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2,697 results for “Lipids”
Calories Derived from Lipids in Adelie and Gentoo Penguin Diets at Palmer Station, 2022–2023
This dataset contains measurements of caloric energy (in kilojoules) derived from lipids in regurgitated diet samples collected from Adélie and gentoo penguins during the PAL2223 and PAL2324 field seasons near Palmer Station, along the western Antarctic Peninsula. Diet samples were homogenized through blending, and lipids were subsequently extracted for calorimetric analysis to quantify energy content. These data were used in support of the manuscript "Trophic transfer of lipid-derived energy through Adélie and Gentoo penguins near Palmer Station along the west Antarctic Peninsula", published in *Polar Biology* 48, 110 (2025), by Shavonna M. Bent et al. https://doi.org/10.1007/s00300-025-03430-5
Connexin-46/50 in a dynamic lipid environment resolved by CryoEM at 1.9 Å
<p>These are the molecular dynamics (MD) data that are analyzed, in Flores et al. 2020. Each trajectory file (.dcd) has an associated structure file (.psf), which can be analyzed in VMD. Each gap junction system, Cx46 & Cx50, were simulated with either KCl or NaCl in the intracellular space: Cx46_KCl/NaCl, Cx50_KCl/NaCl. All four systems were equilibrated for 30ns and then followed up with 2 separate 100ns production runs.</p> <p>For MD lipid-densities the Cx50_KCl system was used as the representative dataset. Lipid densities from all other systems can be calculated with the provided TCL script <em>calc-density.tcl</em>. </p> <p><strong>In VMD TK-Console:</strong></p> <p>> mol new <system>.psf<br> > mol addfile <system>.dcd waitfor all<br> > source /path/to/scripts/LipNetwork.tcl<br> > align<br> > source /path/to/scripts/calc-density.tcl<br> > dmpcdensity <outname><br> [output] outname_ltailden.dx<br> <br> Convert from .dx to .mrc using <em>UCSF-Chimera Volume_Viewer</em> plugin.<br> [output] outname_ltailden.mrc<br> <br> <strong>Using Relion:</strong><br> <br> $ relion_image_handler --i outname_ltailden.mrc --o outname_ltailden_D6-Sym.mrc --sym D6<br> [output] outname_ltailden_D6-Sym.mrc</p> <p> </p> <p>All trajectory files (.dcd) are 100ns longs (1,000 frames x 100ps/frame).</p> <p>For questions regarding MD-data analysis and full trajectory files (2ps/frame), please contact Dr. Steve Reichow (reichow@pdx.edu).</p>
Simulation files for POPC lipid membrane with Slipids-VIS force field for Gromacs MD simulation engine
<p>The tar.gz archive contains simulation input files that were used in the publication Transmembrane potential modeling: Comparison between methods of constant electric field and ion imbalance.</p> <p>http://pubs.acs.org/doi/abs/10.1021/acs.jctc.5b01202</p> <p>The files are meant to be used with <strong>Gromacs</strong> simulation package (gromacs.org).</p> <p>A modified Slipids force field, <strong>Slipids-VIS</strong>, is introduced. It uses Virtual Interaction sites in order to speed up simulation. The technique is described in the aforementioned work. The archive contains working topology for <strong>POPC</strong> lipid molecules and 6fs timestep without any significant loss of accuracy.</p>
Lipid center-of-mass trajectory: long-time dynamics
<p>This file contains the center-of-mass coordinates of the lipid molecules in a Molecular Dynamics simulation of a hydrated lipid bilayer. The simulated system consists of 2033 POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) molecules and 57952 water beads (equivalent to 231808 water molecules), using the coarse-grained representation of the MARTINI force field. Note that the mass of a POPC molecule is significantly higher (936 g/mol) in this representation than the mass of a real POPC molecule (760 g/mol). The simulation was performed in an NVT ensemble at T = 320 K.</p> <p>This trajectory stores the long-time dynamics of the lipid centers of masses, sampled at a time step of 18 ps up to a total length of 600 ns. The short-time dynamics are available at http://dx.doi.org/10.5281/zenodo.61742.