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108 results for “ACE2”
All-atom 500-nano seconds Molecular Dynamics Simulations of SARS-CoV-2 Spike Receptor-binding Domain bound with ACE2
<p>Data includes all of the trajectories (1000) of classical all-atom molecular dynamics (MD) simulations of of SARS-CoV2 Spike Protein/ACE2 complex (PDB ID: 6M0J). In order to decrease the size of the file only protein rajectories were provided. Simulation has been performed with Desmond. Protein was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 500 nano-seconds (ns) production run was performed for the simulation.</p>
Spike-ACE2 interaction overview
<p>UnityMol 3D model export related to FAIR sharing of molecular visualization experiences illustrated with COVID-19-related data. See our paper (to come)</p>
All atom simulations snapshots and contact maps analysis scripts for SARS-CoV-2002 and SARS-CoV-2 spike proteins with and without ACE2 enzyme
<p><strong>The dataset contains a total of 40 snapshots of the four trajectories (10 snapshots each system = two per replica x 5 replicas/system):</strong></p> <ol> <li>SARS-CoV-2002 spike protein without ACE2</li> <li>SARS-CoV-2 spike protein without ACE2</li> <li>SARS-CoV-2002 spike protein with ACE2</li> <li>SARS-CoV-2 spike protein with ACE2</li> </ol> <p>Molecular dynamics simulation trajectories (320ns each) have been performed using the Amber ff14SB force field running with the Amber18 package at the the NSF-funded (OAC-1826915, OAC-1828163) ELSA high performance computing cluster at The College of New Jersey. Under the following simulation methodology:</p> <p><em>All-atom simulations were carried out with Amber18 (<a href="https://slack-redir.net/link?url=http%3A%2F%2Fambermd.org">ambermd.org</a>), and system components (protein, ions, water) were modeled with the included FF14SB and TIP3P parameter sets. Energy minimization used CPU pmemd, while later simulation stages used GPU pmemd. CoV2 and CoV1 systems with one RBD up (with/without ACE2) were solvated in 12 angstrom water shells. Cysteine residues identified in the initial models as having a disulfide bond (DB) were bonded using tLeap. All simulations used 0.150 M NaCl. Hydrogen mass repartitioning was applied only to the protein to enable a 4 fs timestep (<a href="https://slack-redir.net/link?url=https%3A%2F%2Fpubs.acs.org%2Fdoi%2Fabs%2F10.1021%2Fct5010406">https://pubs.acs.org/doi/abs/10.1021/ct5010406</a>). The SHAKE algorithm was applied to hydrogens, and a real-space cutoff of 8 angstroms was used. Periodic boundary conditions were applied and PME was used for long-range electrostatics. Minimization was by steepest descent (2000 steps) followed by conjugate gradient (3000 steps). Heating used two stages: (1) NVT heating from 0 K to 100 K (50 ps), and (2) NPT heating from 100 K to 300 K (100 ps). Restraints of 10 kcal mol<sup>-1</sup> angstrom<sup>-2</sup> were applied during minimization and heating to C-alpha atoms. During 6 ns of equilibration at 300 K C-alpha restraints were gradually reduced from 10 kcal mol<sup>-1</sup> angstrom<sup>-2</sup> to 0.1 kcal mol<sup>-1</sup> angstrom<sup>-2</sup>. Finally, restraints were released and 320 ns unrestrained production simulations were carried out for CoV2 and CoV1 systems. Production simulations began from the final equilibrated snapshots, and five copies of each system were simulated. As unrestrained systems can freely rotate we monitored simulations for any close contacts and found that in one copy of the CoV1 simulation without ACE2 and one RBD up that a few contacts close to 8 angstrom occur near the end of the 320 ns between the RBD and a different subdomain of the spike complex in a periodic image. However this did not influence analyzed structural properties which is verified by comparing results across simulations. The Monte Carlo barostat was used to maintain pressure (1 atm), and the Langevin thermostat was used to maintain 300 K temperature (collision frequency 1 ps<sup>-1</sup>), as implemented in Amber18. In aggregate, nearly 7 microseconds of simulation of systems ranging from 396,147 to 879,100 atoms was carried out for this work.