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218 results for “electron imaging”
Dataset related to article "Imaging the kidney with an unconventional scanning electron microscopy technique: analysis of the subpodocyte space in diabetic mice".
<p><strong>Datasets:</strong></p> <p><strong>Table 1_Systemic parameters.xlsx </strong>- dataset related to the systemic parameters. These data are presented in Table 1. </p> <p><strong>Figure 6_Morphometric analysis.xlsx </strong>- dataset related to the morphometric characterization of the subpodocyte space and podocytes. These data are presented in Figure 6. </p> <p><strong>Abstract of the manuscript</strong></p> <p>Transmission electron microscopy (TEM) remains the gold standard for renal histopathological diagnoses, given its higher resolving power compared to light microscopy. However, it imposes several limitations on pathologists, including longer sample preparation time and a small observation area. To overcome these, we introduced a scanning electron microscopy (SEM) technique for imaging resin-embedded semi-thin sections of renal tissue. We developed a rapid tissue preparation protocol for experimental models and human biopsies which, alongside SEM digital imaging acquisition of secondary electrons (SE-SEM), enables fast electron microscopy examination, with a resolution similar to that achieved by TEM. We used this unconventional SEM imaging approach to investigate the subpodocyte space (SPS) in BTBR <em>ob/ob</em> mice with type 2 diabetes. Analysis of semi-thin sections with secondary electrons revealed that the SPS had expanded in volume and covered large areas of the glomerular basement membrane, forming wide spaces between the podocyte body and underlying filtering membrane. Our results show that SE-SEM is a valuable tool for imaging the kidney at the ultrastructural level, filling the magnification gap between light microscopy and TEM, and reveal that in diabetic mice the SPS is larger than in normal controls, which is associated with podocyte damage and impaired kidney function.</p>
IODP Expedition 385 Scanning electron microscope images
<p>Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.</p>
IODP Expedition 396 Scanning electron microscope images
<p>Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.</p>
IODP Expedition 374 Scanning electron microscope images
<p>Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.</p>
IODP Expedition 376 Scanning electron microscope images
<p>Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.</p>
Dataset of "Challenging Point Scanning across Electron Microscopy and Optical Imaging using Computational Imaging"
<p>Dataset containing the jupyter notebook with codes for the simulation of the structured illumination patterns used for image reconstruction (the simulation parameters have been optimized to make sure that the patterns were almost identical to the experimental ones), the reconstruction algorithms. Moreover, there are three experimental dataset saved as txxt file, where each line contains the six biases applied to the electron modulator and the intensity measured by the single pixel detector that we used.</p>
Dataset of "Single-Pixel Imaging in Space and Time with Optically Modulated Free Electrons"
<p>This dataset contains the simulated spatial images and temporal profiles reconstructed using the Electron Single-Pixel Imaging where free-electrons are shaped by light pulses. The reconstruction is performed using two different basis (Hadamard and Fourier) and for three different light frequency cutoffs. Some of these data and images are published in https://doi.org/10.1021/acsphotonics.3c00047. </p>
IODP Expedition 354 Scanning electron microscope images
<p>Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.</p>
IODP Expedition 369 Scanning electron microscope images
<p>Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.</p>
IODP Expedition 382 Scanning electron microscope images
<p>Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.</p>
IODP Expedition 392 Scanning electron microscope images
<p>Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.</p>
Scanning electron images of nanodiscs
<p>Images obtained by scanning electron microscopy of magnetic nanodiscs dried on a silicon substrate and nanodiscs interacting with skin cancer cells</p>
Segmentations of 3D electron microscopy image volume from an albino mouse dorsal lateral geniculate nucleus
Open the record for dataset details and reuse information.
Segmented high-resolution transmission electron microscopy images of nanoparticles
Open the record for dataset details and reuse information.
