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Cisplatin enhances cell stiffness and decreases invasiveness rate in prostate cancer cells by actin accumulation: Confocal and atomic force microscopy
<p><strong>Summary</strong></p> <p>Dataset of imaging data related to the publication Raudenska, M., Kratochvilova, M., Vicar, T., Gumulec, J., Balvan, J., Polanska, H. Pribyl, J. & Masarik, M.:Cisplatin enhances cell stiffness and decreases invasiveness rate in prostate cancer cells by actin accumulation. <em>Scientific Reports </em><strong>2019, </strong>9, 1660</p> <p>This dataset includes image data of <em>atomic force microcopy</em> (Young modulus) and <em>confocal microscopy</em>(staining of F-actin and β-tubulin) of prostate cell lines PNT1A, 22Rv1, and PC-3. </p> <p><strong>Materials and Methods</strong></p> <p><em>Cells, cell culture conditions</em></p> <p>Cells confluent up to 50–60% were washed with a FBS-free medium and treated with a fresh medium with FBS and required antineoplastic drug concentration (IC50 concentration for the particular cell line). The cells were treated with 93 µM (PC-3), 38 µM (PNT1A), and 24 µM (22Rv1) of cisplatin (Sigma-Aldrich, St. Louis, Missouri), respectively. IC50 concentrations used for treatment with docetaxel (Sigma-Aldrich, St. Louis, Missouri) were 200nM for PC-3, 70nM for PNT1A, and 150nM for 22Rv1. </p> <p><em>Long-term zinc (II) treatment of cell cultures</em></p> <p>Cells were cultivated in the constant presence of zinc(II) ions. Concentrations of zinc(II) sulphate in the medium were increased gradually by small changes of 25 or 50 µM. The cells were cultivated at each concentration no less than one week before harvesting and their viability was checked before adding more zinc. This process was used to select zinc resistant cells naturally and to ensure better accumulation of zinc within the cells (accumulation of zinc is usually poor during the short-term treatment of prostate cancer cells). Total time of the cultivation of cell lines in the zinc(II)-containing media exceeded one year. Resulting concentrations of zinc(II) in the media (IC50 for the particular cell line) were 50 µM for the PC-3 cell line, 150 µM for the PNT1A cell line, and 400 µM for the 22Rv1 cell line. The concentrations of zinc(II) in the media and FBS were taken into account. </p> <p><em>Actin and tubulin staining</em></p> <p>β-tubulin was labeled with anti- β tubulin antibody [EPR1330] (ab108342) at a working dilution of 1/300. The secondary antibody used was Alexa Fluor® 555 donkey anti-rabbit (ab150074) at a dilution of 1/1000. Actin was labeled with Alexa Fluor™ 488 Phalloidin (A12379, Invitrogen); 1 unit per slide. For mounting Duolink® In Situ Mounting Medium with DAPI (DUO82040) was used. The cells were fixed in 3.7% paraformaldehyde and permeabilized using 0.1% Triton X-100. </p> <p><em>Confocal microscopy</em></p> <p>The microscopy of samples was performed at the Institute of Biophysics, Czech Academy of Sciences, Brno, Czech Republic. Leica DM RXA microscope (equipped with DMSTC motorized stage, Piezzo z-movement, MicroMax CCD camera, CSU-10 confocal unit and 488, 562, and 714 nm laser diodes with AOTF) was used for acquiring detailed cell images (100× oil immersion Plan Fluotar lens, NA 1.3). Total 50 Z slices was captured with Z step size 0.3 μm.</p> <p><em>Atomic force microscopy</em></p> <p>We used the bioAFM microscope JPK NanoWizard 3 (JPK, Berlin, Germany) placed on the inverted optical microscope Olympus IX‑81 (Olympus, Tokyo, Japan) equipped with the fluorescence and confocal module, thus allowing a combined experiment (AFM‑optical combined images). The maximal scanning range of the AFM microscope in X‑Y‑Z range was 100‑100‑15 µm. The typical approach/retract settings were identical with a 15 μm extend/retract length, Setpoint value of 1 nN, a pixel rate of 2048 Hz and a speed of 30 µm/s. The system operated under closed-loop control. After reaching the selected contact force, the cantilever was retracted. The retraction length of 15 μm was sufficient to overcome any adhesion between the tip and the sample and to make sure that the cantilever had been completely retracted from the sample surface. Force‑distance (FD) curve was recorded at each point of the cantilever approach/retract movement. AFM measurements were obtained at 37°C (Petri dish heater, JPK) with force measurements recorded at a pulling speed of 30 µm/s (extension time 0.5 sec).