</em><br> For further details on the trajectories, please contact Joseph Baker (bakerj@tcnj.edu).</p> <p><strong>Regarding the contact map analysis scripts (contactMaps_Analysis.tar.gz), they contain the following workflow:</strong></p> <p>contactmap --> source files from contact_map executable<br> process_nc.sh --> convert raw data from all-atom simulation to numbered PDB files and get the contact maps<br> frequency.lua --> read a set of PDB files and output the frequency count for each contact<br> consensus.fasta --> align sequence of Covid19 and SARS from Chimera<br> consensus.lua --> read data previously generated and compute the frequency per residue, among other things.<br> consensus.sh --> input information to consensus.lua<br> consensus.gp --> gnuplot script to plot figures</p> <p>This dataset and the code is part of tripartite collaboration between:</p> <ul> <li>The Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland (supported by the National Science Centre, Poland, under grant No. 2017/26/D/NZ1/0046)</li> <li>Department of Chemistry, The College of New Jersey, New Jersey, United States (supported by National Science Foundation under grant numbers OAC-1826915 and OAC-1828163).</li> <li>Jozef Stefan Institute, Ljubljana, Slovenia (supported by the Slovenian Research Agency (Funding No. P1-0055)).</li> </ul>
Simple structural views of the SARS spike glycoprotein complex with human angiotensin-converting enzyme 2 (ACE2)
<p>A set of 5 screenshots of UnityMol running the first example system. Three screenshots are from a multi-user virtual reality session with 3 participants, two screenshots illustrate a custom menu to drive the example more efficiently and make it simple for the end user.</p>
ACE2 EXPRESSION LEVELS IN THE BRAIN AND EYE
<p>To Whom It May Concern:</p> <p>As evidenced by multiple research studies, the SARS-CoV2 virus employs the angiotensin converting enzyme 2 (ACE 2) cell surface receptor to gain entry into host cells; this is a necessary first step for SARS-CoV2 invasion, replication and multiplication within human host cells; </p> <p>To ascertain what types of cells and tissues might be the most susceptible to SARS-CoV2 invasion, we have quantified ACE2 expression (at the mRNA level and some at the protein level) in about ~100 different cell types and tissues of the human brain, eye and central nervous system (CNS);</p> <p>Some of the data appear in this recent report from our laboratory:</p> <p>Lukiw WJ, Pogue A, Hill JM. SARS-CoV-2 Infectivity and Neurological Targets in the Brain. Cell Mol Neurobiol. 2020 Aug 25:1–8. doi: 10.1007/s10571-020-00947-7. Epub ahead of print. PMID: 32840758; PMCID: PMC7445393.</p> <p>and in the figures and tables associated with this publication; [appended; please also refer to the Abstract below]</p> <p>Another very recent report has been submitted to the Journal Cellular and Molecular Neurobiology (15 November 2020) for peer-review and is tentatively entitled:</p> <p><em><strong>‘ACE2 receptor expression in the human visual system” </strong></em></p> <p>These data should be of sincere interest to SARS-CoV2 and COVID-19 researchers and expand our understanding of potential cell and tissue targets bearing the ACE2 receptor for SARS-CoV2 invasion and infectivity, and suggest possible visual and neurological routes for SARS-CoV2-cellular entry during the COVID-19 pandemic.