</p> <p>For a detailed description of the simulation, see the thesis of Sławomir Stachura, available at http://www.theses.fr/2014PA066239</p> <p>Two analyses of this simulation have already been published:</p> <ul> <li>S. Stachura and G.R. Kneller Anomalous lateral diffusion in lipid bilayers observed by molecular dynamics simulations with atomistic and coarse-grained force fields Mol. Sim. 40, 245-250 (2014) (http://dx.doi.org/10.1080/08927022.2013.840902)</li> <li>S. Stachura and G.R. Kneller Probing anomalous diffusion in frequency space J. Chem. Phys. 143, 191103 (2015) (http://dx.doi.org/10.1063/1.4936129)</li> </ul> <p>This work was funded by the French Agence Nationale de la Recherche (Contract No. ANR- 2010-COSI-01-001).</p> <p><strong>Trajectory data</strong></p> <p>The trajectory is stored in an HDF5 file that uses the ActivePapers conventions (http://www.activepapers.org/). Any HDF5-compatible software can be used to read the trajectory data. The ActivePapers software is only required to re-use the included conversion script.</p> <p>The trajectory is contained in the group<br /> /data/POPC_martini_nvt</p> <p>It is stored in H5MD/MOSAIC format. The positions and time labels are contained in the following datasets:<br /> /data/POPC_martini_nvt/particles/universe/position/value<br /> /data/POPC_martini_nvt/particles/universe/position/time</p> <p>For a complete specification of the H5MD/MOSAIC format, see:<br /> http://nongnu.org/h5md/index.html<br /> http://mosaic-data-model.github.io/mosaic-specification/h5md_mosaic_module.html</p> <p><strong>Plots</strong></p> <p>Two 3D plots are provided to give an overview of the lipid motions:<br /> /documentation/all_lipids.pdf<br /> shows all the lipid center-of-mass positions once every 0.3 ps.<br /> /documentation/one_lipids.pdf<br /> shows a single lipid center of mass position every 10 ps.</p>
Lipid center-of-mass trajectory: short-time dynamics
<p>This file contains the center-of-mass coordinates of the lipid molecules in a Molecular Dynamics simulation of a hydrated lipid bilayer. The simulated system consists of 2033 POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) molecules and 57952 water beads (equivalent to 231808 water molecules), using the coarse-grained representation of the MARTINI force field. Note that the mass of a POPC molecule is significantly higher (936 g/mol) in this representation than the mass of a real POPC molecule (760 g/mol). The simulation was performed in an NVT ensemble at T = 320 K.</p> <p>This trajectory stores the short-time dynamics of the lipid centers of masses, sampled at a time step of 0.03 ps up to a total length of 300 ps. The long-time dynamics are available at http://dx.doi.org/10.5281/zenodo.61743.</p> <p>For a detailed description of the simulation, see the thesis of Sławomir Stachura, available at http://www.theses.fr/2014PA066239</p> <p>Two analyses of this simulation have already been published:</p> <ul> <li>S. Stachura and G.R. Kneller Anomalous lateral diffusion in lipid bilayers observed by molecular dynamics simulations with atomistic and coarse-grained force fields Mol. Sim. 40, 245-250 (2014) (http://dx.doi.org/10.1080/08927022.2013.840902)</li> <li>S. Stachura and G.R. Kneller Probing anomalous diffusion in frequency space J. Chem. Phys. 143, 191103 (2015) (http://dx.doi.org/10.1063/1.4936129)</li> </ul> <p>This work was funded by the French Agence Nationale de la Recherche (Contract No. ANR- 2010-COSI-01-001).</p> <p><strong>Trajectory data</strong></p> <p>The trajectory is stored in an HDF5 file that uses the ActivePapers conventions (http://www.activepapers.org/). Any HDF5-compatible software can be used to read the trajectory data. The ActivePapers software is only required to re-use the included conversion script.</p> <p>The trajectory is contained in the group<br /> /data/POPC_martini_nvt</p> <p>It is stored in H5MD/MOSAIC format. The positions and time labels are contained in the following datasets:<br /> /data/POPC_martini_nvt/particles/universe/position/value<br /> /data/POPC_martini_nvt/particles/universe/position/time</p> <p>For a complete specification of the H5MD/MOSAIC format, see:<br /> http://nongnu.org/h5md/index.html<br /> http://mosaic-data-model.github.io/mosaic-specification/h5md_mosaic_module.html</p> <p><strong>Plots</strong></p> <p>Two 3D plots are provided to give an overview of the lipid motions:<br /> /documentation/all_lipids.pdf<br /> shows all the lipid center-of-mass positions once every 3 ps.<br /> /documentation/one_lipids.pdf<br /> shows a single lipid center of mass position every 0.3 ps.</p>