</p> <p>The Young's modulus (E) was calculated by fitting the Hertzian‑Sneddon model on the FD curves measured as force maps (64x64 points) of the region containing either a single cell or multiple cells. JPK data evaluation software was used for the batch processing of measured data. The adjustment of the cantilever position above the sample was carried out under the microscope by controlling the position of the AFM‑head by motorized stage equipped with Petri dish heater (JPK) allowing precise positioning of the sample together with a constant elevated temperature of the sample for the whole period of the experiment. Soft uncoated AFM probes HYDRA-2R-100N (Applied NanoStructures, Mountain View, CA, USA), i.e. silicon nitride cantilevers with silicon tips are used for stiffness studies because they are maximally gentle to living cells (not causing mechanical stimulation). Moreover, as compared with coated cantilevers, these probes are very stable under elevated temperatures in liquids – thus allowing long-time measurements without nonspecific changes in the measured signal.</p> <p><em>Image analysis</em></p> <p>Fluorescence microscopy data were analyzed in ImageJ 1.52h and Python 3.7.1 as follows: cells were manually segmented using actin fluorescence channel, two regions were created for analysis: whole cell and cell periphery, lining a 4 μm thick region around cell border and including most of periphery actin cytoskeleton. In these two regions following parameters were measured for both actin and tubulin fluorescence: Integrated intensity, median intensity, and following regions were measured to describe cell morphology: Cell area, Maximum caliper (max feret diameter), roundness, and aspect ratio. Moreover, stress fibers were manually segmented in every cell and following parameters were measured: number of fibers per cell, feret angle of fiber, integrated intensity, fiber length, mean intensity. Next, a standard deviation of feret angles of individual fibers was calculated relatively to mean of feret angle using a circstd function from scipy package for Python.</p> <p><strong>Identification of files</strong></p> <p><em>Microscopy data</em></p> <p>Files are separated into individual zip files. The dataset of <em>confocal microscopy </em>is separated based on treatments: untreated control, docetaxel-treated cells, cisplatin-treated cells, zinc-treated cells. Filenames actin_tubulin_Zstack_cisplatin.zip, actin_tubulin_Zstack_untreated_control.zip, actin_tubulin_Zstack_zinc.zip, actin_tubulin_Zstack_docetaxel.zip. Files included in these ZIP archives are named as follows: "cellline_treatment_FOV". Files are 3-layer 16bit tiff files with layer sequence as follows: F-Actin (Phalloidin)/b-tubulin/Hoechst 33342. The dataset contains 242 FOVs of three cell line types/three treatments + one control, files are Z-stacks made of 50 slices.</p> <p>The dataset of <em>atomic force microscopy </em>(AFM) is included in one ZIP archive "AFM_YoungModulus_SetpointHeight.zip", which includes data on Young modulus and Setpoint Height of cell lines 22Rv1, PNT1A and PC-3 and treatments zinc, docetaxel, cisplatin (+control), i.e. identical like for confocal microscopy. The file naming is as follows: "AFM_cellline_treatment_FOV_Youngmodulus.tif" for Young modulus and "AFM_cellline_treatment_FOV_setpointheight.tif" for setpoint height. The data are filtered 32-bit tiff images, where the pixel value correspond to cell stiffness (young modulus) in Pa or setpoint height in m.</p> <p><em>Confocal microscopy analysis files</em></p> <p>Following files are csv tables including image analysis of actin/tubulin staining captured by confocal microscope:</p> <p>Cytoskeleton_fluo_analysis_Cell_Cell_periphery_morphology.csv: table includes analyzed data for actin and tubulin staining in following cellular regions: cell, cell periphery. Standard ImageJ parameters regarding intensity and morphology included.</p> <p>Cytoskeleton_fluo_analysis_Fibers.csv: table includes results of manual segmentation and consequent analysis of actin stres fibers in the cells. Apart from standard ImageJ parameters, also number of stress fibers per cell and standard deviation of fiber angle relative to the cell mean angle (for details see methods) are included.</p>
LIDAROC dataset 10m: Realistic LiDAR Cover Contamination Dataset for Enhancing Autonomous Vehicle Perception Reliability.
