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2,007 results for “Image Studies”
MASiVar: Multisite, Multiscanner, and Multisubject Acquisitions for Studying Variability in Diffusion Weighted Magnetic Resonance Imaging
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Images of article "Sexy ways: the methodical approaches to study plant sex chromosomes"
<p><strong>Figure 1. </strong>Schematic diagram of sex chromosome evolution in dioecious plants. Species are shown according to their level of sex chromosome differentiation and Y chromosome asynapsis. In<em> S. oleracea, A. officinalis</em> and <em>C. papaya</em>, the sex chromosomes are mostly homomorphic with recently formed non-recombining regions (region with suppressed recombination). The non recombining region is largely extended almost to entire chromosomal length in species with heteromorphic sex chromosomes, namely in <em>S. latifolia, R. hastatulus</em> (XY cytotype), <em>R. acetosa, H. lupulus, H. japonicus </em>and<em> M. polymorpha</em>. The position of the centromere, the PAR length and the ratio between X and Y is illustrative. </p> <p><strong>Figure 2.</strong> Laser microdissection as a tool to reduce genome complexity. Sex chromosomes in metaphase are isolated from plant cells (mostly pollen mother cells or root tips) and subsequently spread on a special microscopic slide covered with the membrane. After microdissection, chromosomes are transferred into a tube and processed to other applications. In case of chromosome sorting, the chromosome suspension is stained with a DNA-specific dye and introduced into a flow chamber. Within this chamber, individual chromosomes interact with a laser beam, and the scattered light and emitted fluorescence are measured. Through this process, a histogram of fluorescence intensity (known as a flow karyotype) is generated. Sorting is accomplished by breaking the liquid stream into droplets and electrically charging the droplets containing the chromosomes of interest.</p> <p><strong>Figure 3.</strong> Cytogenetic tools to study sex chromosome origin and evolution. Cytogenetics nowadays combine genomic tools to study repeat fraction including TEs and satellites (a), design unique barcodes to distinguish particular chromosome or chromosomal domain using chromosome oligo-painting probe design (b), and bioinformatic tools to dissect single chromosomes or genome parts (c). The combination of above methods helps to understand sex chromosome evolution regarding their autosomal origin, chromosomal rearrangements, and Y(W) chromosome differentiation. Arrows represent evolutionary steps during sex chromosome divergence (d). The sex chromosome barcoding allows understanding of meiotic pairing which in turn supports chromosomal fusions and inversion/translocations. To chromosomes belong to species with references, from the top to the bottom as follows: <em>S. latifolia </em>Ogre retroelement (Kubat et al., 2014), <em>R. hastatulus</em> XY cytotype satellite Cl135 (Sacchi et al., 2023, Preprint), <em>S. latifolia</em> PAR oligo-painting probe with the subtelomeric satellite X43.1 and centromeric satellite STAR-C (Bačovský et al., 2020), and the same DNA probes on chromosomes in metaphase I in <em>S. latifolia </em>(Bernasconi et al., 2009; Bačovský et al., 2022). </p> <p><strong>Figure 4.</strong> Methodical strategies to assess the function of sex chromosomes in plants. Experimental assays with polyploids (alternatively aneuploids) represent the classical way to determine the role of individual sex chromosomes (a). These assays with plants of various ploidy levels were usually supported by analyses of deletion lines (plants carrying short-chromosomal <br>deletions or microdeletions) (b) that allowed researchers to identify sex-linked regions involved in sex determination and floral development. Modern assays using reverse genetics, such as CRISPR/Cas9, virus-induced gene silencing (VIGS) or peptide treatment of shoot apical meristem (c) provide direct evidence of the gene function and its contribution to the development <br>of reproductive organs. Parasite infected (d) or chemically induced (e) hermaphrodites from either female or male individuals, e.g. in <em>Silene</em> or kaki, let to the identification of key mechanisms and genes that regulate sexual phenotypes, and to understand the regulatory networks leading to separate sexes. </p>