Competitive growth experiments with a high-lipid Chlamydomonas reinhardtii mutant strain and its wild-type to predict industrial and ecological risks
<p>Key microalgal species are currently being exploited as biomanufacturing platforms using mass cultivation systems. The opportunities to enhance productivity levels or produce non-native compounds are increasing as genetic manipulation and metabolic engineering tools are rapidly advancing. Regardless of the end product, there are both environmental and industrial risks associated to open pond cultivation of mutant microalgal strains. A mutant escape could be detrimental to local biodiversity and increase the risk of algal blooms. Similarly, if the cultivation pond is invaded by a wild-type microalgae or the mutant reverts to wild-type phenotypes, productivity could be impacted. To investigate these potential risks, a response surface methodology was applied to determine the competitive outcome of two <em>Chlamydomonas reinhardtii</em> strains, a wild-type (CC-124) and a high-lipid accumulating mutant (CC-4333), grown in mixotrophic conditions, with differing levels of nitrogen and initial wild-type to mutant ratios. Results of the growth experiments show that mutant cells have double the exponential growth rate of the wild-type in monoculture. However, due to a slower transition from lag phase to exponential phase, mutant cells are outcompeted by the wild-type in every co-culture treatment. This suggests that, under the conditions tested, outdoor cultivation of the <em>C. reinhardtii</em> cell wall-deficient mutant strains does not carry a significant environmental risk to its wild-type in an escape scenario. Furthermore, lipid results show the mutant strain accumulates over 200% more TAGs per cell, at 50 mg/L NH<sub>4</sub>Cl, compared to the wild-type, therefore, the fragility of the mutant strain could impact on overall industrial productivity.</p>
Gaussian-accelerated Molecular Dynamics simulations of CCR8-CCL1-Gprotein complex in a POPC lipid bilayer
<p>Gaussian-accelerated Molecular Dynamics simulations of the CCR8-CCL1-Gprotein complex in a POPC lipid bilayer. Simulation system was prepared with OpenMM v7.7 and simulations were performed using the GaMD-OpenMM package (https://github.com/MiaoLab20/gamd-openmm) with a modification to include the MDTraj h5 file formate reporter as the output file format. These simulations were then converted to pdb topologies and dcd trajectories using MDTraj. </p><p>Files include:</p><p>CCL1_CCR8_noSer23_oriented_repaired1_system.pdb : system topology</p><p>CCL1_CCR8_config.xml : config for running GaMD-OpenMM</p><p>CCL1_CCR8_N_1ns_imaged_structure.pdb : initial topology/structure</p><p>CCL1_CCR8_N_1ns_imaged_trajectory.dcd : trajectory file</p><p> </p><p>Simulations can be loaded in python using MDTraj:</p><p>import mdtraj</p><p>trj = mdtraj.load(<dcd file>, top=<pdb file>)</p>
Input files for paper Insertases Scramble Lipids: Molecular Simulations of MTCH2
<p>Input files for simulations in publication: Ladislav Bartoš, Anant K. Menon, and Robert Vácha: Insertases Scramble Lipids: Molecular Simulations of MTCH2<br> </p>
Transcriptional determinants of lipid mobilization in human adipocytes
