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670 results for “HeLa”
Additional Data - Phototoxicity induced in living HeLa cells by focused femtosecond laser pulses
<p>Nonlinear optical microscopy is a powerful label-free imaging technology, providing biochem-ical and structural information in living cells and tissues. A possible drawback is photodamageinduced by high-power ultrashort laser pulses. Here we present an experimental study on thou-sands of HeLa cells, to characterize the damage induced by focused femtosecond near-infraredlaser pulses as a function of laser power, scanning speed and exposure time, in both wide-field andpoint-scanning illumination configurations. Our data-driven approach offers an interpretation ofthe underlying damage mechanisms and provides a predictive model that estimates its probabilityand extension and a safety limit for the working conditions in nonlinear optical microscopy. Inparticular, we demonstrate that cells can withstand high temperatures for a short amount of time,while they die if exposed for longer times to mild temperatures. It is thus better to illuminatethe samples with high irradiances: thanks to the nonlinear imaging mechanism, much strongersignals will be generated, enabling fast imaging and thus avoiding sample photodamage.</p>
Automatic labelling of HeLa "Kyoto" cells using Deep Learning tools
<p><strong>Name</strong>: Automatic labelling of HeLa “Kyoto” cells using Deep Learning tools</p> <p><strong>Data type</strong>: Microscopy images from the dataset “<strong>HeLa “Kyoto” cells under the scope</strong>”, Brightfield (BF), Digital Phase Contrast (DPC, either “raw” or “square-rooted”), Tubulin and H2B fluorescent channel, paired with their corresponding nuclei or cell/cyto label images.</p> <p><strong>Labels images</strong>: Labels images were generated using the script <em>“prepare_trainingDataset_cellpose.ijm</em>”.</p> <p>Briefly, for 5 defined time-points (1,10,50,100,150), channels of interest were duplicated, resaved and :</p> <p>- nuclei label images were obtained using <a href="https://github.com/stardist/stardist">StarDist</a> on H2B channel</p> <p>- cell label images were obtained using <a href="https://github.com/MouseLand/cellpose">Cellpose</a> on Tubulin and H2B channels</p> <p>A quick visual inspection of the resulting label images concluded that they were satisfying enough, despite certainly not being perfect.</p> <p>Notes :</p> <p>- This labelling strategy:</p> <p>o will not produce 100% accurate labels, but they might be more reproducible than labels generated by humans and are (definitely) much faster to obtain.</p> <p>o is <strong>NOT a recommended way of generating labels images</strong>, but for educational purposes.</p> <p>- The fluorescent channels are part of the dataset to ease the process of review of the labels and are NOT used for training. We generated the labels from the fluorescent channels to later predict labels from the BF or DPC channels only. As such, the fluorescent channels should not be “reused” with our labels during training.</p> <p><strong>File format</strong>: .tif (16-bit)</p> <p><strong>Image size</strong>: 540x540 (Pixel size: 0.299 nm)</p> <p> </p> <p><strong><em>NOTE</em></strong>: This dataset uses the “HeLa “Kyoto” cells under the scope” dataset (<a href="https://doi.org/10.5281/zenodo.6139958">https://doi.org/10.5281/zenodo.6139958</a>) to automatically generate annotations</p> <p><strong><em>NOTE</em></strong>: This dataset was used to train cellpose models in the following Zenodo entry <a href="https://doi.org/10.5281/zenodo.6140111">https://doi.org/10.5281/zenodo.6140111</a></p>
