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127 results for “Self-Assembly”
Data related to Lauryl-NrTP6 lipopeptide self-assembled nanorods for nuclear target delivery of doxorubicin
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Deepening the Insight into Poly(butylene oxide)-block-poly(glycidol) Synthesis and Self-assemblies: Micelles, Worms and Vesicles
<p>Data underlying the figures in the publication “Deepening the insight into poly(butylene oxide)-block-poly(glycidol) synthesis and self-assemblies: micelles, worms and vesicles”, published in <em>RSC Adv., </em><strong>2020</strong>, 10, 22701. <a href="https://pubs.rsc.org/en/content/articlelanding/2020/ra/d0ra04274a#!divAbstract">https://pubs.rsc.org/en/content/articlelanding/2020/ra/d0ra04274a#!divAbstract</a></p> <p>Table of contents:</p> <p><strong>1. Figure 2</strong>; Zip file containing the numerical data for the Kinetic studies of <em>Figure 2</em>.</p> <p><strong>2. Figure 3</strong>; Zip file containing the numerical data for the SEC and DSC traces of <em>Figure 3</em>.</p> <p><strong>3. Figure 4</strong>; Zip file containing the TEM, Cryo-TEM and CLSM images of the nano- and macroscopic self-assemblies, showed in <em>Figure 4</em>.</p> <p><strong>4. Figure 6</strong>; Zip file containing the TEM images of the nanoscopic self-assemblies formed by film rehydration, showed in <em>Figure 6</em>.</p> <p> </p>
Monitoring Solid-Phase Reactions in Self-Assembled Monolayers by Surface-Enhanced Raman Spectroscopy
<p>Data underlying the figures in the publication “Monitoring Solid-Phase Reactions in Self-Assembled Monolayers by Surface-Enhanced Raman Spectroscopy”, published in <em>Angew. Chem. Int. Ed.,</em> <strong>2021</strong>, 60, 2–10<strong>.</strong></p> <p><a href="https://onlinelibrary.wiley.com/doi/full/10.1002/anie.202102319">https://onlinelibrary.wiley.com/doi/full/10.1002/anie.202102319</a></p> <p>Table of contents:</p> <p><strong>1. Figure 1C</strong>; Zip file containing the numerical data for <em>Figure 1C</em>.</p> <p>The data were obtained from optical numerical simulations using the software <em>Lumerical</em>. The parameters used for the simulations are described in the SI of the publication. The file “OCH04-015_0nm.txt” has been exported from the simulated solution. It includes the distribution of the electric field intensity (|E|^2) in x and y directions at the Au-air interface. The data were then plotted as the electromagnetic enhancement factor in log scale (log|E|^4) using the origin lab software (“OCH04-015.opju”.</p> <p><strong>2. Figure 1D, 1E, 1F</strong>; Zip file containing the numerical data for <em>Figures 1D, 1E</em> and <em>1F.</em></p> <p><strong>Figure 1D:</strong> 100 data files with the general file name:</p> <p>“OCH04-021_3_633nm_300lpermm_10perc_2x30s_300hole_100x_Yyy_Xxx.txt”</p> <p>The yy and xx are different numeric values for each file indicating the position in the 10 x 10 map. And:</p> <p>«OCH02-072_2_blankAu_2x30s_10perc_633nm_100x_01.txt” is the dataset of the orange dotted spectrum which was recorded on the planar Au surface.</p> <p>In all text files, there are two columns: The first one is the Raman shift in cm–1 and the second one the intensity in photon counts. The Raman spectroscopy data in the files starting with “OCH04-021…” were generated using the Horiba LabRAM Software and the baseline has already been subtracted using this software. The 100 spectra were plotted without further data smoothing (grey spectra) and the average spectrum (black) was generated by using the dedicated function in the Origin Lab software. The orange spectrum originates from «OCH02-072_2_blankAu_2x30s_10perc_633nm_100x_01.txt”. It was smoothed with 10 points using a Savitzky-Golay Filter in Origin Lab and the Baseline was subtracted.</p> <p><strong>Figure 1E:</strong> The Box Plot was generated using the 100 grey spectra from 1D and applying a Gaussian fit to the three peaks indicated in the figure and extracting the peak positions. Using these peak position data, the box plot was generated using the Origin Lab software.</p> <p><strong>Figure 1F:</strong> The contour plot was generated using the 100 grey spectra from 1D and applying a gaussian fit to the peak indicated in the figure description and extracting the peak heights. Using these peak height data, the contour plot was generated using the Origin Lab software.