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1,255 results for “High-resolution”
High-resolution transcriptome analysis of mouse subventricular zone reveals features of stem cell lineage, anatomy, and aging
GEO Series GSE107220. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
High-resolution Comparative Analysis Reveals a Primitive 3D Genome in Embryonic Stem Cells
GEO Series GSE85977. Homo sapiens. 4 samples. Type: Other; Third-party reanalysis.
High-resolution CRISPR/Cas9 screens identify PAK2 as a suppressor of macrophage proliferation and macropinocytosis.
GEO Series GSE251887. Mus musculus. 32 samples. Type: Other.
Dataset related to article "Assessing the Feasibility and Accuracy of High-resolution Microultrasound Imaging for Bladder Cancer Detection and Staging"
<p>BACKGROUND:</p> <p>Magnetic resonance imaging (MRI) has been proposed as a staging tool for bladder cancer (BC), but its use has been limited by its high costs and limited availability. Microultrasound (mUS) is a novel technology capable of providing high-resolution images of the prostate.</p> <p>OBJECTIVE:</p> <p>To test the feasibility of high-resolution mUS in patients diagnosed with BC and its ability to differentiate between non-muscle-invasive BC (NMIBC) and muscle-invasive BC (MIBC).</p> <p>DESIGN, SETTING, AND PARTICIPANTS:</p> <p>This is an observational prospective study performed in 23 patients with a diagnosis of primary BC scheduled for an endoscopic treatment.</p> <p>SURGICAL PROCEDURE:</p> <p>Micro-US was performed before transurethral resection of bladder tumor using the ExactVu system with an EV29L 29-MHz side-fire transducer (Exact Imaging, Markham, Canada).</p> <p>MEASUREMENTS:</p> <p>The endpoints were to test the feasibility, describe the normal bladder wall anatomy, identify the lesions, and compare the mUS findings with the histopathological results.</p> <p>RESULTS AND LIMITATIONS:</p> <p>Micro-US was accurate in differentiating the three layers of the bladder wall in all cases. Bladder cancers were clearly identified as heterogeneous structures protruding from the normal bladder wall. In 14 cases the lesions appeared confined to the lamina propria, and in all cases NMIBC was confirmed by the final pathological report. In the other patients, the lesions seemed to extend into the muscular layer, but MIBC was confirmed in five out of seven cases (71.4%) from the pathologist. The small sample size was the main limitation of the current study.</p> <p>CONCLUSIONS:</p> <p>Our findings showed that mUS is able to differentiate the bladder wall layers and identify the bladder cancer stage. Further studies with a larger population and imaging correlation with MRI are warranted before its introduction in clinical practice.</p> <p>PATIENT SUMMARY:</p> <p>In this report, a new imaging technique was tested for the characterization of bladder cancer. Microultrasound appears to be feasible and capable of discriminating between superficial and invasive tumors</p>
FIGURE 38 in Osteology of Tyrannosaurus rex: insights from a nearly complete skeleton and high-resolution computed tomographic analysis of the skull
FIGURE 38. FMNH PR2081, Tyrannosaurus rex. Parasphenoid rostrum in left lateral view.
