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1,048 results for “unveil”
Dataset of "Molecular Dynamics Simulations Unveil the Aggregation Patterns and Salting out of Polyarginines at Zwitterionic POPC Bilayers in Solutions of Various Ionic Strengths"
<p>Molecular dynamics simulations are performed for a series of model cell-penetrating peptides (in particular nona-arginines) in aqueous solutions, in contact with model phosphocholine (POPC) membranes in conditions of different ionic strengths. The unusual aggregation properties of peptides at model lipid bilayers are analyzed and different sizes and lifetimes of aggregates are presented.<br>This dataset contains molecular dynamics simulation data with trajectories, input files, and topology files for all studied systems. They contain low peptide concentration in water, low NaCl concentration, high NaCl concentration, low CaCl2 concentration, and high CaCl2 concentration.<br>In addition to low peptide concentration, high peptide concentration in water, low NaCl concentration, high NaCl concentration, low CaCl2 concentration, and high CaCl2 concentration are also studied.</p>
Unveiling the potential of redox chemistry to form size tunable, high index silicon particles
<p>In the present work, the effect of changing the precursor ratio of silicon between sodium silicde and a hexacoordinated silicon complex to form various sizes of particles is studied. TEM images show the size difference between particles produced with different ratios. Particles produced with a 1:1 ratio are 45 nm in diameter and up to a 1:4 precursor ratio is used to make 230 nm particles. X-ray diffraction patterns confirm the presence of crystalline silicon for all sizes, while Raman spectroscopy shows how different degree of oxidation occurs thanks to different particle sizes, shifting the Raman peak. The surface chemistry is also studied to evidence the growth mechanism.</p>
Data underlying the paper titled "Positron unveiling high mobility graphene stack interfaces in Li-ion cathodes"
<p>The folder includes data regarding 4 figures shown in this paper. </p> <p>FIG_1: Simulation structure of 6 layers of graphene bulk and slab (6C_Bulk.vasp, 6C_Slab.vasp), LiCoO2(LCO_336.vasp), ABA Graphite coating LiCoO2(G@LCO.vasp). </p> <p>FIG_2: Raw data of band structure of Graphite coating LCO (Band_G@LCO_EIGENVAL), Density of States (DOS_G@LCO_DOSCAR)</p> <p>FIG_3: Calculated plane-averaged charge density difference of SW-G@LCO perpendicular to (001) plane at the equilibrium distance. G@LCO_CHGCAR, LCO_CHGCAR, C_CHGCAR are the CHGCAR for Graphitte coating LCO, LCO, graphite, respectively. </p> <p>d24_diff.vasp is the charge difference</p> <p>d24_PACD.dat is the plane-averaged charge density difference. </p> <p>FIG_4: posden indicates the positron density, while posvtot means positron potential. Data are named by their structure. </p>
Data for: World's human migration patterns in 2000-2019 unveiled by high-resolution data
<p> </p> <p>This dataset provides a<strong> global gridded (5 arc-min resolution) detailed annual net-migration dataset for 2000-2019</strong>. We also provide global annual birth and death rate datasets – that were used to estimate the net-migration – for same years. The dataset is presented in details, with some further analyses, in the following publication. <strong><em>Please cite this paper when using data. </em></strong></p> <p>Niva et al. 2023. World's human migration patterns in 2000-2019 unveiled by high-resolution data. Nature Human Behaviour 7: 2023–2037. Doi: <a href="https://doi.org/10.1038/s41562-023-01689-4" target="_blank" rel="noopener">https://doi.org/10.1038/s41562-023-01689-4</a> </p> <p>You can explore the data in our online net-migration explorer: <a href="https://wdrg.aalto.fi/global-net-migration-explorer/" target="_blank" rel="noopener">https://wdrg.aalto.fi/global-net-migration-explorer/</a></p> <p> </p> <p><strong>Short introduction to the data</strong></p> <p>For the dataset, we collected, gap-filled, and harmonised: </p> <ol> <li>a comprehensive national level birth and death rate datasets for altogether 216 countries or sovereign states; and </li> <li>sub-national data for births (data covering 163 countries, divided altogether into 2555 admin units) and deaths (123 countries, 2067 admin units).