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369 results for “droplet”
Comparative Analysis of Droplet- vs. Microwell-based Whole Transcriptome Single-Cell Sequencing Technologies in Complex Human Tissues
<p>In the past decade, high-dimensional single-cell omics tools have enabled scientists to study the tumor microenvironment (TME) in unprecedented detail. However, recent investigations suggest that each technique has its unique strengths but also technology-inherent limitations. Here we directly compared two commercially available high-throughput single-cell RNA sequencing (scRNA-seq) technologies - droplet-based 10X Chromium <em>vs.</em> microwell-based BD Rhapsody - using paired samples from patients with localized prostate cancer (PCa) undergoing a radical prostatectomy.</p> <p>Although high technical consistency was observed in unraveling the whole transcriptome, the relative abundance of detectable cell populations differed. This could in part be ascribed to differences in the performance to recover cells with low-mRNA content. Hence, immune cells such as neutrophils are underrepresented in data generated with the widely used droplet-based scRNA-seq protocol, highlighting the importance of considering platform limitations in low mRNA content cell recovery. In contrast, droplet-based scRNA-seq demonstrated superiority in terms of recovering cells of epithelial origin. Moreover, we discovered platform-dependent variabilities in mRNA quantification and cell-type marker annotation, affecting the composition of identified tissue profiles and the exploratory value of the generated datasets. Overall, our study emphasizes the importance of carefully selecting the appropriate scRNA-seq platform to improve cell type representation and obtain a more comprehensive and accurate understanding of the TME.</p>
Data for: Multi-campaign ship and aircraft observations of marine cloud condensation nuclei, and droplet concentrations
<p class="MsoNormal"><span>In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns, ACTIVATE, NAAMES, CAMP2EX, ORACLES, SOCRATES, MARCUS, and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements are collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, representing a range of clean to polluted conditions in various climate regimes. With the large range of environmental conditions sampled, this collection of data is ideal for testing satellite remote detection methods of CDNC and CCN in marine environment. Remote measurement methods are key to expanding the available data, in these difficult to reach regions of the Earth, and improving our understanding of aerosol-cloud interactions. Additional particle composition and continental tracers are included to identify potential contributing CCN source. Several of these campaigns, include both High Spectral Resolution Lidar and polarimetric imaging measurements that will be the basis for the next generation of space-based remote sensors and, thus, can be utilized as satellite surrogates.</span></p>
Supplement to the "Response to the Referee" of the article "Simulation of marine stratocumulus using the super-droplet method: Numerical convergence and comparison to a double-moment bulk scheme"
<p>This is the supplement to the "Response to the Referee" of the article "Simulation of marine stratocumulus using the super-droplet method: Numerical convergence and comparison to a double-moment bulk scheme".</p> <p><a href="https://zenodo.org/api/files/87a1c801-d2f8-4c0c-b408-db56481cf97d/Movie%201_w_theta_v_t.mp4">Movie 1_w_theta_v_t.mp4</a>: Time evolution of vertical profiles of buoyancy production and its decomposition.</p> <p><a href="https://zenodo.org/api/files/6eabdd4d-61fd-4f7a-8656-0c9d1fb7ce6f/Movie%202_scatter_w_theta_v_t.mp4">Movie 2_scatter_w_theta_v_t.mp4</a>: Time evolution of scatter plots of w vs theta_v.</p> <p><a href="https://zenodo.org/api/files/6eabdd4d-61fd-4f7a-8656-0c9d1fb7ce6f/Movie%203_boy_incloud_real_z_t.mp4">Movie 3_boy_incloud_real_z_t.mp4</a>: Time evolution of buoyancy production and cloud fraction, and time series of cloud cover.</p> <p><a href="https://zenodo.org/api/files/2f5a17d9-6cb1-4769-88cd-65fd8efd0225/qr_cross.mp4">qr_cross.mp4</a>: Time evolution of cross section of rain water mixing ratio (q<sub>r</sub>) of SDM and SN14 simulation.</p>
Data for: Multi-campaign ship and aircraft observations of marine cloud condensation nuclei, and droplet concentrations
Open the record for dataset details and reuse information.
Data from: Correlated evolution between orb weaver glue droplets and supporting fibers maintains their distinct biomechanical roles in adhesion
Open the record for dataset details and reuse information.