Supplementary MRSI Data for "High-Resolution Metabolic Imaging of High-Grade Gliomas using 7T-CRT-FID-MRSI" - NIFTI Format FIXED
<p>Intended as supplementary data to the manuscript "High-Resolution Metabolic Imaging of High-Grade Gliomas using 7T-CRT-FID-MRSI"</p> <p>Authors:<br> Gilbert Hangel, Cornelius Cadrien, Philipp Lazen, Julia Furtner, Alexandra Lipka, Eva Hečková, Lukas Hingerl, Stanislav Motyka, Stephan Gruber, Bernhard Strasser, Barbara Kiesel, Mario Mischkulnig, Matthias Preusser, Thomas Roetzer, Adelheid Wöhrer, Georg Widhalm, Karl Rössler, Siegfried Trattnig and Wolfgang Bogner</p> <p>###################################################<br> MRSI Maps from the Vienna 7T scanner in MINC format<br> ###################################################</p> <p>Contact: wolfgang.bogner@meduniwien.ac.at , gilbert.hangel@meduniwien.ac.at<br> https://hfmr.meduniwien.ac.at/</p> <p>For use with NIFTI-displaying software.</p> <p>MRSI method published as Hingerl et al 2020, doi: 10.1097/RLI.0000000000000626</p> <p>Patient 1:<br> Glioblastoma WHO Grade 4, with IDH1 mutation, male<br> Patient 2:<br> Glioblastoma WHO Grade 4, with IDH1 mutation, male<br> (Same numbers as in the manuscript)</p>
A large-scale high-resolution cropland non-agriculturalization (Hi-CNA) dataset
<p><span>The Hi-CNA is a high-resolution remote sensing dataset dedicated to the cropland non-agriculturalization (CNA) tasks, featuring high-quality semantic and change annotations for cropland. The study area covers parts of Hebei, Shanxi, Shandong, Hubei provinces in China, with a total area exceeding 1100 km<sup>2</sup>. These regions exhibit significant variations in crop planting, ensuring the diversity of cropland morphologies. The first temporal phase spans from 2015 to 2017, while the second phase ranges from 2020 to 2022, covering multiple phenological periods of crops. These characteristics provide a rich variety of samples for CNA tasks.</span></p> <p><span><span>The dataset is sourced from multispectral GF-2 fusion images with a spatial resolution of 0.8m, encompassing four bands including visible light and near-infrared. All images are cropped to 512*512, resulting in a total of 6797 pairs of dual-temporal images with corresponding annotations. Figure 1 illustrates different forms of cropland and some types of changes.</span></span></p>
Dataset related to article "Use of high-resolution micro-ultrasound to predict extraprostatic extension of prostate cancer prior to surgery: a prospective single-institutional study "
<p>This record contains raw data related to article “Use of high-resolution micro-ultrasound to predict extraprostatic extension of prostate cancer prior to surgery: a prospective single institutional study"</p> <p><strong>Purpose: </strong> We aim to evaluate the accuracy of micro-ultrasound (microUS) in predicting extraprostatic extension (EPE) of Prostate Cancer (PCa) prior to surgery.</p> <p><strong>Methods: </strong> Patients with biopsy-proven PCa scheduled for robot-assisted radical prostatectomy (RARP) were prospectively recruited. The following MRI-derived microUS features were evaluated: capsular bulging, visible breach of the prostate capsule (visible extracapsular extension; ECE), presence of hypoechoic halo, and obliteration of the vesicle-prostatic angle. The ability of each feature to predict EPE was determined.</p> <p><strong>Results: </strong> Overall, data from 140 patients were examined. All predictors were associated with non-organ-confined disease (p < 0.001). Final pathology showed that 79 patients (56.4%) had a pT2 disease and 61 (43.3%) ≥ pT3. Rate of non-organ-confined disease increased from 44% in those individuals with only 1 predictor (OR 7.71) to 92.3% in those where 4 predictors (OR 72.00) were simultaneously observed. The multivariate logistic regression model including clinical parameters showed an area under the curve (AUC) of 82.3% as compared to an AUC of 87.6% for the model including both clinical and microUS parameters. Presence of ECE at microUS predicted EPE with a sensitivity of 72.1% and a specificity of 88%, a negative predictive value of 80.5% and positive predictive value of 83.0%, with an AUC of 80.4%.</p> <p><strong>Conclusions: </strong> MicroUS can accurately predict EPE at the final pathology report in patients scheduled for RARP.</p>
Data from: High-resolution methylome analysis uncovers stress-responsive genomic hotspots and drought-sensitive TE superfamilies in the clonal Lombardy poplar