</li> </ol> <p>These birth and death rates were downscaled with selected socio-economic indicators to 5 arc-min grid for each year 2000-2019. These allowed us to calculate the 'natural' population change and when this was compared with the reported changes in population, we were able to estimate the annual net-migration. See more about the methods and calculations at Niva et al (2023). </p> <p><strong><em>We recommend using the data either over multiple years (we provide 3, 5 and 20 year net-migration sums at gridded level) or then aggregated over larger area (we provide adm0, adm1 and adm2 level geospatial polygon files). This is due to some noise in the gridded annual data. </em></strong></p> <p>Due to copy-right issues we are not able to release all the original data collected, but those can be requested from the authors. </p> <p> </p> <p><strong>List of datasets</strong></p> <p><em>Birth and death rates: </em></p> <p>raster_birth_rate_2000_2019.tif: Gridded birth rate for 2000-2019 (5 arc-min; multiband tif) </p> <p>raster_death_rate_2000_2019.tif: Gridded death rate for 2000-2019 (5 arc-min; multiband tif) </p> <p>tabulated_adm1adm0_birth_rate.csv: Tabulated sub-national birth rate for 2000-2019 at the division to which data was collected (subnational data when available, otherwise national) </p> <p>tabulated_ adm1adm0_death_rate.csv: Tabulated sub-national death rate for 2000-2019 at the division to which data was collected (subnational data when available, otherwise national) </p> <p> </p> <p><em>Net-migration: </em></p> <p>raster_netMgr_2000_2019_annual.tif: Gridded annual net-migration 2000-2019 (5 arc-min; multiband tif) </p> <p>raster_netMgr_2000_2019_3yrSum.tif: Gridded 3-yr sum net-migration 2000-2019 (5 arc-min; multiband tif) </p> <p>raster_netMgr_2000_2019_5yrSum.tif: Gridded 5-yr sum net-migration 2000-2019 (5 arc-min; multiband tif) </p> <p>raster_netMgr_2000_2019_20yrSum.tif: Gridded 20-yr sum net-migration 2000-2019 (5 arc-min) </p> <p> </p> <p>polyg_adm0_dataNetMgr.gpkg: National (adm 0 level) net-migration geospatial file (gpkg) </p> <p>polyg_adm1_dataNetMgr.gpkg: Provincial (adm 1 level) net-migration geospatial file (gpkg) (if not adm 1 level division, adm 0 used) </p> <p>polyg_adm2_dataNetMgr.gpkg: Communal (adm 2 level) net-migration geospatial file (gpkg) (if not adm 2 level division, adm 1 used; and if not adm 1 level division either, adm 0 used) </p> <p> </p> <p><strong>Files to run online net migration explorer </strong></p> <p>masterData.rds and admGeoms.rds are related to our online ‘Net-migration explorer’ tool (<a href="https://wdrg.aalto.fi/global-net-migration-explorer/">https://wdrg.aalto.fi/global-net-migration-explorer/</a>). The source code of this application is available in <a href="https://github.com/vvirkki/net-migration-explorer">https://github.com/vvirkki/net-migration-explorer</a>. Running the application locally requires these two .rds files from this repository. </p> <p> </p> <p><strong>Metadata </strong></p> <p><em>Grids: </em></p> <p>Resolution: 5 arc-min (0.083333333 degrees) </p> <p>Spatial extent: Lon: -180, 180; -90, 90 (xmin, xmax, ymin, ymax) </p> <p>Coordinate ref system: EPSG:4326 - WGS 84 </p> <p>Format: Multiband geotiff; each band for each year over 2000-2019 </p> <p>Units: </p> <ul> <li> <p>Birth and death rates: births/deaths per 1000 people per year </p> </li> <li> <p>Net-migration: persons per 1000 people per time period (year, 3yr, 5yr, 20yr, depending on the dataset) </p> </li> </ul> <p> </p> <p><em>Geospatial polygon (gpkg) files: </em></p> <p>Spatial extent: -180, 180; -90, 83.67 (xmin, xmax, ymin, ymax) </p> <p>Temporal extent: annual over 2000-2019 </p> <p>Coordinate ref system: EPSG:4326 - WGS 84 </p> <p>Format: gkpk </p> <p>Units: </p> <ul> <li> <p>Net-migration: persons per 1000 people per year </p> </li> </ul>
Unveiling the atomistic and electronic structure of NiII–NO adduct in a MOF-based catalyst by EPR spectroscopy and quantum chemical modelling
