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opencc-zeroFeb 2024View details →

Data from: A mechanism of lysosomal calcium entry

Lysosomal calcium (Ca2+) release is critical to cell signaling and is mediated by well-known lysosomal Ca2+ channels. Yet, how lysosomes refill their Ca2+ remains hitherto undescribed. Here, from an RNAi screen in C. elegans we identify an evolutionarily conserved gene, lci-1, that facilitates lysosomal Ca2+ entry in C. elegans and mammalian cells. We found that its human homolog TMEM165, previously designated as a Ca2+/H+ exchanger (CAX), imports Ca2+ pH-dependently into lysosomes. Using two-ion mapping and electrophysiology we show that TMEM165, hereafter referred to as human LCI, acts as a proton-activated, lysosomal Ca2+ importer. Defects in lysosomal Ca2+ channels cause several neurodegenerative diseases, and knowledge of lysosomal Ca2+ importers may provide new avenues to explore the physiology of Ca2+ channels.

opencc-zeroApr 2024View details →

The workload of manual data entry for integration between mobile health applications and eHealth infrastructure

<div> In this study, we conducted a time-motion study observing healthcare workers (HCWs) completing data management activities including monitoring and evaluation (M&E) and manual data linkage of individual-level app data to electronic medical records (EMRS). This study served as a baseline study for an open-source app to mirror EMRS and reduce HCW workload while improving care in the Nurse-led Community-based Antiretroviral therapy Program (NCAP) in Lilongwe, Malawi. </div>

zenodo36/100

Docking data for "The evolution of the SARS-CoV-2 spike protein for differential usage of the host transmembrane serine proteases entry pathway"

The dataset includes predicted complexes of the SARS-CoV-2 Spike protein (specifically at the S2' cleavage site) with Hepsin and TMPRSS2 proteins. It contains data on three variants: Wuhan, Delta, and Omicron BA.1. Compressed folders: -357596-DeltaHepsin.tgz -357597-DeltaTMPRSS2.tgz -360039-WuhanHepsin.tgz -360042-TMPRSSWuhan.tgz -392981-TMPRSS-BA1_all.tgz -392982-Hepsin-BA-all.tgz Each compressed folder contains the following: -Initial structures in pdb format -Output complexes in pdb format -Clusters in pdb format -Protocols -Parameters -Scoring files   Protein-protein docking  Molecular docking between the SARS-CoV-2 S protein of Wuhan, Delta (PDB: 7W92, [DOI: 10.1038/s41467-022-28528-w]), and BA.1 (PDB: 7XO5, [DOI: 10.1038/s41422-022-00672-4]) and the human proteases TMPRSS2 (PDB: 8HD8, [DOI: 10.1038/s41467-023-42527-5]) and Hepsin (PDB: 1Z8G, [DOI: 10.1042/BJ20041955]) was performed using the HADDOCK v2.5-2024.03 webserver ([DOI: 10.1021/ja026939x], [DOI: 10.1016/j.jmb.2015.09.014]). Missing loops in the protein structures were reconstructed using Modeller v10.5 ([DOI: 10.1006/jmbi.1993.1626]). Every heteroatom was removed from the reference structures. The relaxed atomistic coordinates for each S protein variant were derived via all-atom molecular dynamics (MD) simulations. These simulations were performed using AMBER22 with the FF19SB force fields and the pmemd.cuda module for enhanced performance ([DOI: 10.1021/acs.jcim.3c01153], [DOI: 10.1021/jz501780a], [DOI:10.1021/ct400314y]). For the Wuhan variant the S protein was retrieved from our previous modeling study [DOI: 10.1039/D0NR03969A] where for Delta and BA.1, ecah S protein was placed in a dodecahedral box, extending 20 Å beyond the solute in every cartesian direction, and solvated with the four-site OPC water model ([DOI: 10.1021/jz501780a]). The systems were neutralized with counterions, specifically one Cl− ion for the Delta variant and three Cl- ions for the BA.1 variant. To remove local clashes, a geometric optimization was performed using the steepest descent algorithm for 5000 cycles. The MD equilibration process consisted of several stages. First, temperature equilibration in the NVT ensemble was performed by gradually increasing the temperature through steps of 150, 200, 250, 300, and finally 310 K, each lasting 200 ps. During this phase, position restraints were applied to the heavy atoms of the proteins, with progressively decreasing spring constants of 5.0, 4.0, 3.0, and 1.0 kcal mol−1 Å−2, facilitating gradual relaxation. This was followed by a 1 ns equilibration at 310 K in the NPT ensemble without restraints. For production MD, the simulations were run in the NPT ensemble with periodic boundary conditions and Particle Mesh Ewald (PME) method ([DOI: 10.1063/5.0040966], [DOI: 10.1021/ct9001015]) using a grid spacing of 1.0 Å for long-range electrostatics. Non-bonded interactions were modeled with a Lennard-Jones potential using a 9Å cutoff. Temperature control was maintained using Langevin dynamics ([DOI: 10.1021/ct800573m]) with a collision frequency of 4.0 ps−1, and pressure control was managed by the Monte Carlo barostat ([DOI: 10.1016/j.cplett.2003.12.039]) with a 2.0 ps relaxation time at 1 bar. Bond constraints on hydrogen atoms were applied using the SHAKE algorithm ([DOI: 10.1016/0021-9991(77)90098-5]), and the hydrogen mass repartitioning scheme was applied via ParmEd ([DOI: 10.1371/journal.pcbi.1005659]), enabling a 4 fs integration time step ([DOI: 10.1021/ct5010406]). Each protein complex was simulated for a total of 20 ns. For the Wuhan variant, the 3D coordinates were retrieved from [DOI: 10.5281/zenodo.3817446]. The active interaction region on the spike protein was defined as the cleavage site (residues P809-R815). For TMPRSS2 and Hepsin, the active sites were defined based on their catalytic residues: H296, D345, D435, S441, S460, and G462 for TMPRSS2, and H203, D257, D347, A348, and S353 for Hepsin. These specific regions were selected to guide the docking process and maximize biologically relevant interactions. Docking clusters were analyzed by selecting those with the lowest interaction energies for further structural analysis. To evaluate binding accuracy, native contacts between the S protein and proteases were computed using the contact map analysis based on the OV+rCSU method ([DOI: 10.12693/APhysPolA.145.S9, 10.1021/acs.jctc.6b00986]), which allows for a precise identification of critical stabilizing interactions, both specific and non-specifics. High-frequency contacts, defined as those appearing in over 70% of the generated models, were highlighted as key determinants of protein-protein recognition, providing insight into the most stable and consistent interactions across docking configurations.