<p>The following dataset contains the processed data presented in the article<strong> "High-resolution methylome analysis uncovers stress-responsive genomic hotspots and drought-sensitive TE superfamilies in the clonal Lombardy poplar"</strong></p> <ul> <li><strong>Supplementary_methods.docx: </strong>contain detailed information for the experimental stress treatments, sequencing library preparation, sequencing and DMR calling.</li> </ul> <ul> <li><strong>BedGraph files (CpG.bed, CHG.bed, CHH.bed):</strong> contain methylation levels (%) for each cytosine in the Lombardy poplar genome, in the respective sequence context. The first three columns represent the genomic coordinates of the cytosine, the 56 following columns indicate the methylation levels for each of the samples. Missing values are represented with NA (when particular cytosines were not captured by the sequencing method). </li> <li><strong>DMR_annotation_Populus_nigra_Italica_after_biotic_and_abiotic_treatments.txt: </strong>contains all the identified regions that showed significant stress-induced differential methylation (DMR). The file include all annotation for each single DMR: genomic location, genomic feature, gene, TE, sequence context and stress treatment, besides other specific relevant information.</li> <li><strong>sample_IDs_basic_metadata.txt</strong>: contains the sample ID and the associated metadata (stress treatment and ortet location and ID) for all samples used in the analysis.</li> <li><strong>Supplementary_file_1_metadata_samples.xlsx: </strong>contains the metadata associated to each sample including: sequencing statistics before and after quality and adapter trimming, read mapping and coverage statistics, and number of interrogated cytosines on each sequence context (CpG, CHG, CHH).</li> <li><strong>Supplementary_file_2_GO_enrichments.xlsx: </strong>contains the complete results for the GO enrichment analysis for different gene datasets associated to: drought-CHH-DMRs, SINEs, MITEs, SINEs + MITEs.</li> <li><strong>italica_denovo_TE_280920.gff</strong>: contains the predicted TEs using the following methodology. First, TEs were de-novo annotated using the Extensive de-novo TE Annotator (EDTA) (version 1.8.3) (https://github.com/oushujun/EDTA) with default parameters, except for option --sensitive: 1, which uses RepeatModeler (version 2.0.1) to identify remaining TEs. All the steps in EDTA pipeline were selected (filter, final and anno) in order to perform whole-genome annotation/analysis after the TE library was constructed. Then, in the annotated library from EDTA, we merged overlapping fragments and fragments located at a close distance (<10bp) in a strand wise manner. The merged fragment was annotated as the family of longer merged fragment. Structural variants derived from nanopore data were used to redefine the boundaries of overlapping TE fragments to be more precise with actual predictions. LINE elements were identified independently by RepeatModeler in order to construct a more comprehensive de-novo TE library.</li> <li><strong>SaliS.fasta:</strong> contains the consensus sequences of <strong>Sali</strong>caceae <strong>S</strong>INE families (SaliS), the file was built by extracting information from the supplementary table 2 of the publication: "Divergence of 3′ ends as a driver of short interspersed nuclear element (SINE) evolution in the Salicaceae" (https://doi.org/10.1111/tpj.14721)</li> <li><strong>Pnigra_Italica_SaliS.bed: </strong>the file contains the annotated SaliS found by blastn over the P. nigra Italica reference genome (-qcov_hsp_perc 90 -perc_identity 70 -word_size 7). Column headers: chr, start, end, length, strand, perc_identity, SaliS family.</li> <li><strong>Pnigra_Italica_all_TEs_for_anno.bed: </strong>contains the merged information from <strong>italica_denovo_TE_280920.gff </strong>and<strong> Pnigra_Italica_SaliS.bed.</strong> Column headers: chr, start, end, length, strand, perc_identity (only for SaliS), TE superfamily.</li> <li><strong>CXX_ortet_DMRs_merged.bed</strong>: contains DMRs merged from all pairwise DMR callings between two ortets. One file per context. Column headers: chr, start, end, number of comparisons where the DMR occur, avg number of cytosines (when called in multiple DMR callings), avg differential methylation vs. control (when called in multiple DMR callings), avg adjusted p value (when called in multiple DMR callings), avg DMR length (when called in multiple DMR callings).