<p><strong>Description of the dataset: </strong></p> <ul> <li><strong>Data type</strong>: Experimental spectroscopic measurements, computer simulation and analysis</li> <li>Files are with filename extensions: <strong>DSC</strong>, <strong>DAT</strong>, <strong>m</strong>, <strong>txt</strong></li> <li>Information on <strong>origin of the data</strong>:</li> </ul> <ul> <li>EPR spectroscopic measurements with filename extensions <strong>DSC</strong>, <strong>DTA.</strong></li> <li>EPR spectroscopic simulation and analyses with filename extension <strong>m</strong>.</li> <li>EPR spectra are exported as <strong>txt</strong> files in ASCII format.</li> </ul> <ul> <li>X-band CW-EPR spectroscopic measurements were generated by EMX spectrometer equipped with SHQ cavity produced by Bruker.</li> <li><strong>If the dataset includes multiple files that relate to each other:</strong> <ul> <li>Files in <strong>PARACAT_WP4_20230706_01_CW_Xband </strong>folder includes X-band CW-EPR spectroscopic measurements; original data are in DTA/DSC and txt formats.</li> <li>Files in <strong>PARACAT_WP4_20230706_02_HYSCORE </strong>and <strong>PARACAT_WP4_20230706_03_ENDOR </strong>folders include X-band HYSCORE and ENDOR data; original data are in DTA/DSC and txt formats.</li> <li>Files in <strong>PARACAT_WP4_20230706_ 04_MATLAB</strong> and<strong> PARACAT_WP4_20230706_ 05_Modelling</strong> folders include matlab and computer simulations/analyses of the EPR measurements; data are in m and txt formats.</li> <li>File <strong>PARACAT_WP4_20230706_ 06_Origin</strong> include origin plotted data</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>Information on</strong>: <ul> <li>specialized abbreviations: <strong>MFU– </strong>MFU-4l:NO<sub>2</sub> MOF material</li> <li>NiNO – NO adsorbed MFU-4l:NO<sub>2</sub> MOF</li> <li>@10K – measured at 10 K</li> <li>definitions of variables: <strong>Magnetic field, Temperature.</strong></li> <li>units of measurement: <strong>Gauss (G), K, degree (°), milliTesla (mT)</strong>.</li> </ul> </li> </ul>
Data supplement to 'Vertical land motion reconstruction unveils non-linear effects on relative sea level changes from 1900-2150'
<p>This is a data supplement to <strong>'Vertical land motion reconstruction unveils non-linear effects on relative sea level changes from 1900-2150</strong>'. It presents a global-scale Vertical Land Motion (VLM) reconstruction that resolves height changes in the period 1995-2020. It is based on the joint probabilistic analysis of an extensive network of more than 11,000 GNSS stations, tide gauges, and satellite altimetry. The approach used to derive this reconstruction is described in the paper. The dataset variables are explained in the .pdf file.</p>
Earthquakes unveil the global-scale fractality of the lithosphere
<p>The repository contains the post-processed data required to produce the figures of the article entitled <i>"Earthquakes unveil the global-scale fractality of the lithosphere"</i> under consideration in Communications Earth & Environment.</p><p>Data are divided in directories, each corresponding to an article figure and numbered accordingly.</p>
BSEC Method for Unveiling Clusters and 83 New Clusters
<p>Data of star clusters that are used in the paper entitled "BSEC method for unveiling open clusters and its application to Gaia DR3: 83 new clusters".</p>
Data and Code for "Why are generalists the 'winners' of habitat loss? Unveiling the process underlying specialist-generalist replacements in fragmented landscapes"
<p><span>Data and R-based workflow for the study "Why are generalists the ‘winners’ of habitat loss? Unveiling the process underlying specialist-generalist replacements in fragmented landscapes".</span></p>
Supporting data for "Unveiling Vertebrate Development Dynamics in Frog Xenopus laevis using Micro-CT Imaging"
<p>The dataset contains X-ray Micro Computed Tomography data of Xenopus laevis frog. There are twenty datasets of ten individual animals. Each animal was CT scanned twice – once as a native scan to visualize the hard tissues, and once contrast-stained to visualize the soft tissues. The datasets include nine developmental stages (NF44-45, NF52, NF53, NF54, NF57, NF59, NF62, NF66 and adult). There are two adults, one male and one female. The CT data (in 8bit .tiff format compressed as .tar.gz files) are supported by .stl files created from each dataset. The database also includes .stl files of selected structures of interest (body, skeleton, skull, brain and guts of individual animals).</p>
Unveiling Genomic Rearrangements in Engineered iPSC Lines
<p>Bionano smap files of Dual Analysis of each detected unique SV not present in parental cells. Only SVs within 12kbp of a canonical gene are presented for clarity.</p>
Dataset of "Unveiling the gating mechanism of CRAC channel: a computational study"