Mass spectrometry Imaging dataset for the study on fungicide application to tomato leaves - I
<p>The dataset uploaded here is in association to a manuscript in press by Ajith et al. titled, "Visualizing active fungicide formulation mobility in tomato leaves with Desorption Electrospray Ionisation Mass Spectrometry Imaging". This dataset contains .imzML format files of Mass Spectrometry Imaging data along with the zipped .ibd files for a fungicide application study with a commerical Azoxystrobin formulation. The files were generated with a DESI Imprint imaging method for a commercial pesticide formulation applied young tomato leaves after 2 hours, 24 hours, 56 hours and a week after application.</p> <table> <tbody> <tr> <td>File Name</td> <td>Time point</td> </tr> <tr> <td>DTIM_2h</td> <td>2h Adaxial Imprint</td> </tr> <tr> <td>DTIM_24h_1</td> <td>24h Adaxial Imprint</td> </tr> <tr> <td>DTIM_24h_2</td> <td>24h Adaxial Imprint</td> </tr> <tr> <td>DTIM_24h_3</td> <td>24h Adaxial Imprint</td> </tr> <tr> <td>DTIM_56h_1</td> <td>56h Adaxial Imprint</td> </tr> <tr> <td>DTIM_56h_2</td> <td>56h Adaxial Imprint</td> </tr> <tr> <td>DTIM_56h_3</td> <td>56h Adaxial Imprint</td> </tr> <tr> <td>DTIM_1week_1</td> <td>1 week Adaxial Imprint</td> </tr> <tr> <td>DTIM_1week_2</td> <td>1 week Adaxial Imprint</td> </tr> <tr> <td>DTIM_1week_3</td> <td>1 week Adaxial Imprint</td> </tr> <tr> <td>DTIM_48h_Abaxial</td> <td>48h Abaxial imprint</td> </tr> <tr> <td>DTIM_48h_Adaxial</td> <td>48h Adaxial Imprint</td> </tr> </tbody> </table> <p> </p>
RAW SEM images mosaics dataset for the HRDIC strain localization study in shot peened Ni superalloy
<p>We used a FEI Magellan HR 400L FE-SEM with a theoretical resolution of ≤ 0.9 nm at <1kV and ≤ 0.8 nm at ≥ 5kV to take backscattered electron images of the fine, homogeneous distributed gold speckle pattern obtained by remodelling of a thin gold layer previously deposited on the polished sample surface. The images were obtained at a working distance of 3.5 mm, 5 kV and 0.8 nA beam current. Mosaics of 30x15 images were used to cover 950x420 µm<sup>2</sup>. Each image contains 2048 x 1768 pixels and has a horizontal field of view of 43 µm. The images were overlapped by 20% to enable easy stitching prior to the digital image correlation. We obtained 7 mosaics, one before tensile testing and 6 after each deformation step.</p> <p>This set of images at different strain steps is coupled with the EBSD data set in https://doi.org/10.5281/zenodo.4730184, the HRDIC strain maps in http://doi.org/10.5281/zenodo.4728016 and data visualisation scripts in http://doi.org/10.5281/zenodo.4727939</p> <p>0_def corresponds to the undeformed sample, while 1_def to 6_def were obtained after each deformation step.</p>
An Empirical Study of Container Image Configurations and Their Impact on Start Times (Container Image Data)
<p>Dataset with the container image metadata used for our IEEE/ACM CCGRID 2023 paper "An Empirical Study of Container Image Configurations and Their Impact on Start Times".</p> <p>Abstract of the paper: A core selling point of application containers is their fast start times compared to other virtualization approaches like virtual machines. Predictable and fast container start times are crucial for improving and guaranteeing the performance of containerized cloud, serverless, and edge applications. While previous work has investigated container starts, there remains a lack of understanding of how start times may vary across container configurations. We address this shortcoming by presenting and analyzing a dataset of approximately 200,000 open-source Docker Hub images featuring different image configurations (e.g., image size and exposed ports). Leveraging this dataset, we investigate the start times of containers in two environments and identify the most influential features. Our experiments show that container start times can vary between hundreds of milliseconds and tens of seconds in the same environment. Moreover, we conclude that no single dominant configuration feature determines a container's start time and that hardware and software parameters must be considered together for an accurate assessment.