</p> <p>Yours truly,</p> <p>Walter J. Lukiw BS, MS, PhD, Professor of Neuroscience and Ophthalmology, Bollinger Professor of Alzheimer’s disease, LSU Neuroscience Center and Department of Ophthalmology, Louisiana State University Health Sciences Center, 2020 Gravier Street, Room 904, New Orleans LA 70112 USA </p> <p>TEL (504) 599-0842; EMAIL wlukiw@lsuhsc.edu </p> <p>================================================================================</p> <p>Paper of interest:</p> <p><strong>Lukiw WJ, Pogue A, Hill JM. SARS-CoV-2 Infectivity and Neurological Targets in the Brain. Cell Mol Neurobiol. 2020 Aug 25:1–8. doi: 10.1007/s10571-020-00947-7. Epub ahead of print. PMID: 32840758; PMCID: PMC7445393.</strong></p> <p><strong>Abstract</strong></p> <p>The gateway for invasion by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into human host cells is via the angiotensin-converting enzyme 2 (ACE2) transmembrane receptor expressed in multiple immune and nonimmune cell types. SARS-CoV-2, that causes coronavirus disease 2019 (COVID-19; CoV-19) has the unusual capacity to attack many different types of human host cells simultaneously via novel clathrin- and caveolae-independent endocytic pathways, becoming injurious to diverse cells, tissues and organ systems and exploiting any immune weakness in the host. The elicitation of this multipronged attack explains in part the severity and extensive variety of signs and symptoms observed in CoV-19 patients. To further our understanding of the mechanism and pathways of SARS-CoV-2 infection and susceptibility of specific cell- and tissue-types and organ systems to SARS-CoV-2 attack in this communication we analyzed ACE2 expression in 85 human tissues including 21 different brain regions, 7 fetal tissues and 8 controls. Besides strong ACE2 expression in respiratory, digestive, renal-excretory and reproductive cells, high ACE2 expression was also found in the amygdala, cerebral cortex and brainstem. The highest ACE2 expression level was found in the pons and medulla oblongata in the human brainstem, containing the medullary respiratory centers of the brain, and may in part explain the susceptibility of many CoV-19 patients to severe respiratory distress.</p> <p><strong>Keywords: </strong>Alzheimer’s disease; Angiotensin-converting enzyme 2 (ACE2) receptor; COVID-19; CoV-19; Coronavirus; Hartnup's disease; SARS-CoV-2; miRNA-5197; microRNA; single stranded RNA (ssRNA).</p> <p> </p> <p>================================================================================</p>
Screen captures illustrating and depicting EM densities of the ACE2 (PDB ID 6CS2) model
<p>Depicting of cryo-EM density maps using the provided python script option of the first example of our paper (see links). The lack of sufficient density for a few of the outer loops is quite obvious from these images.</p>
All-atom Molecular Dynamics Simulations of SARS-CoV-2 Spike Receptor-binding Domain bound with ACE2
<p>Data includes all of the trajectories (1000) of classical all-atom molecular dynamics (MD) simulations of of SARS-CoV2 Spike Protein/ACE2 complex (PDB ID: 6M0J). In order to decrease the size of the file only protein rajectories were provided. Simulation has been performed with Desmond. Protein was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 100 ns production run was performed for the simulation.</p>
R1A-R1AB-SPIKE-ACE2_Dataset
<p>SARS-Cov-2 proteins: a comparison with ACE2 protein</p>
SIRAH-CoV2 initiative: SARS-Cov2 Spike´s RBD / ACE2-B0AT1 complex (PDB id:6M17)
