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75 results for “lipid droplets”

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zenodo44/100

Light and confocal micrographs on the response of Mesotaenium endlicherianum SAG 12.97 to a bifactorial environmental gradient, the accumulation of lipid droplets, and the heterologous expression and localisation of signature LD protein homologs to tobacco pollen tubes

<p>These micrographs accompany the work &quot;Environmental gradients reveal stress hubs predating plant terrestrialization&quot;, posted as a pre-print on bioRxiv&nbsp;https://doi.org/10.1101/2022.10.17.512551&nbsp;</p> <p>The&nbsp;light and confocal micrographs&nbsp;show the response of Mesotaenium endlicherianum SAG 12.97 to a bifactorial environmental gradient, especially their&nbsp;accumulation of lipid droplets (LDs); in confocal micrographs,&nbsp;LDs appeared as distinct structures upon staining with BODIPY.</p> <p>Further confocal micrographs show&nbsp;the heterologous expression and localisation of signature LD protein homologs detected in&nbsp;Mesotaenium endlicherianum SAG 12.97;&nbsp;heterologous expression was carried out in&nbsp;tobacco pollen tubes were also stained with BODIPY&nbsp;and proteins were tagged with mCherry.</p>

opencc-by-4.0May 2023View details →
zenodo36/100

Lipid droplet quantification datasheet of different MIGA2 constructs expressing cells

<p>Lipid droplet quantification datasheet of different MIGA2 constructs expressing Hela cells: WT, MIGA2 KO, MIGA2 KO cells transfected with WT MIGA2, MIGA2&nbsp;KO cells transfected with MIGA2 mutants.</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Hairpin protein partitioning from the ER to Lipid Droplets involves major structural rearrangements

<div> <p>The project includes dataset from MD simulations and EPR measurements.</p> <p>Description of the MD simulation dataset:<br>-Data type: MD simulations of UBXD8 peptide at varying depths/conformations in POPC &nbsp;bilayer,&nbsp; POPC/Triolein:Cholesteryl oleate monolayer, and in Bilayer-Lipid droplet setup. <br>-Force fields: All-atom simulations were carried out using Charmm36 force field. &nbsp;The parameters for Triolein and Cholesteryl oleate are derived from Olarte et al., 2020 and were obtained from the corresponding authors of that publication. Coarse-grained simulations were &nbsp;carried out using Martini force field. &nbsp;<br>-Simulation Package: All simulations were carried out using GROMACS 2021 simulation package.<br>-File types: The uploaded files include structure files in PDB format, input parameter files &nbsp;(.mdp), topology (topol.top), and force field files.</p> </div> <div>Description of the EPR dataset:<br>- Data type: Experimental spectroscopic measurements, Easyspin simulation and analysis<br>- Files are with filename extensions: DSC, DAT<br>- Information on origin of the data:<br>- EPR spectroscopic measurements with filename extensions DSC and DTA.<br>- EPR spectroscopic simulation and analyses with filename extension m.<br>- EPR simulations were generated using Easyspin version 5.2.36 and Matlab version 23.2.0.2428915.<br>- X-band CW-EPR spectroscopic measurements were generated by EMX spectrometer equipped with ER4123D cavity produced by Bruker.</div>

opencc-by-4.0Mar 2024View details →
zenodo32/100

The GBA variant E326K is associated with alpha-synuclein aggregation and lipid droplet accumulation in human cell lines.

<p>Raw data corresponding to graphs in publication:&nbsp;The GBA&nbsp;variant E326K is associated with alpha-synuclein aggregation and lipid droplet accumulation in human cell lines. Files are titled with the figure number. Each graph is on a different tab within the excel spreadsheet.</p>

opencc-by-4.0May 2022View details →
zenodo32/100

Jojoba (Simmondsia chinensis) LDAP1 facilitates the efficient packaging of wax esters into lipid droplets

<p>Input structures for a manuscript, along with selected output data and structures. This directory structure contains a cut-down copy of the directories used to generate the simulation data and the analysis. In order to make this fit into the 50GB Zenodo limit, it was constructed with the following tar command:&nbsp;<br><code>tar -zcvf LDAP1.tar.gz &nbsp;--exclude="*BAK" --exclude="*#" --exclude="*log" --exclude="*xsc" --exclude="*coor" --exclude="*vel" --exclude="*[0-9].out" --exclude="*old" --exclude="*dcd" --exclude="*tmp" --exclude="*ppm" --exclude="*png" --exclude="*pdf" &nbsp;--exclude="*catchy*" --exclude="*svg" --exclude="*restart*" --exclude="*history" --exclude="core.*" --exclude="FFTW_NAMD*" --exclude="*avi" --exclude="*mp4" --exclude="*dimer*" --exclude="models" LDAP1</code><br><br></p> <p>The data is split into two directories initially "<strong>build</strong>" and "<strong>Simulations</strong>"</p> <ul> <li>"<strong>build</strong>" directory is the part where initial system for bilayer and lipid droplet simulation were build.</li> <li>"<strong>Simulations</strong>" directory has the different namd files for running simulation, and a sub folder of "<strong>Analysis"</strong> contains script for analysis of the simulation trajectory.</li> </ul>