</p> <p>Dataset description: Our images dataset contains 200,986 entries with 21 features associated to each container image. In the following, we describe the meaning of each feature. Further information is available in <a href="https://github.com/opencontainers/image-spec">OCI Image Specification</a> and the <a href="https://docs.docker.com/engine/reference/run/">Docker Run Documentation</a>. Besides the 20 features grouped in the five categories below, each dataset entry has a image_id, which is used to uniquely identify the dataset entry.</p> <p>Features</p> <p>Metadata features (prefix: meta)</p> <ul> <li><strong>meta_repo_digest</strong> : The repo digest is a SHA-256 hash which is used to uniquely identify and pull the image from Docker Hub</li> <li><strong>meta_architecture</strong> : The CPU architecture which the binaries in the image are built to run on</li> <li><strong>meta_os</strong> : The name of the operating system which the image is built to run on</li> <li><strong>meta_docker_version</strong> : The Docker version used to built this image</li> </ul> <p>I/O stream features (prefix: io)</p> <ul> <li><strong>io_attach_stdin</strong> : boolean setting to determine whether the console should be attached to the process stdin stream</li> <li><strong>io_attach_stdout</strong> : boolean setting to determine whether the console should be attached to the process stdout stream</li> <li><strong>io_attach_stderr</strong> : boolean setting to determine whether the console should be attached to the process stderr stream</li> <li><strong>io_tty</strong> : boolean setting to determine whether the console should pretend to be a TTY when attached</li> <li><strong>io_open_std_in</strong> : boolean setting to determine whether the process stdin stream should be kept open even if console not attached</li> <li><strong>io_std_in_once</strong> : boolean setting to determine whether the process retrieved input from the stdin stream at least once</li> </ul> <p>Start command features (prefix: cmd)</p> <ul> <li><strong>cmd_args</strong> : Length of list of arguments to use as the command to execute when the container starts</li> <li><strong>cmd_envvars</strong> : Environment variables set per default when the container starts</li> <li><strong>cmd_additional_args</strong> : Length of list for additional arguments to the containers entrypoint</li> </ul> <p>File system features (prefix: fs)</p> <ul> <li><strong>fs_volumes</strong> : Number of volumes to create/use by default</li> <li><strong>fs_size</strong> : Size of this image in bytes</li> <li><strong>fs_virtual_size</strong> : Virtual size of this image in bytes (equals size)</li> <li><strong>fs_graph_driver_name</strong> : Name of the image's graph driver</li> <li><strong>fs_root_fs_type</strong> : Name of the file system type used in the image</li> <li><strong>fs_layers</strong> : Number of root file system layers</li> </ul> <p>Networking features (prefix: net)</p> <ul> <li><strong>net_ports</strong> : Number of ports to expose per default</li> </ul> <p> </p> <p>Dataset acquisition: The dataset has been acquired from Docker Hub using a web crawler. We used substring matches with the <a href="https://hub.docker.com/explore">Docker Hub Explore function</a>. As search strings, we used all letter combination with sizes 1 to 3, meaning that our first search string was 'a' and our last was 'zzz'. We included both results from the 'recently updated' and the 'most popular' selection. We came up with an initial list of 286,294 image names. We then tested we could pull and start these images once. These tests have been conducted from April to June 2022. We sorted out all images that were either not pullable or startable and retrieved all total of 200,986 valid images. In the following, we describe the error types that we encountered and that let to the removal of the causing image from the dataset:</p> <ul> <li>The image manifest was unknown when we tried to download it meaning that is has been renamed or deleted from the time when our web crawler was running</li> <li>The entrypoint command required a dependency that was missing in the image and therefore the container could not be started</li> <li>The image did not specify an entrypoint command and could therefore not be started</li> <li>The image declared an invalid root file system type</li> <li>The image had a malformed root file system</li> <li>The image configuration was incomplete and therefore not all required data could be obtained</li> </ul> <p>See also our CodeOcean capsule with the processing scripts for our paper: https://doi.org/10.24433/CO.4595026.v2</p>
