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185 results for “flow cytometry”
Abundance, biovolume, and biomass of Synechococcus and eukaryote pico- and nano- plankton from continuous underway flow cytometry during NES-LTER Transect cruises, ongoing since 2018
These data represent the abundance, biovolume, and biomass of prokaryotic and eukaryotic picoplankton and nanoplankton sampled continuously underway during Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018. Samples were obtained with an Attune NxT Flow Cytometer sampling at approximately 2-min intervals from the underway science seawater. Cells were identified and enumerated from the flow cytometry data files based on their scattering, phycoerythrin (575 nm) and chlorophyll (680 nm) fluorescence signals.
Abundance, biovolume, and biomass of Synechococcus, eukaryote pico- and nano- phytoplankton, and heterotrophic bacteria from flow cytometry for water column bottle samples on NES-LTER Transect cruises, ongoing since 2018
These data represent the abundance, biovolume, and biomass of prokaryotic phytoplankton, eukaryotic pico- and nano- phytoplankton, and heterotrophic bacteria from discrete flow cytometry samples collected during the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018. Samples were collected and preserved from the water column at multiple depths using Niskin bottles on a CTD rosette system along the NES-LTER transect, and analyzed post cruise. Cells were identified and enumerated from the flow cytometry data files based on their scattering, SYBR (525 nm), phycoerythrin (575 nm) and chlorophyll (680 nm) fluorescence signals. Gating was completed manually in the Attune NXT software interface.
Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes
<p>Type 1 diabetes is a chronic autoimmune disease resulting in an immune-mediated loss of pancreatic β-cells; however, an unbiased and reproducible profiling of type 1 diabetes-specific circulating immunome at disease onset has yet to be explored. In this study, fresh whole blood was collected from a pediatric cohort of 107 patients with new-onset type 1 diabetes, 85 relatives of patients with type 1 diabetes with 0-1 islet autoantibodies, 58 patients with celiac disease or autoimmune thyroiditis and 76 healthy controls. Up to 6 mL of blood was collected from each subject into a VACUETTE® TUBE 6 ml ACD-B (Greiner). Fresh whole blood underwent red blood cell lysis, was washed and stained with specific monoclonal antibodies. Fresh whole blood samples were stained with five panels of antibodies labelled as T cells, T&NK cells, B cells, Tregs and DCs/monos encompassing main subsets of T cells, NK cells, B cells, Tregs, DCs and monocytes detected using 26 surface markers and the intracellular marker forkhead box P3 (FoxP3); for the Treg panel, intracellular staining was performed after fixation and permeabilization. Cells were acquired on a BD FACSCanto-II flow cytometer equipped with FACSDiva software (Becton Dickinson, Franklin Lakes, NJ). </p>
Flow cytometry of mesenteric lymph nodes, small and large intestinal lamina propria, and spinal cord cells from fibre-rich and fiber-free diet-fed gnotobiotic mice at baseline and after experimental autoimmune encephalomyelitis (EAE) induction
<p>We perform profiling of different immune cell populations in the small (SILP) and large intestine lamina propria (CLP), mesenteric lymph nodes (MLN) and spinal cords (SC). We are specifically interested to evaluate the impact of dietary fiber deprivation followed by mucus erosion on the immune cell profiles of T helper cells (Th cells, T cell population) of gnotobiotic mice fed a fiber-rich (FR) or fiber-free (FF) diet. This dataset aims to assess the impact of microbiome and diet on disease course in a mouse model of multiple sclerosis (experimental autoimmune encephalomyelitis, EAE) via T cell populations. Mice are either germ-free or colonized by intragastric gavage with a defined variation of a 14-member synthetic human gut microbiome (doi: 10.1016/j.cell.2016.10.043 and 10.1016/j.xpro.2021.100607): SM01 (Akkermansia muciniphila monocolonisation), SM03 (Bacteroides caccae, Bacteroides thetaiotaomicron, Barnesiella intestinihominis), SM04 (B. caccae, B. thetaiotaomicron, B. intestinihominis, A. muciniphila), SM12 (full community except mucin-specialists B. intestinihominis and A. muciniphila), SM13 (full community except mucin specialist A. muciniphila), or SM14 (full community: Roseburia intestinalis, Faecalibacterium prausnitzii, Marvinbryantia formatexigens, Collinsella aerofaciens, Desulfovibrio piger, B. caccae, B. thetaiotaomicron, Bacteroides ovatus, Bacteroides uniformis, B. intestinihominis, Eubacterium rectale, Clostridium symbiosum, Escherichia coli, and A. muciniphila). At age 5 to 8 weeks, mice were colonized with SM combinations while fed an FR diet. Mice were either maintained on an FR diet or switched to an FF diet at 5 days after initial colonization, until the end of experiment. Baseline samples were collected 20 days following the diet switch. Otherwise, EAE induction was performed 15 days after the diet switch and samples were collected 30 days after the induction.</p>
Ultrasensitive detection of cancer-associated nucleic acids and mutations by primer exchange reaction-based signal amplification and flow cytometry
<p>This dataset contains the raw data that were used for the publication entitled, "Ultrasensitive detection of cancer-associated nucleic acids and mutations by primer exchange reaction-based signal amplificaiton and flow cytometry" published in Biosensors and Bioelectronics on 5 October 2024.</p>
Dataset and Code for Manuscript "Multi-angle pulse shape detection of scattered light in flow cytometry for label-free cell cycle classification"
<p>Dataset of measurements for cell cycle analysis with description:</p> <ul> <li>ReadMe file with explanations on the data set and analysis</li> <li>exemplary Matlab script file for analysis</li> <li>binary data files conatining the pulse shapes in all channels</li> <li>FCS data files containing common flow cytometry parameters in each channel</li> </ul> <p>Data on unsorted HEK cells, HEK cells sorted for cell cycle phases, and unsorted Jurkat cell are included.</p>
Picophytoplankton and bacteria abundances analyzed with flow cytometry (FCM) from CCE-CalCOFI Augmented cruises in the California Current System, 2004 - 2023 (ongoing).
