorded talk with head of the THOR project - Jacob Fog Bentzon, where he presents the latest project progress.</p> <p>The talk was given at one of ODIN's (the Open Discovery Innovation Network) Knowledge Sharing Events in May 2022.</p>
Viscoelastic properties of suspended cells measured with shear flow deformation cytometry
<p>Numerous cell functions are accompanied by phenotypic changes in viscoelastic properties, and measuring them can help elucidate higher-level cellular functions in health and disease. We present a high-throughput, simple and low-cost microfluidic method for quantitatively measuring the elastic (storage) and viscous (loss) modulus of individual cells. Cells are suspended in a high-viscosity fluid and are pumped with high pressure through a 5.8 cm long and 200 μm wide microfluidic channel. The fluid shear stress induces large, near ellipsoidal cell deformations. In addition, the flow profile in the channel causes the cells to rotate in a tank-treading manner. From the cell deformation and tank treading frequency, we extract the frequency-dependent viscoelastic cell properties based on a theoretical framework developed by R. Roscoe that describes the deformation of a viscoelastic sphere in a viscous fluid under steady laminar flow. We confirm the accuracy of the method using atomic force microscopy-calibrated polyacrylamide beads and cells. Our measurements demonstrate that suspended cells exhibit power-law, soft glassy rheological behavior that is cell cycle-dependent and mediated by the physical interplay between the actin filament and intermediate filament networks.</p>
Opt2Q Example cell_viability_calibration_results
<p>A model of apoptosis (aEARM) was calibrated to published cell viability data using PyDREAM. The posterior sample for the model parameters and log-posterior traces are included as .npy files. The .txt files show the Gelman Rubin metric for each of the model parameters. The data was generated using https://github.com/LoLab-VU/aEARM_cell_viability_calibration</p>
CD8+ T cell differentiation status correlates with the feasibility of sustained unresponsiveness following oral immunotherapy
<p>While food allergy oral immunotherapy (OIT) can provide safe and effective desensitization (DS), the immune mechanisms underlying development of sustained unresponsiveness (SU) following a period of avoidance are largely unknown. We compared high dimensional immunophenotypes of innate and adaptive immune cell subsets of participants in a phase 2 randomized, controlled, peanut OIT trial who achieved SU vs. DS (no vs. with allergic reactions upon food challenge after a withdrawal period; n=21 vs. 30 respectively among total 120 intent-to-treat participants). Lower frequencies of naïve CD8<sup>+</sup> T cells and terminally differentiated CD57+ CD8<sup>+</sup> T cell subsets at baseline (pre-OIT) were highly associated with SU. Frequency of naïve CD8<sup>+</sup> T cells showed a significant positive correlation with peanut- and Ara h 2-specific IgE at baseline. Higher frequencies of IL-4<sup>+</sup> and IFNg<sup>+</sup> CD8<sup>+</sup> T cells post-OIT were negatively correlated with SU. Our findings provide compelling evidence that an immune signature consisting of certain CD8<sup>+</sup> T cell subset frequencies is predictive of SU following OIT.</p>
Extended zenodo data figures for, "An atlas of healthy and injured cell states and niches in the human kidney"
<p>This repository includes extended data zenodo figures for the manuscript, "An atlas of healthy and injured cell states and niches in the human kidney." Figures and figure legends are included in the included pdf file.</p>
Supporting data and analysis for, "An atlas of healthy and injured cell states and niches in the human kidney"
<p>Online repository for contents associated with kidney cell state atlas: </p> <p>This combines the image datasets used for the manuscript describing an approach for the integrated tissue cytometry analysis of mesoscale confocal imaging datasets.</p> <p>Linked deposits:</p> <table> <tbody> <tr> <td>Zenodo Extended Data figures</td> <td>10.5281/zenodo.7120908</td> </tr> <tr> <td>3D Cytometry and neighborhood analysis</td> <td>10.5281/zenodo.7120941</td> </tr> <tr> <td>Github repository, "Cell-State-Atlas_2022"</td> <td>https://github.com/KPMP/Cell-State-Atlas-2022</td> </tr> </tbody> </table> <p> </p> <p> </p>
Do changes in body mass alter white blood cell profiles and immune function in Australian cane toads (Rhinella marina)?