Magnetic Resonance Imaging Glucose Study Dataset
<p>The data has been produced by the Institut für Mikrostrukturtechnik (IMT) at Karlsruher Institut für Technologie (KIT). This dataset represents the DICOM (Digital Imaging and Communications in Medicine) files, which belong to one MRI (Magnetic Resonance Imaging) study and contain a series of images that have been measured with different protocols. The samples shown by the images are tubes, which contain different concentrations of Glucose. The DICOM file headers have metadata tags, which embody additional information about the study and the particular series.</p>
Pond Area Estimates: Nine Study Regions in Alaska for 3 time periods (1950s, 1978-1982, 1999-2001) using remotely sensed images
The data are ArcGIS shapefiles by USGS quadrangle within 9 study regions: Arctic Coastal Plain, Stevens Village area, Yukon Flats, Minto Flats, Denali Flats, Talkeetna, Innoko Flats, Tetlin Flats, and Copper River Basin. Each shapefile polygon represents the shoreline of a pond as visually interpreted from each georectified remotely sensed image. All images were rectified based on at least 25 control points from 1:63 360 USGS digital raster graphics topographic maps using a second-order polynomial with a RMS error of less than one satellite image pixel (30 meters). All closed-basin ponds greater than 0.2 hectares were visually delineated and manually traced as polygons using ArcGIS. Each pond polygon has an ID and Hectares field representing the pond ID and area in hectares for the time period of the remotely sensed image.
Dataset used for making conclusions in article Gesture-controlled image management for operating room: A randomized crossover study.
<p>Dataset used for article titled:</p> <p>Gesture-controlled image management for operating room: A randomized crossover study.</p>
Experimental datasets and CT-images for dilatant hardening study - Williams and French 2024
<p>Experimental datasets include collected and calculated parameters for the suite of experiments conducted. CT image datasets are the raw core scans.</p>
Figure 3: The microscopy images fo neuronal cells generated by SWCNT (a) and MWCNT (b)-COMPARATIVE STUDY OF SINGLE- AND MULTI-WALL CARBON NANOTUBES WITH APPLICATION IN CEREBRAL ANEURYSM
<p>Carbon nanotubes (CNTs) are nanometer-scale cylindrical graphitic struc-<br> tures that exhibit extraordinary physical properties as determined by their<br> structure [6]. Developing neural implants and the process of neuron regener-<br> ation are extremely di±cult. Nerve cells require the right environment and<br> the right growth factors at the right time to grow and proliferate. The elec-<br> trical conductive properties of these nanotubes o®er the possibility of using<br> it as a replacement to transmit and receive signals. The resulting 'hair like'<br> conductive wires that incorporate the properties of electrodes, permeable mi-<br> cro°uidic conduits and the porosity of the CNTs was found to promote cell<br> growth, migration and proliferation. The bridging consists either of an axon<br> or bundles of axons and dendrites. In some cases the bridge is covered with<br> clusters of cells [7]. These bridges form very e±ciently over quartz surfaces<br> which are apparently very poor surfaces for cell attachment. Fig. 2 shows the<br> evolution of a network generated by SWCNT and MWCNT. The data show<br> that cells ¯rst aggregate at the NT islands. As they complete this step axons<br> and dendrites begin to form and to build connections.<br> Also, has been observed for MWCNT higher connections than for SWCNT,<br> Figure 3.</p>
Figure 2: The microscopy images fo neuronal cells control (a) generated by MWCNT (b) and SWCNT (c)-COMPARATIVE STUDY OF SINGLE- AND MULTI-WALL CARBON NANOTUBES WITH APPLICATION IN CEREBRAL ANEURYSM
