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12,346 results for “derivatives”
Raw Data for the article: Extracellular Vesicle-Derived microRNAs of Human Wharton's Jelly Mesenchymal Stromal Cells May Activate Endogenous VEGF-A to Promote Angiogenesis
<p>Despite low levels of vascular endothelial growth factor (VEGF)-A, the secretome of human Wharton's jelly (WJ) mesenchymal stromal cells (MSCs) effectively promoted proangiogenic responses in vitro, which were impaired upon the depletion of small (~140 nm) extracellular vesicles (EVs). The isolated EVs shared the low VEGF-A profile of the secretome and expressed five microRNAs, which were upregulated compared to fetal dermal MSC-derived EVs. These upregulated microRNAs exclusively targeted the <em>VEGF-A</em> gene within 54 Gene Ontology (GO) biological processes, 18 of which are associated with angiogenesis. Moreover, 15 microRNAs of WJ-MSC-derived EVs were highly expressed (Ct value ≤ 26) and exclusively targeted the thrombospondin 1 (<em>THBS1</em>) gene within 75 GO biological processes, 30 of which are associated with the regulation of tissue repair. The relationship between predicted microRNA target genes and WJ-MSC-derived EVs was shown by treating human umbilical-vein endothelial cells (HUVECs) with appropriate doses of EVs. The exposure of HUVECs to EVs for 72 h significantly enhanced the release of VEGF-A and THBS1 protein expression compared to untreated control cells. Finally, WJ-MSC-derived EVs stimulated in vitro tube formation along with the migration and proliferation of HUVECs. Our findings can contribute to a better understanding of the molecular mechanisms underlying the proangiogenic responses induced by human umbilical cord-derived MSCs, suggesting a key regulatory role for microRNAs delivered by EVs.</p>
Dataset for "Oxidase-type C-H/C-H coupling using an isoquinoline-derived organic photocatalyst"
<p>We have uploaded the corresponding raw and processed data for each figure from main text and supporting information. We also uploaded the raw data of NMR and HR-MS for characterization of the organic products.</p>
Raw Data for the article: Human Amnion-Derived Mesenchymal Stromal Cells: A New Potential Treatment for Carbapenem-Resistant Enterobacterales in Decompensated Cirrhosis
<p><strong>Background: </strong>Spontaneous bacterial peritonitis (SBP) is a severe and often fatal infection in patients with decompensated cirrhosis and ascites. The only cure for SBP is antibiotic therapy, but the emerging problem of bacterial resistance requires novel therapeutic strategies. Human amniotic mesenchymal stromal cells (hA-MSCs) possess immunomodulatory and anti-inflammatory properties that can be harnessed as a therapy in such a context.</p> <p><strong>Methods: </strong>An in vitro applications of hA-MSCs in ascitic fluid (AF) of cirrhotic patients, subsequently infected with carbapenem-resistant Enterobacterales, was performed. We evaluated the effects of hA-MSCs on bacterial load, innate immunity factors, and macrophage phenotypic expression.</p> <p><strong>Results: </strong>hA-MSCs added to AF significantly reduce the proliferation of both bacterial strains at 24 h and diversely affect M1 and M2 polarization, C3a complement protein, and ficolin 3 concentrations during the course of infection, in a bacterial strain-dependent fashion.</p> <p><strong>Conclusion: </strong>This study shows the potential usefulness of hA-MSC in treating ascites infected with carbapenem-resistant bacteria and lays the foundation to further investigate antibacterial and anti-inflammatory roles of hA-MSC in in vivo models.</p>
Sea-Ice Floe Segmentation Products Derived from MEDEA Imagery for 1999 through 2014 in the Canada Basin
<p>This dataset contains sea-ice floe segmentation products derived from 78 Medea images from the United States Geological Survey (USGS) Global Fiducials Library (GFL) acquired in the Arctic's Canada Basin from 1999 to 2014. Sea-ice floe segmentation is the identification of individual sea ice floes in imagery for the purpose of retrieval of unique properties of those individual floes, such as their size or shape. </p> <p>The product was developed for and used in the analysis of the accompanying paper, <a title="Characterizing the sea-ice floe size distribution in the Canada Basin from high-resolution optical satellite imagery" href="https://doi.org/10.5194/tc-16-1563-2022" target="_blank" rel="noopener">Denton and Timmermans (2022)</a>. The product was created using an <a title="Sea-Ice Floe Segmentation" href="https://doi.org/10.5281/zenodo.6146144" target="_blank" rel="noopener">algorithm</a> written by Alexis Denton (Yale University) in tandem for the manuscript analysis. The script is also available at <a href="https://github.com/dentonaa/sea-ice-floe-segmentation">github.com/dentonaa/sea-ice-floe-segmentation</a>. </p> <p>This image product was developed to contribute a novel, multidecadal dataset of identified sea ice characteristics, namely floe size, to the Arctic science community. If you use this product in your work or research or for any other reason, credit the authors here and cite the code DOI issued by Zenodo. The DOI badge to the right points to the latest released version of the repository.