<p>Keywords: LiDAR Point Cloud corruption, Sensor phenomena, anomaly, autonomous vehicle, contamination, dataset, object detection benchmark, perception robustness testing, sensor.</p> <div>LiDAR is the foundation of many autonomous vehicle perception systems, so it is essential to study and ensure the integrity and robustness of the data collected by LiDAR. To facilitate future research into robust and resilient LiDAR processing, we present a dataset containing a collection of uncontaminated and realistically contaminated LiDAR samples.</div> <div> </div> <div> <div> <p>This dataset is the 10m dataset, which is part of the larger LIDAROC dataset.</p> <p>The experiment was conducted in two environments: The first was a subterranean narrow hallway with the target approximately 5 meters away, referred to as the 5m dataset, simulating a complex urban driving scenario. The second environment was a spacious outdoor area with two distance variations (10 and 20 meters).</p> <p>For the 5m and 20m datasets, please refer to the link below:</p> </div> <div><a title="LIDAROC 5m" href="../records/12800039">LIDAROC 5m</a></div> <div><a title="LIDAROC 20m" href="../records/12800632">LIDAROC 20m</a></div> </div> <div> </div>
LIDAROC dataset 5m: Realistic LiDAR Cover Contamination Dataset for Enhancing Autonomous Vehicle Perception Reliability.
<p>Keywords: LiDAR Point Cloud corruption, Sensor phenomena, anomaly, autonomous vehicle, contamination, dataset, object detection benchmark, perception robustness testing, sensor.</p> <div>LiDAR is the foundation of many autonomous vehicle perception systems, so it is essential to study and ensure the integrity and robustness of the data collected by LiDAR. To facilitate future research into robust and resilient LiDAR processing, we present a dataset containing a collection of uncontaminated and realistically contaminated LiDAR samples.</div> <div> </div> <div> <p>This dataset is the 5m dataset, which is part of the larger LIDAROC dataset.</p> <p>The experiment was conducted in two environments: The first was a subterranean narrow hallway with the target approximately 5 meters away, referred to as the 5m dataset, simulating a complex urban driving scenario. The second environment was a spacious outdoor area with two distance variations (10 and 20 meters).</p> <p>For the 10m and 20m datasets, please refer to the link below:</p> </div> <div><a title="LIDAROC 10m" href="../records/12800559">LIDAROC 10m</a></div> <div><a title="LIDAROC 20m" href="../records/12800632">LIDAROC 20m</a></div>
LIDAROC dataset 20m: Realistic LiDAR Cover Contamination Dataset for Enhancing Autonomous Vehicle Perception Reliability.
