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7,370 results for “supplement”
Supplemental data for "Intramolecular feedback regulation of the LRRK2 Roc G domain by a LRRK2 kinase dependent mechanism" (Gilsbach et al., eLife 2024, doi:10.7554/eLife.91083)
<p><strong>Supportive data for the eLife version of record.</strong></p> <p><strong>(1) Data used for the Michaelis Menten Kinetics.</strong></p> <p><strong>HPLC-based assay.</strong> Steady-state kinetic measurements of LRRK2-mediated GTP hydrolysis were performed as previously described (Ahmadian et al., 1997). Briefly, 0.1 µM of full-length LRRK2 was incubated with different amounts of GTP (0, 25, 75, 150, 250, 500, 1000, 2000, 3000 and 5000 µM) and production of GDP was monitored by reversed phase C18 HPLC. To this end, the samples (10 µl) were directly injected on a reversed-phase C18 column (pre-column: Hypersil Gold, 3µm particle size, 4.6x10mm; main column: Hypersil Gold, 5µm particle size, 4.6x250mm, Thermo Scientific) using an Ultimate 3000 HPLC system (Thermo Scientific, Waltham, MA, USA) in HPLC-buffer containing 50 mM KH<sub>2</sub>PO<sub>4</sub>/K<sub>2</sub>HPO<sub>4</sub> pH 6.0, 10 mM tetrabutylammonium bromide and 10-15% acetonitrile. Subsequently, samples were analyzed using the HPLC integrator (Chromeleon 7.2, Thermo Scientific, Waltham, MA, USA). Initial rates of GDP production were plotted against the GTP concentration using GraFit5 (v.5.0.13, Erithacus Software). The number of experiments is indicated in the graph and data point is the average (±s.e.m.) of indicated repetitions. The Michaelis-Menten equation was fitted to determine K<sub>M</sub> (±s.e.) and k<sub>cat</sub> (±s.e.). Excel sheets used for the calculation of means are provided. No values are reported if the HPLC separation failed (e.g. unstable baseline).</p> <p><strong>Charcoal GTP hydrolysis assay. </strong>The [γ-32P]GTP charcoal assay was performed as previously described (Bollag and McCormick, 1995). Briefly, 0.1 µM full-length LRRK2 or 0.5 µM 6xHIS-MBP-RocCOR was incubated with different GTP concentrations, ranging from 75 µM to 8 mM, in the presence of [γ-<sup>32</sup>P] GTP in GTPase assay buffer (30 mM Tris pH 8, 150 mM NaCl, 10 mM MgCl<sub>2</sub>, 5% (v/v) Glycerol and 3 mM DTT). Samples were taken at different time-points and immediately quenched with 5% activated charcoal in 20 mM phosphoric acid. All non-hydrolyzed GTP and proteins were stripped by the activated charcoal and sedimented by centrifugation. The radioactivity of the isolated inorganic phosphates was then measured by scintillation counting. The initial rates of γ-phosphate release and the Michaelis-Menten kinetics were calculated as described above.</p> <p><strong>(2) Profile plots (Raw data) obtained for the Mass photometry analysis for T1343A vs WT LRRK2.</strong></p> <p>MP was performed as described in (Guaitoli et al., 2023).<strong> </strong>Briefly, the dimer ratio of LRRK2 was determined on a Refeyn Two MP instrument (Refeyn). Prior to the experiment, a standard curve relating particle contrasts to molecular weight was established using a Native molecular weight standard (Invitrogen, 1:200 dilution in HEPES-based elution buffer: 50 mM HEPES [pH 8.0], 150 mM NaCl supplemented with 200 µM desthiobiotin). Prior to mass photometry, the proteins, either WT or T1343A LRRK2, were incubated with 0.5 mM ATP or buffer (control) for 30 min at 30 ℃. The LRRK2 protein was diluted to 2x of the final concentration (end concentrations: 75 nM and 100 nM) in elution buffer. The optical setup was focused in 10 μl elution buffer before adding 10 µl of the adjusted protein sample. Depending on the obtained count numbers, acquisition times were chosen between 20 s to 1 min. The dimer ratio in each measurement was normalize according to the equation. The measurement was perfomed in triplicates.</p> <p><strong>(3) AlphaFold3 model of LRRK2-pT1343 either bound to GDP/Mg or GTP/Mg.</strong></p> <p>Using AlphaFold3 (Abramson et al., 2024), we modeled and compared the GDP vs the GTP-state of phospho-T1343 LRRK2. Interestingly, the AlphaFold3 model suggests, that the phosphate group of the pT1343 residue is orientated inwards thereby substituting the gamma phosphate of the GTP in the GDP-bound state of LRRK2. This finding is in well agreement with MD simulations published recently (Stormer et al., 2023).