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127 results for “Self-Assembly”
Self-assembling peptide nanofiber HIV vaccine elicits robust vaccine-induced antibody functions and modulates Fc glycosylation.
<p>To develop vaccines for certain key global pathogens such as HIV, it is crucial to elicit both neutralizing and non-neutralizing Fc-mediated effector antibody functions. Clinical evidence indicates that non-neutralizing antibody functions including antibody-dependent cellular cytotoxicity (ADCC) and antibody-dependent cellular phagocytosis (ADCP) contribute to protection against several pathogens. In this study, we demonstrated that conjugation of HIV Envelop (Env) antigen gp120 to a self-assembling nanofiber material named Q11 induced antibodies with higher breadth and functionality when compared to soluble gp120. Immunization with Q11-conjugated gp120 vaccine (gp120-Q11) demonstrated higher tier 1 neutralization, ADCP and ADCC as compared to soluble gp120. Moreover, Q11 conjugation altered the Fc N-glycosylation profile of antigen-specific antibodies, leading to a phenotype associated with increased ADCC in animals immunized with gp120-Q11. Thus, this nanomaterial vaccine strategy can enhance non-neutralizing antibody functions possibly through modulation of IgG Fc N-glycosylation.</p>
Distance Tuneable Integral Membrane Protein Containing Floating Bilayers via In Situ Directed Self-Assembly : Data and Analysis Scripts
<p>Neutron Reflectometry data and analysis scripts (for RasCal software) and Quartz Crystal Microbalance data and plotting script for data shown in Figures 1, 3, 4 and 5 of the Article: Distance Tuneable Integral Membrane Protein Containing Floating Bilayers via In Situ Directed Self-Assembly.</p>
Data and code for, "Predicting self-assembly of sequence-controlled copoly- mers with stochastic sequence variation"
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Data and STL files supporting article: Encoding Quadrupolar Capillary Information into Saddle- Shaped Objects for Self-Assembly
<ul> <li>Data and STL files supporting the article entitled: Encoding Quadrupolar Capillary Information into Saddle-Shaped Objects for Self-Assembly</li> <li>Text files for Figures 3 and 5 are the raw positions and orientations of the particles extracted frame by frame from experimental videos. </li> <li>Text files for Figure 4 are the liquid elevation around objects.</li> <li>Figure_roughness.pdf shows zoomed-in pictures of our typical object, focusing on edge roughness for the readers to evaluate the edge roughness.</li> </ul>
Synthesis and Complex Self-Assembly of Amphiphilic Block Copolymers with a Branched Hydrophobic Poly(2-oxazoline) into Multicompartment Micelles, Pseudovesicles and Yolk/Shell Nanoparticles
<p>Data underlying the figures in the publication “Synthesis and complex self-assembly of amphiphilic block copolymers with a branched hydrophobic poly(2-oxazoline) into multicompartment micelles, pseudovesicles and yolk/shell nanoparticles”, published in <em>Polym. Chem.</em>, <strong>2020</strong>, 11, 1237–1248. <a href="https://pubs.rsc.org/en/content/articlepdf/2020/py/c9py01559k">https://pubs.rsc.org/en/content/articlepdf/2020/py/c9py01559k</a></p> <p>Table of contents:</p> <p><strong>1. Figure 2_Kinetics</strong>; Origin file with the data for <em>Figure 2</em>, presenting the kinetics of polymerization of EHOx on PEO-Nos in Chlorobenzene and Acetonitrile. </p> <p><strong>2. Figure 3_GPC Trace</strong>; Origin file with the data for the GPC traces in <em>Figure 3</em>. It contains the exportation of the raw data from our GPC instrument, processing of the data (normalization) and the final illustration as a graphic. </p> <p><strong>3. Figure 4_DSC</strong>; Origin file with the data for <em>Figure 4.</em> It contains the exportation of all the DSC curves measured by our DSC and the final curves/graphic used.</p> <p><strong>4. Figure 5</strong>; Zip file containing all the different Cryo-TEM and TEM images used for <em>Figure 5 </em>with a precise label, please refer to Table 1 for the name of the polymers.</p> <p><strong>5. Figure 7_Self-assembly</strong>; Origin file with the data for <em>Figure 7</em>. It contains all the data from the deblocks used in this publication and gathered it in the corresponding graph. Labels were added later by Powerpoint.