</p> <p>The development of this product and the research presented in the manuscript was funded by the Office of Naval Research as a part of their Multi-University Research Initiative (MURI) Mathematics and Data Science for Physical Modeling and Prediction of Sea Ice. To learn more about the work of the Sea Ice MURI, please visit <a href="https://seaicemuri.org/" target="_blank" rel="noopener">https://seaicemuri.org/</a>.</p> <p>For further details about the dataset, please see <a title="Characterizing the sea-ice floe size distribution in the Canada Basin from high-resolution optical satellite imagery" href="https://doi.org/10.5194/tc-16-1563-2022" target="_blank" rel="noopener">Denton and Timmermans (2022)</a>.</p> <p><strong>A full description of the product files is as follows:</strong></p> <p>This dataset is comprised of the sea-ice floe segmentation products derived from 78 MEDEA images acquired at various locations in the Canada Basin from 1999 through 2014, and one ReadMe file.</p> <p>For each sea-ice floe segmented image, there are 3 files. Each of the 3 files starts with the naming convention, "sifloeseg_MEDEAImageName_segmentationParameters_", followed by a filename ending designated by the type of segmentation data stored, as described below.</p> <ul> <li>sifloeseg stands for sea-ice floe segmentation.</li> <li>MEDEAImageName is the original filename of the MEDEA image, usually a series of 3 or 4 strings delimited by "_" in which the first string is the site/project of acquisition, the second is the date (YYYYMMDD), and the third and fourth describe whether the image is a mosaic or a tile in a mosaic. <ul> <li>e.g., "beaufo_19990728_2" indicates a MEDEA image acquired in the Beaufort Sea on 28 July 1999 which is the 2nd tile of a larger mosaic. Please visit the USGS GFL for more details on the naming of MEDEA image files.</li> </ul> </li> <li>segmentationParameters describes the parameters used to segment the image and follows the format "bwt0##e##hs". <ul> <li>bwt stands for "black-white threshold" and is followed by the value of the classification threshold (0.##) between 0 and 1 used to classify the image.</li> <li>e stands for "erosions" and is followed by the number of erosions used to erode the image during the first heirarchical step.</li> <li>hs indicates that the erosion scheme used a half-step, or halving of the number of erosions between hierarchical iterations. <ul> <li>e.g., "sifloeseg_beaufo_19990728_2_bwt015e1hs_" indicates a segmentation of the above MEDEA image example which used a classification threshold of 0.15 and 1 erosion for the first hierarchical segmentation step.</li> </ul> </li> </ul> </li> </ul> <p>The 3 files for each segmented image are:</p> <ol> <li>A MATLAB file containing the areas (in square meters) of the segmented floes in an image. The file has the naming convention, "sifloeseg_MEDEAImageName_segmentationParameters_areas_sqm.mat", in which sqm stands for "square meters". <ul> <li>This file contains the following variables: <ul> <li>L_areas_nobc_sqm, which is a vector containing floe areas retrieved from the original segmentation (no border-clearing; contains floe areas wholly and partially in the image), where L stands for "Label".</li> <li>L_areas_bc_sqm, which contains the floe areas retrieved from the border-cleared segmentation (contains only floe areas wholly in the image). </li> </ul> </li> </ul> </li> <li>A MATLAB file containing the image segmentation, which is a labeled numeric array in which each positive integer numeric label corresponds to a unique sea-ice floe. The file has the naming convention, "sifloeseg_MEDEAImageName_segmentationParameters_labeled.mat". <ul> <li>This file contains the following variables: <ul> <li>rows: the number of image rows (y-direction array size, <em>double</em>)</li> <li>cols: the number of image columns (x-direction array size, <em>double</em>)</li> <li>bwt: the classification (black-white) threshold used to classify the image during segmentation (fractional value between 0 and 1, <em>double</em>)</li> <li>numErosions: a vector containing the number of erosions used to erode the image during segmentation at each hierarchical step, in which the first value indicates the number of erosions used during the first step, and