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2,216 results for “membrane”
Homologous membrane protein structures (HOMEP) version 1
<p><strong>Table 1</strong> = List of membrane protein structures in the <strong>HOMEP</strong> data set (version 1).<br> From Forrest, Tang & Honig 2006 Biophysical Journal (Supplementary Table 1)<br> <a href="https://www.ncbi.nlm.nih.gov/pubmed/16648166">https://www.ncbi.nlm.nih.gov/pubmed/16648166</a></p> <p>Contains the following columns:<br> PDB-Code Protein-Name Source Res-(Å) Length (Num-TM) Number-of-TM-domains Family</p> <p><strong>Table 2</strong> = List of pairs of membrane protein structures in the <strong>HOMEP</strong> data set (version 1).<br> From Forrest, Tang & Honig 2006 Biophysical Journal (Supplementary Table 2)</p> <p>Contains the following columns:<br> Model Family Query Template ID(%) RMS(Å) GDT_TS(%) TM-ID(%) TM-RMS(Å) TM GDT_TS(%)</p> <p><strong>Table 3 </strong>= Manually-defined transmembrane regions in the <strong>HOMEP</strong> data set (version 1), listed for each family by transmembrane segment number. From Forrest, Tang & Honig 2006 Biophysical Journal (Supplementary Table 3).</p> <p>Contains the columns defined as follows:<br> Protein chain identifier, start (-s) and end (-e) residues for each PDB structure in the family</p>
Dataset of "Activity-stability relationship in magnetron co-sputtered bimetallic catalysts for proton exchange membrane fuel cells"
<p>In the present study, magnetron sputtered PtxM100-x (M = Co, Cu, Y; x = 25, 50, 75 and 100) bimetallic alloys were investigated as PEMFC cathodes. Accurate composition control enabled a systematic study of the correlation between alloy composition, activity, and stability. The catalysts underwent thorough characterization, employing a diverse portfolio of characterization techniques such as scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy and cyclic voltammetry. The activity of all investigated alloys was tested directly in a fuel cell device, while stability was assessed through potentiodynamic cycling in a half-cell. <br>The activity-stability index, considering experimental results for both activity and stability, was calculated and compared for all investigated catalysts. All alloys exhibited a volcano-type trend in activity-stability index as a function of the concentration of alloying element with peaks observed at Pt50Co50, Pt50Cu50 and Pt75Y25 for respective alloys, surpassing that of monometallic platinum. Overall, Pt50Co50 emerged as a catalyst with the highest activity-stability ratio.</p>
Dataset of "MoO3-xNiMoO4 nanorods synthetized using NiO nanoparticles for hydrogen evolution in anion exchange membrane water electrolysis"
<p>Novel method of Mo-Ni catalyst for hydrogen evolution reaction in anion exchange membrane water electrolysis was used. Complete physico-chemical and electrochemical characterization was done. Prepared material showed enhanced performance when compared to the similar Ni based materials. Physico-chemical characterization showed, that final material is formed by NiMoO4 nanorods coverd on the surface by the layer of the MoO3-x.</p>
Dataset of "Microporous electrode binders for anion exchange membrane water electrolyzers"
<p>Membranes made of SEBS/DABCO/PIM-1 blends were prepared and characterized. In the next step, the several blends were used as polymer binder's of the catalysts layers. Characterization of SEBS-DABCO/PIM-1 blends in the form of the catalyst layer revealed the significance of the catalyst layer porosity, which controls the permeation of gasses.</p>