<p>Keywords: LiDAR Point Cloud corruption, Sensor phenomena, anomaly, autonomous vehicle, contamination, dataset, object detection benchmark, perception robustness testing, sensor.</p> <div>LiDAR is the foundation of many autonomous vehicle perception systems, so it is essential to study and ensure the integrity and robustness of the data collected by LiDAR. To facilitate future research into robust and resilient LiDAR processing, we present a dataset containing a collection of uncontaminated and realistically contaminated LiDAR samples.</div> <div> </div> <div> <div> <p>This dataset is the 20m dataset, which is part of the larger LIDAROC dataset.</p> <p>The experiment was conducted in two environments: The first was a subterranean narrow hallway with the target approximately 5 meters away, referred to as the 5m dataset, simulating a complex urban driving scenario. The second environment was a spacious outdoor area with two distance variations (10 and 20 meters).</p> <p>For the 5m and 10m datasets, please refer to the link below:</p> </div> <div><a title="LIDAROC 5m" href="../records/12800039">LIDAROC 5m</a></div> <div><a title="LIDAROC 10m" href="../records/12800559">LIDAROC 10m</a></div> </div> <div> </div>
Dataset for Enhancing stimulated Brillouin scattering in suspended silicon waveguides through subwavelength nanostructuration [Invited]
<p>This dataset contains the raw data for the figures (Fig. 2, Fig. 5, and Fig. 7) in the publication entitled "Enhancing stimulated Brillouin scattering in suspended silicon waveguides through subwavelength nanostructuration" published by Optical Materials Express (DOI: 10.1364/OME.534474). Datafiles are in .txt format.</p> <p>All relevant information regarding the dataset, how it was obtained and its context is contained in the manuscript.</p>
Data, Analytical Code, and Model Outputs From: Restoration Treatments Enhance Tree Growth and Alter Climatic Constraints During Extreme Drought
<p>This archive includes data (forest inventories, tree ring measurements, climate variables), statistical code, model outputs, and a preprint copy of Rodman et al. (2024). For more information on specific information, processing methods, and data formats, see "README.md" or "README.html" files associated with this archive</p>
Data for the manuscript "Enhanced microscopic dynamics in mucus gels under a mechanical load in the linear viscoelastic regime" (PNAS).
<p>Data files for the figures published in</p> <p>D. Larobina, A. Pommella, A.-M. Philippe, M. Y. Nagazi, and L. Cipelletti, <em>Enhanced Microscopic Dynamics in Mucus Gels under a Mechanical Load in the Linear Viscoelastic Regime</em>, Proc Natl Acad Sci USA <strong>118</strong>, e2103995118 (2021).</p> <p>DOI: 10.1073/pnas.2103995118</p> <p>Each data set is available as a plain text file (description in the file __README__DataDescription.txt), and as an Excel file.<br> The Excel files typically contain the data sets of several panels of a given figure, as separated sheets. See the description<br> provided in the "GeneralInfo" sheet of each Excel file.</p>
Enhanced 3D velocity structure, seismicity relocation and basement characterization of Changning shale gas and salt mining regions in Sichuan Basin
<p>This repository contains the datasets and results of the joint inversion-based Vp/Vs model consistency constrained double difference seismic tomography carried out for the manuscript titled “Enhanced 3D velocity structure, seismicity relocation and basement characterization of Changning shale gas and salt mining regions in Sichuan Basin.” Included are the following: column descriptions of data files, catalog earthquake information (CX_event.dat), relocated events after inversion (CX_tomoDDMC.reloc), inverted Vp model (CX_Vpmodel.dat), inverted Vs model (CX_Vsmodel.dat) and inverted Vp/Vs model (CX_VpVsmodel.dat). Please consult the manual for tomoDD by Zhang and Thurber (2003) for detailed formats of these files. In addition, an averaged velocity model (MOD_averaged) computed based on the inversion results is included, and the converged model (Vp_model_reinverted) resulting from the reinversion, as well as basement structure data for Figure 14.</p>
Dataset to Manuscript: Schiedung et al. (2023; SBB) Enhanced loss but limited mobility of pyrogenic and organic matter in continuous permafrost-affected forest soils.
