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Temporal stability of fMRI in medetomidine-anesthetized rats
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In vivo rat brain for Ultrasound Localization Microscopy: raw and beamformed data.
<p><strong>Datasets provided for Open Platform for Ultrasound Localization Microscopy: Performance Assessment of Localization Algorithms.</strong></p> <p><strong>Abstract:</strong></p> <p>Ultrasound Localization Microscopy (<strong>ULM</strong>) is an ultrasound imaging technique that relies on the acoustic response of sub-wavelength ultrasound scatterers to map the microcirculation with an order of magnitude increase in resolution. Initially demonstrated <em>in vitro</em>, this technique has matured and sees implementation<em> in vivo</em> for vascular imaging of organs, and tumors in both animal models and humans. The performance of the localization algorithm greatly defines the quality of vascular mapping. We compiled and implemented a collection of ultrasound localization algorithms and devised three datasets<em> in silico</em> and<em> in vivo</em> to compare their performance through 18 metrics. We also present two novel algorithms designed to increase speed and performance. By openly providing a complete package to perform ULM with the algorithms, the datasets used, and the metrics, we aim to give researchers a tool to identify the optimal localization algorithm for their usage, benchmark their software and enhance the overall image quality in the field while uncovering its limits.</p> <p>This article provides all materials and post-processing scripts and functions.</p> <p><strong>Methods:</strong></p> <p>200.000 ultrasound images have been acquired <em>in vivo </em>on a rat brain with skull removal at 1000 Hz with a 15 MHz linear probe.</p> <p>This dataset contains raw radiofrequency data (<strong>RF</strong>) and beamformed images (<strong>IQ</strong>) of the brain vascularization with flowing microbubbles (ultrasound contrast agent).</p> <p><strong>Article to be cited:</strong> Heiles, Chavignon, Hingot, Lopez, Teston and Couture.<br> <a href="http://doi.org/10.1038/s41551-021-00824-8"><em>Performance benchmarking of microbubble-localization algorithms for ultrasound localization microscopy</em>, Nature Biomedical Engineering, 2022, (doi.org/10.1038/s41551-021-00824-8)</a>.</p> <p><strong>Related processing scripts and codes:</strong> <a href="https://github.com/AChavignon/PALA">github.com/AChavignon/PALA</a></p> <p><strong>Related datasets:</strong> <a href="https://doi.org/10.5281/zenodo.4343435">doi.org/10.5281/zenodo.4343435</a></p> <p><strong>Acknowledgments:</strong></p> <p>We thank Cyrille Orset (INSERM UMR-S U1237, Physiopathology and Imaging of Neurological Disorders, GIP Cyceron, BB@C, Caen, France) for animals’ preparation and perfusion of contrast agent and the biomedical imaging platform CYCERON (UMS 3408 Unicaen/CNRS, Caen, France).</p>
Rat_rest_STZ
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An isotropic EPI database for rat brain resting-state fMRI
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Genome, repeat, and functional annotation associated with the naked mole-rat genome assembly, mHetGlaV3 (GCA_964261345.1)
<p>The naked mole-rat (NMR; Heterocephalus glaber) is a eusocial subterranean rodent with a highly unusual set of physiological traits, such as extreme longevity, that has attracted great interest amongst the scientific community. However, the genetic basis of most of these traits has not been elucidated. To facilitate our understanding of the molecular mechanisms underlying NMR physiology and behaviour, we generated a long-read chromosomal-level genome assembly of the NMR. This genome, mHetGlaV2, was subsequently annotated and incorporated into a “91 eutherian mammals” multiple whole genome alignment in Ensembl. </p> <p>We identified intra-chromosomal misassemblies within mHetGlaV2. We fixed these misassemblies by comparing syntenic blocks between this assembly and the Canadian Porcupine (EreDor) genome assembly (https://www.ncbi.nlm.nih.gov/datasets/genome/GCA_028451465.1/) and a FISH-Karyotype of the naked mole-rat completed by Romanenko et al., 2023 (PMID: 380307020) to address any misassemblies and place centromeres. Chromosome numbering was identified from a composite karyogram of karyotypes from over 350 cells. This scaffold-corrected assembly is labelled mHetGlaV3 (https://www.ebi.ac.uk/ena/browser/view/GCA_964261345.1).</p> <p>This repository stores the repeat, genome, and epigenome annotations for HetGlaV3.</p> <p>mHetGlaV3.primary.gtf.gz. Gene structures and gene symbols are transferred from ENSEMBL annotations of mHetGlaV2 using liftOff with default parameters. Additional gene symbols were identified using TOGA and manual curation.