In-depth insights on multi-ionic transport in Electrodialysis with bipolar membrane systems
<p>Electrodialysis with Bipolar Membranes (EDBM) has become a key technology for valorising waste brine streams as a new chemical production route. Even though its application has been widely studied using single electrolyte solutions (e.g., NaCl or Na2SO4), there is still a lack of knowledge about using multi-ionic mixtures. For the first time, this work aims to evaluate the EDBM performance when treating synthetic solutions mimicking the waste brines produced in a integrated process for the valorisation of solar saltworks bitterns. The behaviour of a lab-scale EDBM unit was assessed using SUEZ ion exchange membranes (IEMs), operating at 300 A m− 2, and the ion transport through IEMs was investigated, based on the calculation of apparent transport numbers and selectivities. The results highlighted that multi-ionic solutions barely affected the production of hydroxide ions. Chlorides were transported up to 7 times faster than sulphates across the anion-exchange membranes, while the cation-exchange membranes exhibited slightly higher selectivity for potassium than for sodium (~1.2). The current efficiencies ranged between 70 % and 80 %, while a minimum specific energy consumption of 1.60 kWh kg-1 NaOH was obtained for the most concentrated brine at 1 mol L-1 OH–. These results provide novel and valuable information to support the development and implementation of EDBM as a sustainable technology for supporting a resource-efficient and competitive economy through on-site and delocalized chemicals production routes.</p>
Datasets for "Single-molecule and super-resolved imaging deciphers membrane behaviour of onco-immunogenic CCR5"
<p><strong>Flow cytometry</strong></p> <p>Modality / instrument: <em>Flow cytometer</em> <em>(CytoFLEX LX, Beckman Coulter)</em></p> <p>File format:<em> FCS + XIT (CytExpert, Beckman Coulter).</em></p> <p>Samples and acquisitions:</p> <p>Fluorescent fusions in live Chinese Hamster ovary (CHO) cells.</p> <table> <tbody> <tr> <td> <p><em>File</em></p> </td> <td> <p><em>Cell line</em></p> </td> <td> <p><em>Runs</em></p> </td> <td> <p><em>Cells counted</em></p> </td> </tr> <tr> <td> <p>CONTROL.fcs</p> </td> <td> <p>CHO wild-type</p> </td> <td> <p>1</p> </td> <td> <p>7000</p> </td> </tr> <tr> <td> <p>GFP-CCR5.fcs</p> </td> <td> <p>CHO-GFP-CCR5</p> </td> <td> <p>1</p> </td> <td> <p>7000</p> </td> </tr> <tr> <td> <p>Exp_20220916_1_GFP.xit</p> </td> <td> <p>N/A - metadata</p> </td> </tr> </tbody> </table> <p>Approx. size 6 MB</p> <p> </p> <p><strong>PaTCH microscopy images</strong></p> <p>Imaging modality / instrument: <em>Brightfield</em> + <em>PaTCH fluorescence microscopy</em></p> <p>Image format:<em> OME TIFF (16 bit) + MicroManager metadata files</em></p> <p>Microscope settings:</p> <p><em>488 nm triggered excitation; split red/green detection, cropped to green (GFP) channel only; 10 ms/frame laser exposure; 13.5 ms/frame-to-frame; 53 nm/px. Photometrics Prime95b CMOS.</em></p> <p>Samples and acquisitions:</p> <p>Fluorescent fusions of GFP-CCR5 receptor in live CHO cells imaged with and without 100 nM CCL5 ligand. Each subfolder corresponds to a field of view and contains one brightfield and one PaTCH acquisition of the same cell.