</li> </ul> <p><strong>SCRIPTS</strong></p> <ul> <li><strong>cov_filtering.sh:</strong> to filter individual positions according to a custom threshold.</li> <li><strong>unionbedg_with_NAs.sh:</strong> to merge information from different samples in a single file taking into account the percentage of missing values per position across the given samples.</li> <li><strong>anovas_and_contrasts_boxplots_barplots_cld.r</strong>: to perform statistical tests for the effect of treatments and ortets on the average global methylation. Each sequence context was analyzed separately.</li> <li><strong>CHH_noise_filter.sh:</strong> to remove cytosines with invariable methylation values across 90% of the samples.</li> <li><strong>GlobalMethAvg_calculation.r</strong>: to calculate global average methylation given a methylation file (CpG.bed, CHG/bed or CHH.bed) and sample file.</li> <li><strong>Hclustering_and_PCAs_analysis.r:</strong> to perform hierarchical clustering, principal component analysis and plot the respective figures.</li> <li><strong>ICC_matrices_analysis.r:</strong> to calculate intraclass correlation coefficients among all pairwise combinations and plot colored grids</li> </ul> <p> </p> <p>Annotations are based on the de novo reference genome of the Populus nigra cv. Italica clone uploaded in the ENA project: PRJEB44889 (<a href="http://www.ebi.ac.uk/ena/browser/view/GCA_950102115">www.ebi.ac.uk/ena/browser/view/GCA_950102115</a>). Bisulfite sequencing data can be found under the ENA project: PRJEB51831</p>
High-resolution transcriptional analysis of immunoglobulin variable regions reveals the absence of direct relationships between somatic hypermutation, nascent transcription and epigenetic marks [MutPE
GEO Series GSE202039. Homo sapiens; Mus musculus. 36 samples. Type: Other.
High-resolution mapping of transcribing Pol III by CRAC in the WT and C128 mutants
GEO Series GSE196398. Saccharomyces cerevisiae. 8 samples. Type: Other.
High-resolution transcriptional analysis of immunoglobulin variable regions reveals the absence of direct relationships between somatic hypermutation, nascent transcription and epigenetic marks
GEO Series GSE202042. Drosophila melanogaster; Mus musculus; Homo sapiens. 78 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Other.
High-Resolution Genome-Wide Maps Reveal Widespread Presence of Torsional Insulation
GEO Series GSE284352. Saccharomyces cerevisiae. 20 samples. Type: Other.
The human transcription factor occupancy landscape viewed using high-resolution in situ base-conversion strand-specific single-molecule chromatin accessibility mapping
GEO Series GSE301497. Homo sapiens. 8 samples. Type: Other.
High-resolution transcriptional analysis of immunoglobulin variable regions reveals the absence of direct relationships between somatic hypermutation, nascent transcription and epigenetic marks [ChIP-
GEO Series GSE202038. Homo sapiens; Drosophila melanogaster. 12 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
High-resolution transcriptional analysis of immunoglobulin variable regions reveals the absence of direct relationships between somatic hypermutation, nascent transcription and epigenetic marks [PRO-c
GEO Series GSE202040. Homo sapiens; Mus musculus; Drosophila melanogaster. 11 samples. Type: Other.
High-resolution genome-wide copy number analysis of low grade serous ovarian tumours
GEO Series GSE58579. Homo sapiens. 179 samples. Type: Genome variation profiling by SNP array.
High-resolution analysis of chromatin structure by Mnase-SSP
GEO Series GSE125053. Mus musculus. 14 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
High-resolution transcriptional analysis of immunoglobulin variable regions reveals the absence of direct relationships between somatic hypermutation, nascent transcription and epigenetic marks [ATAC-
GEO Series GSE202037. Homo sapiens. 1 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Single-cell profiling of Acute Myeloid Leukemia for high-resolution chemo-immunotherapy target discovery
For more information, including a more complete description, data generator contact information, and reference, please see: https://scpca.alexslemonade.org/projects/SCPCP000007.
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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.