<p>Defects in adipocyte lipolysis drive multiple aspects of cardiometabolic disease but the transcriptional framework controlling this process has not been established. To address this, we performed a targeted perturbation screen in primary human adipocytes. Our analyses identified 37 transcriptional regulators of lipid mobilization, which we classified as: i) transcription factors, ii) histone chaperones, and iii) mRNA processing proteins. Based on its strong relationship with multiple readouts of lipolysis in patient samples, we performed mechanistic studies on one hit, ZNF189, which encodes the Zinc Finger Protein 189. Using mass-spectrometry and chromatin profiling techniques, we show that ZNF189 interacts with the tripartite motif family member TRIM28 and represses the transcription of an adipocyte-specific isoform of Phosphodiesterase 1B (PDE1B2). The regulation of lipid mobilization by ZNF189 requires PDE1B2 and overexpression of PDE1B2 is sufficient to attenuate hormone-stimulated lipolysis. Thus, our work identifies the ZNF189-PDE1B2 axis as a determinant of human adipocyte lipolysis and highlights a link between chromatin architecture and lipid mobilization.</p>
Dataset for Mechanistic Insights into Interactions Between Ionizable Lipid Nanodroplets and Biomembranes
<p>This repository contains data from the manuscript:</p> <p>Čechová, P., Paloncýová, M., Šrejber, M., Otyepka, M. </p> <p><strong>Mechanistic Insights into Interactions Between Ionizable Lipid Nanodroplets and Biomembranes <br></strong><strong><em>Journal of Biomolecular Structure and Dynamics <br></em></strong></p> <p><strong><a href="https://doi.org/10.1080/07391102.2024.2329307"> https://doi.org/10.1080/07391102.2024.2329307</a> </strong></p> <p>> Data > : contains detail informations about simulated systems;<br>Data_4Zenodo.xlsx (detail properties of simulated systems);<br>Melting_dynamics.xlsx (processed data used in Figure 4);<br>Systems_and_simulations_Detailed_SI.xlsx (molecular composition and simulation parameters for all simulations)</p> <p>> Data > Figures : data used for generation of figures in the article</p> <p>> Data > input_files : *.mdp files used for simulations (for details see Systems_and_simulations_Detailed_SI.xlsx)</p> <p>> Data > PMF_data_share :</p> <p>> Data > scripts : scripts used for data analysis of system properties</p> <p>> Starting_structures > Membrane only : starting structures and topologies files for lipid bilayers</p> <p>> Starting_structures > Pulling : starting structures and topologies for pulling simulations</p> <p>> Starting_structures > Pulling > Post_pulling : final structures after biased pulling later used as starting structures for unbiased simulations</p> <p>> Starting_structures > Stress : snapshots of simulations used as starting points for for simulations used for calculations of lateral pressures</p> <p>> Trajectories_Membrane_only : compressed simulation trajectories (*.xtc) and corresponding run input files (*.tpr) for lipid bilayer</p> <p>> Trajectories_Pulling : compressed trajectories (*.xtc) for pulling simulations and subsequent unbiased runs and corresponding run input files (*.tpr)</p> <p>> Builder_4Zenodo : script for bilayer building and the input file for membrane composition definition</p> <p>> Builder_4Zenodo > lipids : lipid structure, topology and equilibration files used by the Builder.sh script</p> <p>> Builder_4Zenodo > Building_folder_test : folder with a finished building process with a sample bilayer </p> <p> </p> <p>NOMENCLATURE</p> <p>A3D : ALC-0315 ionizable lipid (deprotonated) </p> <p>A3P : ALC-0315 ionizable lipid (protonated)</p> <p>p1-p3 : replicas 1-3 for individual systems (pulling and subsequent unbiased runs)</p> <p>free : replica for given system (unbiased runs)</p> <p>ndisk : denotes simulations used for preparation of nanodisc/LNP</p> <p>tiny : denotes simulations used for long term membrane stability assessment</p> <p>pure : denotes pure lipid bilayer</p> <p>CHL : denotes cholesterol content (35 % of molar ratio) in lipid bilayers</p> <p> </p> <p>NOTE: For more details on simulation setup please see the file Systems_and_simulation_Details_SI.xlsx (in > Data)</p>
Can calmodulin bind to lipids of the cytosolic leaflet of plasma membranes?