</p> <p>mHetGlaV3.primary.gtf.gz. Simple repetitive regions and transposable elements were annotated using EarlGrey (https://github.com/TobyBaril/EarlGrey) using "Rodentia" annotations for RepeatMasker.</p> <p>mHetGlaV3.primary.genesymbol_table.txt.txt.gz. A tab-delimited file where rows are gene IDs and columns are gene symbols generated with each method. "Consensus" shows the best matching gene symbol for each gene ID.</p> <p>mHetGlaV3.primary_annotated_blacklist.bed.gz. Provides an assembly "blacklist" for mHetGlaV3. This blacklist is a bed file annotating assembly breakpoints between HetGlaV2 and HetGlaV3. This blacklist contains additional columns (e.g., closest gene, overlapping TE etc.) and should therefore be filtered to the first column before being incorporated into traditional genomic pipelines.</p> <p>mHetGlaV3.primary_hypothalamus_ABC_enhancer.bedpe.gz. Activity-By-Contact enhancers (https://github.com/broadinstitute/ABC-Enhancer-Gene-Prediction) generated in the female subordinate naked mole-rat hypothalamus using Hi-C-seq, ChIP-seq of H3K27Ac data, ATAC-seq, and RNA-seq information.</p> <p>mHetGlaV3.primary_hypothalamus_chromHMM.bed.gz. Chromatin states (using Chromhmm) annotating the female subordinate naked mole-rat hypothalamus using H3K4me3 (promoter), H4K4me2 (promoter-enhancer), H3K27Ac (active enhancer), H3K36me3 (elongated), H3K27me3 (polycomb repressed), H3K9me3 (heterochromatin), and CTCF (whole brain) ChIP-seq data, as well as ATAC-seq and RNA-seq data.</p> <p>mHetGlaV3.primary.fa.gz. Genome assembly fasta file for the naked mole-rat (V3, primary assembly). This assembly matches the primary assembly stored on ENA, however the chromosome names match these files, rather than have chromosome names processed by ENA (e.g. chr 1 instead of "OZ179169.1 Heterocephalus glaber genome assembly, chromosome: 1").</p> <p> </p> <p>UPDATES:</p> <p>* The 1.2 update fixed unscaffolded contig names from those used in-lab to those compatible with ENA.</p> <p>* The 1.3 update added small (50~100kbp) contigs onto mHetGlaV3.primary.fa.gz that were filtered before the ENA submission.</p> <p>* The 1.4 update fixed a small chromosome naming inconsistency spotted in the 1.3 update.</p>
Preprocessed rat brain voxel time series
<p>Preprocessed version of voxel time-series for three rats, originally described in Becq et al., Functional connectivity is preserved but reorganized across several anesthetic regimes, NeuroImage, 2020. Used in Achard et al., Inter-regional correlation estimators for functional magnetic resonance imaging, arXiv, 2022, arXiv:2011.08269.</p> <p>The files named "coord_ROI_x.txt" contain the coordinates of the voxels inside region x (each line corresponds to one voxel).</p> <p>The files named "ts_ROI_x.txt" contain the BOLD signal time series of the voxels inside region x (each line corresponds to one voxel, each column to one timepoint). The voxels with time series equal to zero have been removed</p> <p>The files named "weight_ROI_x.txt" contain the weights associated with the voxels inside region x (each line corresponds to one voxel). Indeed, when assigning voxels to regions, some voxels end up at the border of several regions. These weights characterize the proportion of a given voxel present inside a given region. Hence, some voxels are included in several different regions. So when we compute the voxel-to-voxel inter-correlation between two regions we sometimes end up with inter-correlations equal to 1. In the current dataset this issue has been resolved and each voxel has been assigned to a single region.</p>
Aligned bam files for "Phylogenetic modeling of enhancer shifts in mole-rats reveals regulatory changes associated with tissue-specific traits"
<p>Aligned bam files used for analysis in "Phylogenetic modeling of enhancer shifts in mole-rats reveals regulatory changes associated with tissue-specific traits".</p> <p>This is an accompanying dataset to Datasets and code for "Phylogenetic modeling of enhancer shifts in mole-rats reveals regulatory changes associated with tissue-specific traits" (https://zenodo.org/record/7442105).</p>
Deciphering the scopolamine rat model by preclinical functional MRI
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Deep and complex vascular anatomy in the rat brain described with Ultrasound Localization Microscopy in 3D