HeLa "Kyoto" cells under the scope
<p><strong>Name</strong>: HeLa “Kyoto” cells under the scope</p> <p><strong>Microscope</strong>: Perkin Elmer Operetta microscope with a 20x N.A. 0.8 objective and an Andor Zyla 5.5 camera.</p> <p><strong>Microscopy data type</strong>: The time-lapse datasets were acquired every 15 minutes, for 60 hours. From the individual plan images (channels, time-points, field of view exported by the PerkinElmer software Harmony) multi-dimension images were generated using the <a href="https://github.com/BIOP/ijp-operetta-importer/releases/tag/Operetta_Importer-0.1.21">Operetta_Importer-0.1.21</a> with a downscaling of 4. </p> <p>Channel 1 : Low Contrast DPC (Digital Phase Contrast)</p> <p>Channel 2 : High Contrast DPC</p> <p>Channel 3 : Brightfield</p> <p>Channel 4 : EGFP-α-tubulin</p> <p>Channel 5 : mCherry-H2B</p> <p><strong>File format</strong>: .tif (16-bit)</p> <p><strong>Image size</strong>: 540x540 (Pixel size: 0.299 nm), 5c, 1z , 240t</p> <p> </p> <p><strong>Cell type</strong>: HeLa “Kyoto” cells, expressing EGFP-α-tubulin and mCherry-H2B ( <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3839080/">Schmitz <em>et al</em>, 2010</a> )</p> <p><strong>Protocol</strong>: Cells were resuspended in <strong>Imaging media</strong> and were seeded in a microscopy grade 96 wells plate ( <a href="https://catalyse-erm.epfl.ch/erd-client/app/secure/sourcesearch/results?p=1&channel=SpendDirectorCatalog">CellCarrier Ultra 96</a>, Perkin Elmer). The day after seeding, and for 60 hours, images were acquired in 3 wells, in 25 different fields of view, every 15 minutes.</p> <p><strong>Imaging media</strong>: DMEM red-phenol-free media (FluoroBrite™ DMEM, Gibco) complemented with Fetal Calf Serum and Glutamax.</p> <p> </p> <p><strong>NOTE: </strong>This dataset was used to automatically generate label images in the following Zenodo entry: <strong> <a href="https://doi.org/10.5281/zenodo.6140064">https://doi.org/10.5281/zenodo.6140064</a></strong></p> <p><strong>NOTE: </strong>This dataset was used to train the cellpose models in the following Zenodo entry:<strong> <a href="https://doi.org/10.5281/zenodo.6140111">https://doi.org/10.5281/zenodo.6140111</a></strong></p>
Benchmark FIB SEM and Airyscan data of HeLa cells
<p>Sample volume electron microscopy dataset cropped from EMPIAR-10819 and fluorescence dataset from BioImage Archive S-BSST707 for the CLEM-Reg paper.</p>
HeLa-DAPI-EdU488-mCherryH2B
<p>Sample : HeLa cells fixed cells <br> Hyperstack : 3c, 1z, 1t<br> Microscope : Confocal Zeiss 710,<br> Objective : Plan-Aprochromat 40x/1.3 Oil DIC M27<br> Pinhole size : 37 um<br> Pixel size : 0.42 um<br> c1 : DAPI , 405<br> c2 : EdU-Alexa488, 488<br> c3 : mCherry, 555</p> <p>License: CC-BY 4.0, Romain Guiet, BIOP, EPFL</p>
HeLa_H2BmCherry_GFPtubulin_Mitotracker
<p>HeLa cell expressing H2B-mCherry, GFP-tubulin, stained with MitoTracker-DeepRed, acquired on Spinning Disk CSU-W1 (https://www.epfl.ch/research/facilities/ptbiop/equipment/visitron-csu-w1/) with an objective 60X N.A 1.42, Orca Flash 4.0 sCMOS camera.</p> <p>The time-lapse serie was cropped, time-lapse step reduced from 1 min to 3 min and rescaled to 8-bit (to reduce dataset size)</p>
Multiple Nuclei HeLa cell ground truth images with four labels (nuclear envelope, nucleus, rest of the cell, and background) for deep learning architecture training.