<p>Dataset to Schiedung et al. (2023; SBB) Enhanced loss but limited mobility of pyrogenic and organic matter in continuous permafrost-affected forest soils.</p> <p>All published data is provided in the files "<strong>dd_</strong>". This includes:</p> <ul> <li>dd_cores: All data of soil cores and with depth</li> <li>dd_fractions: All data obtained from fractionation of the 0-3cm core layers</li> <li>dd_teabag: All data and mass losses of incubated teabags</li> <li>dd_temperature: All data and recorded soil temperatures</li> </ul> <p>All parameters and names are described in the corresponding file starting with "<strong>Var_names_</strong>". Details on methods and calculations are given in the manuscript and supporting information.</p> <p>NanoSIMS data is provided in the folder "<strong>dd_NanoSIMS.zip</strong>". This contains a file with descriptions of the provided tif-files "<strong>dd_NanoSIMS</strong>". Descriptions of the variables and parameters as well as further instructions are given in the file "<strong>Var_names_description_dd_NanoSIMS</strong>". Images and additional data can be requested by the corresponding author (marcusschiedung@gmail.com).</p> <p> </p> <p> </p>
Modulation Engineering: Stimulation Design for Enhanced Kinetic Information from Modulation-Excitation Experiments on Catalytic Systems
<p>Dataset used in the publication "Modulation Engineering: Stimulation Design for Enhanced Kinetic Information from Modulation-Excitation Experiments on Catalytic Systems" (<a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1021%2Facscatal.3c00646&data=05%7C01%7CValentijn.DeCoster%40UGent.be%7C2a7a2c81f646405654d308db2f58f8ec%7Cd7811cdeecef496c8f91a1786241b99c%7C1%7C0%7C638155831400735344%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=e%2Fyp50KsegsMtKcY9ijwh3AqUbrsxFLo%2BTXyGmzOLps%3D&reserved=0">https://doi.org/10.1021/acscatal.3c00646</a>).<br> A description document ("Data overview.docx") is included and provides an overview of the dataset.</p>
Pathways to enhance electrochemical CO2 reduction identified through direct pore-level modeling (data for figures)
<p>This is the data used to create the figures in the article "Pathways to enhance electrochemical CO2 reduction identified through direct pore-level modeling".</p> <p>Published in EES Catalysis</p> <p>DOI: 10.1039/d3ey00122a<br> Evan Johnson<br> Etienne Boutin<br> Shuo Liu<br> Sophia Haussener</p> <p><br> Additional notes are given in the "ReadMe.txt" file.</p>
Dataset for publication "Enhancing C≥2 product selectivity in electrochemical CO2 reduction by controlling the microstructure of gas diffusion electrodes"
<p>Data used for publication:</p> <p>Broad topic: electrochemical reduction of CO2 using gas diffusion electrodes and neutral electrolyte</p> <p>Data is devided in subfolders named after the figure of the paper.</p> <p>Raw data, processed data, and Origin/Power Point files are all contained in the subfolders </p> <p>A subfolder corresponding to a sample contains: data from a potentiostat, gas and liquid chromatograms, recording of flow, pressure and temperature, tables of calculated Faradaic efficiency (FE), png image of the FE vs t, zipped raw files.</p> <p>.json file was created using a yadg scheme (https://dgbowl.github.io/yadg/master/index.html), and data was processed by a dgpost scheme (<a href="https://pypi.org/project/dgpost/">https://dgbowl.github.io/dgpost/master/index.html</a>)</p>
Aligned bam files for "Phylogenetic modeling of enhancer shifts in mole-rats reveals regulatory changes associated with tissue-specific traits"
<p>Aligned bam files used for analysis in "Phylogenetic modeling of enhancer shifts in mole-rats reveals regulatory changes associated with tissue-specific traits".</p> <p>This is an accompanying dataset to Datasets and code for "Phylogenetic modeling of enhancer shifts in mole-rats reveals regulatory changes associated with tissue-specific traits" (https://zenodo.org/record/7442105).</p>
Interagency Ecological Program and US Fish and Wildlife Service: Enhanced Delta Smelt Monitoring Program Experimental Larval Survey Data 2018-2019
The United States Fish and Wildlife Service’s (USFWS) Experimental Larval Survey was designed and implemented by the Enhanced Delta Smelt Monitoring Program to assess alternative sampling methods for monitoring the larval life stages of the federally endangered Delta Smelt (Hypomesus transpacificus) within the San Francisco Estuary, California, USA. From 2018 to 2019, four different sampling methods (Beach Seine, Manta Trawl Net, 20-mm Surface Trawl Net, 20-mm Midwater Trawl Net) nested in time and space were used to estimate the occupancy rate, relative density, and size distribution of larval Delta Smelt across sampling methods and water depth strata within the San Francisco Estuary. For more information on the Lodi USFWS Office and the Enhanced Delta Smelt Monitoring Program: https://www.fws.gov/lodi/.