96x96 Electron Microscopy Images
<p>Three datasets available as numpy (.npy) files that can be opened in Python with np.load().</p> <p>There are 3 variants:</p> <ol> <li>Crops from full STEM images.</li> <li>STEM images area downsampled with MATLAB and default antialiasing.</li> <li>TEM images area downsampled with MATLAB and default antialiasing.</li> </ol> <p>Images were saved to University of Warwick dataservers by dozens of scientists working on hundreds of projects. </p> <p>Full-sized versions of datasets are available on a University of Warwick Electron Microscopy dataserver: <a href="https://warwick.ac.uk/fac/sci/physics/research/condensedmatt/microscopy/research/machinelearning/">https://warwick.ac.uk/fac/sci/physics/research/condensedmatt/microscopy/research/machinelearning/</a></p>
Machine learning refinement of in situ images acquired by low electron dose LC-TEM
<p>This is a dataset of images acquired in vacuum condition and corresponding images in a solution listed in the text file list_dataset.txt. </p><p> </p><p>The code is available at <a href="https://github.com/hiroyasukatsuno/Machine-learning-refinement-of-images-acquired-by-LC-TEM">this website</a>:</p><p>https://github.com/hiroyasukatsuno/Machine-learning-refinement-of-images-acquired-by-LC-TEM/</p><p><br>Equipment of TEM:</p><ul><li>field-emission gun (JEM-2100F, JEOL, Tokyo)</li><li>OneView IS (Gatan, Inc., Pleasanton, CA, USA)</li></ul><p> </p>
Data from: Combined fluorescent and electron microscopic imaging unveils the specific properties of two classes of meiotic crossovers
<p>Crossovers (COs) shuffle genetic information and allow balanced segregation of homologous chromosomes during the first division of meiosis. Recombination nodules (RNs) are closely correlated with crossing over, and, because they are observed by electron microscopy of synaptonemal complexes (SCs) in extended pachytene chromosomes, RNs provide the highest-resolution cytological marker currently available for defining the frequency and distribution of crossovers along the length of chromosomes. In several organisms, mutants demonstrate that two molecularly distinct pathways produce COs. One pathway produces class I COs that exhibit interference (lowered probability of nearby COs), and the other pathway produces class II COs with little or no interference. However, the relative contributions, genomic distributions, and interactions of these two pathways are essentially unknown in nonmutant organisms because marker segregation only indicates that a CO has occurred, not its class type. Here, we combine the efficiency of light microscopy for revealing cellular functions using a fluorescent probe to MLH1 proteins to mark class I COs with the high resolution of electron microscopy to localize and characterize all COs (RNs) in the same sample of meiotic pachytene chromosomes from wild-type tomato. To our knowledge, for the first time, every CO along each chromosome can be identified by class to unveil specific characteristics of each pathway. We find that class I (MLH1-positive) and class II (MLH1-negative) COs have different recombination profiles along chromosomes. In particular, class II COs, which represent about 18% of all COs, exhibit no interference and are disproportionately represented in pericentric heterochromatin, a feature potentially exploitable in plant breeding. Finally, our results demonstrate that the two pathways are not independent because there is interference between class I and II COs.</p>
Transmission electron microscopy (TEM) images of Silisyum dioxide nanoparticles.
<p>Transmission electron microscopy (TEM) images of Silisyum dioxide nanoparticles.</p>
Electron backscatter diffraction data and backscatter electron images from a cold-rolled and recovered Al-Mn alloy
<p>Three electron backscatter diffraction (EBSD) data sets and three sets of backscatter electron (BSE) images from the same region of interest in a cold-rolled and recovered Al-Mn alloy.</p> <p>The data forms part of the supplementary material to the paper H W Ånes, A T J van Helvoort, K Marthinsen "Correlated subgrain and particle analysis of a recovered Al-Mn alloy by directly combining EBSD and backscatter electron imaging" (2022), published in Materials Characterization.</p> <p>The data was acquired in order to study the effect of particles on recovery and recrystallization in the Al-Mn alloy. The particles detected in the BSE images were inserted in the EBSD map after the EBSD map had been corrected for distortions by image registration using the BSE images.</p> <p>See the GitHub repository https://github.com/hakonanes/correlated-grains-particles-workflow for Jupyter notebooks and (MATLAB) MTEX scripts used to analyze the data.</p>
Electron diffraction image files of rhodamine-6g microcrystals with CRYO ARM 300
<p>Diffraction images of rhodamine-6g collected with JEOL CRYO ARM 300 electron microscope at RIKEN, SPring-8. High-tension voltage was 300 kV. Camera distance was nominally 800 mm, but it could be calibrated with power-diffraction pattern of a gold sputtered grid. They were recorded with DirectElectron DE64 detector. Diffractions for orthorhombic crystals were collected at R.T. and cryo conditions and those for triclinic crystals were at cryo condition. Images were x2 binned and used for processing with DIALS. The output hkl files are also included in this entry.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.