the last indicates the number of erosions used during the last step, which is always 0 (<em>1 x n double</em>, in which n is the number of hierarchical steps used)</li> <li>numfmax: the total number of wholly and partially segmented floes in the original segmentation (before border clearing, <em>double</em>)</li> <li>L: the original image segmentation containing wholly and partially segmented floes (prior to border clearing), which is a numerical label array, in which positive integer values represent unique floes and values of 0 represent ocean pixels (<em>rows x cols, double</em>). </li> <li>Lbc: the border-cleared image segmentation containing only wholly segmented floes (after border clearing), which is a numerical label array in the same vein as L (<em>rows x cols, double</em>)</li> </ul> </li> </ul> </li> <li>A PNG representation of the segmented image in RGB (red-green-blue) color, in which non-unique colors represent different floes. This file is for visualization and display purposes. The same image and its border-cleared counterpart can be produced with the following lines of code in MATLAB:</li> </ol> <pre><code>load(sifloseg_MEDEAImageName_segmentationParameters_labeled.mat); Lrgb = label2rgb(L,'jet','k','shuffle'); imshow(Lrgb) Lbcrgb = label2rgb(Lbc,'jet','k','shuffle'); imshow(Lbcrgb)</code></pre> <p>For more information on any of the above terms, please see <a title="Characterizing the sea-ice floe size distribution in the Canada Basin from high-resolution optical satellite imagery" href="https://doi.org/10.5194/tc-16-1563-2022" target="_blank" rel="noopener">Denton and Timmermans (2022)</a>.</p> <p> </p>
Benchmark Dataset (2D/3D) of an Industrial Rotary Kiln Combustion Chamber with Refuse-Derived Fuel Particles from a Light-Field-Camera
<p>Benchmark dataset for the detection of fuel particles (refuse-derived fuels - RDF) in 2D and 3D image data in a rotary kiln combustion chamber.</p> <p>Organization:<br> 01_Images: 50 Images (2D)<br> 02_Labels: Labeled ground truth image with rotary kiln, burner flame, burning particle in air, non-burning particle in air and particle on wall.<br> 03_Particle List: Lists of the coordinates of the center of gravity of particles in image coordinates.<br> 04_Point Cloud: 3D point cloud for the 50 images.<br> 05_Matlab: Code and visualization examples.<br> 06_All_Data: Images and 3D point cloud for 2010 images of a sequence containing the images with ground truth (see TXT file).</p>
Somatic mutations alter the differentiation outcomes of iPSC-derived neurons (Metadata and AnnData/H5AD files)
<p><strong>Data S1:</strong> Metadata information for the 828,937 processed cells from the DN dataset: donor identity, cell type annotation, pool identifier, 10x sample, time point and replicate information. Related to STAR Methods: Reanalysis of pooled single-cell data (DA).</p> <p><strong>Data S2-S4:</strong> AnnData/H5AD files containing the single-cell gene expression matrices and the metadata for day 11, day 30 and day 52, respectively. The gene expression is normalised and log-transformed, but not scaled. md5 files are also included. Related to STAR Methods: DE analysis between failed and successful lines.</p> <p>#File names:</p> <p><strong>File-Data S1: </strong>suppData1.RDS</p> <p><strong>File-Data S2: </strong>allpools.scanpy.D11.wMetaClustUmapGraph.exprLogNormNotScaled_notKO.h5ad</p> <p><strong>File-Data S3: </strong>allpools.scanpy.D30.wMetaClustUmapGraph.exprLogNormNotScaled_notKO.h5ad</p> <p><strong>File-Data S4: </strong>allpools.scanpy.D52.wMetaClustUmapGraph.exprLogNormNotScaled_notKO.h5ad</p>
Investigation the cytotoxicity of newly synthesized quinazo-line–sulfonamide derivatives in human leukemia cell lines and hematopoietic activity in zebrafish embryos.
<p>These videos contain the time lapse imaging of the wild type zebrafish embryos showing the circulation, control (mock 0.5% V/V DMSO) and compound 4a treated embryos at 72 hours post fertilization. The compound 4a specifically blocked the formation of blood and no circulation was seen in these embryos. </p>
Selection strategies to introgress water deficit tolerance derived from Solanum galapagense accession LA1141 into cultivated tomato (datasets)
<p>This dataset includes best linear unbiased predictors (BLUPs) used for composite interval mapping in the LA1141 × OH8245 BC<sub>2</sub>S<sub>3</sub> families (tab - BC2S3_BLUP_data_for_CIM), greenhouse data corresponding to the BC<sub>2</sub>S<sub>5</sub> advanced lines (tab - BC2S5_GH_trial), and field performance data corresponding to the BC<sub>2</sub>S<sub>5</sub> advanced lines (tab - BC2S5_Field_Trial).</p>
Data from: How well do embryo development rate models derived from laboratory data predict embryo development in sea turtle nests?