</p> <p><strong>6. Table 1</strong>; Excel file that contains all the various information about the different polymers used in this publication that were obtained by NMR, GPC. (Cf Materials and Methods)</p> <p><strong>7. Table 2</strong>; Excel file that contains all the various information about DLS/SLS of the various self-assemblies by film rehydration and solvent switch.</p> <p><strong>8. SI Dataset</strong>; Zip file that contains all the various TEM and Cryo-TEM images in jpg/tif and in higher resolution, the extra DSC diblocks curves as well as the calculation of dn/dc used in the Supplementary Information.</p> <p> </p>
Dataset for: Porous Self-assemblies Mediated by Dumbbell Particles as Cross-linking Agents
<p>Input files (.py format) to perform Langevin dynamics simulations of binary mixtures of lobed colloidal particles using Hoomd-Blue 2.9.7, and respective trajectory files (.gsd format).</p>
MD simulation trajectories associated to the publication: Multi-eGO: model improvements towards the study of complex self-assembly processes
<p>The three tgz compressed files include the simulations data and resulting trajectories for the three systems discussed in the work. In particular: </p><ul><li>ab42.tgz includes a random_coil simulation, the multi-eGO simulation of the monomer performed in triplicate and the simulations performed with the original multi-eGO model.</li><li>ttr.tgz includes the randomcoil simulations for both the intramolecular as well as the intermolecular interactions at the three different concentrations, the simulation of the monomer performed in triplicate, and the aggregation kinetics performed in triplicate at the three reported concentrations</li><li>protein_g.tgz includes the reference GB1 simulation, a randomcoil simulation and the 200 multi-eGO folding simulations.</li></ul>
Self-Assembled Modified Macintosh Videolaryngoscope Versus McGrath Macintosh (MAC®) Videolaryngoscope: Which is Better?
ClinicalTrials.gov study NCT04850976. IPD Sharing: YES. Countries: 1. Publications: 7.
Treatment of Postsphincterotomy Bleeding With a Novel Self-assembling Peptide Hemostatic Gel.
ClinicalTrials.gov study NCT05886127. IPD Sharing: YES. Countries: 1. Publications: 5.
The Mechanism of Melanocyte Self-Assembly on Biomaterials and the Functional Analysis
ClinicalTrials.gov study NCT00509314. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Self-Assembling Matrix Forming Gel to Prevent Stricture Formation
ClinicalTrials.gov study NCT05581173. IPD Sharing: NO. Countries: 1. Publications: 5.
Remineralization of White Spot Lesions Using Self-Assembling Peptide P11-4 in Primary Anterior Teeth A Randomized Clinical Trial
ClinicalTrials.gov study NCT03927794. IPD Sharing: NO. Countries: 1. Publications: 4.
Data from: Characterization of self-assembled silver nanoparticle ink based on nanoemulsion method
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Data from: Facile fabrication of fluoro-polymer self-assembled ZnO nanoparticles mediated, durable and robust omniphobic surfaces on polyester fabrics
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Brewster angle optical reflection observation of self-limiting nanoparticle monolayer self-assembly at a liquid/liquid interface
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Examining the Self-Assembly of Patchy Alkane-Grafted Silica Nanoparticles using Molecular Simulation
<p>This is the dataset for the work published with the above title.</p>
Data from: State-space reduction and equivalence class sampling for a molecular self-assembly model
Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving 'target information' from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models.
ATP/azobenzene-guanidinium self-assembly into fluorescent and multi-stimuli responsive supramolecular aggregates
<p>This repository contains the data source of all graphics displayed in the main figures.</p>
Self-Assembly and Synchronization: Crafting Music with Multi-Agent Embodied Oscillators - DATASET
<p>Dataset for amalysis replication</p>
Engineered Self-Organization for Resilient Robot Self-Assembly with Minimal Surprise - Paper Material
<p>Supplementary Videos </p>
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