</p> <p><strong>(4) Western blot RAW files for the cell-based phospho Rab asssay (RAW data for Figure 6 supplement 2/ Supplemental Figure 4 in the preprint version, Gilsbach et al, 2024)</strong></p> <p>Cell-based LRRK2 activity assays were performed as previously described (Singh et al., 2022). Briefly,<strong> </strong>HEK293T cells were cultured in DMEM (supplemented with 10% Fetal Bovine Serum and 0.5% Pen/Strep). For the assay, the cells were seeded onto six-well plates and transfected at a confluency of 50-70% with SF-tagged LRRK2 variants using PEI-based lipofection. After 48 hours cells were lysed in lysis buffer [30 mM Tris-HCl (pH7.4), 150 mM NaCl, 1% NonidentP-40 substitute, complete protease inhibitor cocktail, PhosStop phosphatase inhibitors (Roche)]. Lysates were cleared by centrifugation at 10,000 x g and adjusted to a protein concentration of 1 µg/µl in 1x Laemmli Buffer. Samples were subsequently subjected to SDS PAGE and Western Blot analysis to determine LRRK2 pS935 and Rab10 T73 phosphorylation levels, as described below. Total LRRK2 and Rab10 levels were determined as a reference for normalization. For Western blot analysis, protein samples were separated by SDS–PAGE using NuPAGE 10% Bis-Tris gels (Invitrogen) and transferred onto PVDF membranes (Thermo Fisher). To allow simultaneous probing for LRRK2 on the one hand and Rab10 on the other hand, membranes were cut horizontally at the 140 kDa MW marker band. After blocking non-specific binding sites with 5% non-fat dry milk in TBST (1 h, RT) (25 mM Tris, pH 7.4, 150 mM NaCl, 0.1% Tween-20), membranes were incubated overnight at 4°C with primary antibodies at dilutions specified below. Phospho-specific antibodies were diluted in TBST/ 5% BSA (Roth GmbH). Non-phospho-specific antibodies were diluted in TBST/ 5% non-fat dry milk powder (BioRad). Phospho-Rab10 levels were determined by the site-specific rabbit monoclonal antibody anti-pRAB10(pT73) (Abcam, ab230261) and LRRK2 pS935 was determined by the site-specific rabbit monoclonal antibody UDD2 (Abcam, ab133450), both at a dilution of 1:2,000. Total LRRK2 levels were determined by the in-house rat monoclonal antibody anti-pan-LRRK2 (clone 24D8; 1:10,000) (Carrion et al., 2017). Total Rab10 levels were determined by the rabbit monoclonal antibody anti-RAB10/ERP13424 (Abcam, ab181367) at a dilution of 1:5,000. For detection, goat anti-rat IgG or anti-rabbit IgG HRP-coupled secondary antibodies (Jackson ImmunoResearch) were used at a dilution of 1:15,000 in TBST/ 5% non-fat dry milk powder. Antibody–antigen complexes were visualized using the ECL plus chemiluminescence detection system (GE Healthcare) using the Stella imaging system (Raytest) for detection and quantification.</p> <p><strong>Figure 6 Source Data 1:</strong> <span>Images generated by the Stella system are shown which were used for quantification. The annotation file equals Figure6-figure supplement 2 (Gilsbach et al., eLife 2024, doi:10.7554/eLife.91083). The lines corresponding to </span>LRRK2 pS935, total LRRK2, Rab10 pT73 and total Rab10 were <span>used for the quantification shown in Figure 6.</span></p>
Supplemental Data from the article "The SmARTR pipeline: a modular workflow for the cinematic rendering of 3D scientific imaging data"
<h1><strong>Please, refer to <a href="https://github.com/MeVisLab/SmARTR-Networks">this GitHub repository</a> for additional info, updates, issue reports, and discussion<br></strong></h1> <p><strong>A collection of configuration files (SmARTR networks) published in "<a href="https://doi.org/10.1016/j.isci.2024.111475">The SmARTR Pipeline: a modular workflow for the cinematic rendering of 3D scientific imaging data</a>", enabling the creation of cinematic (photorealistic) renderings of 3D data in the FREE software <a href="https://www.mevislab.de/download">MeVisLab</a><br></strong></p> <ul> <li>Each folder in the archive contains one or more SmARTR network files, the scan and mask files required for the practical examples detailed in the <a href="https://www.cell.com/cms/10.1016/j.isci.2024.111475/attachment/8d79036b-acb6-4cda-a5ff-f56317691ebc/mmc1.pdf">Supplemental Data</a> of the article, and an additional folder with LUT presets.</li> </ul>
Supplement to "Proof of concept for Bayesian inference of dynamic rating curve uncertainty" (v3)