<p>Molecular Dynamics simulation trajectories of CRAC ion channel. All of the trajectories can be visualized using the topology file CRAC_topol.prmtop. Three trajectories refer to equilibrium simulations of the closed state of the channel PDB: 4HKR (4HKR_equil_100ns.dcd) and of the two putative open states PDB: 6BBF (6BBF_equil_100ns.dcd) and PDB ID: 6AKI (6AKI_equil_100ns.dcd). The remaining two trajectories refer to Targeted Molecular Dynamics simulations steering the molecular system from the closed to the open state (TMD_C_to_O_100ns.dcd) and from the open to the closed state (TMD_O_to_C_500ns.dcd).</p> <p>All simulations have been performed with the NAMD 2.11b2 suite of programs using the Amber ff15ipq force field for the protein, the Lipid17 force field for the phospholipids and the SPC/E water model. </p> <p> </p> <p> </p>
NMR Data for "Unveiling a Key Catalytic Pocket for the Ruthenium NHC-Catalysed Asymmetric Heteroarene Hydrogenation" (DOI: 10.1039/D1SC06409F)
<p># NMR Data for "Unveiling a Key Catalytic Pocket for the Ruthenium NHC-Catalysed Asymmetric Heteroarene Hydrogenation" (DOI: 10.1039/D1SC06409F)</p> <p>In the following, the original NMR Data for the publication "Unveiling a Key Catalytic Pocket for the Ruthenium NHC-Catalysed Asymmetric Heteroarene Hydrogenation" (DOI: 10.1039/D1SC06409F) is provided. </p> <p>## Experimental methodology and associated data</p> <p>### Dataset 200113.40a</p> <p>Inside an argon filled glovebox, 4.6 mg of **1-A** (5.4 µmol) was dissolved in 0.65 mL THF-d<sub>8</sub> (distilled over sodium/benzophenone and stored over 3 Å molecular sieves), yielding a clear, dark yellow solution. The solution was then transferred into a medium pressure J Young NMR tube and sealed. Subsequently, initial NMR spectra under argon atmosphere were recorded (t = 0 h).</p> <p>Afterwards, 2 bar of H2 pressure were applied to the J Young NMR tube, resulting in a partial H<sub>2</sub> pressure of 1 bar (due to the presence of 1 bar argon). After shaking to dissolve the added H<sub>2</sub>, a slow color change to orange could be observed. The reaction was monitored using 1H NMR (Bruker AV 400, 400 MHz), showing consumption of dissolved H<sub>2</sub> as evidenced by a decrease in intensity for the H<sub>2</sub> signal at δ(1H) = 4.55 ppm. Six hours after the first addition of H<sub>2</sub>, the J Young NMR tube was re-pressurized with 2 bar H<sub>2</sub>, and again after 36 h, shaking the NMR tube regularly to dissolve H<sub>2</sub>. After the third pressurization, no further decrease of dissolved H<sub>2</sub> could be observed.</p> <p>#### NMR experiments and timestamps</p> <p>File name | NMR Experiment | Time stamp / h (relative to H<sub>2</sub> addition)<br> --- | --- | ---<br> 200113.40a.1 | 1H | 0<br> 200113.40a.2 | 1H | 0<br> 200113.40a.3 | 1H | 0.5<br> 200113.40a.4 | 1H | 1<br> 200113.40a.5 | 1H | 2.5<br> 200113.40a.6 | 1H | 2.5<br> 200113.40a.7 | 1H | 5 <br> 200113.40a.8 | 1H COSY-45 | 5<br> 200113.40a.9 | 1H | 6.5<br> 200113.40a.10 | 1H | 22.5<br> 200113.40a.11 | 1H | 30<br> 200113.40a.12 | 1H | 31<br> 200113.40a.13 | 29Si-inept | 31<br> 200113.40a.14 | 1H-29Si HMBC | 31<br> 200113.40a.15 | 1H | 45.5<br> 200113.40a.16 | 1H-29Si HMBC | 45.5<br> 200113.40a.17 | 1H | 55<br> 200113.40a.18 | 1H | 69.5<br> 200113.40a.110 | 1H (larger measurement window) | 22.5<br> 200113.40a.111 | 1H (larger measurement window) | 30<br> 200113.40a.115 | 1H (larger measurement window) | 45.5<br> 200113.40a.117 | 1H (larger measurement window) | 55<br> 200113.40a.118 | 1H (larger measurement window) | 69.5</p> <p>### Dataset 200117.40a</p> <p>69.5 h after the first addition of H<sub>2</sub> no significant changes could be observed in the 1H NMR spectra anymore. At this point, 0.15 mL of a 0.052 M solution of benzofuran in THF-d<sub>8</sub> (7.8 µmol benzofuran, ca. 1.5 equivalents relative to **1-A**) were added to the NMR tube while applying 2 bar of H<sub>2</sub> pressure. No significant color change was observed upon addition of the substrate. Subsequently, the NMR tube was sealed and the reaction was monitored using 1H NMR for an additional 119 h, especially following the hydride signals at δ(1H) = −3.7 ppm and δ(1H) = −3.8 ppm as well as the signals of 2,3-dihydrobenzofuran at δ(1H) = 4.48 ppm and δ(1H) = 3.15 ppm. After 119 h of reaction time, the color of the reaction solution had changed to light orange.</p> <p>#### NMR experiments and timestamps</p> <p>File name | NMR Experiment | Time stamp / h (relative to substrate addition)<br> --- | --- | ---<br> 200117.40a.1 | 1H | 0.5<br> 200117.40a.2 | 1H | 1.5<br> 200117.40a.3 | 1H | 7<br> 200117.40a.4 | 1H | 24<br> 200117.40a.5 | 1H | 24.5 <br> 200117.40a.6 | 1H | 72 <br> 200117.40a.7 | 1H COSY-45 | 72<br> 200117.40a.101 | 1H (larger measurement window) | 0.5<br> 200117.40a.103 | 1H (larger measurement window) | 7<br> 200117.40a.104 | 1H (larger measurement window) | 24</p>