<p><span>Variation in food resources can result in dramatic fluctuations in the body condition of animals dependent on those resources. Decreases in body mass can disrupt patterns of energy allocation and impose stress, thereby altering immune function. In this study we investigated links between changes in body mass of captive cane toads (Rhinella marina), their circulating white blood cell populations, and their performance in immune assays. Captive toads that lost weight over a 3-month period had increased levels of monocytes and heterophils and reduced levels of eosinophils. Basophil and lymphocyte levels were unrelated to changes in mass. Because individuals that lost mass had higher heterophil levels but stable lymphocyte levels, the ratio of these cell types was also higher, partially consistent with a stress response. Phagocytic ability of whole blood was higher in toads that lost mass, due to increased circulating levels of phagocytic cells. Other measures of immune performance were unrelated to mass change. These results highlight the challenges faced by invasive species as they expand their range into novel environments which may impose substantial seasonal changes in food availability that were not present in the native range. Individuals facing energy restrictions may shift their immune function towards more economical and general avenues of combating pathogens. </span></p>
T cell deficiency precipitates antibody evasion and emergence of neurovirulent polyomavirus
<p>JC polyomavirus (JCPyV) causes progressive multifocal leukoencephalopathy (PML), a life-threatening brain disease in immunocompromised patients. Inherited and acquired T cell deficiencies are associated with PML. The incidence of PML is increasing with the introduction of new immunomodulatory agents, several of which target T cells or B cells. PML patients often carry mutations in the JCPyV VP1 capsid protein, which confer resistance to neutralizing VP1 antibodies (Ab). Polyomaviruses (PyV) are tightly species-specific; the absence of tractable animal models has handicapped understanding of PyV pathogenesis. Using mouse polyomavirus (MuPyV), we found that T cell deficiency during persistent infection, in the setting of monospecific VP1 Ab, was required for outgrowth of VP1 Ab-escape viral variants. CD4 T cells were primarily responsible for limiting polyomavirus infection in the kidney, a major reservoir of persistent infection by both JCPyV and MuPyV, and checking emergence of these mutant viruses. T cells also provided a second line of defense by controlling the outgrowth of VP1 mutant viruses that evaded Ab neutralization. A virus with two capsid mutations, one conferring Ab-escape yet impaired infectivity and a second compensatory mutation, yielded a highly neurovirulent variant. These findings link T cell deficiency and evolution of Ab-escape polyomavirus VP1 variants with neuropathogenicity.</p>
[3/3] Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation
<p>Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation</p>
[2/3] Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation
<p>Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation</p>
[1/3] Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation
<p>Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation</p>
New protein production in primary pulmonary artery endothelial cells treated with insulin-like growth factor 1 treatment
<p>Maximum projections of flat-fielded and deconvolved epi-fluorescence imaging data for primary sheep pulmonary artery endothelial cells (PAEC) treated with vehicle or insulin-like growth factor 1 (IGF1) media.</p> <p>Two cell types: normal PAEC and persistent pulmonary hypertension of the newborn (PPHN) PAEC</p> <p>Three time points: 0 minutes, 1 hour, and 24 hours post-treatment</p> <p>Two fluorescence channels:<br> C0 - DAPI for nuclei (R37606, Life Technologies)<br> C1 - Click-IT new protein translation kit (C10428, C10429, Life Technologies)</p>
Chorá - Single Cell
The first typology develops from the basic module (simple cell) in a multitude of variants that arise from the horizontal or vertical combination of one or more cells. It is the most widespread and characterizes the vernacular urban structure of Chorá. It is formed between the 13th and 19th centuries. The variants depend on the way of aggregation of the simple cell and its position in the block that are influenced by the morphology of the site. [Learn more](https://esg.pt/3dpast/platform) Source: Objaverse 1.0 / Sketchfab