<div>This deposit contains part of the updated supplement to “Proof of concept for Bayesian inference of dynamic rating curve uncertainty” (<a href="https://www.tandfonline.com/doi/full/10.1080/02626667.2024.2401094" target="_blank" rel="noopener">Cornelio et al. 2024, HSJ</a>). This version, in particular, contains two files in which the following changes were made from the earlier version (v2.0.1):</div> <div> <ul> <li><strong><em>250117_Lbn_RC_new.R</em></strong> is the updated R code. The argument for the random number generator (RNG) kind is defined for the set.seed() functions used in the script. </li> <li><strong><em>Lbn-DMs-csv0.csv</em></strong> is the updated input file containing the stage-discharge gaugings. The column for the stage values has been renamed to "H_rec" (instead of "H_m" as in the original CSV) to be consistent with the attribute name used throughout the R code.</li> </ul> <p>Except for the above files, all the input and output files in <a href="https://zenodo.org/records/12792513" target="_blank" rel="noopener">v2.0.1</a><span> remain unchanged. </span></p> </div> <p><u> </u></p>
Supplemental Data for "Eyewall Asymmetries and Their Contributions to the Intensification of an Idealized Tropical Cyclone Translating in Uniform Flow"
<p>The repository contains a set of files required to reproduce the idealized tropical cyclone simulation analyzed in the manuscript entitled "Eyewall asymmetries and their contributions to the intensification of an idealized tropical cyclone translating in uniform flow", submitted to the Journal of the Atmospheric Sciences. See the README file for brief descriptions about the content of each file within this repository.</p> <p>The simulation was produced with the Cloud Model 1 (CM1) version 19.7, and CM1 can be downloaded at https://www2.mmm.ucar.edu/people/bryan/cm1/. </p>
Hoofprints in the Sand Supplement S3: ADI & GMM datasheet, TPS and sliders for GMM analysis
<p>Datasheet: Provenience, dating, measurements (mm), astragalar index values, and catalogue numbers for the astragali used in the ADI and GMM analyses (.csv file); thin plate spline coordinates (.tps file) and sliders (.csv file) for use in the GMM analysis. As demonstrated in Harding, S. et al. Hoofprints in the Sand: A Metric Study of Livestock on the Southern Phoenician Coast. In preparation for <em>Quaternary International</em>. </p>
Hoofprints in the Sand Supplement S4: R Code for LSI, ADI, GMM Analyses
<p>R code to reproduce the statistics and graphic plots shown in our study on the maritime mobility of sheep in the Iron Age eastern Mediterranean, as demonstrated in Harding, S. et al. Hoofprints in the Sand: A Metric Study of Livestock on the Southern Phoenician Coast. In preparation for <em>Quaternary International</em>. </p>
Data supplement for "Gradient flows for coupling order parameters and mechanics"
<p>In this data repository we provide additional information necessary for the generation of the images in the paper "Gradient flows for coupling order parameters and mechanics". The simulation results are generated by a FEniCS code, run on Google Colab and the code is available at <a href="https://github.com/schmellerl/gradient_flows_order_parameters_mechanics">https://github.com/schmellerl/gradient_flows_order_parameters_mechanics</a>. The preprint of the article can be found under the DOI 10.20347/WIAS.PREPRINT.2909.</p> <p> </p> <p> </p>
Data_Supplemental_Tab3_Albendazole reduces endoplasmic reticulum stress induced by Echinococcus multilocularis in mice
<p>Data of supplemental Tab3, “Albendazole reduces endoplasmic reticulum stress induced by Echinococcus multilocularis in mice”</p> <p>The Dataset contains the original supplemental table 3 as PDF-format (PNTD-D-21-00134R2_S_T3.pdf). Related information (meta-data) are provided as one file in TXT format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_ST3_M_1.txt) and three files in PDF format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_ST3_M_1-3.pdf).</p>
Data_Supplemental_Fig4_Albendazole reduces endoplasmic reticulum stress induced by Echinococcus multilocularis in mice