<p>Fig. 2 shows the evolution of a network generated by SWCNT and MWCNT. The data show<br> that cells ¯rst aggregate at the NT islands. As they complete this step axons and dendrites begin to form and to build connections.</p>
Images from the textile study visit at the Yale University Art Gallery, New Haven, USA for the TEX-KR project
<p>These pictures were taken at the Yale University Art Gallery storage facility as part of a study trip in March 2022 to research on the Cambodian textiles in the Yale collection for the EU-funded MSCA TEX-KR project.<br>The objects photographed by Magali An BERTHON are part of Helen Ibbitson Jessup's gift to Yale University Art Gallery.</p> <p>These objects are also accessible on the Yale University Art Gallery database: <a href="https://artgallery.yale.edu/collection?query=jessup&page=0" target="_blank" rel="noopener">Jessup gift textiles Yale</a></p> <p>To find out more: <br><span>"Acquisitions July 1, 2017–June 30, 2018," <em>Yale University Art Gallery Bulletin: Online Supplement</em> (accessed December 1, 2018), 21.</span></p> <p>This repository presents what has been relevant to the TEX-KR project, that is, images of textile details, marks of wear and tears, repairs, and motifs in the resist-dyed ikat technique. </p> <p>To credit the images appropriately:<br>- The photos with BERTHON in the file names are to credit © Magali An Berthon for TEX-KR. <br>- The photos with Yale in the file names come from the Yale University Art Gallery and are to credit ©Yale University Art Gallery with <a href="https://rightsstatements.org/page/UND/1.0/?language=en">Copyright undetermined</a>.</p>
Multi-modal image analysis for large scale cancer tissue studies within IMMUcan: multiplex immunofluorescence images
<p>In cancer research, multiplexed imaging has enabled the in-depth characterization of the tumor microenvironment (TME) and how it relates to patient prognosis. However, standardized, multi-modal data from large numbers of patients to identify robust biomarkers is missing. To provide such data across five cancer indications, the IMMUcan consortium performs broad molecular and cellular spatial profiling of thousands of cancer samples. Two reproducible and scalable workflows have been developed for whole slide multiplexed immunofluorescence (mIF) and imaging mass cytometry (IMC) to overcome challenges of reproducibility and scalability. For mIF we developed IFQuant, a web-based tool optimized for user-friendliness and reproducibility. This Zenodo record contains the mIF images and IFQuant settings to reproduce the results presented in the referenced publication. The companion IMC dataset is available as a joint Zenodo record.</p>
Figure 6.Amygdala hypofunction after a single oral 40-mg dose, 1.5-hours post-dose, in young study participants.The image has been adapted from (Hurlemann et al., 2010).-The Brain and Propranolol Pharmacokinetics in the Elderly
<p>In the past decade, there has been much interest in identifying treatment in adding to the<br> current treatment options for war veterans suffering from Post-Traumatic Stress Disorder (PTSD).<br> The studies investigating secondary-preventative measures for PTSD using Propranolol due to the<br> drug’s ability to inhibit the actions of the neurotransmitter norepinephrine,which has been<br> implicated to enhance the consolidation(McGhee et al., 2009; Pitman et al., 2002; Stein et al.,<br> 2007).Further, in a double-blind, placebo-controlled,functional Magnetic Resonance Imaging<br> (fMRI) study, in healthy volunteers, Hurlemann et al. found that a single oral 40mg dose of<br> propranolol attenuatedthe leftbasolateral amygdala responses to the face perception<br> paradigm(Hurlemann et al., 2010). The study participants were eighteen healthy (9 females, 9<br> males; mean age 23 years; age range 19–31 years) who had their fMRI acquisition 1.5-hours after<br> the oral administration of propranolol. An adapted image of the study findings are shown in Figure<br> 6.</p>
Figure 5.(a)Linear (y=0.45x + 57.74) dose-response relationship between plasma propranolol to % β- adrenergeric blockade derived from healthy study participants and translate into patients with angina pectoris. This image has been adapted from(Pine et al., 1975).-The Brain and Propranolol Pharmacokinetics in the Elderly