Multi-organ CD45+ immune cell atlas
<p><em>File Description</em></p> <p><strong>MultiOrgan_MetaAtlas_total_level3_qc.rds:</strong> an rds file containing a Seurat object 114275 cells (RNA integrated assays, PCA and UMAP reductions and quality metrics)</p> <p><strong>MultiOrgan_MetaAtlas_total_level3_qc.h5ad: </strong>an h5 file containing the single cell object as the above</p> <p><strong>MultiOrgan_MetaAtlas_total_level3_qc_metadata.csv</strong>: a table containing the metadata for each cell</p> <p> </p> <p><em>Methodology </em></p> <p>162 loom files were downloaded from the 12 different projects of the HCA consortium. In more detail, we focused on 14 different organs: prostate gland, eye, heart, skeletal muscle organ, blood, liver, spleen, brain, kidney, colon, esophagus, lung, thymus, and bone marrow. The files were transformed into Seurat objects with the function as.Seurat() from Seurat package in R. After incorporating metadata information, each object was screened for immune cells based on the expression of the CD45 immune marker. Specifically, cells were considered immune cells if they exhibited at least one read of the PTPRC - CD45 surface marker gene. Finally, the Seurat object was transformed into a .h5 object for Python users.</p> <p> </p> <p><em>Metadata</em></p> <p>All the files contain the following donor metadata variables:</p> <ul> <li>Tissue: Organ/tissues</li> <li>Project: Project of HCA</li> <li>Library_prep: single cell technology</li> <li>Sample_ID: assigned patient identifiers</li> <li>Tissue_part: specific location of the sampling</li> <li>Sex: the donor's sex</li> <li>Age: the donor's age</li> <li>percent.mt: Calculation of mitochondrial proportion</li> <li>percent.ribo: Calculation of ribosomal proportion</li> <li>annotation_level1: characterization of cells into the main immune compartments</li> <li>annotation_level2: focusing on each annotation_level1 category and performing in-depth characterization of the immune</li> <li>cells</li> <li>annotation_level3: focusing on the different subtypes of macrophages and the Tregs compartment</li> <li>The columns scDblFinder.class_rna, scDblFinder.score_rna, scDblFinder.weighted_rna, scDblFinder.cxds_score_rna are related</li> <li>to metrics for doublet detection using scDblFinder</li> <li>The columns S.Score, G2M.Score and Phase are related to cell cycling</li> </ul>
Court Cell Raw Point Cloud
The raw pointcloud from an AR worldmap scan of one of the felons' cells at York Castle Museum. Scanned using ARKit. Source: Objaverse 1.0 / Sketchfab
Cela | Ruins of a nuns' cell
Esta é uma cela do Convento de Nossa Senhora da Saudação em Montemor-o-Novo, edifício religioso da ordem dominicana situado no interior do perímetro amuralhado do Castelo de Montemor-o-Novo e cuja fundação data da primeira metade do século XVI. Esta era uma das celas de reclusão e isolamento das freiras dominicanas que habitavam este Convento. Source: Objaverse 1.0 / Sketchfab
Twin Cell
The various methods of expansion of the covered dwelling area, according to the progressive 'doubling', both in height and in depth, have determined the so-called 'typological process': from the 'matrix' type of elementary cells to the single-family row house or terrace-house type, up to the recent multi-family in-line house type (present sporadically in Pienza and only for the 'recast' of terraced houses). Single-cell homes, especially during the 19th century, expanded in height with the addition of a third floor, or merged together giving rise to online associations, to one or two apartments per floor. The stairs that connect the floors together are generally located in a central position. Although today the survey of the number of floors shows that most of the buildings consists of three floors above ground, probably the same houses originally did not exceed two floors. [Learn More](https://esg.pt/3dpast/platform/pienza/multiple-cells.html) Source: Objaverse 1.0 / Sketchfab
Drum-like airdrop capsule, "little cell"
ID no.: MAK/991/M Museum: The Museum of the Home Army dedicated Gen. Emil Fieldorf "Nil" https://muzea.malopolska.pl/en/objects-list/591 Digitalisation: RDW MIC, Małopolska's Virtual Museums project Source: Objaverse 1.0 / Sketchfab
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.