Generating an expression matrix for droplet single-cell RNA-seq (dscRNA-seq) data
<p>This tutorial is adapted from the 'Generating an expression matrix' training session at the EBI (https://www.ebi.ac.uk/training/events/2019/single-cell-rna-seq-analysis-questions-clusters).</p>
The airborne lifetime of small speech droplets and their potential importance to SARS-CoV-2 transmission
<p> Movies that show the experimental setup and the full 85-minute observation of speech droplet nuclei.</p> <p> </p> <p>The full movie recording of highly sensitive laser light scattering observations that indicate loud-speaking generates, in addition to hundreds of regular droplets, also many thousands of micro-droplets per second. This movie clip shows the decay of airborne particles.</p> <p> </p> <p>Note: some parts of the audio of the clips were muted for privacy.</p>
Supplement to the article "Predicting the morphology of ice particles in deep convection using the super-droplet method" (Shima et al., 2020, GMD)
<p>This is a supplement to the article "Predicting the morphology of ice particles in deep convection using the super-droplet method" authored by Shin-ichiro Shima, Yousuke Sato, Akihiro Hashimoto, and Ryohei Misumi, published in Geosci. Model Dev., 2020.</p> <p>Typical realization of CTRL, simulated by SCALE-SDM 0.2.5-2.2.0</p> <ul> <li>Movie01.QHYD_TYP-CTRL_2.2.0.gif: Spatial structure of the cumulonimbus</li> <li>Movie02.M-D_TYP-CTRL_2.2.0.gif: Mass-dimension relationship of the ice particles</li> <li>Movie03.phi-D_TYP-CTRL_2.2.0.gif : Aspect ratio–dimension relationship of the ice particles</li> <li>Movie04.rho-D_TYP-CTRL_2.2.0.gif : Apparent density–dimension relationship of the ice particles</li> <li>Movie05.V-D_TYP-CTRL_2.2.0.gif : Velocity-dimension relationship of the ice particles</li> </ul> <p>One realization of DX/2, simulated by SCALE-SDM 0.2.5-2.2.0</p> <ul> <li>Movie06.QHYD_DXx0.5_2.2.0.gif: Spatial structure of the cumulonimbus</li> </ul> <p>The same setup as Moves 1-5 (typical realization of CTRL) is used, but simulated by SCALE-SDM 0.2.5-2.2.1</p> <ul> <li>Movie07.QHYD_TYP-CTRL.2.2.1.gif: Spatial structure of the cumulonimbus</li> <li>Movie08.M-D_TYP-CTRL_2.2.1.gif: Mass-dimension relationship of the ice particles</li> <li>Movie09.phi-D_TYP-CTRL_2.2.1.gif: Aspect ratio–dimension relationship of the ice particles</li> <li>Movie10.rho-D_TYP-CTRL_2.2.1.gif: Apparent density–dimension relationship of the ice particles</li> <li>Movie11.V-D_TYP-CTRL_2.2.1.gif: Velocity-dimension relationship of the ice particles</li> </ul> <p>The same setup as Moves 1-5 (typical realization of CTRL) is used, but simulated by SCALE-SDM 0.2.5-2.2.2</p> <ul> <li>Movie12.QHYD_TYP-CTRL.2.2.2.gif: Spatial structure of the cumulonimbus</li> <li>Movie13.M-D_TYP-CTRL_2.2.2.gif: Mass-dimension relationship of the ice particles</li> <li>Movie14.phi-D_TYP-CTRL_2.2.2.gif: Aspect ratio–dimension relationship of the ice particles</li> <li>Movie15.rho-D_TYP-CTRL_2.2.2.gif: Apparent density–dimension relationship of the ice particles</li> <li>Movie16.V-D_TYP-CTRL_2.2.2.gif: Velocity-dimension relationship of the ice particles</li> </ul>
SARS-CoV-2 transmission via speech-generated respiratory droplets
<p>The physics of generating acoustic waves involves the high-speed passage of air pressurized by the lungs through narrow passages, past the mucosal epithelial layers of the vibrating vocal folds. Sounds are further modulated by the passage of this air through narrow passages between the tongue, lips, and teeth, dislodging oral fluid at all of these locations. Generation of droplets is inevitably linked to the physics of speech generation, and not limited to one person as is highlighted in a short video recording</p>
Microfluidic droplet application for bacterial surveillance in fresh-cut produce wash waters
<p>Foodborne contamination and associated illness in the United States is responsible for an estimated 48 million cases per year. Increased food demand, global commerce of perishable foods, and the growing threat of antibiotic resistance are driving factors elevating concern for food safety. Foodborne illness is often associated with fresh-cut, ready-to-eat produce commodities due to the perishable nature of the product and relatively minimal processing from farm to the consumer. The research presented here optimizes and evaluates the utility of microfluidic droplets, also termed ultraminiaturized bioreactors, for rapid detection of viable Salmonella enterica ser. Typhimurium in a shredded lettuce wash water acquired from a major Mid-Atlantic produce processing facility (denoted as Producer) in the U.S. Using a fluorescentlylabeled anti- S. Typhimurium antibody and relative fluorescence intensities, paired with in-droplet incubation, S. Typhimurium was detected and identified with 100% specificity in less than 5 h. In initial optimization experiments using S. Typhimuriumspiked sterile water, the relative fluorescence intensity of S. Typhimurium was approximately two times that of the observed relative intensities of five non- S. Typhimurium negative controls at 4-h incubation in droplets containing Rappaport-Vasiliadis (RV) broth at 37 ° C: relative fluorescence intensity for S. Typhimurium = 2.36 (95% CI: 2.15-2.58), Enterobacter aerogens 1.12 (95% CI: 1.09-1.16), Escherichia coli 700609 = 1.13 (95% CI: 1.09-1.17), E. coli 13706 1.13 (95% CI: 1.07-1.19), E. coli 700891 1.05 (95% CI: 1.03-1.07) and Citrobacter freundii 1.04 (95% CI: 1.03-1.05). S. Typhimurium - and E. aerogens -spiked shredded lettuce wash waters acquired from the Producer were then incubated 4 h in-droplet at 37 ° C with RV broth. The observed relative fluorescence of S. Typhimurium was significantly higher than that of E. aerogens , 1.56 (95% CI: 1.42-1.71) and 1.10 (95% CI: 1.08-1.12), respectively. While further optimization focusing on compatible concentration methodologies for highly-dilute produce water samples is needed, this application of droplet microfluidics shows great promise in dramatically shortening the time necessary – from days to hours – to confirm viable bacterial contamination in ready-to-eat produce wash waters used throughout the domestic and international food industry.</p>
AutoCAD drawings of 2 pL droplet generator.