<p>This is a data set that contains <strong>labelled HeLa cell images</strong>, indicating the four different classes - nuclear envelope, nucleus, rest of the cell, and background. Similar ground truth have been published for this data set, but in this case, multiple nuclei have been labelled, whilst previous ones only focused on the central cell (https://doi.org/10.5281/zenodo.3874949)</p> <p>Details of the imaging, preparation and segmentation have been published in:</p> <ul> <li>Cefa Karabağ, Martin L. Jones, Christopher J. Peddie, Anne E. Weston, Lucy M. Collinson, Constantino Carlos Reyes-Aldasoro. Segmentation and Modelling of the Nuclear Envelope of HeLa Cells Imaged with Serial Block Face Scanning Electron Microscopy. <em>J. Imaging</em> <strong>2019</strong>, <em>5</em>(9), 75; <a href="https://doi.org/10.3390/jimaging5090075">https://doi.org/10.3390/jimaging5090075</a></li> <li>Cefa Karabağ, Martin L. Jones, Christopher J. Peddie, Anne E. Weston, Lucy M. Collinson, Constantino Carlos Reyes-Aldasoro. Semantic segmentation of HeLa cells: An objective comparison between one traditional algorithm and four deep-learning architectures, PLOS ONE, <strong>2020</strong>; <a href="https://doi.org/10.1371/journal.pone.0230605">https://doi.org/10.1371/journal.pone.0230605</a></li> <li> <p>Cefa Karabağ, Martin L. Jones, Constantino Carlos Reyes-Aldasoro, Segmentation of the Plasma Membrane of HeLa Cells,<em> J. Imaging</em> <strong>2021</strong>, <em>7</em>(6), 93; <a href="https://doi.org/10.3390/jimaging7060093">https://doi.org/10.3390/jimaging7060093</a></p> </li> </ul> <ul> <li>The data sets are freely available through EMPIAR: http://dx.doi.org/10.6019/EMPIAR-10094 EMPIAR.</li> </ul>
Oneat division model for Hela cells
<p>Trained models for hela cells for the bright field channel for locating mitosis events. Provided is an example dataset for bright field image and its corresponding model that can be used using the notebook here: https://github.com/Kapoorlabs-CAPED/CAPED-AI-oneat</p> <p> </p> <p>Made by oneat software, pip install oneat for training of such datasets.</p> <p> </p> <p>Original data published by Romain Guiet at https://zenodo.org/record/6139958#.YmAh1NpBxhG</p>
High-throughput poly(A) length measurement of HeLa and NIH 3T3 cells using TAIL-seq with MiSeq
<p>This dataset contains the full raw data directory from Illumina MiSeq generated for Chang et al. (2014, DOI: 10.1016/j.molcel.2014.02.007). Please refer to the original paper and its supplementary materials for further details.</p>
uncropped western blots for analysis of RPN13 ubiquitylation and NRF1 activation by protein aggregates, as well as source data for qPCR plots and flow cytometry gating and FCS files for agDD-GFP in HeLa or HEK cells
<p>This entry contains uncropped blots for Fig 4D and Fig S4C, Fig. 5B, Fig S5 and Fig S6, and the raw FCS files for Flow Cytometry data in doi.org/10.1101/2024.08.30.610524.</p>
Figures 1–4 in Vavizola hela - new species and genus of Afrotropic Lasiocampini (Lepidoptera, Lasiocampidae)
Figures 1–4. Nomenclature of the wing pattern and genitalia of Vavizola hela. 1. Holotype male, Tanzania, Arusha (MWM/ZSM). 2. Paratype female, Kenya, Kitui (CGM). 3. Paratype male, Tanzania, Arusha, slide 1267 (CGM). 4. Paratype female, Kenya, Kitui, slide 0501 (CGM). Scale bar – 1 cm for adults and 1 mm for genitalia.
Figures 28–33. Female genitalia. 28 in Vavizola hela - new species and genus of Afrotropic Lasiocampini (Lepidoptera, Lasiocampidae)
Figures 28–33. Female genitalia. 28. Vavizola hela, paratype, Kenya, Taita-Taveta, slide 17.447 (CGM). 29. Seydelora semna, DRC, Haut-Lomani, slide 1448 (NHML). 30. Braura ligniclusa, RSA, KwaZulu-Natal, slide 2006-24 (MfNB). 31. Gufria limosa powelli, Morocco, Tangier-Tétouan-Al Hoceima, slide 11.544 (MWM/ZSM). 32. Lasiocesa lanceolata, Angola, Ituri, slide 2006-53 (RMCA). 33. Eutricha capensis, RSA, Western Cape, slide 2006-47 (MfNB).
Figures 5–20 in Vavizola hela - new species and genus of Afrotropic Lasiocampini (Lepidoptera, Lasiocampidae)
Figures 5–20. Adults of Lasiocampini. 5–10. Vavizola hela. 5. Holotype male, Tanzania, Arusha, slide 17.446, LBEOW1233-11 (MWM/ZSM). 6. Paratype male, Tanzania, Arusha, slide 1267 (CGM). 7. Paratype female, Kenya, Kitui, slide 0501 (CGM). 8. Paratype male, Kenya, Lamu, slide 20.690 (CGM). 9. Paratype male, Kenya, Taita-Taveta (ZISP). 10. Paratype female, Taita-Taveta, slide 17.447, LBEOW975-11 (CGM). 11–12. Braura ligniclusa. 11. Male, RSA, Transvaal, slide 2006-08 (MfNB). 12. Female, RSA, KwaZulu-Natal, slide 2006-24 (MfNB). 13–14. Seydelora semna. 13. Male, DRC, Katanga (RMCA). 14. Female, DRC, Haut-Lomani, slide 1448 (NHML). 15–16. Lasiocesa fulgurata, male and female, DRC, Haut-Uele (RMCA). 17–18. Gufria limosa powelli, male and female, Tunisia, Nabeul (MWM/ZSM). 19–20. Eutricha capensis. 19. Male, RSA, Western Cape, slide 2006-12 (MfNB). 20. Female, RSA, Western Cape (NHML). Scale bar – 1 cm.