</p> <table> <tbody> <tr> <td> <p>Folder</p> </td> <td> <p>Condition</p> </td> <td> <p>Fields of view</p> </td> </tr> <tr> <td> <p>AC6 CONTROL sc</p> </td> <td> <p>CCL5-</p> </td> <td> <p>11</p> </td> </tr> <tr> <td> <p>AC6 CCL5 sc</p> </td> <td> <p>CCL5+ (100 nM)</p> </td> <td> <p>10</p> </td> </tr> </tbody> </table> <p>Approx. size before compression: 14 GB</p> <p> </p> <p><strong>Structured illumination microscopy - volumetric stacks</strong></p> <p>Imaging modality / instrument: <em>SIM fluorescence microscopy (custom setup at NPL based on Olympus IX71)</em></p> <p>Image format:<em> OME TIFF (16 bit) with intrinsic metadata (voxel size)</em></p> <p>Microscope settings: <em>638 nm excitation; 60x/1.3 NA; Flash 4.0, Hamamatsu Photonics. For additional details see the reference below (Hunter et al, bioRxiv).</em></p> <p>Samples and acquisitions:</p> <p>Dylight 650-MC-5 labeled CCR5 receptor in fixed CHO-CCR5 cells, imaged with and without 100 nM CCL5 ligand. Each acquisition is of a unique field of view and contains one SIM reconstruction as an XYZ volumetric stack. ‘Basal membrane’ acquisitions consist of 5 slices at 200 nm z-intervals across the range of the basal membrane. ‘Whole cell' acquisitions are made up of 7 slices with 500 nm z-interval ranging from just below the basal membrane to just above the apical membrane. </p> <table> <tbody> <tr> <td>Folder</td> <td>Subfolder/condition</td> <td>Fields of view</td> </tr> <tr> <td>Basal membrane</td> <td>CCL5-</td> <td>5</td> </tr> <tr> <td>Basal membrane</td> <td>CCL5+ (100 nM)</td> <td>6</td> </tr> <tr> <td>Whole cells</td> <td>CCL5-</td> <td>5</td> </tr> <tr> <td>Whole cells</td> <td>CCL5+ (100 nM)</td> <td>8</td> </tr> </tbody> </table> <p>Approx. size before compression: 300 MB</p>
Homologous membrane protein structures (HOMEP) dataset version v2
<p><strong>Protein structures from the dataset of Homologous MEmbrane Protein structures (HOMEP)</strong> version v2 created in 2010, published in 2013. A more automated version of HOMEP v1: <a href="https://doi.org/10.5281/zenodo.2646534">10.5281/zenodo.2646534</a><br> </p> <p><strong>Table 1</strong> = List of protein databank structure entries<br> From Stamm et al, PLOS One 2013, <a href="https://www.ncbi.nlm.nih.gov/pubmed/23469223">https://www.ncbi.nlm.nih.gov/pubmed/23469223</a>, Supplementary Table 1, with the following entries:<br> Family grouping, Protein databank identifier, Name, Source organism, Resolution (Å)</p> <p> </p> <p><strong>Table 2</strong> = List of pairs of structures<br> From Stamm et al, PLOS One 2013, <a href="https://www.ncbi.nlm.nih.gov/pubmed/23469223">https://www.ncbi.nlm.nih.gov/pubmed/23469223</a>, Supplementary Table 2, with the following entries:<br> Family grouping, PDB code for first structure, Chain ID from PDB1, PDB for second structure, Chain ID from PDB2, protein structural difference (PSD), % sequence identity</p> <p> </p> <p><strong>File S2 HOMEP2 Dataset.tar.gz</strong> = Protein databank format files (PDB) are attached in the Dataset tar zipped file, organized by family. From Stamm et al, PLOS One 2013, <a href="https://www.ncbi.nlm.nih.gov/pubmed/23469223">https://www.ncbi.nlm.nih.gov/pubmed/23469223</a>, Supplementary dataset.</p>
Simulation systems for: "Pore formation in complex biological membranes: torn between evolutionary needs"
<p>Simulation systems for the publication:</p> <div> <div> <div> <p>Leonhard J. Starke, Christoph Allolio, and Jochen S. Hub, <em>Pore formation in complex biological membranes: torn between evolutionary needs</em>, BioRxiv (2024), doi: <a href="https://doi.org/10.1101/2024.05.06.592649">10.1101/2024.05.06.592649</a></p> <p>Required software:<br>GROMACS Chain Coordinate, a modified GROMACS variant for pore formation across membranes or stalk formation between membranes: <a href="https://gitlab.com/cbjh/gromacs-chain-coordinate">https://gitlab.com/cbjh/gromacs-chain-coordinate</a></p> <p>See README_small.sh and README_large.sh files for instructions on how to run pulling simulations for inducing pores in the provided complex membrane models.</p> </div> </div> </div>