Forest composition and diversity buffer microclimates and enhance productivity
The Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity, and functional diversity planted in 100 m2 and 400 m2 plots at 1 m spacing, appropriate for testing long-term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of twelve species was planted in 16 m2 plots at 0.5 m spacing. Both are adjacent to the BioDIV prairie-grassland diversity experiment, enabling comparative investigations of diversity and ecosystem function relationships between experimental grasslands and forests at different planting densities and plot sizes. This data package examines mortality in the first six years of the experiment. This data package examines the relationships between forest biodiversity, forest structure, microclimates, leaf-level physiology, and tree growth. A wide variety of data types are included, such as metrics of tree diversity, UAV-LiDAR metrics, spectral indices, microclimate data, gas exchange measurements, and tree growth inventories. This data package is included in the submission of the manuscript entitled “Forest composition and diversity buffer microclimates and enhance productivity.”
Photosynthetic rates of leaves from reduced and enhanced precipitation treatments at the Jornada Basin LTER site, 2007-2008
This data package contains photosynthetic rate data for leaves collected from mesquite shrubs and black grama grasses at the Jornada Basin LTER site in 2007-2008. The purpose of this study was to quantify ecophysiological performance of shrubs and grasses in the context of precipitation manipulations. One mesquite and one black grama leaf from each plot (n = 20 plots; 5 PPT treatments X 4 replicate plots/treatment) were measured 5 times beginning July 2007 and ending in August 2008. Plots were subjected to precipitation treatments consisting of +/-80%, +/-50%, and ambient/control. A subset of plots also had a nitrogen addition treatment. Leaves were excised from plants and immediately measured for photosynthetic rate under ideal conditions in a LiCor cuvette. This study has been completed.
Tracegas fluxes in forests and old fields under enhanced nitrogen regimes at the Kellogg Biological Station, Hickory Corners, MI (2001 to 2020)
Dataset Abstract 10 m2 plots in the old field and forest ecosystems were fertilized with 2 rates of nitrogen. N2O, CO2 and CH4 measurements were made with a static chamber method original data source http://lter.kbs.msu.edu/datasets/53
Exploring Data Evaluation Strategies for Enhanced Identification of Host Cell Proteins in Drug Products of Therapeutic Antibodies and Fc-Fusion Proteins
<p>This data repository contains all previously unpublished raw data files for the manuscript “Exploring Data Evaluation Strategies for Enhanced Identification of Host Cell Proteins in Drug Products of Therapeutic Antibodies and Fc-Fusion Proteins” by Wolfgang Esser-Skala, Marius Segl, Therese Wohlschlager, Veronika Reisinger, Johann Holzmann, and Christian G. Huber. See <em>readme.md</em> for further information.</p>
Enhanced genome annotation strategy provides novel insights on the phylogeny of 'Flaviviridae': Supplementary material
<p>SUPPLEMENTARY MATERIAL</p> <p><strong>Index</strong></p> <ul> <li> <p>Table S1 (tableS1.csv): genomic data.</p> </li> <li> <p>Table S2 (tableS2.csv): character categorization for selected nodes.</p> </li> <li> <p>Table S3 (tableS3.csv): programs and parameters.</p> </li> <li> <p>Table S4 (tableS4.csv): annotation efficiency.</p> </li> <li> <p>File S1 (fileS1.gff): gene annotation.</p> </li> <li> <p>File S2 (fileS2.xml): configuration file for BEAST 2 (configuration.xml).</p> </li> <li> <p>Figure S1 (figureS1.pdf): dendrogram depicting the hierarchical clusters of trees based on match-split distances.