<p>This dataset contains the trajectory of a 3 microseconds-long coarse-grained molecular dynamics simulation of the hexameric complex between SARS-CoV2 Spike´s RBD, ACE2, and B0AT1 (PDB id: 6M17). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in <a href="https://pubs.acs.org/doi/10.1021/acs.jctc.9b00006">Machado et al. JCTC 2019</a>, adding 150 mM NaCl according to <a href="https://pubs.acs.org/doi/10.1021/acs.jctc.9b00953">Machado & Pantano JCTC 2020</a>. Zinc ions were parameterized as reported in <a href="https://pubs.acs.org/doi/10.1021/acs.jcim.0c00160">Klein et al. 2020</a>.</p> <p>The files 6M17_SIRAHcg_rawdata_0-1.tar, 6M17_SIRAHcg_rawdata_1-2.tar, and 6M17_SIRAHcg_rawdata_2-3.tar contain all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using <a href="https://academic.oup.com/bioinformatics/article/32/10/1568/1743152">SirahTools</a> can be found at www.sirahff.com.</p> <p>Additionally, the file 6M17_SIRAHcg_3us_prot.tar contains only the protein coordinates, while 6M17_SIRAHcg_3us_prot_skip10ns.tar contains one frame every 10ns.</p> <p>To take a quick look at the trajectory:</p> <p>1- Untar the file 6M17_SIRAHcg_10us_prot_skip10ns.tar</p> <p>2- Open the trajectory on VMD 1.9.3 using the command line:</p> <p>vmd 6M17_SIRAHcg_prot.prmtop 6M17_SIRAHcg_prot.ncrst 6M17_SIRAHcg_3us_prot_skip10ns.nc -e sirah_vmdtk.tcl</p> <p>Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. </p> <p>This dataset is part of the SIRAH-CoV2 initiative.</p> <p>For further details, please contact Florencia Klein (fklein@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).</p>
HADDOCK screening against human Angiotensin Converting Enzyme 2 (ACE2)
<p>The novel coronavirus (SARS-CoV-2) that has emerged from Wuhan, China in December 2019 has spread to almost all countries in the world causing a dramatic number of deaths. The current absence of antiviral treatment against the SARS-CoV-2 urges the scientific community to accelerate the drug discovery research process.</p> <p>One way to identify potential treatments and to be able to administer it swiftly is to focus on drug repurposing studies, i.e. to investigate the SARS-CoV-2 antiviral potential of drugs that have already been approved for human use.</p> <p>Proteins that are crucial for the survival and replication of the virus are the most attractive targets for such studies. Here we have focused on the Angiotensin Converting Enzyme 2 receptor (ACE2) that acts as one of the main gateways for viral entry in the host cell. We have screened ~2000 compounds against the inhibitor-bound closed form of the receptor.</p> <p>This is one part of a multi-target screen emphasising the main protease (Mrpo), the RNA-dependent-RNA-polymerase (RdRp) and human ACE2. The other datasets can found at the following locations:</p> <ul> <li><a href="https://zenodo.org/record/3929438">Mpro: Shape-based assay</a></li> <li><a href="https://zenodo.org/record/3929446">Mpro: Pharmacophore-based assay</a></li> <li><a href="https://zenodo.org/record/3929449">RdRp</a></li> </ul> <p>More information about this screen along with interactive visualisations of the top compounds can be found on our website <a href="https://bonvinlab.org/covid/">bonvinlab.org</a>.</p>
SIRAH-CoV2 initiative: UPDATED TRAJECTORY of SARS-Cov2 Spike´s RBD / ACE2-B0AT1 complex (PDB id:6M17)
<p>This dataset contains an updated trajectory of a four microseconds-long coarse-grained molecular dynamics simulation of the hexameric complex between SARS-CoV2 Spike´s RBD, ACE2, and B0AT1 (PDB id: 6M17). It substitutes the previous one on the same system, which was performed in the absence of disulfide bridges.</p> <p>Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in <a href="https://pubs.acs.org/doi/10.1021/acs.jctc.9b00006">Machado et al. JCTC 2019</a>, adding 150 mM NaCl according to <a href="https://pubs.acs.org/doi/10.1021/acs.jctc.9b00953">Machado & Pantano JCTC 2020</a>. Zinc ions were parameterized as reported in <a href="https://pubs.acs.org/doi/10.1021/acs.jcim.0c00160">Klein et al. 2020</a>.