<p>Data of supplemental Fig4, “Albendazole reduces endoplasmic reticulum stress induced by Echinococcus multilocularis in mice”</p> <p>The Dataset contains the original supplemental figure 4 as PNG-format (PNTD-D-21-00134R2_SFig4.png). Corresponding raw data and subsequent data analysis obtained from RT-PCR analysis provided as four files in CSV format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_SF4_1_3-4_1-4.csv), all further experiment related information provided as one meta-data-file in txt format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_SF4_1_3-4_M_1.txt) and three meta data files in pdf format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_SF4_M_1-3.pdf).</p>
Data_Supplemental_Fig2_Albendazole reduces endoplasmic reticulum stress induced by Echinococcus multilocularis in mice
<p>Data of supplemental Fig2, “Albendazole reduces endoplasmic reticulum stress induced by Echinococcus multilocularis in mice”</p> <p>The Dataset contains the original supplemental figure 2 as PNG-format (PNTD-D-21-00134R2_SFig2.png), original supp. table S1 (31003A-179400_PNTD-D-21-00134R2_FJ_MW_SS_Echinococcus_F1_M_3.pdf) and the original supplemental file S1 (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_F1_M_5.pdf).</p> <p>Corresponding raw data, subsequent data analysis and all further experiment related information (meta-data) from Western Blot analysis provided as one file in TXT format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_SF2_2_1-26_M_1.txt) and two files in PDF format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_SF2_M_2-3.pdf).</p>
Data_Supplemental_Fig3_Albendazole reduces endoplasmic reticulum stress induced by Echinococcus multilocularis in mice
<p>Data of supplemental Fig3, “Albendazole reduces endoplasmic reticulum stress induced by Echinococcus multilocularis in mice”</p> <p>The Dataset contains the original supplemental figure 3 as PNG-format (PNTD-D-21-00134R2_SFig3.png). Corresponding raw data and subsequent data analysis obtained from RT-PCR analysis provided as two files in CSV format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_SF3_1_1-2_1-2.csv), all further experiment related information provided as one meta-data-file in txt format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_SF3_1_1-2_M_1.txt) and seven meta data files in pdf format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_SF3_1_1-2_M_2-4.pdf and 31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_SF3_M_1-3.pdf).</p>
Data_Supplemental_Fig1_Albendazole reduces endoplasmic reticulum stress induced by Echinococcus multilocularis in mice
<p>Data of supplemental Fig1, “Albendazole reduces endoplasmic reticulum stress induced by Echinococcus multilocularis in mice”</p> <p> </p> <p>The Dataset contains the original supplemental figure 1 as PNG-format (PNTD-D-21-00134R2_SFig1.png). Related information (meta-data) are provided as one file in TXT format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_SF1_M_1.txt) and one file in PDF format (31003A-179400_PNTD-D-21-00134R2 _FJ_MW_SS_Echinococcus_SF1_M_2.pdf).</p>
Plaskett 1.8 metre Observations of Starlink Satellites: Supplemental Information
<p>Release of GitHub repo in conjunction with the publication of "Plaskett 1.8 metre Observations of Starlink Satellites" in The Astronomical Journal, also available at arXiv: 2109.12494. The related paper presents observations of 23 Starlink satellites in the g' bandpass, obtained from the Dominion Astrophysical Observatory's Plaskett 1.8 metre telescope.</p>
Supplemental material of the Streptococcus pyogenes whole genome MLST schema deposited in Chewie-NS
<p>This supplemental material includes the lists of accession numbers for the Blackwell et al. and NCBI RefSeq assemblies used to populate the whole genome MLST schema for <em>Streptococcus pyogenes</em>, the UniProt identifiers of the reference proteomes used for schema annotation and the set of complete genomes, and associated metadata, used for schema creation.</p> <p>The wgMLST schema was created with <a href="https://github.com/B-UMMI/chewBBACA">chewBBACA</a> and is publicly available at <a href="https://chewbbaca.online/species/1/schemas/1">chewie-NS</a>, where a more detailed description of schema creation, annotation and curation can be found.</p>
Supplemental data from: "From lake to river: Documenting an environmental transition across the Jura/Knockfarril Hill members boundary in the Glen Torridon region of Gale crater (Mars)."