Metabolic alterations in Strongyloidiasis stool samples unveil potential biomarkers of infection_dataset
<p>Strongyloidiasis, a parasitosis caused by <em>Strongyloides stercoralis</em> in humans, is a very prevalent infection in tropical or subtropical areas. Gaps on public health strategies corroborates to the high global incidence of strongyloidiasis especially due to challenges involved on its diagnosis. Based on the lack of a gold-standard diagnostic tool, we aimed to present a metabolomic study for the assessment of stool metabolic alterations. Stool samples were collected from 25 patients segregated into positive for strongyloidiasis (n = 10) and negative control (n = 15) and prepared for direct injection high-resolution mass spectrometry analysis. Using metabolomics workflow, 18 metabolites were annotated increased or decreased in strongyloidiasis condition, from which a group of 5 biomarkers comprising caprylic acid, mannitol, glucose, lysophosphatidylinositol and hydroxy-dodecanoic acid demonstrated accuracy over 89% to be explored as potential markers. The observed metabolic alteration in stool samples indicates involvement of microbiota remodeling, parasite constitution, and host response during <em>S. stercoralis</em> infection.</p>
Explainable AI for unveiling deep learning pollen classification model - Pollen dataset
<p>Dataset consists automatic particle detector Rapid-E measurements of pollen grains from 12 classes: Acer, Alnus, Alopecurus, Carex, Cupressus, Dactylis, Juglans, Morus, Platanus, Populus, Salix and Ulmus. Data are available i json format.</p> <p>Dataset also contains preprocessed data packed into csv files of 3 modalities: spectrum, lifetime, scattering and additional features from scattering and lifetime data are also available. These are ready to be used with machine learning models. Labels 0, 1, 2, ... 11 correspond to alphabetical order of examined pollen classes Acer, Alnus, Alopecurus ... Ulmus.</p> <p> </p>
Supplementary Information and Data for "Unveiling the 3D Morphology of Epitaxial GaAs/AlGaAs Quantum Dots"
<p>Raw and processed TEM and AFM data for the article <strong><em>Unveiling the 3D Morphology of Epitaxial GaAs/AlGaAs Quantum Dots</em></strong>.</p> <p>Paper: <a href="https://doi.org/10.1021/acs.nanolett.4c02182" target="_blank" rel="noopener">https://doi.org/10.1021/acs.nanolett.4c02182</a></p> <p>Preprint: <a href="https://arxiv.org/abs/2405.16073" target="_blank" rel="noopener">https://arxiv.org/abs/2405.16073</a></p> <p>The TEM data has a PDF information file included with description of the file types and how to open them.</p> <p>The AFM Nanosurf .nid files can be opened, e.g., with <a href="http://gwyddion.net/" target="_blank" rel="noopener">Gwyddion</a>.</p>
Single-cell transcriptomic profiling unveils dysregulation of cardiac progenitor cells and cardiomyocytes in a mouse model of maternal hyperglycemia
<p>Congenital heart disease (CHD) is the most prevalent structural malformations of the heart affecting ∼1% of live births. To date, both damaging genetic variations and adverse environmental exposure such as maternal diabetes have been found to cause CHD. Clinical studies show ∼fivefold higher risk of CHD in the offspring of mothers with pregestational diabetes. Maternal pregestational diabetes affects the gene regulatory networks key to proper cardiac development in the fetus. However, the cell-type specificity of these gene regulatory responses to maternal diabetes and their association with the observed cardiac defects in the fetuses remains unknown. To uncover the transcriptional responses to maternal diabetes in the early embryonic heart, we used an established murine model of pregestational diabetes. In this model, we have previously demonstrated an increased incidence of