<p>Apharmacodynamic model,with parameters in the table below, may be used to visualize the<br> propranolol concentration-effect (β-blockade) relationship in patients suffering from angina pectoris.<br> These results have been adapted from the Pine et al article published in Circulation in 1975 which<br> identified a linear relationship plasma Propranolol (ng/mL) to an effect of % β-Adrenergic Blockade<br> in a single-oral dose of 40mg Propranolol in exercising individuals (Pine et al., 1975).</p>
Dataset of Cervical Cell Images for the Study of Changes Associated with Malignancy in Conventional Pap Test
<p>This data set was approved by CEP, a human-research ethics committee {Comitê de Ética em Pesquisa de Campinas}, Brazil <em>(CAAE approval number: 71277217.6.0000.5404) </em></p> <p>Cervical cancer prevention campaign was carried out at the University of Campinas (Brazil), where 71 women were treated. For this study, six women were chosen: non-pre-menopausal, non-pregnant and between the ages of 25 and 40 years. Samples diagnosed with normal squamous lesions, atypia in squamous cells of undetermined significance (AC-US), low-grade squamous intraepithelial lesion LEI (changes associated with HPV infection or light dislocation (NIC 1)), and immature squamous metaplasia, were chosen. All samples were collected before treatment. The patients were anonymized and assigned a unique identifier. The criterion to limit the number of plates used in this study is related to the large amount of data to be processed and the computational cost necessary for this process.</p> <p>Raw data sets are available as CSV files. Each data was numbered to include the identification of the meta-data, along with the tag of the images following a sequence. For example, the data file<em> “ 01-CAP091868-MORF.csv ”</em> has the prefix 01 that refers to the sequential numbering of the files with the data from the digitized slide.</p> <p>The data set contains 102 digitized images of the human papilloma examination of 7 different patients. They were segmented 962</p>
Myotonic dystrophy research: imaging result files ( DTI, VBM) from a 5-year longitudinal follow-up study
<p>This ZIP-file contains supplementary data belonging to the manuscript</p> <p><strong>"Tracking the brain in myotonic dystrophy: a 5-year longitudinal follow-up study", published in PLOS ONE.</strong></p> <p>In this manuscript we aimed to examine the natural history of brain involvement in adult-onset myotonic dystrophies type 1 and 2 (DM1, DM2). We conducted a longitudinal observational study to examine functional and structural cerebral changes in myotonic dystrophies. We enrolled 16 adult-onset DM1 patients, 16 DM2 patients, and 17 controls. At baseline (T1) and at follow-up (T2) participants underwent neurological, neuropsychological, and 3T-brain MRI examinations using identical study protocols that included voxel-based morphometry and diffusion tensor imaging.</p> <p>The ZIP-file contains imaging result files from the different statistical analyses. </p>
Figure 4 in Using digital images in the study of fluctuating asymmetry in the spur-thighed tortoise Testudo graeca
Figure 4. The distribution of the differences between the average values for area (A), height (B), and width (C) for the left (LSP) and right (RSP) sides of the plastron relative to straight carapace length (SCL) and the corresponding average value in each SCL class (females n = 79, male n = 76).
Figure 5 in Using digital images in the study of fluctuating asymmetry in the spur-thighed tortoise Testudo graeca
Figure 5. The distribution of the differences between the average values for area (A), height (B), and width (C) for the left (LSP) and right (RSP) sides of the plastron relative to straight carapace length (SCL) and the corresponding average value in each CCL class (females n = 79, male n = 76).
Fig. 4 in Applications and limitations of micro-XCT imaging in the studies of Permian radiolarians: A new genus with bi-polar main spines
Fig. 4. Dendrogram of the cluster analysis under the corresponding analysis based on nine genera (performed by software "R" and the EZR).
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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.