<p>Development rate of ectothermic animals varies with temperature. Here we use data derived from laboratory constant temperature incubation experiments to formulate development rate models that can be used to model embryonic development rate in sea turtle nests. We then use a novel method for detecting the time of hatching to measure the in situ incubation period of sea turtle clutches to test the accuracy of our models in predicting the incubation period from nest temperature traces. We found that all our models overestimated the incubation period. We hypothesize three possible explanations which are not mutually exclusive for the mismatch between our modeling and empirically measured in situ incubation period: (1) a difference in the way the incubation period is calculated in laboratory data and in our field nests, (2) inaccuracies in the assumptions made by our models at high incubation temperatures where there is no empirical laboratory data, and (3) a tendency for development rate in laboratory experiments to be progressively slower as temperature decreases compared with in situ incubation.</p>
Raw data of multiplex assay on cyto-/chemokine secretion from human monocyte-derived dendritic cells
<p>Raw data of <em>in vitro</em> investigations on immune activation by bare and surface-functionalized SiO<sub>2</sub> NP-allergen conjugates using human monocyte-derived dendritic cells as model antigen-presenting cells. Data repository for Punz B. et al., 2022.</p>
water level change rate over 2003-2021 derived from ICESat and ICESat-2 data
<p>This dataset is the water level change rate information over 2003-2021 derived from ICESat and ICESat-2 data for 22008 lakes and reservoirs across the globe.</p>
Dataset: Glass-forming ability and structural features of melt-quenched and gel-derived SiO2-TiO2 glasses
<p>Research data for Manuscript submission with title</p> <p><strong>Glass-forming ability and structural features of melt-quenched and gel-derived SiO<sub>2</sub>-TiO<sub>2</sub> glasses</strong></p> <p><strong>Abstract</strong></p> <p>SiO<sub>2</sub>-TiO<sub>2 </sub>glasses produced by melt-quenching or sol-gel spray-drying were compared to highlight their structural differences. Glass formation was possible by melt-quenching up to 10 mol% TiO<sub>2</sub>, while higher contents led to devitrification. Raman spectroscopy and solid-state <sup>17</sup>O and <sup>29</sup>Si MAS NMR confirmed the clear emergence of Ti-O-Si bonds and a tetrahedral oxygen coordination of Ti<sup>4+</sup> leading to full network connectivity, as also substantiated by the synthesis of TiO<sub>2</sub>-doped cristobalite. In gel-derived glasses, water content induced partial network depolymerization, thereby enhancing the solubility of TiO<sub>2</sub> in the hydrous silicate matrix. However, full dehydration during heating proved challenging due to the competing devitrification tendency: the glass-forming range in the anhydrous binary SiO<sub>2</sub>-TiO<sub>2</sub> system does not therefore appear to be significantly enlarged by the sol-gel synthesis route.</p>
Nighttime Atmospheric Scattering Phase Function Derived from the Scattered Light of a Laser Beam - supplementary material
<p>The ZIP-package contains:</p> <ul> <li>Canon RAW (CR2) and DCRAW pre-processed (PGM) pictures of the sky with the green laser switched on/off, elevations 10 and 20 degrees</li> <li>Calibration data for Canon EOS 6D Mark II + Fish-Eye lens EF8-16mm at 8mm (wignetting, geometrical distortion)</li> <li>C/C++ software 'green_laser.cpp' for extracting the data from the pictures (incl. Windows-executable). Version 2 has improved median filtering and built-in correction if the laser beam does not go exactly overhead. </li> <li>Detailed description of the software and the method of taking and processing the RAW pictures in PDF format</li> <li>Extracted data in EXCEL workbooks</li> </ul>
Large dataset of soil organic carbon and topographic derivatives
<p><strong>Abstract</strong>: The dataset compiles 840 georeferenced SOC measurements over a 26-ha agricultural field located in southern Ontario, Canada with a sampling density of ~32 points per ha. As SOC is influenced by site topography (i.e., slope and landscape position), each point of the database was associated with a wide range of topographic derivatives. The columns include sample ID, SOC measurement, latitude, Longitude, NDVI values, as well as a set of 54 topographic derivatives (i.e., primary and secondary - see metadat.pdf attached file) with a spatial resolution of a 5 m. </p>
Adipose-derived stromal cells preserve pancreatic islet function in a transplantable 3D bioprinted scaffold