Picophytoplankton populations and non-pigmented prokaryotes are sampled within the California Current Ecosystem (CCE) for abundances from 3 to 8 depths at CalCOFI stations. Seawater is collected from Niskin bottles and cells are fixed in the field aboard the survey cruises (since 2004, ongoing) with paraformaldehyde, and stained with a DNA-specific dye back in the laboratory. The cells are enumerated by an Altra flow cytometer (with a syringe pump for volumetric sample delivery) simultaniously with argon ion lasers, to distinguish three major populations of photoautotrophs (Prochlorococcus, Synechococcus, and pico-eukaryotes) and the assemblage of heterotrophic prokaryotes collectively referred to as H-Bact.
Picophytoplankton and bacteria total carbon estimates from cell counts analyzed with flow cytometry (FCM) from CCE-CalCOFI Augmented cruises in the California Current System, 2004 - 2023(ongoing).
Picophytoplankton populations and non-pigmented prokaryotes are sampled within the California Current Ecosystem (CCE) for abundances from 3 to 8 depths at CalCOFI stations. Seawater is collected from Niskin bottles and cells are fixed in the field aboard the survey cruises (since 2004, ongoing) with paraformaldehyde, and stained with a DNA-specific dye back in the laboratory. The cells are enumerated by an Altra flow cytometer (with a syringe pump for volumetric sample delivery) simultaniously with argon ion lasers, to distinguish three major populations of photoautotrophs (Prochlorococcus, Synechococcus, and pico-eukaryotes) and the assemblage of heterotrophic prokaryotes collectively referred to as H-Bact. FCM abundance estimates for each are converted to carbon biomass equivalents using mixed-layer estimates.
Discrete flow cytometry of underway samples from the Gradients 2019 cruise using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected underway during the Gradients 2019 (Gradients 3/KM1906) oceanographic research cruise in the Northeast Pacific Ocean. The analysis includes cell abundance, forward light scatter, and pigment fluorescence of individual cells, including picoeukaryotes and the cyanobacteria Prochlorococcus and Synechococcus. Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton</p>
Discrete flow cytometry from the Gradients 2019 cruise using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations and heterotrophic bacteria from discrete flow cytometry data collected during the Gradients 2019 (Gradients 3/KM1906) oceanographic research cruise in the Northeast Pacific Ocean. The analysis includes cell abundance, forward light scatter, and pigment fluorescence of individual cells, including bacteria, picoeukaryotes, and the cyanobacteria Prochlorococcus and Synechococcus. Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton</p>
Flow cytometry data from human iPSC-derived macrophages
<p>Human induced pluripotent cells (iPSCs) were obtained from the HipSci project (http://www.hipsci.org) and differentiated into macrophages using an established protocol (van Wilgenburg, 2013). The genotype_id column of the flow_sample_metadata.txt file contains the canonical HipSci iPSC line name from which the macrophages were differentiated.</p> <p><strong>Data acquisition</strong></p> <p>We used flow cytometry to measure the cell surface expression of three canonical macrophage markers: CD14, CD16 (FCGR3A/FCGR3B) and CD206 (MRC1). Macrophages were cultured in 10 cm tissue-culture treated plates and detached from the plates by incubation in 6 mg/ml lidocaine-PBS solution (Sigma L5647) for 30 minutes followed by gentle scraping. From each cell line we harvested between 300,000-500,000 cells. Detached cells were washed in media, centrifuged at 1200 rpm for 5 minutes and resuspended in flow cytometry buffer (2% BSA, 0.001% EDTA in D-PBS) and split into two wells of a 96-well plate. Nonspecific antibody binding sites were blocked by incubating cells with Human TruStain FcX (Biolegend) for 45 minutes and washing with flow cytometry buffer. Half of the cells were stained for 1 hour with the PE-isotype control (BD 555749) antibody. The other half of the cells were co-stained for 1 hour with following three antibodies: CD14-Pacific Blue (BD 558121), CD16-PE (BD 555407), CD206-APC (BD 550889). After staining, the cells were washed three times. Resuspended cells were filtered through cell-strainer cap tubes (BD 352235) and measured on the BD LSRFortessa Cell Analyzer.</p>
Discrete Flow Cytometry of Underway Samples from TN427 Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected underway during the University of Washington School of Oceanography 2024 undergraduate senior thesis research cruise (TN427) from American Samoa. The data consists of cell abundance, cell size (equivalent spherical diameter), carbon quota, and carbon biomass for picophytoplankton populations, namely the cyanobacteria Prochlorococcus and Synechococcus, and small eukaryotic phytoplankton (<5 μm ESD). Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: [https://github.com/fribalet/FCSplankton](https://github.com/fribalet/FCSplankton)</p>