opencc-by-4.0Nov 2024View details →

publicApr 2024View details →

The workload of manual data entry for integration between mobile health applications and eHealth infrastructure

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publicFeb 2024View details →

Data from: A mechanism of lysosomal calcium entry

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opencc-by-4.0Jul 2020View details →

Classify on the Clock (CloCk) - An Entry Level Image Data Set for Neural Networks

General information This data set contains synthetic images of an analog clock. Each time point from 00:00:00 - 11:59:59 is included as a separate image. We provide three different versions of each image with an increasing number of additional information: <ul> <li>Sparse: The image includes just the hour, minute and second hand</li> <li>Reduced: Additional markings around the clock</li> <li>Full: Additional written numbers</li> </ul> The hands differ in size and color: <ul> <li>Hour: Black, short, wide</li> <li>Minute: Blue, long, medium</li> <li>Second: Red, long, slim</li> </ul> We provide the following files in this data repository: <ul> <li>RGB images with a size of 512x512 for all three versions</li> <li>A suggested training, validation and test split</li> <li>The creation script as Python file</li> </ul> The script can easily be modified to create images with a different size and color.   Clock System The movements of the hands follow a linear relationship. Their angles can be calculated by the forward system: \( \begin{bmatrix} 6^\circ & 0 & 0 \\ 0.1^\circ & 6^\circ & 0 \\ 0 & 0.5^\circ & 30^\circ \end{bmatrix} \begin{pmatrix} n_{\text{sec}} \\ n_{\text{min}} \\ n_{\text{hour}} \end{pmatrix} = \begin{pmatrix} \alpha_{\text{sec}}\\ \alpha_{\text{min}} \\ \alpha_{\text{hour}} \end{pmatrix}.\) One can also introduce rotated versions of the images. The system becomes non-linear in this case: \(\operatorname{mod}\left( \begin{bmatrix} 6^\circ & 0 & 0 \\ 0.1^\circ & 6^\circ & 0 \\ 0 & 0.5^\circ & 30^\circ \end{bmatrix} \begin{pmatrix} n_{\text{sec}} \\ n_{\text{min}} \\ n_{\text{hour}} \end{pmatrix} + \omega, \, 360^\circ \right) = \begin{pmatrix} \alpha_{\text{sec}}\\ \alpha_{\text{min}} \\ \alpha_{\text{hour}} \end{pmatrix}.\)   Use Cases This data set was originally designed for basic research on Capsule Networks. Use cases are: <ul> <li>Evalutation of classification and regression performance</li> <li>Influence of image transformations, e.g. rotations</li> <li>Detection of the hierarchy & relationship of image parts</li> <li>Concealment of objects in the image</li> <li>Interpretability of the learned model</li> <li>Solving a discrete inverse problem (sparse version)</li> <li>...</li> </ul>