Data in: Aging power spectrum of membrane protein transport and other subordinated random walks
<p>Datasets generated in the report "Aging power spectrum of membrane protein transport and other subordinated random walks". Included data are:</p> <p><strong>Numerical simulations </strong><br> RWdata1.mat: 10,000 realizations, subordinated random walk with Hurst exponent, <em>H</em>=0.3 and <span class="math-tex">\(\alpha\)</span>=0.4.<br> RWdata3.mat: 10,000 realizations, subordinated random walk with Hurst exponent, <em>H</em>=0.7 and <span class="math-tex">\(\alpha\)</span>=0.4.<br> RWdata8.mat: 5,000 realizations, subordinated random walk with Hurst exponent, <em>H</em>=0.75 and <span class="math-tex">\(\alpha\)</span>=0.8.<br> RWdataCTRW.mat: 10,000 realizations, continuous time random walk (CTRW), <span class="math-tex">\(\alpha\)</span>=0.7.</p> <p><strong>Spectra of simulations</strong><br> PSDdata1.mat: Power spectral density (PSD) of a subordinated random walk with Hurst exponent, <em>H</em>=0.3 and <span class="math-tex">\(\alpha\)</span>=0.4. Five different realization times are used to compute the PDS: 2^8, 2^10, 2^12, 2^14, and 2^16.<br> PSDdata3.mat: PSD of a subordinated random walk with Hurst exponent, <em>H</em>=0.7 and <span class="math-tex">\(\alpha\)</span>=0.4. Five different realization times are used to compute the PDS: 2^8, 2^10, 2^12, 2^14, and 2^16.<br> PSDdata8.mat: PSD of a subordinated random walk with Hurst exponent, <em>H</em>=0.75 and <span class="math-tex">\(\alpha\)</span>=0.8. Four different realization times are used to compute the PDS: 2^15, 2^16, 2^17, and 2^18.<br> PSDs_CTRW.mat: PSD of a continuous-time random walk (CTRW), <span class="math-tex">\(\alpha\)</span>=0.7. Five different realization times are used to compute the PDS: 2^8, 2^10, 2^12, 2^14, and 2^16.</p> <p><strong>Experimental data of Nav1.6 channels in the soma of hippocampal neurons</strong><br> NavMSDtimes.csv: ensemble-averaged (EA) MSD and time-averaged (TA) MSD. The TA-MSD is measured for three observation times, 64, 128, and 256 frames (3.2, 6.4, and 12.8 s).<br> NavPSD.csv: Power spectral density (PSD) measured for three observation times, 64, 128, and 256 frames.</p>
Absorbed soil nutrients on ion exchange membranes in the reciprocal transplant gardens at Toolik Lake, Coldfoot, and Sagwon in 2016
Transplant gardens at Toolik Lake and Sagwon were established in 2014. At each location, 60 tussocks each from ecotypes of Eriophorum vaginatum from Coldfoot (CF, 67°15′32″N, 150°10′12″W), Toolik Lake (TL, 68°37′44″N, 149°35′0″W), and Sagwon (SG, 69°25′26″N, 148°42′49″W) were transplanted. At the reciprocal transplant gardens, ion exchange membranes were used to measure nutrient availability over two time periods: Early season (June) and mid season (July). Membranes were deployed in the field for either 20 or 21 days, depending on travel constraints.
Ion exchange membrane measure of nutrient availability of the 2015 experimental burn at Toolik Lake Field Station, Alaska 2016
An experimental burn conducted in the summer of 2015 to provide sites for an experiment whether seeds of Eriophorum vaginatum from different ecotypes could establish in recently burned areas. It consisted of ten 2 meter X 2 meter plots along with a similar number of control plots. There was little seedling establishment but other data were collected on the plots. Ion exchange membranes were used to measure nutrient availability over two time periods: Early season (June) and mid season (July).