<p>This document, uploaded on the FAIR repository Zenodo, contains large data tables pertaining to the Supplementary Online Material of the above-mentioned article.</p> <p>These tables contain the complete list of individual MAHLI and ChemCam targets investigated, detailed laminae measurements and complete ChemCam compositional data.</p>
Supplemental Material to "Consistent quantification of precipitate shapes and sizes in two and three dimensions using central moments"
<p>Supplemental material to manuscript "Consistent quantification of precipitate shapes and sizes in two and three dimensions using central moments" published in IMMJ "Integrating Materials and Manufacturing Innovation" 2022</p>
Perspectives on Medical Education Journal Data and Supplemental Files (2012 - 2019)
<p>This is the supplemental data, figures, and tables for <em>Joining the meta-research movement: A bibliometric case study of Perspectives on Medical Education</em>. </p> <p>For Figures 2-4 from the manuscript, to open the network maps, use both the network and map file for each figure in VoS viewer - https://www.vosviewer.com/</p>
Supplemental data and code for "Global patterns in water flux partitioning: Irrigated and rainfed agriculture drives asymmetrical flux to vegetation over runoff"
<p>This dataset provides all data compiled and generated for the manuscript entitled "Global patterns in water flux partitioning: Irrigated and rainfed agriculture drives asymmetrical flux to vegetation over runoff" (https://doi.org/10.1016/j.oneear.2023.08.002). This includes the boundaries for 3614 hydrological catchments, the curated data used for analysis and modelling, the developed machine learning model, shapley values and area of applicability results, and data for global extrapolation</p> <p>It also contains a markdown file ('code.html') which shows how to access and use the data, and generic sample codes used to generate these results.</p> <p> </p> <p> </p> <p> </p>
Supplement photos for paper: New genus Navipelta (Peltaspermales, Pteridospermae) from Permian-Triassic boundary of Moscow sineclise
<p>Additional images of ovuliferous organs <em>Navipelta </em>from the terrestrial deposits of the Nedubrovo locality (village of Nedubrovo, Vologda Region, Russia), belonging to the base of Vetlugian Group (Upper Permian–Lower Triassic)</p>
Supplemental Material for a Systematic Literature Review on Benchmarks for Evaluating Debugging Approaches
<p>Bug benchmarks are used in development and evaluation of debugging approaches. Quantitative performance comparison of different debugging approaches is only possible when they have been evaluated on the same dataset or benchmark. However, benchmarks are often specialized towards usage for certain debugging approaches in their contained data, metrics, and artifacts. Such benchmarks can not be easily used on debugging approaches outside their scope as such approach may rely on specific data such as bug reports or code metrics not included in the dataset. Furthermore, benchmarks vary in their size w.r.t. the number of subject programs and the size of the individual subject programs. For these reasons, we have performed a systematic literature review where we have identified 73 benchmarks that can be used to evaluate debugging approaches.</p> <p>We compare the different benchmarks with respect to their size and the provided information such as bug reports, contained test cases, and other code metrics. Furthermore, we have investigated how well the benchmarks realize the <a href="https://www.go-fair.org/fair-principles/">FAIR guiding principles</a>. This comparison is intended to help researchers to quickly identify all suitable benchmarks for evaluating their specific debugging approaches. More information can be found in the publication:</p> <blockquote> <p>Thomas Hirsch and Birgit Hofer: "A Systematic Literature Review on Benchmarks for Evaluating Debugging Approaches", Journal of Systems and Software, in press, 2022.</p> </blockquote>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.