SeaFlow data v1: High-resolution abundance, size and biomass of small phytoplankton measured by flow-cytometry
<p>SeaFlow is an underway flow cytometer designed to continuously monitor the optical properties of the smallest phytoplankton from a ship's flow-through seawater system. It collects high-resolution data, generating the equivalent of 1 sample every 3 minutes or every 1 km (for a ship moving at 10 knots).</p> <p>The dataset provides measurements of cell abundance, cell size (equivalent spherical diameter) and carbon biomass for small phytoplankton populations: the cyanobacteria Prochlorococcus, Synechococcus, Crocosphaera, and small eukaryotic phytoplankton (<5 μm ESD). Data processing followed the methods outlined in <a href="https://doi.org/10.1038/s41597-019-0292-2">Ribalet et al. (2019)</a>. For more information, visit the <a href="https://seaflow.netlify.app/">SeaFlow website</a>.</p> <p><strong>New in version 1.6 </strong>The updated dataset includes flow cytometric measurements from 89 cruises, spanning nearly 14,000 hours of observations across 130,000 km of the surface oceans.</p>
Discrete Flow Cytometry of Underway Samples from Gradients 4 (2021) Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected underway during the Gradients 2021 (Gradients 4/TN397) oceanographic research cruise in the equatorial Pacific Ocean. The analysis includes cell abundance, forward light scatter, and pigment fluorescence of individual cells, including picoeukaryotes and the cyanobacteria Prochlorococcus and Synechococcus. The analysis also includes estimates of cell size, carbon content, and biomass using forward light scatter values and Mie Theory. Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton</p>
Codes for "High-throughput parallel optofluidic 3D-imaging flow cytometry"
<p>Codes used in Ugawa & Ota. "High-throughput parallel optofluidic 3D-imaging flow cytometry". Small size data is also included.</p>
Discrete Flow Cytometry of Underway Samples from TN398 Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of picophytoplankton populations from discrete flow cytometry data collected underway during the University of Washington School of Oceanography undergraduate senior thesis cruise (TN398) during December 2021 from Honolulu to San Diego, crossing through the Great Pacific Garbage Patch. The data includes cell abundance, cell size (equivalent spherical diameter), carbon quota, and carbon biomass for picophytoplankton populations, namely the cyanobacteria Prochlorococcus, Synechococcus, and and small eukaryotic phytoplankton (<5 μm ESD). Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton</p>
Discrete Flow Cytometry of Depth Profile Samples from the Gradients 5 (2023) Cruise Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected during the Gradients 2023 (Gradients 5/TN412) oceanographic research cruise in the equatorial Pacific Ocean. The data consists of cell abundance, cell size (equivalent spherical diameter), carbon quota, and carbon biomass for heterotrophic bacteria, picophytoplankton populations, namely the cyanobacteria Prochlorococcus and Synechococcus, and small eukaryotic phytoplankton (<5 μm ESD). Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton</p>
Discrete Flow Cytometry of Underway Samples From TN428 Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected underway during a transit cruise (TN428) from American Samoa to Australia. The data consists of cell abundance, cell size (equivalent spherical diameter), carbon quota, and carbon biomass for picophytoplankton populations, namely the cyanobacteria Prochlorococcus, Synechococcus and Crocosphaera, and small eukaryotic phytoplankton (<5 μm ESD). Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: [https://github.com/fribalet/FCSplankton](https://github.com/fribalet/FCSplankton)</p>
Discrete Flow Cytometry of Depth Profile Samples from TN413 (2023) Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected underway during the University of Washington School of Oceanography 2023 undergraduate senior thesis cruise (TN413) oceanographic research cruise from Hawaii to Fiji. The data consists of cell abundance, cell size (equivalent spherical diameter), carbon quota, and carbon biomass for heterotrophic bacteria, picophytoplankton populations, namely the cyanobacteria Prochlorococcus and Synechococcus, and small eukaryotic phytoplankton (<5 μm ESD). Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton</p>
uncropped western blots for analysis of RPN13 ubiquitylation and NRF1 activation by protein aggregates, as well as source data for qPCR plots and flow cytometry gating and FCS files for agDD-GFP in HeLa or HEK cells
<p>This entry contains uncropped blots for Fig 4D and Fig S4C, Fig. 5B, Fig S5 and Fig S6, and the raw FCS files for Flow Cytometry data in doi.org/10.1101/2024.08.30.610524.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.