<p>AutoCAD drawings of 2 pL droplet generator.</p>
Sample video of 2pL droplet generation.
<p>Sample video of 2pL droplet generation. Can be opened using ImageJ.</p>
AutoCAD drawings of 10 x 2 pL droplet merging device.
<p>AutoCAD drawings of 10 x 2 pL droplet merging device. Must be made 20 um high.</p>
AutoCAD drawings of 20 x 20 um droplet picoinjection device.
<p>AutoCAD drawings of 20 x 20 um droplet picoinjection device. Must be made 20 um high.</p>
Sample video of 25 um diameter droplet sorting
<p>Sample video of 25 um diameter droplet sorting. </p>
Sample video of picoinjection into 20 um diameter droplets.
<p>Sample video of picoinjection into 20 um diameter droplets.</p>
Droplet characteristics as a function of experimental parameters in electrospray on deposition process
<p>The droplet characteristics of electrostatic atomization change with fluid properties and experimental parameters. Ring electrodes modulate the atomization properties through the electric field of the ring. Experimental equations for electrostatic atomization only exist for varying fluid properties in the 90s. In this experiment, the atomization mode and droplet characteristics were checked according to the experimental parameters, and the experimental parameters of the ring electrode, ring applied voltage, ring diameter, nozzle, and substrate distance were varied, and the droplet size equation was made using ethanol and distilled water.</p>
Supplement to the article "Simulation of marine stratocumulus using the super-droplet method: Numerical convergence and comparison to a double-moment bulk scheme"
<p>This is a supplement to the article "Simulation of marine stratocumulus using the super-droplet method: Numerical convergence and comparison to a double-moment bulk scheme".</p> <p>The time evolution of horizontal distribution of LWP:</p> <ul> <li>SDM_lwp_2d_sdm.mp4: from nine SDM runs with different grid resolutions.</li> <li>SN14_lwp_2d_sn14.mp4: from nine SN14 runs with different grid resolutions.</li> </ul> <p>The time evolution of vertical profiles:</p> <ul> <li>sdm_profile_t.mp4: from nine SDM runs with different grid resolutions.</li> <li>sn14_profile_t.mp4: from nine SN14 runs with different grid resolutions.</li> <li>sdm_incloud_t.mp4: vertical profiles in cloudy areas and cloud holes in SDM runs.</li> <li>sn14_incloud_t.mp4: vertical profiles in cloudy areas and cloud holes in SN14 runs.</li> <li>sdm_50x5_incloud_t.mp4: comparison between original SDM and SDM without sedimentation.</li> </ul>
Compressed raw videos for Directed droplet motion along thin fibers
<p>Compressed video of experiments to determine droplet velocities. The videos are at the same scale as the the videos in the supplemental material of the paper "Directed droplet motion along thin fibers". Specifically these videos follow the panels in SI Movie 1. Droplet positions, droplet spans and fiber angles are extracted from these videos. </p>
Data from "Toward vanishing droplet friction on repellent surfaces"
<p>Data, examples of raw experimental movies, and MATLAB codes from "Toward vanishing droplet friction on repellent surfaces", Backholm et al. PNAS (2024). Please see the README files for all details about the files. The datasets needed to plot Figs. 1C, 2C, 3C, 4F, 4G, 5A, 5D, and 5E of the article are published in the SI file of the PNAS paper.</p>
ScienceDex guides
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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.