</p> <p><strong>3. Figure 2</strong>; Zip file containing the numerical data for <em>Figure 2</em>.</p> <p>In all text files, there are two columns: The first one is the Raman shift in cm<sup>–1</sup> and the second one the intensity in photon counts. The spectra were smoothed with 10 points using a Savitzky-Golay Filter in Origin Lab and the Baseline was subtracted. The y intensity was normalized so that the Si peak at approx. 950 cm<sup>–1</sup> had the same height. The Raman shift in x direction was shifted so that the Si peak at 300 cm<sup>–1</sup> was at the same position in each spectrum.</p> <p><strong>4. Figure 3A, 3C</strong>; Zip file containing the numerical data for <em>Figures 3A</em> and <em>3C</em>.</p> <p>In all text files, there are two columns: The first one is the Raman shift in cm–1 and the second one the intensity in photon counts. The spectra were smoothed with 8 points using a Savitzky-Golay Filter in Origin Lab and the Baseline was subtracted. The average of three spectra was calculated for the spectra with the same y description for the plotted spectra in 3A. Figure 3C was generated by applying a gaussian fit to the three peaks indicated in the figure in the original 12 data sets and extracting the peak heights. The average and standard deviation of the peak height data from the spectra with the same y description was then calculated to generate Figure 3C.</p> <p><strong>5. Figure 4A, 4B</strong>; Zip file containing the numerical data for <em>Figures 4A</em> and <em>4B</em>.</p> <p><strong>4A:</strong> In all text files, there are two columns: The first one is the Raman shift in cm<sup>–1</sup> and the second one the intensity in photon counts. The spectra were smoothed with 10 points using a Savitzky-Golay Filter in Origin Lab and the Baseline was subtracted. The y intensity was normalised so that the Si peak at approx. 950 cm<sup>–1</sup> had the same height. The Raman shift in x direction was shifted so that the Si peak at 300 cm<sup>–1</sup> was at the same position in each spectrum.</p> <p><strong>4B:</strong> The peak positions from <em>Figures 2</em> and <em>4A</em> were used to generate <em>Figure 4B</em>.</p>
Research Data supporting "Photonic particles made by the confined self-assembly of a supramolecular comb-like block copolymer"
<p><strong>Research Data supporting “</strong><strong>Photonic particles made by the confined self-assembly of a supramolecular comb-like block copolymer</strong><strong>”</strong></p> <p><strong><em>Macromolecular Rapid Communications,</em></strong> doi: 10.1002/marc.202100522</p> <p>The data is arranged into different folders (.zip file), containing the following files (.txt, .tif, etc.; <em>italics</em>). This data and the descriptions below should be read in conjunction with the manuscript and “Supporting Info”, both of which may be found at the following DOI: <a href="https://doi.org/10.1002/marc.202100522">https://doi.org/10.1002/marc.202100522</a></p>
Mechanically Tunable Lattice-Plasmon Resonances by Templated Self-Assembled Superlattices for Multi- Wavelength Surface-Enhanced Raman Spectroscopy
<p>Related publication: Charconnet, M; Kuttner, C; Plou, J; Garcia-Pomar, JL; Mihi, A; Liz-Marzan, LM; Seifert, A. Mechanically Tunable Lattice-Plasmon Resonances by Templated Self-Assembled Superlattices for Multi-Wavelength Surface-Enhanced Raman Spectroscopy. <em>Small Methods</em> 2021, 2100453. 10.1002/smtd.202100453</p>
Datasets accompanying "Ultrafast reversible self-assembly of living tangled matter"
<p>Datasets showing the structure and dynamics of tangling worms</p>
Data from: Self-assembly behaviors of peptide-drug conjugates: influence of multiple factors on aggregate morphology and potential self-assembly mechanism
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Data from: Designer self-assembling hydrogel scaffolds can impact skin cell proliferation and migration
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Data from: State-space reduction and equivalence class sampling for a molecular self-assembly model
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Self-assembly of hybrid 3D cultures by integrating living and synthetic cells
GEO Series GSE308254. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing.