Dataset for publication: "Photosystem II supercomplexes lacking light-harvesting antenna protein LHCB5 and their organization in the thylakoid membrane"
<p>Data repository for "<strong>Photosystem II supercomplexes lacking light-harvesting antenna protein LHCB5 and their organization in the thylakoid membrane</strong>".</p> <p><strong>FIGURE </strong><strong>1</strong><strong><em> </em></strong><strong>Phenotype and photosynthetic characteristics of the <em>lhcb5</em> mutant. </strong>(A) Phenotype of <em>Arabidopsis thaliana</em> wild type (WT) and <em>lhcb5</em> mutant plants grown at controlled conditions for 6 weeks (8 h light/16 h dark cycle; 22/20°C; <br>110 µmol photons m<sup>-2</sup> s<sup>-1</sup>; 60% humidity). (B) Immunoblot analysis of thylakoid membranes of WT and <em>lhcb5</em> mutant plants with antibody directed against LHCB5. (C) Content of light-harvesting proteins LHCB1-6 evaluated relatively to the content of CP43 protein in the WT and the <em>lhcb5</em> mutant. The protein content was determined in isolated thylakoid membranes by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The columns represent means ± SD, individual points show technical replicates. All data passed the normality and equal variance tests and according to Student t-test the datasets of WT and <em>lhcb5</em> were not significantly different (α ≤ 0,05), except for the relative content of LHCB5/CP43. (D) Protein ratios of photosynthesis-related thylakoid membrane proteins of the WT and the <em>lhcb5</em> mutant. The protein content was determined by LC-MS/MS in isolated thylakoid membranes. PSII represents the sum of relative PG intensities of D1, D2, CP43, and CP47 proteins, LHCII - LHCB1–3 proteins, PSI - PSAA and PSAB proteins, LHCI - LHCA1–4 proteins, ATPS - α and β subunits of ATP synthase, and cyt f represents cytochrome f component of cytochrome b<sub>6</sub>f complex. The columns represent means ± SD, individual points show technical replicates. All data passed the normality and equal variance tests and according to Student t-test the datasets of WT and <em>lhcb5</em> are not significantly different (α ≤ 0,05).</p> <p><strong>FIGURE </strong><strong>2</strong><strong><em> </em></strong><strong>Separation and structural characterization of PSII supercomplexes from <em>lhcb5</em> mutant plants. </strong>(A) Separation of pigment–protein complexes from thylakoid membranes from <em>Arabidopsis thaliana</em> WT and <em>lhcb5</em> mutant plants by clear native polyacrylamide gel electrophoresis. Thylakoid membranes were solubilized by n-dodecyl α-D-maltopyranoside (detergent/chlorophyll mass ratio of 10). (B) Electron density maps of characteristic PSII supercomplexes from the separated green gel bands of the <em>lhcb5 </em>mutant designated as C<sub>2</sub>S<sub>2</sub>M<sub>2</sub>, C<sub>2</sub>S<sub>2</sub>M and C<sub>2</sub>SM. Projection maps are fitted by corresponding structural high-resolution models of PSII supercomplexes (Van Bezouwen et al., 2017) without LHCB5. Individual PSII subunits are color-coded according to (E). (C), (D) Comparison of structural models of the PSII C<sub>2</sub>S<sub>2</sub>M<sub>2</sub> supercomplexes from <em>Arabidopsis thaliana</em> WT and the <em>lhcb5</em> mutant. (C) Projection map of the PSII C<sub>2</sub>S<sub>2</sub>M<sub>2</sub> supercomplex from <em>Arabidopsis thaliana</em> wild type (Ilíková et al., 2021) fitted by the high-resolution structure from Van Bezouwen et al. (2017). (D) Overlay of structural models of the PSII