</p> </li> <li> <p>Figure S2 (figureS2.pdf): full version of the working phylogenetic hypothesis (tree No. 0 in table 1).</p> </li> </ul> <p><strong>Figure captions</strong></p> <ul> <li>Figure S1: A dendrogram depicting the hierarchical clusters of trees based on match-split distances. Outgroup sequences (<em>Hepacivirus</em>, <em>Pegivirus</em>, and <em>Pestivirus</em>) were removed to guarantee the compared tree topologies would have the same terminals. Tree numbers correspond to those in table 1 of the manuscript. I. No outgroup sequences; some matrices were partitioned. II. Outgroup sequences and partitioned matrices. *This tree was produced without outgroup sequences.</li> <li>Figure S2: Full version of the working phylogenetic hypothesis (tree No. 0 in table 1). Branch lengths represent an estimation of the number of substitutions per site. Node labels indicate SH-aLRT support / ultrafast bootstrap (only shown if one of there is a value below 90%). Clade names correlate to the character categorization analysis (see table S2). Branch labels represent the four genera: I = <em>Pestivirus</em>; II = <em>Pegivirus</em>; III = <em>Hepacivirus</em>; IV = <em>Flavivirus</em>. * The Ecuador Paraiso Escondido virus (EPEV) was isolated from sand flies (<em>Psathyromyia abonnenci</em>). The EPEV was the first sand fly-borne <em>Flavivirus</em> identified in the New World.</li> </ul> <p><strong>Manuscript title</strong></p> <p>FLAVi: an enhanced annotator for viral genomes of <em>Flaviviridae</em>.</p> <p><strong>Authors</strong></p> <ul> <li> <p>de Bernardi Schneider, Adriano. University of California San Diego. ORCID: 0000-0001-7487-266X.</p> </li> <li> <p>Jacob Machado, Denis. University of North Carolina at Charlotte. ORCID: 0000-0001-9858-4515. Corresponding author.</p> </li> <li> <p>Guirales, Sayal. University of North Carolina at Charlotte.</p> </li> <li> <p>Janies, Daniel. University of North Carolina at Charlotte.</p> </li> </ul> <p><em>First author</em>: Adriano de Bernardi Schneider and Denis Jacob Machado have contributed equally to the manuscript.</p> <p><strong>Contact information</strong></p> <ul> <li> <p>Corresponding author: Denis Jacob Machado, Ph.D.</p> </li> </ul> <ul> <li> <p>OrcID: 0000-0001-9858-4515.</p> </li> </ul> <ul> <li> <p>Email: dmachado [at] uncc.edu.</p> </li> </ul> <p><strong>Other additional material</strong></p> <ul> <li>In addition to the material listed above, all 31 tree topologies and 15 alignment matrices discussed in this manuscript will are available in TreeBASE (<a href="http://purl.org/phylo/treebase/phylows/study/TB2:S24096">http://purl.org/phylo/treebase/phylows/study/TB2:S24096</a>) after the publication of the manuscript.</li> <li>The FLAVi pipeline and all the original scripts are available at GitLab (<a href="https://gitlab.com/MachadoDJ/FLAVi">https://gitlab.com/MachadoDJ/FLAVi</a>).</li> <li>The web application can be accessed at <a href="http://flavi-web.com">http://flavi-web.com</a>.</li> </ul>
Dynamic Contrast Enhanced MRI Raw Data Acquired with 3D Cones Trajectory
<p>This repository contains the raw data for the second dynamic contrast enhanced (DCE) MRI in <a href="https://arxiv.org/abs/1909.13482">Extreme MRI: Large-Scale Volumetric Dynamic Imaging from Continuous Non-Gated Acquisitions</a>. The data is stored as numpy arrays, containing k-space data (ksp.npy), coordinates (coord.npy), and density compensation factors (dcf.npy). Code to process and reconstruct the data is available here: <a href="https://github.com/mikgroup/extreme_mri">https://github.com/mikgroup/extreme_mri</a></p> <p>For more information about how the data is acquired, please see the linked paper.</p>
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.