<p>Can calmodulin bind to lipids of the cytosolic leaflet of plasma membranes?:</p> <p><br>This data set contains all the experimental raw data, analysis and source files for the final figures reported in the manuscript: "Can calmodulin bind to lipids of the cytosolic leaflet of plasma membranes?". It is divided into five (1-5) zipped folders, named as the technique used to obtain the data. Each of them, where applicable, consists of three different subfolders (raw data, analysed data, final graph). Read below for more details. </p> <p>1) ConfocalMicroscopy</p> <p> 1a) Raw_Data: the raw images are reported as .dat and .tif formats, divided into folders (according to date first yymmdd, and within the same day according to composition). Each folder contains a .txt file reporting the experimental details </p> <p> 1b) GUVs_Statistics<br> - GUVs_Statistics.txt explains how we generated the bar plot shown in Fig. 1E</p> <p> 1c) Final_Graph<br> - Figure_1B_1D.png is the figure representing figure 1B and 1D<br> - Figure1E_%ofGUVswithCaMAdsorbptions.csv is the source file x-y of the bar plot shown in figure 1E (% of GUVs which showed adsorption of CaM over the total amount of measured GUVs) <br> - Where_To_Find_Representative_Images.txt states the folders where the raw images chosen for figure 1 can be found </p> <p>2) FCS<br> <br> 2a) Raw_Data: <br> - 1_points: .ptu files <br> - 2_points: .ht3 files <br> - Raw_Data_Description.docx which compositions and conditions correspond to which point in the two data sets<br> <br> 2b) Final_Graphs:<br> - Figure_2A.xlsx contains the x-y source file for figure 2A</p> <p> 2c) Analysis: <br> - FCS_Fits.xlsx outcome of the global fitting procedure described in the .docx below (each group of points represents a certain composition and calcium concentration, read the Raw_Data_Description.docx in the FCS > Raw_Data)<br> - Notes_for_FCS_Analysis.docx contains a brief description of the analysis of the autocorrelation curves</p> <p>3) GPLaurdan<br> <br> 3a) Raw Data: all the spectra are stored in folders named by date (yymmdd_lipidcomposition_Laurdan) and are in both .FS and .txt formats </p> <p> 3b) GP calculations: contains all the .xlsx files calculating the GP values from the raw emission and excitation spectra</p> <p> 3c) Final_Graphs<br> - Data_Processing_For_Fig_2D.csv contains the data processing from the GP values calculated from the spectra to the DeltaGP (GP with- GP without CaM) reported in fig. 2D<br> - Figure_2C_2D.xlsx contains the x-y source file for the figure 2C and 2D</p> <p>4) LiveCellsImaging </p> <p> 3a) Intensity_Protrusions_vs_Cell_Body: <br> - contains all the .xlsx files calculating the intensity of the various images. File renamed by date (yymmdd) <br> - All data in all excel sheets gathered in another Excel file to create a final graph </p> <p> 3b) Final_Graphs<br> - Figure_S2B.xlsx contains the x-y source file for the figure S2B</p> <p>5) LiveCellImaging_Raw_Data: it contains some of the images, which are given in .tif. They are divided by date (yymmdd) and each contains subfolders renamed by sample name, concentration of ionomycin. Within the subfolders, the images are divided into folders distinguishing the data acquired before and after the ionomycin treatment and the incubation time.</p> <p> </p> <p>6) 211124_BioCev_Imaging_1 folder has the .jpg files of the time laps, these are shown in fig 1A and S2.</p> <p>7) 211124_BioCev_Imaging_2 and 8) 211124_BioCev_Imaging_3 contain the images of HeLa cells expressing EGFP-CaM after treatment with ionomycin 200 nM (A1) and 1 uM (A2), respectively. </p> <p><br>9) SPR</p> <p> 9a) Raw Data: <br> - SPR_Raw_Data.xlsx x/y exported sensorgrams <br> - the .jpg files of the software are also reported and named by lipid composition</p> <p> 9b) Final_Graph: <br> - Fig.2B.xlsx contains the x-y source file for the figure 2B</p> <p> 9c) Analysis<br> - SPR_Analysis.xlsx: excel file containing step-by-step (sheet by sheet) how we processed the raw data to obtain the final figure (details explained in the .docx below)<br> - Analysis of SPR data_notes.docx: read me for detailed explanation</p>
Fig. 2. 3D in Novel Media for Lipid Production of Chlorococcum oleofaciens: A RSM Approach
Fig. 2. 3D surface plot of lipid production with a function of a) NaHCO 3 and KNO 3 b) NaHCO 3 and KNO 3 c) NaHCO 3 and MgSO 4 The surface plot depicts the functional association of the desired response, lipid production with the screened parameters, sodium bicarbonate (A), sodium nitrate (B) and potassium nitrate (C). More precisely, the secondary interactive effects of the parameters with the desired response can be elucidated and the optimized conditions for the appropriate response (maximum) could be computed from the use of such plots.