C<sub>2</sub>S<sub>2</sub>M<sub>2</sub> supercomplex from <em>Arabidopsis thaliana</em> wild type (surface representation, partially transparent) and the <em>lhcb5</em> mutant shows a specific shift of the S and M LHCII trimers as well as the monomeric antenna LHCB6 (see arrows in the corresponding colors) due to the absence of LHCB5. Individual PSII subunits are color-coded according to (E). (E) Legend of individual PSII subunits, which are color-coded as follows: PSII core complex in green, S and M LHCII trimers in red and blue, respectively, and the monomeric antenna proteins, LHCB4, LHCB5, LHCB6, in yellow, cyan, and dark orange, respectively.</p> <p><strong>FIGURE </strong><strong>3</strong><strong> </strong><strong>Organization of photosystem II in thylakoid membranes of the <em>lhcb5</em> mutant. </strong>(A, B) Examples of electron micrographs of negatively stained thylakoid membrane isolated from the <em>lhcb5</em> mutant with densities corresponding to the PSII core complex. Representative picture of PSII supercomplexes “randomly” organized (A) and organized into 2D semi-crystalline array (B). (C, D, E) Projection maps of PSII megacomplexes obtained using image analysis of PSII particles in thylakoid membranes. Three specific associations of PSII supercomplexes are shown and fitted by the model of PSII supercomplex C<sub>2</sub>S<sub>2</sub>M<sub>2</sub> without LHCB5 (see Figure 2B). Megacomplexes are averaged projections of 1 925 (C), 2 241 (D), and 2 305 (E) particles. (F) Isolated PSII particle from thylakoid membranes with “randomly” organized PSII as an average projection of 3 741 particles fitted by the model of PSII supercomplex C<sub>2</sub>S<sub>2</sub>M<sub>2</sub> without LHCB5 (see Figure 2B). (G) PSII supercomplexes organized into 2D semi-crystalline array as an average projection of 418 sub-areas together with the fitted model of PSII C<sub>2</sub>S<sub>2</sub>M<sub>2</sub> supercomplexes (see Figure 2B). Projection maps of PSII supercomplexes show core complexes in green, S trimers in red, M trimers in blue, LHCB4 in yellow, and LHCB6 in dark orange color.</p> <p><strong>FIGURE </strong><strong>4</strong><strong><em> </em></strong><strong>Distribution of mutual distances between neighboring photosystem II particles in thylakoid membranes of <em>Arabidopsis thaliana</em> WT and the <em>lhcb5 </em>mutant. </strong>The distances between two closest neighboring PSII supercomplexes were analyzed using EM. Histograms are normalized to the maximum.</p> <p><strong>SUPPORTING FIGURE 1 Analysis of chosen photosystem I and II photosynthesis related parameters. </strong>(A) Quantum yield of photochemistry of PSI - Y(I). (B) Quantum yield of photochemistry of PSII - Y(II). (C) Non-photochemical quenching – NPQ. Parameters were measured during actinic light exposure (800 µmol photons m<sup>-2</sup> s<sup>-1</sup>) and dark relaxation using saturating light pulses (300 ms, 10 000 µmol photons m<sup>-2</sup> s<sup>-1</sup>) in WT and <em>lhcb5</em> mutant plants. Results represent mean values ± SD from 4 measurements. Plants were dark-adapted for 30 min before the measurement.</p> <p><strong>SUPPORTING FIGURE 2 Single-particle image analysis and classification of protein complexes from CN−PAGE C<sub>2</sub>S<sub>2</sub>M<sub>2 </sub>band from the Arabidopsis <em>lhcb5</em> mutant (Figure 2A). </strong>Number of averaged projections in given classes are indicated.