<p><span>Intra-portal islet transplantation is the method of choice for treatment of insulin dependent type 1 diabetes, but its outcome is hindered by limited islet survival due to the immunological and metabolic stress post transplantation. Adipose-derived stromal cells (ASCs) promise to improve significantly the islet micro-environment but an efficient long-term delivery method has not been achieved. We therefore explore the potential of generating ASC enriched islet transplant structure by 3D bioprinting. Here, we fabricate a double-layered 3D bioprinted scaffold for islets and ASCs by using alginate-nanofibrillated cellulose bioink. We demonstrate the diffusion properties of the scaffold and report that human ASCs increase the islet viability, preserve the endocrine function, and reduce pro-inflammatory cytokines secretion <em>in vitro</em>. Intraperitoneal implantation of the ASCs and islets in 3D bioprinted scaffold improve the long-term function of islets in diabetic mice. Our data reveals an important role for ASCs on the islet micro-environment. We suggest a novel cell therapy approach of ASCs combined with islets in a 3D structure with a potential for clinical beta cell replacement therapies at extrahepatic sites. </span></p>
Satellite-derived water quality data for Lake Harsha (USA) 2015-2019
This dataset contains satellite-derived water quality (WQ) data of Lake Harsha (USA) for the years 2015-2019. Available parameters are: Total Absorption (ABS), Chlorophyll-a (CHL), Harmful Algae Bloom Indicator (HAB), True-color image (RGB), Secchi Disc Depth (SDD), Sea Surface Temperature (SST), Total Suspended Matter (TSM) and Turbidity (TUR). WQ parameters have been calculated using EOMAPs physics-based MIP from Sentinel-2 and Landsat 8. The data are available as GeoTiff files in web-mercator projection (EPSG: 3857). Further information can be found in the readme files. Contains Copernicus data. Credits: ESA (2022). Landsat data courtesy of the United States Geological Survey (2022).
Satellite-derived water quality data for Lake Hume (Australia) 2015-2019
<p>This dataset contains satellite-derived water quality (WQ) data of Lake Hume (Australia) for the years 2015-2019. Available parameters are: Total Absorption (ABS), Chlorophyll-a (CHL), Harmful Algae Bloom Indicator (HAB), True-color image (RGB), Secchi Disc Depth (SDD), Sea Surface Temperature (SST), Total Suspended Matter (TSM) and Turbidity (TUR). WQ parameters have been calculated using EOMAPs physics-based MIP from Sentinel-2 and Landsat 8. The data are available as GeoTiff files in web-mercator projection (EPSG: 3857). Further information can be found in the readme files. Contains Copernicus data. Credits: ESA (2022). Landsat data courtesy of the United States Geological Survey (2022).</p>
Satellite-derived water quality data for Western Water Treatment Plant (Melbourne, Australia) 2015-2019
This dataset contains satellite-derived water quality (WQ) data of Western Water Treatment Plant (Melbourne, Australia) for the years 2015-2019. Available parameters are: Total Absorption (ABS), Chlorophyll-a (CHL), Harmful Algae Bloom Indicator (HAB), True-color image (RGB), Secchi Disc Depth (SDD), Total Suspended Matter (TSM) and Turbidity (TUR). WQ parameters have been calculated using EOMAPs physics-based MIP from Sentinel-2. The data are available as GeoTiff files in web-mercator projection (EPSG: 3857). Further information can be found in the readme files. Contains Copernicus data. Credits: ESA (2022).
Satellite-derived water quality data for Lake Mulargia (Sardinia, Italy) 2015-2019
This dataset contains satellite-derived water quality (WQ) data of Lake Mulargia (Sardinia, Italy) for the years 2015-2019. Available parameters are: Total Absorption (ABS), Chlorophyll-a (CHL), Harmful Algae Bloom Indicator (HAB), True-color image (RGB), Secchi Disc Depth (SDD), Sea Surface Temperature (SST), Total Suspended Matter (TSM) and Turbidity (TUR). WQ parameters have been calculated using EOMAPs physics-based MIP from Sentinel-2 and Landsat 8. The data are available as GeoTiff files in web-mercator projection (EPSG: 3857). Further information can be found in the readme files. Contains Copernicus data. Credits: ESA (2022). Landsat data courtesy of the United States Geological Survey (2022).
Data_The impact of derivatives use on systemic risk of Africa's banking system
<p>This file contains the data supporting the findings of our study, the impact of derivatives use on systemic risk of Africa’s banking system, including that generated by transforming original variables before performing relevant data analyses and other output data describing the systemic risk prevalence of banks in Africa.</p>
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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.