Improving Stability of Tear Film Lipid Layer via Concerted Action of Two Drug Molecules: A Biophysical View
<p>Surface pressure/area isotherms, stress relaxation transients, molecular dynamic simulation parameters of surface films composed of tear lipids and drug molecules.</p>
Dataset related to article "Plasma Lipid Profiling Contributes to Untangle the Complexity of Moyamoya Arteriopathy"
<p>DATABASE REPORTING CLINICAL, NEURORADIOLOGICAL, DEMOGRAPHICAL AND BIOLOGICAL (“OMICS”) ANONIMYZED DATA OF A SELECTED SUBGROUP OF PATIENTS AFFECTED BY MOYAMOYA ARTERIOPATHY</p>
Dataset related to article "PLASMA LIPID PROFILING CONTRIBUTES TO UNTANGLE THE COMPLEXITY OF MOYAMOYA ARTERIOPATHY"
<p>DATABASE REPORTING CLINICAL, NEURORADIOLOGICAL, DEMOGRAPHICAL AND BIOLOGICAL (“OMICS”) ANONIMYZED DATA OF A SELECTED SUBGROUP OF PATIENTS AFFECTED BY MOYAMOYA ARTERIOPATHY</p>
Gene expression plasticity, genetic variation and fatty acid remodelling in divergent populations of a tropical bivalve species: lipid profiles
<p><span>Ocean warming challenges marine organisms' resilience, especially for species experiencing temperatures close to their upper thermal limits. A potential increase in thermal tolerance might significantly reduce the risk of population decline, which is intrinsically linked to variability in local habitat temperatures.</span></p> <p><span>Our goal was to assess the plastic and genetic potential of response to elevated temperatures in a tropical bivalve model, <em>Pinctada margaritifera</em>. We benefit from two ecotypes for which local environmental conditions are characterized by either large diurnal variations in the tide-pools (Marquesas archipelago) or lower mean temperature with stable to moderate seasonal variations (Gambier archipelago).</span><br><br><span>We explored the physiological basis of individual responses to elevated temperature<em>, </em>genetic divergence as well as plasticity and acclimation by combining lipidomic and transcriptomic approaches.</span><br><br><span>We show that <em>P. margaritifera</em> has certain capacities to adjust to long-term elevated temperatures that was thus far largely underestimated. Genetic variation across populations overlaps with gene expression and involves the mitochondrial respiration machinery, a central physiological process that contributes to species thermal sensitivity and their distribution ranges.</span><br><br><span>Our results present evidence for acclimation potential in <em>P. margaritifera</em> and urge for longer term studies to assess populations resilience in face of climate change.</span></p>
FORECASTING MOLECULAR DYNAMICS SIMULATIONS OF POLYMER-LIPIDS IN SOLUTION WITH RNNs
<p>Files and scripts pertaining to our work: </p> <ul> <li>GROMACS files for the topology (DSPE+PEG.top) and the initial structure of the aggregate (DSPE+PEG_EA_NPT.gro)</li> <li>GROMACS topology file for the ethyl acetate molecule: EA_SI.top</li> <li>Scripts to submit the <em>GROMACS</em> utilities for calculation of the interaction energies are described in README.txt (Subset_energy.sh , Interaction_energies.sh)</li> <li>Scripts pertaining to <em>PyTorch</em> use and access of methods are described in README.txt (Multiple-run.sh. Job.sh, Pytorch_train-model.py)</li> <li>Scripts pertaining to <em>scikit learn </em>access for the Expectation Maximization clustering are described in the README.txt (Job_EM.sh, EM_Clustering.py)</li> <li>Files with the time series of the potential energy (PE) and interaction energy (IE) of the DSPE-PEG aggregate with the ethyl acetate solvent. Series contain 500,000 snapshots taken every 10 fs along the NVT Molecular Dynamics trajectory at 300 K and 906.3 kg/m<sup>3</sup> density. The molecular solution is in a cubic box of edge length 13.76 nm, containing 16,000 ethyl acetate molecules and one aggregate of 4 DSPE-PEG-amide macromolecules (224,000 atoms): Data_Andrews_etal_DSPE-PEG_2022.zip</li> <li>ArXiv preprint: https://doi.org/10.48550/arXiv.2203.00151 (JAndrews_etal_arXiv-doi.pdf)</li> </ul>
