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168 results for “NMR Data”
CASP14 target T1027 (Gluc) NMR data
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NMR data for Synthesis of dialkylphosphine and chlorodialkylphosphine paper
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Analytical and optimization data for determination of azelastine hydrochloride and fluticasone propionate by quantitative proton NMR
<p>A facile, rapid, accurate, and selective quantitative proton nuclear magnetic resonance (<sup>1</sup>H-qNMR) method was developed for the simultaneous determination of fluticasone propionate and azelastine hydrochloride in pharmaceutical nasal spray for the first time. The <sup>1</sup>H-qNMR analysis of the studied analytes was performed using inositol as the internal standard and dimethyl sulfoxide-<i>d<sub>6</sub></i> (DMSO-<i>d<sub>6</sub>) </i>as the solvent. The quantitative selective proton signal of fluticasone propionate was doublet of doublet at 6.290, 6.294, 6.316, and 6.319 ppm, while that of azelastine hydrochloride was doublet at 8.292 and 8.310 ppm. The internal standard (inositol) produced a doublet signal at 3.70 and 3.71 ppm. The method was rectilinear over the concentration ranges of 0.25–20.0 mg mL<sup>-1</sup> and 0.2–15.0 mg mL<sup>-1</sup> for fluticasone propionate and azelastine hydrochloride, respectively. No labeling or pretreatment steps were required for NMR analysis of the studied analytes. The proposed <sup>1</sup>H-qNMR method was validated efficiently according to the International Council on Harmonisation (ICH) guidelines in terms of linearity, limit of detection, limit of quantification, accuracy, precision, specificity, and stability. Moreover, the method was applied to assay the analytes in their combined nasal spray formulation. The results ensured the linearity (r<sup>2</sup> > 0.999), precision (% RSD < 1.5), stability, specificity, and selectivity of the developed method.</p>
2D NMR Data
<p>2D NMR Data</p>
Fig. 2 in Alkaloids from Picrasma quassioides: An overview of their NMR data, biosynthetic pathways and pharmacological effects
Fig. 2. Structures of canthinone alkaloids isolated from P. quassioides.
Fig. 1 in Alkaloids from Picrasma quassioides: An overview of their NMR data, biosynthetic pathways and pharmacological effects
Fig. 1. Structures of β-carboline alkaloids isolated from P. quassioides.
Fig. 4 in Alkaloids from Picrasma quassioides: An overview of their NMR data, biosynthetic pathways and pharmacological effects
Fig. 4. The putative biosynthetic pathway of β-carboline and canthinone alkaloids.
Fig. 3 in Alkaloids from Picrasma quassioides: An overview of their NMR data, biosynthetic pathways and pharmacological effects
Fig. 3. Structures of alkaloid dimers isolated from P. quassioide.
Data for article "Solid-State NMR Spectra of Protons and Quadrupolar Nuclei at 28.2 T: Resolving Signatures of Surface Sites with Fast Magic Angle Spinning"
<p>Solid-state NMR data for article:</p> <p>Solid-State NMR Spectra of Protons and Quadrupolar Nuclei at 28.2 T: Resolving Signatures of Surface Sites with Fast Magic Angle Spinning</p> <p> Zachariah J. Berkson, Snædís Björgvinsdóttir, Alexander Yakimov, Domenico Gioffrè, Maciej D. Korzyński, Alexander B. Barnes, and Christophe Copéret</p> <p>https://doi.org/10.1021/jacsau.2c00510</p>
Raw Data of GC, NMR and cell tests
<p>Raw data of GC measurements, NMR measurements and half cell testings</p>
Analytical and optimization data for determination of azelastine hydrochloride and fluticasone propionate by quantitative proton NMR
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Data from: Investigation of the acid/base behaviour of the opium alkaloid thebaine in LC-ESI-MS mobile phase by NMR spectroscopy
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3x 1 µs all-atom MD trajectories; AMBER ff15ipq & SPC/Eb; T4 Lysozyme; 'Fitting side-chain NMR relaxation data using molecular simulations'