Figure 34 in Vavizola hela - new species and genus of Afrotropic Lasiocampini (Lepidoptera, Lasiocampidae)
Figure 34. NJ tree (Kimura-2 parameter model, built with MEGA X) based on sequence variation at COI (658 bp) and pairwise distances (%) between the sequences of some genera from the former "Pachypasa sensu lato" group (Lasiocampini).
Figures 21–27. Male genitalia. 21–22. Vavizola hela. 21 in Vavizola hela - new species and genus of Afrotropic Lasiocampini (Lepidoptera, Lasiocampidae)
Figures 21–27. Male genitalia. 21–22. Vavizola hela. 21. Holotype, Kenya, Lamu, slide 20.690 (CGM). 22. Paratype, Tanzania, Arusha, slide 17.446, LBEOW1233-11 (MWM/ZSM). 23. Gufria limosa powelli, Morocco, Tangier- Tétouan-Al Hoceima, slide 10.633 (MWM/ZSM). 24. Braura ligniclusa, RSA, Transvaal, slide 2006-08 (MfNB). 25. Seydelora semna, holotype, DRC, Haut-Katanga (RMCA). 26. Lasiocesa fulgurata, DRC, Haut-Uele, slide 2006-59 (RMCA). 27. Eutricha morosa, RSA, Western Cape, slide 2006-12 (MfNB).
3D time-course iSIM dataset HeLa cells MitoTracker Red CMXRos
<p>2020-03-17</p> <p>Microscopy dataset:</p> <p>- Type: Fluorescence, 3D, time-course, iSIM Visitech, 100x Silicon NA 1.35 (65 nm x 65 nm x 300 nm xyz pixel sizes), 20s time interval</p> <p>- Cell type: HeLa, labelled with MitoTracker Red CMXRos</p> <p> </p> <p>Romain F. Laine, r.laine@ucl.ac.uk, MRC-LMCB, UCL, London, UK</p>
Bred 104 Boda Hela Notexture
Boda i Bred 104, Uppland. Hällristning, hela ytan. Opus Heritas Fotogrammetri 3D-SfM av Catarina Bertilsson. Stockholms universitet, "Digitala bilder för forskning och publik". Source: Objaverse 1.0 / Sketchfab
Ullevi Gas Dilln 207 10 11 Hela Textur
Ullevi, Gåsinge-Dillnäs 207:10-11, Södermanland. Hällristning med skeppsfigur och skålgrop. Sörmlands museum och Opus-Heritas. 3D_SFM Source: Objaverse 1.0 / Sketchfab
Sequencing data for Flp-In T-Rex HeLa PINK1 CRISPR/CAS9 knock-out (CVCL_D5JI)
<p>PCR and sequencing data (.ab1 and .seq files) for CRISPR-Cas9 PINK1 knockout HeLa cells (clone 3C9) described in <a title="doi link" href="https://doi.org/10.1098/rsob.210264">doi.org/10.1098/rsob.210264</a>. Knock-out generated using the following guides (targeting exone 2), available from MRC-PPU Reagents and Services, University of Dundee: DU52528 and DU52530 (CRISPR Project #CR252). This cell line has been deposited to Cellosaurus: CVCL_D5JI.</p>
Fluorescence Microscopy Images of Hela Cell infected with Plasmodium Berghei parasite expressing mCherry in cytoplasm
<p>The purpose of our experiments was to delve into the liver stage development of the P. berghei parasite and examine the host-parasite interactions using HeLa cells. This research is primarily focused on in vitro analysis and does not extend to in vivo applications. Our study investigated the integration of fluorescent microscopy with artificial intelligence to <br>track and predict the developmental milestones of Plasmodium liver stage development. </p> <p>This is the dataset used in our study.</p>
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Allen Brain Atlas
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