MD simulation data for Helicobacter pylori TonB-CTD (residues 194-285) (PDB ID: 5LW8; BMRB entry: 34043), Amber ff99SB-ILDN, tip3p, 310K, Gromacs

MD simulation data for Helicobacter pylori TonB-CTD (residues 194-285) (PDB ID: 5LW8; BMRB entry: 34043). Simulated with Amber ff99SB-ILDN force field, tip3p water model at 310K, Gromacs software package. Simulation reported in "Rotational dynamics of proteins from spin relaxation times and molecular dynamics simulations", Ollila et al. Submitted (2017).

MD simulation data for Helicobacter pylori TonB-CTD (residues 194-285) (PDB ID: 5LW8; BMRB entry: 34043), Amber ff99SB-ILDN, tip4p, 310K, Gromacs

MD simulation data for Helicobacter pylori TonB-CTD (residues 194-285) (PDB ID: 5LW8; BMRB entry: 34043). Simulated with Amber ff99SB-ILDN force field, tip4p water model at 310K, Gromacs software package. Simulation reported in "Rotational dynamics of proteins from spin relaxation times and molecular dynamics simulations", Ollila et al. Submitted (2017).

MD simulation data for Helicobacter pylori TonB-CTD (residues 194-285) (PDB ID: 5LW8; BMRB entry: 34043), Amber ff99SB-ILDN, OPC4, 310K, Gromacs

MD simulation data for Helicobacter pylori TonB-CTD (residues 194-285) (PDB ID: 5LW8; BMRB entry: 34043). Simulated with Amber ff99SB-ILDN force field, OPC4 water model at 310K, Gromacs software package. Simulation reported in "Rotational dynamics of proteins from spin relaxation times and molecular dynamics simulations", Ollila et al. Submitted (2017).

MD simulation data for Helicobacter pylori TonB-CTD (residues 194-285) (PDB ID: 5LW8; BMRB entry: 34043), Amber ff99SB-ILDN, tip3p, 303K, Gromacs

MD simulation data for Helicobacter pylori TonB-CTD (residues 194-285) (PDB ID: 5LW8; BMRB entry: 34043). Simulated with Amber ff99SB-ILDN force field, tip3p water model at 303K, Gromacs software package. Simulation reported in "Rotational dynamics of proteins from spin relaxation times and molecular dynamics simulations", Ollila et al. Submitted (2017).

MD simulation data for Helicobacter pylori TonB-CTD (residues 194-285) (PDB ID: 5LW8; BMRB entry: 34043), Amber ff99SB-ILDN, tip4p, 303K, Gromacs

MD simulation data for Helicobacter pylori TonB-CTD (residues 194-285) (PDB ID: 5LW8; BMRB entry: 34043). Simulated with Amber ff99SB-ILDN force field, tip4p water model at 303K, Gromacs software package. Simulation reported in "Rotational dynamics of proteins from spin relaxation times and molecular dynamics simulations", Ollila et al. Submitted (2017).

opennotspecifiedMar 2019View details →

Leafcutter ants of the genus Atta in the Insects Collection at the Field Museum of Natural History. The field data on the attached tags are transcribed for entry into databases such as AntWeb and the Global Biodiversity Information Facility. Photograph: Matthew Nelsen. in The Evolution of Natural History Collections

Leafcutter ants of the genus Atta in the Insects Collection at the Field Museum of Natural History. The field data on the attached tags are transcribed for entry into databases such as AntWeb and the Global Biodiversity Information Facility. Photograph: Matthew Nelsen.

opencc-by-nc-sa-4.0Nov 2022View details →

Data set for: "Model atmospheric aerosols convert to vesicles upon entry into aqueous solution"

This document compiles raw data used in the aerosol to vesicle transformation study carried out by Serge Nader et al. For detailed information and context, refer to the main article and its supplementary material published in ACS Earth and Space Chemistry. The Excel file contains data relevant to each figure in the main article and supporting information. The additional compressed file contains raw Transmission Electron Microscopy (TEM) photographs.