<p>Simulation data for "Fitting side-chain NMR relaxation data using molecular simulations" (https://doi.org/10.1101/2020.08.18.256024).</p> <ul> <li>3 x 1 µs all-atom MD simulations of T4 Lysozyme</li> <li>Force field: AMBER ff15ipq with modified methyl rotation barriers<sup>1</sup></li> <li>Water model: SPC/Eb</li> <li>Compressed protein coordinates saved every 1 ps to enable calculation of side-chain NMR relaxation parameters</li> </ul> <p>Contains:</p> <ul> <li>3 x GROMACS .xtc trajectory files for 3 independent simulations</li> <li>3 x corresponding GROMACS .tpr topology files</li> </ul> <p><sup>1</sup> Hoffmann, F., Mulder, F. A. A., & Schäfer, L. V. (2020). Predicting NMR relaxation of proteins from molecular dynamics simulations with accurate methyl rotation barriers. <em>Journal of Chemical Physics</em>, <em>152</em>(8). https://doi.org/10.1063/1.5135379</p>
5x 1 µs all-atom MD trajectories; AMBER ff99SB*-ILDN & TIP4P/2005; T4 Lysozyme; 'Fitting side-chain NMR relaxation data using molecular simulations'
<p>Simulation data for "Fitting side-chain NMR relaxation data using molecular simulations" (https://doi.org/10.1101/2020.08.18.256024).</p> <ul> <li>5 x 1 µs all-atom MD simulations of T4 Lysozyme</li> <li>Force field: AMBER ff99SB*-ILDN with modified methyl rotation barriers<sup>1</sup></li> <li>Water model: TIP4P/2005</li> <li>Compressed protein coordinates saved every 1 ps to enable calculation of side-chain NMR relaxation parameters</li> </ul> <p>Contains:</p> <ul> <li>5 x GROMACS .xtc trajectory files for 5 independent simulations</li> <li>5 x corresponding GROMACS .tpr topology files</li> </ul> <p><sup>1</sup> Hoffmann, F., Mulder, F. A. A., & Schäfer, L. V. (2018). Accurate Methyl Group Dynamics in Protein Simulations with AMBER Force Fields. <em>The Journal of Physical Chemistry B</em>, <em>122</em>(19), 5038–5048. https://doi.org/10.1021/acs.jpcb.8b02769</p>
3x 5 µs all-atom MD trajectories; AMBER ff99SB*-ILDN & TIP4P/2005; T4 Lysozyme; 'Fitting side-chain NMR relaxation data using molecular simulations'
<p>Simulation data for "Fitting side-chain NMR relaxation data using molecular simulations" (https://doi.org/10.1101/2020.08.18.256024).</p> <ul> <li>3 x 5 µs all-atom MD simulations of T4 Lysozyme</li> <li>Force field: AMBER ff99SB*-ILDN with modified methyl rotation barriers<sup>1</sup></li> <li>Water model: TIP4P/2005</li> <li>Compressed protein coordinates saved every 1 ps to enable calculation of side-chain NMR relaxation parameters</li> </ul> <p>Contains:</p> <ul> <li>3 x GROMACS .xtc trajectory files for 3 independent simulations</li> <li>3 x corresponding GROMACS .tpr topology files</li> </ul> <p><sup>1</sup> Hoffmann, F., Mulder, F. A. A., & Schäfer, L. V. (2018). Accurate Methyl Group Dynamics in Protein Simulations with AMBER Force Fields. <em>The Journal of Physical Chemistry B</em>, <em>122</em>(19), 5038–5048. https://doi.org/10.1021/acs.jpcb.8b02769</p>
Bruker NMR data set for journal article: 3.4. Understanding the Microstructure Connectivity in Photopolymerizable Aluminum-Phosphate-Silicate Sol−Gel Hybrid Materials for Additive Manufacturing
<p>Solid state fast MAS 1H data for hybrid polymerizable compounds. </p>
Data for "Resolving Structures of Paramagnetic Systems in Chemistry and Materials Science by Solid-State NMR: the Revolving Power of Ultra-Fast MAS"
<p>Raw NMR data</p>
Solid state NMR data of amorphous MOF [(Eu2Zr)(btc)3(Hbtc)0.5·6H2O)]
<p>Solid state NMR <sup>13</sup>C and <sup>1</sup>H data for the sample [(Eu2Zr)(btc)3(Hbtc)0.5·6H2O)], an amorphous coordination compound with high luminescence and thermal stability.</p>
Raw NMR Data for Catalytic Amide Activation with Thermally Stable Molybdenum(VI) Dioxide Complexes
<p>Raw NMR data for Catalytic Amide Activation with Thermally Stable Molybdenum(VI) Dioxide Complexes</p>
Vang et al. Surface NMR and tTEM data HESS manuscript
<p>A dataset supporting a manuscript submitted to Hydrology and Earth System Sciences. <br> <br> Prefix SNMR for surface nuclear magnetic resonance data and a location. The .emo files have all the processed input data and the inversion results stored. </p> <p>Prefix tTEM for towed Transient electromagnetic. Each .xyz files contain all TEM models from the specified survey area. </p>
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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.