opencc-by-4.0May 2024View details →
zenodo32/100

Molecular Probes for Tracking Lipid Droplet Membrane Dynamics

<p><strong><span>Abstract</span></strong></p> <p><span>Lipid droplets (LDs) and their membrane proteins play crucial roles in lipid metabolism, signaling, and information transport within cells. LDs feature a unique monolayer lipid membrane that has not been extensively studied due to the lack of suitable molecular probes that are able to distinguish this membrane from the LD lipid core. In this work, we present a three-pronged molecular probe design strategy that combines lipophilicity-based organelle targeting with microenvironment-dependent activation. As a proof-of-concept, we designed an <u>LD</u> <u>m</u>embrane labeling pro-probe called<strong> LDM</strong>, which selectively localizes around LD membranes. Upon activation by the HClO/ClO</span><sup><span>&minus;</span></sup><span> microenvironment that surrounds LDs, <strong>LDM</strong> pro-probe undergoes a color change and releases<strong> LDM-OH</strong> probe that binds to LD membrane proteins. This localizes the probe to the LD-as</span><span>sociated protein space which is restricted to the membrane thus enabling visualization of the ring-like LD membrane. By utilizing<strong> LDM</strong>, we identified the dynamic mechanism of LD membrane contacts and their protein accumulation parameters. Furthermore, using <strong>LDM</strong> in liver cancer cells allowed us to examine the changes in LD/mitochondrial protein accumulation caused by the state of starvation these cells encounter. This led to the discovery that liver cancer cells respond to energy stress during hunger by enhancing LD-mitochondria interactions. Taken together, <strong>LDM</strong> represents the first molecular probe for imaging LD membranes in live cells, and represents an attractive tool for further investigations into the specific regulatory mechanisms and drug discovery associa</span><span>ted with LD related metabolism diseases.</span></p> <p><span>&nbsp;</span></p> <p><em><span>Keywords:</span></em><span> Molecular Imaging, Cancer, Lipid droplets, Super-resolution Imaging</span></p>

opencc-by-4.0Aug 2024View details →
zenodo32/100

Dataset for "Segmentation of Lipid Droplets in Histological Images"

<p>Datasets for the publication "Segmentation of Lipid Droplets in Histological Images" (Medical Imaging with Deep Learning (MIDL 2023), short paper track. 2023. https://openreview.net/forum?id=nTnAm_El0RC)</p>

opencc-by-4.0Apr 2023View details →
zenodo28/100

An amphipathic helical insert drives interaction of Fibrillins with plastoglobule lipid droplets

<p>Structures and trajectory files for molecular dynamics protein-membrane binding simulations</p>

opencc-by-4.0Sep 2023View details →
zenodo28/100

lipid droplet training dataset for live cell anatomy segmentation

Open the record for dataset details and reuse information.

opencc-by-4.0Apr 2024View details →
geo24/100

Loss of dihydroceramide desaturase drives neurodegeneration by disrupting endoplasmic reticulum and lipid droplet homeostasis in glial cells

GEO Series GSE263308. Drosophila melanogaster. 10 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenApr 2024View details →
geo24/100

A metabolomics analysis of gallbladder lipid droplet formation due to Salmonella infection

GEO Series GSE27604. Mus musculus. 9 samples. Type: Other.

openGEO-OpenAug 2011View details →
geo24/100

Senescent glia link neuronal mitochondrial dysfunction and lipid droplet accumulation with age [19082_28_MASTER]

GEO Series GSE263929. Drosophila melanogaster. 16 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenMay 2024View details →
geo24/100

Lipid droplets modulate autophagy receptor SQST-1/SQSTM1 dynamics and lifespan

GEO Series GSE204953. Caenorhabditis elegans. 18 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenDec 2022View details →
geo24/100

Microarrays reveal oocyte lipid storage droplet gene as key factor in reproductive dysfunction of captive-reared P. monodon

GEO Series GSE31862. Penaeus monodon. 38 samples. Type: Expression profiling by array.

openGEO-OpenSep 2011View details →
geo24/100

RNA-seq of lipid droplet-low and lipid droplet-rich microglia isolated from the hippocampi of Progranulin KO mice

GEO Series GSE140009. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenNov 2019View details →
geo24/100

RNA-seq of lipid droplet-low and lipid droplet-rich microglia isolated from the hippocampi of LPS-treated young mice

GEO Series GSE139946. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenNov 2019View details →
geo24/100

Lipid droplet availability affects neural stem/progenitor cell metabolism and proliferation

GEO Series GSE187470. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenNov 2021View details →
geo24/100

Analysis of gene expression changes in lipid droplet formation of human liver cancer cell HepG2

GEO Series GSE248166. Homo sapiens. 8 samples. Type: Expression profiling by array.

openGEO-OpenDec 2023View details →
geo24/100

Diet-MEF2 Interactions Shape Lipid Droplet Diversification in Muscle to Influence Drosophila Lifespan

GEO Series GSE147676. Drosophila melanogaster. 4 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenAug 2020View details →
geo24/100

Proteogenomic characterization reveals that lipid droplet formation promotes esophageal squamous cell cancer progression

GEO Series GSE180791. Homo sapiens. 102 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenApr 2025View details →

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International Brain Laboratory public data

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