3 datasets found
  1. Z

    The analysis of composition and abundance of the raft proteome of microglia...

    • data.niaid.nih.gov
    • explore.openaire.eu
    Updated Jul 18, 2024
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    Jou, Ilo (2024). The analysis of composition and abundance of the raft proteome of microglia using a tandem mass tag (TMT)-based quantitative proteomic analysis. [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_5211082
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    Dataset updated
    Jul 18, 2024
    Dataset provided by
    Park, Sang Myun
    Jou, Ilo
    Park, Soo Jung
    Woo, Joo Hong
    Joe, Eun-hye
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    To determine the proteins in the membrane raft, we used the TMT-labeling and nano-liquid chromatography mass spectrometry (nano-LC-MS/MS) analysis by Creative Proteomics (NY, USA; https://www.creative-proteomics.com/). Rat primary microglia were treated with IL-6 (25 ng/ml) for 15 min. Membrane rafts were obtained by flotation assay. Samples were prepared from three independent experiments. Proteins in equal volumes of raft fractions were digested with trypsin, desalted, and labeled with a TMT reagent (Thermo Fisher Science). The TMT-labeled peptides were fractionated and analyzed by nano-LC-MS/MS. The resulting MS/MS data were analyzed and searched against the rat protein database using Proteome Discoverer 2.1.

  2. f

    Data from: Development and Experimental Validation of a Dispersity Model for...

    • acs.figshare.com
    zip
    Updated Jun 21, 2023
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    Clarissa. Y. P. Wilding; Stephen. T. Knox; Richard. A. Bourne; Nicholas. J. Warren (2023). Development and Experimental Validation of a Dispersity Model for In Silico RAFT Polymerization [Dataset]. http://doi.org/10.1021/acs.macromol.2c01798.s002
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    zipAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    ACS Publications
    Authors
    Clarissa. Y. P. Wilding; Stephen. T. Knox; Richard. A. Bourne; Nicholas. J. Warren
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

    The exploitation of computational techniques to predict the outcome of chemical reactions is becoming commonplace, enabling a reduction in the number of physical experiments required to optimize a reaction. Here, we adapt and combine models for polymerization kinetics and molar mass dispersity as a function of conversion for reversible addition fragmentation chain transfer (RAFT) solution polymerization, including the introduction of a novel expression accounting for termination. A flow reactor operating under isothermal conditions was used to experimentally validate the models for the RAFT polymerization of dimethyl acrylamide with an additional term to accommodate the effect of residence time distribution. Further validation is conducted in a batch reactor, where a previously recorded in situ temperature monitoring provides the ability to model the system under more representative batch conditions, accounting for slow heat transfer and the observed exotherm. The model also shows agreement with several literature examples of the RAFT polymerization of acrylamide and acrylate monomers in batch reactors. In principle, the model not only provides a tool for polymer chemists to estimate ideal conditions for a polymerization, but it can also automatically define the initial parameter space for exploration by computationally controlled reactor platforms provided a reliable estimation of rate constants is available. The model is compiled into an easily accessible application to enable simulation of RAFT polymerization of several monomers.

  3. Selected Hits from Mass Spectrometry Assays from Lipid Rafts Proteins.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Andrés B. Lantos; Giannina Carlevaro; Beatriz Araoz; Pablo Ruiz Diaz; María de los Milagros Camara; Carlos A. Buscaglia; Mariano Bossi; Hai Yu; Xi Chen; Carolyn R. Bertozzi; Juan Mucci; Oscar Campetella (2023). Selected Hits from Mass Spectrometry Assays from Lipid Rafts Proteins. [Dataset]. http://doi.org/10.1371/journal.ppat.1005559.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Andrés B. Lantos; Giannina Carlevaro; Beatriz Araoz; Pablo Ruiz Diaz; María de los Milagros Camara; Carlos A. Buscaglia; Mariano Bossi; Hai Yu; Xi Chen; Carolyn R. Bertozzi; Juan Mucci; Oscar Campetella
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Selected Hits from Mass Spectrometry Assays from Lipid Rafts Proteins.

  4. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Click to copy link
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Jou, Ilo (2024). The analysis of composition and abundance of the raft proteome of microglia using a tandem mass tag (TMT)-based quantitative proteomic analysis. [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_5211082

The analysis of composition and abundance of the raft proteome of microglia using a tandem mass tag (TMT)-based quantitative proteomic analysis.

Explore at:
Dataset updated
Jul 18, 2024
Dataset provided by
Park, Sang Myun
Jou, Ilo
Park, Soo Jung
Woo, Joo Hong
Joe, Eun-hye
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

To determine the proteins in the membrane raft, we used the TMT-labeling and nano-liquid chromatography mass spectrometry (nano-LC-MS/MS) analysis by Creative Proteomics (NY, USA; https://www.creative-proteomics.com/). Rat primary microglia were treated with IL-6 (25 ng/ml) for 15 min. Membrane rafts were obtained by flotation assay. Samples were prepared from three independent experiments. Proteins in equal volumes of raft fractions were digested with trypsin, desalted, and labeled with a TMT reagent (Thermo Fisher Science). The TMT-labeled peptides were fractionated and analyzed by nano-LC-MS/MS. The resulting MS/MS data were analyzed and searched against the rat protein database using Proteome Discoverer 2.1.

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