</p> <p><strong>SUPPORTING FIGURE 3 Single-particle image analysis and classification of protein complexes from CN−PAGE C<sub>2</sub>S<sub>2</sub>M<sub> </sub>band from the Arabidopsis <em>lhcb5</em> mutant (Figure 2A). </strong>Number of averaged projections in given classes are indicated.</p> <p><strong>SUPPORTING FIGURE 4 Single-particle image analysis and classification of protein complexes from CN−PAGE C<sub>2</sub>SM band from the Arabidopsis <em>lhcb5</em> mutant (Figure 2A). </strong>Number of averaged projections in given classes are indicated.</p> <p><strong>SUPPORTING FIGURE 5<em> </em>A histogram of the relative abundance of PSII semi-crystalline arrays </strong><strong>in thylakoid membranes of Arabidopsis </strong><strong><em>lhcb5</em></strong><strong> mutant. </strong>The bars represent the number of electron micrographs where the 2D arrays cover the indicated percentage of the membrane. The histogram was obtained by evaluation of 50 randomly selected images.</p> <p><strong>SUPPORTING TABLE 1</strong> Physiological parameters of Arabidopsis WT and lhcb5 mutant plants.</p> <p><strong>SUPPORTING TABLE 2 </strong>Density of bands corresponding to LHCB5-less PSII supercomplexes evaluated relatively to WT.</p> <p><strong>Figure 1 C-D</strong> - source data for Figure 1. (panels C-D) Documentation of similar physiology of Arabidopsis thaliana wild type (WT), and its mutant with loss of LHCB5 protein subunit (lhcb5): (C) relative content of photosysthesis related proteins in thylakoid membranes of Arabidopsis thaliana lhcb5 genotype normalised to WT determined by LC-MS/MS; (D) relative protein ratios normalised to WT of photosynthesis related thylakoid membrane proteins of Arabidopsis thaliana lhcb5 genotype determined in isolated thylakoid membranes by LC-MS/MS.</p> <p><strong>Figure 4</strong> - source data for Figure 4. Relative distribution of photosystem II (PSII) distances in thylakoid grana membranes of Arabidopsis thaliana wild type (WT) and mutant with missing LHCB5 protein (lhcb5).</p> <p><strong>Supporting figure 1</strong> Source data for supporting figure 1 Photosynthesis related parametres describing PSI and PSII function. (A) quantum yield of photochemistry of PSI (Y(I)) in Arabidopsis thaliana WT and lhcb5 genotype leaves during red acitinic light exposure and dark relaxation; (B) quantum yield of photochemistry of PSII (Y(II)) in Arabidopsis thaliana WT and lhcb5 genotype leaves during red acitinic light exposure and dark relaxation; (C) non-photochemical quenching of Arabidopsis thaliana genotypes: The level of NPQ estimated during red acitinic light exposure and dark relaxation of WT and lhcb5 leaves.</p> <p><strong>Supporting figure 5</strong> Source data for Supplement figure 4. Relative abundance of 2D PSII arrays in the thylakoid membranes of Arabidopsis thaliana lhcb5 mutant from 50 randomly selected images.</p> <p><strong>Supporting table 1 - source data</strong> Source data for supporting table 1. Physiological parameters of witl type (WT) Arabidopsis thaliana and its mutant lacking LHCB5 protein (lhcb5): Repetitions of data measured for each genotypes.</p> <p><strong>Supporting table 2 - source data</strong> Source data for supporting table 2. Density of bands corresponding to LHCB5-less PSII supercomplexes evaluated relatively to WT: Repetitions of data measured for each genotypes.</p> <p><strong>Figure 1B source WB </strong>Source WB picture for FIGURE 1B.</p> <p><strong>Figure 1B source WB, marker </strong>Source WB picture with molecular marker for FIGURE 1B.</p>
Datasets for the paper "High-frequency voltage-driven vibrations in dielectric elastomer membranes" by G. Moretti et al.