Pea aphid winged and wingless males exhibit reproductive, gene expression, and lipid metabolism differences
<p><span>Alternative, intraspecific phenotypes offer an opportunity to identify the mechanistic basis of differences associated with distinctive life-history strategies. Wing dimorphic insects, in which both flight-capable and flight-incapable individuals occur in the same population, are particularly well-studied in terms of why and how the morphs trade-off flight for reproduction. Yet despite a wealth of studies examining the differences between female morphs, little is known about male differences, which could arise from different causes than those acting on females. Here we examined reproductive, gene expression, and biochemical differences between pea aphid (<em>Acyrthosiphon pisum</em>) winged and wingless males. We find that winged males are competitively superior in one-on-one mating circumstances, but wingless males reach reproductive maturity faster and have larger testes. We suggest that males </span><span>tradeoff increased local matings with concurrent possible inbreeding for outbreeding and increased ability to find mates. At the mechanistic level, differential gene expression between the morphs revealed a possible role for activin and insulin signaling in morph differences; it also highlighted genes not previously identified as being functionally important in wing polymorphism, such as genes likely involved in sperm production. Further, we find that winged males have higher lipid levels, consistent with their use as flight fuel, but we find no consistent patterns of different levels of activity among five enzymes associated with lipid biosynthesis. Overall, our analyses provide evidence that winged versus wingless males exhibit differences at the reproductive, biochemical, and gene expression levels, expanding the field's understanding of the functional aspects of morph differences.</span></p>
A partnership between the lipid scramblase XK and the lipid transfer protein VPS13A at the plasma membrane
<p>This upload contains files documented in a preprint and a publication.</p> <p>Preprint: https://doi.org/10.1101/2022.03.30.486314</p> <p>Publication: <a href="https://doi.org/10.1073/pnas.2205425119">https://doi.org/10.1073/pnas.2205425119</a></p> <p>The files uploaded here are:</p> <p>- Alphafold predictions for VPS13A N-term (a.a. 1-2100) and C-term (a.a. 1021-3174). The .pse file is the pymol structure alignment of the two predicted VPS13A portions, join at aminoacid position D14 with the different representations presented throughout the paper stored as pymol "scenes". </p> <p>- AlphaFold-Multimer prediction for the interaction between XK and the C-term region of VPS13A is also included.</p> <p>- An excel file containing the tabular data for the graphs in Figures 1G, S2E and 4D.</p>
dataset for paper "Activation energy for pore opening in lipid membranes under an electric field"
<p>Dataset for the paper "Electropermeabilization of hydroperoxidized lipid membranes".</p> <p>Data was generated from Orbit Mini miniaturized bilayer workstation (Nanion Technologies, Munich, Germany), with an inserted microelectrode cavity array (MECA 4) recording chip (Ionera Technologies, Freiburg, Germany).</p> <p>The data files have format .abf, a standard format for electrophysiological data. <br> It can be read by applications such as for instance</p> <p>- Clampex and ClampFit, from the patch-clamp software suite pCLAMP, <br> - Elements Data Analyzer, associated with the elements data reader software from Elements-IC, </p> <p><br> or imported into Python through the package pyABF 2.3.5.</p> <p>import pyabf // abf=pyabf.ABF(path+"/"+f+"/"+abffile) // data = np.vstack((abf.sweepX, abf.data)) </p> <p>Data is organized in five folders named according to target hydroperoxidation degrees:<br> POPC<br> POPC-OOH 25%<br> POPC-OOH 50%<br> POPC-OOH 75%<br> POPC-OOH 100%</p> <p>Inside each of the five above files data is organized by date, and informed with the actual measured hydroperoxidation degree for a given sample. </p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.