</p> <p>The files 6M17_SIRAHcg_rawdata_0-1.tar, 6M17_SIRAHcg_rawdata_1-2.tar, 6M17_SIRAHcg_rawdata_2-3.tar, and 6M17_SIRAHcg_rawdata_3-4.tar contain all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using <a href="https://academic.oup.com/bioinformatics/article/32/10/1568/1743152">SirahTools</a> can be found at www.sirahff.com.</p> <p>Additionally, the file 6M17_SIRAHcg_4us_prot.tar contains only the protein coordinates, while 6M17_SIRAHcg_4us_prot_skip10ns.tar contains one frame every 10ns.</p> <p>To take a quick look at the trajectory:</p> <p>1- Untar the file 6M17_SIRAHcg_4us_prot_skip10ns.tar</p> <p>2- Open the trajectory on VMD 1.9.3 using the command line:</p> <p>vmd 6M17_SIRAHcg_prot.prmtop 6M17_SIRAHcg_prot.ncrst 6M17_SIRAHcg_4usprot_skip.nc -e sirah_vmdtk.tcl</p> <p>Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. </p> <p>This dataset is part of the SIRAH-CoV2 initiative.</p> <p>For further details, please contact Florencia Klein (fklein@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).</p>
ACE2-IgG1 fusions with improved in vitro and in vivo activity against SARS-CoV-2
<p>These are raw data for figures in ACE2-IgG1 fusions with improved in vitro and in vivo activity against SARS-CoV-2, in iScience: PMID: 34957381</p>
Molecular Dynamics of SARS-CoV-2 Delta Variant Receptor Binding Domain in Complex with ACE2 Receptor
<p>Molecular dynamics simulation for 10 ns at 37 C degrees of SARS-CoV-2 delta variant. Performed with NAMD and visualized/analyzed in ChimeraX software using Frontera supercomputer from Texas Advanced Computing Center. By Victor Padilla-Sanchez, PhD.</p> <p>https://www.youtube.com/watch?v=8N_MjWwxbMQ</p>
Force-tuned Avidity of Spike Variant-ACE2 Interactions viewed on the Single-Molecule Level - MD simulations Dataset
<p>Models of SARS-CoV-2 virus spike protein bound to 1-3 of ACE2 receptors embedded in lipid nanodisks. Systems include all files in GROMACS format needed to reproduce simulations performed in the "Force-tuned Avidity of Spike Variant-ACE2 Interactions viewed on the Single-Molecule Level" article.</p> <p> </p> <table> <caption>Details</caption> <thead> <tr> <th scope="col">system</th> <th scope="col">box size (x-y-z) [nm]</th> <th scope="col">Number of atoms</th> </tr> </thead> <tbody> <tr> <td>Spike +<br> 1x ACE2, full length</td> <td>33.44834 28.96711 57.95573</td> <td>5,665,217</td> </tr> <tr> <td>Spike +<br> 1x ACE2, truncated</td> <td>28.05757 24.29856 46.74417</td> <td>3,203,907</td> </tr> <tr> <td>Spike +<br> 2x ACE2, truncated</td> <td>28.30864 21.23141 48.40873</td> <td>2,936,398</td> </tr> <tr> <td>Spike +<br> 3x ACE2, truncated</td> <td>28.32733 21.24544 48.30436</td> <td>2,936,588</td> </tr> </tbody> </table>
F I G U R E 1 in Composition and divergence of coronavirus spike proteins and host ACE2 receptors predict potential intermediate hosts of SARS- CoV-2
F I G U R E 1 Structural diagrams of spike glycoproteins of SARS‐CoV, MERS‐CoV, and SARS‐CoV‐2. All spike proteins of coronaviruses contain S1 subunit and S2 subunit, which were divided by the S cleavage sites. FP, fusion peptide; HR, heptad repeat 1 and heptad repeat 2; RBD, receptor‐binding domain, contains core binding motif in the external subdomain; SP, signal peptide
F I G U R E 2 in Composition and divergence of coronavirus spike proteins and host ACE2 receptors predict potential intermediate hosts of SARS- CoV-2
F I G U R E 2 Phylogenetic analysis of sequences of coronavirus spike glycoproteins. The sequences of spike glycoproteins of SARS‐CoV‐2, bat SARS‐like CoV, pangolin SARS‐like CoV, and SARS‐CoV were analyzed. The red stars indicate pangolin SARS‐like CoV and bat SARS‐like CoV. Host flags are marked after the clusters. SARS‐CoV‐2, severe respiratory syndrome coronavirus‐2
Raw data for Association of ACE2 gene functional variants with gestational diabetes mellitus risk in a southern Chinese population