Spatially-patterned and functional kidney assembloids recapitulate progenitor self-assembly and enable high-fidelity in vivo disease modeling
GEO Series GSE272707. Homo sapiens. 4 samples. Type: Other.
Self-Assembling Hematopoietic Niche on a Chip: Bulk sequencing to investigate effect of proton radioablation
GEO Series GSE162428. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
Spatially-patterned and functional kidney assembloids recapitulate progenitor self-assembly and enable high-fidelity in vivo disease modeling
GEO Series GSE262382. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
RNASeq of total RNA isolated from self-assembling co-cultures of primary human hepatocytes (SACC-PHHs) mono-infected with HBV, co-infected with HBV/HDV, or uninfected at 8 and 28 days post-infection
GEO Series GSE112118. Homo sapiens; Mus musculus. 44 samples. Type: Expression profiling by high throughput sequencing.
Gene expression of antigen presenting cells in tumor and spleen of mice receiving either a self-assembling nanoparticle vaccine or an adenovirus vaccination by different routes.
GEO Series GSE214741. Mus musculus. 16 samples. Type: Expression profiling by high throughput sequencing.
Spatially-patterned and functional kidney assembloids recapitulate progenitor self-assembly and enable high-fidelity in vivo disease modeling [hKPA_invivo_data]
GEO Series GSE297772. Homo sapiens. 5 samples. Type: Expression profiling by high throughput sequencing.
Spatially-patterned and functional kidney assembloids recapitulate progenitor self-assembly and enable high-fidelity in vivo disease modeling [hKPA_TT_data]
GEO Series GSE297771. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
Self-Assembled Supported Ionic Liquids
<p>Raw and processed data from MAS NMR, NMR in solution, Elemental analysis, N2 adsorption–desorption isotherms and Small Angle X-ray scattering (SAXS) measurements, for the article "Self-Assembled Supported Ionic Liquids".</p>
Energy Landscape of the Sugar Conformation Controls the Sol-to- Gel Transition in Self-Assembled Bola Glycolipid Hydrogels
<p>Self-assembled fibrillar network (SAFIN) hydrogels and organogels are commonly obtained by a crystallization process into fibers induced by external stimuli like temperature or pH. The gel-to-sol-to-gel transition is generally readily reversible and the change rate of the stimulus determines the fiber homogeneity and eventual elastic properties of the gels. However, recent work shows that in some specific cases, fibrillation occurs for a given molecular conformation and the sol-to-gel transition depends on the relative energetic stability of one conformation over the other, and not on the rate of change of the stimuli. We observe such a phenomenon on a class of bolaform glycolipids, sophorosides, similar to the well-known sophorolipid biosurfactants, but composed of two symmetric sophorose units. A combination of oscillatory rheology, small-angle X-ray scattering (SAXS) cryogenic transmission electron microscopy (cryo-TEM) and <em>in situ</em> rheo-SAXS using synchrotron radiation shows that below 14°C, twisted nanofibers are the thermodynamic phase. Between 14°C and about 33°C, nanofibers coexist with micelles and a strong hydrogel forms, the sol-to-gel transition being readily reversible in this temperature range. However, above the annealing temperature of about 40°C, the micelle morphology becomes kinetically-trapped over hours, even upon cooling, whichever the rate, to 4°C. A combination of solution and solid-state nuclear magnetic resonance (NMR) suggests two different conformations of the 1ˈˈ, 1ˈ and 2ˈ carbon stereocenters of sophorose, precisely at the β(1,2) glycosidic bond, for which several combinations of the dihedral angles are known to provide at least three energetic minima of comparable magnitude and each corresponding to a given sophorose conformation.</p>
Crafting Nanostructured Hybrid Block Copolymer–Gold Nanoparticles by Confined Self-Assembly in Evaporative Droplets
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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.