<p>This upload contains the numerical datasets used for the numerical plots reported in the paper "High-frequency voltage-driven vibrations in dielectric elastomer membranes" by G. Moretti et al., Mechanical Systems and Signal Processing, Elsevier, 2022 (https://doi.org/10.1016/j.ymssp.2021.108677).</p> <p>Please refer to the readme file for information on the files structures and content. </p>
Rapid Fabrication of Membrane-IntegratedThermoplastic Elastomer Microfluidic Devices
<p>Txt files contain experimental data sets used to obtain the results of Fig. 3 and 4 and the OB1 code. Data files for Fig 3. are named GapSize_membraneConfiguration_#_delaminationPressure and data files for Fig 4. Are named agingTime_membraneConfiguration_incubationCondition_#.</p>
Beyond Substrates: Strain Engineering of Ferroelectric Membranes
<p>Dataset for publication:</p> <p>Beyond Substrates: Strain Engineering of Ferroelectric Membranes</p> <p>D. Pesquera, E. Parsonnet, A. Qualls, R. Xu, A.J. Gubser, J. Kim, Y. Jiang, G. Velarde, Y. Huang, H.Y. Hwang, R. Ramesh, and L.W. Martin, Adv. Mater. <strong>32</strong>, 2003780 (2020).</p> <p> </p> <p>Matlab code for producing Fig.1d, Fig.2a and Fig.4b is given in .txt files</p>
Segmentation of membrane of mouse, sea urchin and human oocytes from transmitted light images
<p>This dataset has been presented in our paper "An interpretable and versatile machine learning approach for oocyte phenotyping", in bioRxiv.</p> <p>It contains images acquired in transmitted light with different settings of mouse and human oocytes and sea urchin eggs, with the corresponding ground-truth of the membrane segmentation. Mouse oocyte images were taken before and during oocyte maturation (meiosis I). Some human oocyte images were taken during oocyte maturation (meiosis I), and some are M-II oocytes just after fertilization. Sea urchin images contains both fertilized and unfertilized eggs.</p> <p> </p>
Tabular datasets for "In situ structural analysis reveals membrane shape transitions during autophagosome formation"
<p>Tabular source data for all plots in the manuscript "In situ structural analysis reveals membrane shape transitions during autophagosome formation". The article is available at https://doi.org/10.1101/2022.05.02.490291. The naming of the sheets in the .xlsx files corresponds to the figure number and panel.</p>
Intermolecular interactions in G protein-coupled receptor allosteric sites at the membrane interface from molecular dynamics simulations and quantum chemical calculations
<p>Allosteric modulators are called to be promising candidates in G protein-coupled receptor (GPCR) drug development by displaying target selectivity and fewer side effects. Among the allosteric sites known to date, extrahelical cavities represent an uncharacteristic binding location that raises many questions about the ligand interactions and stability; the binding site structure, and how all of these are affected by lipid molecules. In this work, we analyze the dynamics and interactions in the PAR2, C5aR1, and GCGR receptors unbound and bound to allosteric modulators at the receptor-lipid interface using molecular dynamics simulations in three lipid compositions. In addition, we performed quantum chemical calculations to further explore electrostatic interactions and the strength of atom pairwise contacts in the stabilization of the ligand-receptor complexes. We show that besides classical hydrogen bonds weak polar interactions such as O-HC, O-Br, and S-HC contacts and aromatic interactions contribute to the binding of allosteric modulators at the extrahelical sites in the middle of the membrane. The allosteric cavities are open and detectable in various membrane compositions but not always predicted as druggable. The availability of polar atoms for interactions in such cavities can be assessed by water molecules from the simulations. Although ligand-lipid interactions are weak, the lipid tails play a role in sizing and shaping the large part of the allosteric cavity. </p> <p>You will find the following files:</p> <ul> <li>Input files of the equilibration and production protocols of MD simulations (MD_simulations_inputs.zip)</li> <li>Input files and coordinate files of F-SAPT and NCIPLOT calculations (quantum_chemical_coordiates_inputs.zip)</li> </ul>
Datasets for the paper "Finite element modelling of the vibro-acoustic response in dielectric elastomer membranes"
<p>This upload contains the numerical datasets used for the numerical plots reported in the paper "Finite element modelling of the vibro-acoustic response in dielectric elastomer membranes" by G. Moretti et al., In <em>Electroactive Polymer Actuators and Devices (EAPAD) XXIV</em> (https://doi.org/10.1117/12.2612784).</p> <p>Please refer to the readme file for information on the files structure and content. </p>
The C-terminus of the oncoprotein TGAT is necessary for plasma membrane association and efficient RhoA-mediated signaling
<p>The figures and raw data that are presented in the paper "<strong>The C-terminus of the oncoprotein TGAT is necessary for plasma membrane association and efficient RhoA-mediated signaling</strong>"</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.