<p class="MsoNormal"><span>These data were generated to investigate the association and functional analysis of angiotensin-converting enzyme 2 genetic variants with the pathogenesis of Gestational diabetes mellitus (GDM). This study conducted a case-control study involving 569 GDM patients and 735 healthy pregnant women to explore the associations between candidate variants in the ACE2 gene variants and the pathogenesis of GDM. This study collected clinical samples and data, and used logistic regression, false positive report rate, multi factor dimension reduction, functional analysis and other analysis methods to process the research data. Potential functional ACE2 gene variants (rs2106809 A>G, rs6632677 G>C, and rs2074192 C>T) were selected and genotyped using kompetitive allele-specific PCR. The strength of the associations between the studied genetic variants and the risk of GDM were evaluated using odds ratios (ORs) and corresponding 95% confidence intervals (CIs). </span><span>Finally, ACE2 gene variants are significantly associated with the risk of GDM via gene-gene and gene-environment combination. The rs2074192 C > T affects the splicing of ACE2 gene, which may be a potential mechanism leading to the altered susceptibility of individual female during pregnancy in Guilin to GDM</span></p>
The relationship between the clinical course of SARS-CoV-2 infection with ACE2 and TMPRSS2 expression and polymorphisms
<p>Background<br> The viral S protein and host ACE2 and TMPRSS2 genetic variations may act as a barrier to viral<br> infection or determine susceptibility to COVID-19 infection.<br> Objectives<br> We investigated the relationship between the expression patterns and polymorphisms of the ACE2<br> and TMPRSS2 receptor genes associated with COVID-19 and the clinical course of COVID-19<br> infection.<br> Material and methods<br> We studied 147 COVID-19 patients (41 asymptomatic, 53 symptomatic and 53 treated in intensive<br> care unit (ICU) cases) and 33 healthy controls. ACE2 and TMPRSS2 expressions were determined<br> using the One-Run RT Q-PCR kit. Genotypic distributions of Single Nucleotide Polymorphisms (SNP)<br> of ACE2 and TMPRSS2 were obtained by RT-PCR.<br> Results<br> The expressions of ACE2 and TMPRSS2 were different between SARS-CoV-2 positive and negative<br> groups. ACE2 rs714205GG genotype and G-allele showed significant differences in the SARS-CoV-2<br> positive asymptomatic group. A significant correlation was found between TMPRSS2 rs8134378GA,<br> rs2070788GA, rs7364083GA and rs9974589AC genotypes and SARS-CoV-2 positivity. The<br> rs1978124 C-allele and rs8134378 A-allele were significant in the SARS-CoV-2 positive symptomatic<br> group. TMPRSS2 rs2070788GA was different in all patient groups from the control group. There was a<br> difference between SARS-CoV-2 positive and negative groups for the CTTA haplotype formed by<br> ACE2 variants. The AGCAG and AGAAG haplotypes formed by TMPRSS2 variants were more<br> common in the asymptomatic patient group than in other patient groups.<br> Conclusions<br> Identifying the relationship between host genetic variants and COVID-19 susceptibility will contribute to<br> further studies that will enable new vaccines and potential therapeutic approaches to be applicable.</p>
A Phase I/II Study of Universal Off-the-shelf NKG2D-ACE2 CAR-NK Cells for Therapy of COVID-19
ClinicalTrials.gov study NCT04324996. IPD Sharing: NO. Countries: 1. Publications: 12.
ACE2 Gender Differences in Stroke With COVID-19
ClinicalTrials.gov study NCT04766645. IPD Sharing: NO. Countries: 1. Publications: 23.
ScienceDex guides
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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)
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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.