CHD. Here, we show maternal hyperglycemia (matHG) elicits diverse cellular responses during heart development by single-cell RNA-sequencing in embryonic hearts exposed to control and matHG environment. Through differential gene-expression and pseudotime trajectory analyses of this data, we identified changes in lineage specifying transcription factors, predominantly affecting Isl1+ second heart field progenitors and Tnnt2+cardiomyocytes with matHG. Using in vivo cell-lineage tracing studies, we confirmed that matHG exposure leads to impaired second heart field-derived cardiomyocyte differentiation. Finally, this work identifies matHG-mediated transcriptional determinants in cardiac cell lineages elevate CHD risk and show perturbations in Isl1-dependent gene-regulatory network (Isl1-GRN) affect cardiomyocyte differentiation. Functional analysis of this GRN in cardiac progenitor cells will provide further mechanistic insights into matHG-induced severity of CHD associated with diabetic pregnancies.</p>
Unveiling Web Fingerprinting in the Wild Via Code Mining and Machine Learning
<p>Dataset of Javascripts used for training and testing the fingerprinting algorithms described in </p> <p>Rizzo, Valentino, Stefano Traverso, and Marco Mellia. "Unveiling Web Fingerprinting in the Wild Via Code Mining and Machine Learning." <em>Proceedings on Privacy Enhancing Technologies</em> 2021.1 (2021): 43-63.</p>
Unveiling metastable ensembles of GRB2 and the relevance of interdomain communication during folding - available data.
<p>The folding process of multidomain proteins is a highly intricate phenomenon involving the assembly of distinct domains into a functional three-dimensional structure. During this process, each domain may fold independently while interacting with other domains to form a functional protein. The folding of multidomain proteins can be influenced by various factors, including the composition and structure of each domain or the presence of disordered linker regions, as well as the surrounding environment. Misfolding of multidomain proteins can lead to the formation of non-functional structures associated with a range of diseases, including cancers and neurodegenerative disorders. Understanding this process is an essential step for many biophysical analyzes, such as stability, interaction, malfunctioning, and rational drug design. One such multidomain protein is the growth factor receptor-bound protein 2 (GRB2), an adaptor protein essential in regulating cell survival. GRB2 consists of one central Src Homology 2 (SH2) domain flanked by two Src Homology 3 (SH3) domains. The SH2 domain interacts with phosphotyrosine regions in other proteins, while the SH3 domains recognize proline-rich regions on protein partners during cell signaling. In this study, we combined computational and experimental techniques to investigate the folding process of GRB2. We sampled the conformational space through computational simulations and mapped the mechanisms involved by calculating free energy profiles, indicating possible intermediate states. From the molecular dynamics and trajectories, we used the Energy Landscape Visualization Method (ELViM), which allowed us to visualize a three-dimensional representation of the overall energy surface. We identified two possible parallel folding routes that cannot be seen in a one-dimensional analysis, with one occurring more frequently during folding. Supporting these results, we used DSC and fluorescence spectroscopy techniques to confirm these intermediate states in vitro. Finally, we analyzed the deletion of domains to compare our model outputs with previously published results, supporting the presence of interdomain modulation. Overall, our study highlights the significance of interdomain communication within the GRB2 protein and its impact on the formation, stability, and structural plasticity, which are crucial for its interaction with other proteins in key signaling pathways.</p> <p> </p>
Fig. 2 in Growth and reproduction in captivity unveils remarkable life-history plasticity in the smallnose fanskate, Sympterygia bonapartii (Chondrichthyes: Rajiformes)
Fig. 2. Egg cases and neonate of Sympterygia bonapartii born at Temaikèn Aquarium (Argentina). ah, anterior horns; mt, mucous tendrils; ph, posterior horns. Scale bar: 20 mm.
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.