<p><strong>Abstract:</strong></p><p>Ultrasound Localization Microscopy (<strong>ULM</strong>) enables imaging microvessels in the brain with a resolution of a few tens of micrometers <i>in vivo</i>. The planar architecture of arterioles and venules was revealed with a 2D ultrasound scanner in the cortex of the rat brain. However, deeper in the brain, where the vascularization becomes tri-dimensional, 2D imaging remains limited by the elevation projection. In this study, volumetric ultrasound imaging was performed in the craniotomized rat brain to yield 3D ULM<i> in vivo</i> within 7.5 min of acquisition with a commercial system. For instance, it highlighted the thalamus or the circle of Willis with small vessels down to 21 µm. Microbubbles tracking also gave access to the 3D velocity vector of blood flow allowing to distinguish flow directions. Volumetric ULM resolved deep complex tri-dimensional vascular structures and was compared to 2D ULM. It is a safe, simple and repeatable system to image wide field of view in the brain.</p><p><strong>Data Description:</strong></p><p>Microbubbles have been detected, localized, and tracking with 3D ultrasound imaging <i>in vivo</i> in a rat brain with skull removal.</p><p>Individual microbubble trajectories are described in 4 columns vectores: <strong>[z, x, y, time]</strong> for each position of the path. Space positions are given in [mm], and times are given in [ms]. Trajectories data are stored in .mat files (<strong>tracks_0xx.mat </strong>and zipped inside <strong>tracks.zip</strong>) as cell arrays.</p><p>Tracks can be binned inside a volumetric grid with the sample code (<strong>ULM_rendering.m</strong>).</p><p><strong>Reference to be cited: </strong>Chavignon, Heiles, Hingot, Orset, Vivien and Couture.</p><p><i>Deep and complex vascular anatomy in the rat brain described with Ultrasound Localization Microscopy in 3D.</i><br> </p>
An assessment of the (anti)androgenic properties of hexachloronaphthalene (HxCN) using a model of immature male rats (Hershberger Bioassay)
<p>The persistent organic pollutants (POPs) include polychlorinated naphthalenes (PCNs); of these, the most toxic, abundant and found in human tissues are the hexachloronaphthalenes (HxCNs). The aim of this study was to evaluate the (anti)androgenic action of HxCN using the Hershberger Bioassay (OECD 441). Castrated male Wistar rats were exposed per os to HxCN at daily doses ranging from 0.3-3.0 mg*kg b.w.-1 for 10 days. Testosterone propionate (TP) was used as the reference androgen, and flutamide (FLU) as the reference antiandrogen. Five assessor sex tissues (ASTs) were weighed: ventral prostate, seminal vesicles, levator ani-bulbocavernosus muscle (LABC), glans penis and Cowper gland. In addition to determining the absolute weight of the ASTs, a number of other tests were performed on serum hormone levels (testosterone [T], triiodothyronine 99 [T3], thyroxine [T4], LH and FSH) and the histopathology of the ASTs. </p>
Data description: Deprivation of loading during early healing of rat Achilles tendons affects extracellular matrix composition and structure, and reduces cell density and cell alignment
<p><a name="_Hlk158643946"></a><strong>Data description: Deprivation of loading during early healing of rat Achilles tendons affects extracellular matrix composition and structure, and reduces cell density and cell alignment</strong></p> <p><em>Malin Hammerman, Maria Pierantoni, Hanna Isaksson<sup> *</sup>, Pernilla Eliasson <sup>*</sup></em></p> <p><em><sup>* </sup></em><em>joint<sup> </sup>last authors</em></p> <p>This dataset contains microscope images obtained from sections of healing and intact rat Achilles tendons undergoing different in vivo loading protocols and different time points post-transection. The data presented are the full resolution microscope images available in lower resolution in the accompanying manuscript’s Supplementary Figures 4-6.</p> <p>Each zipped folders contain images (tif-files) from all time-points for each respective staining and loading group. </p> <ul> <li>Col1: Sections stained with Collagen 1 antibodies</li> <li>Col3: Sections stained with Collagen 3 antibodies</li> <li>Elastin: Sections stained with Elastin antibodies</li> <li>Full_loading: Free cage activity</li> <li>Reduced_loading: Paralysis of the calf muscle with Botox</li> <li>Minimal_loading: Botox combined with joint fixation using a steel-orthosis</li> <li>Intact_reference: Contralateral uninjured Achilles tendons, used as reference</li> </ul> <p>More description of the datasets inside the zipped files are available below and in the file 'Data Description.pdf'</p> <p> </p> <p><strong>Brief re-cap of methods</strong></p> <p>Histological analysis was performed on healing Achilles tendons from Female Sprague-Dawley rats, specific-pathogen free (11-12 weeks, weight 299 ± 15 g), that had undergone full transection [13] of the right Achilles tendon, and been exposed to different levels of loading. Altered loading was imposed through two mechanisms. Reduced loading involved intramuscular Botox injections in the right calf muscles to induce plantar flexor muscle paralysis [24]. Additionally, the rats in the minimal loading group received a steel-orthosis around their right hindlimb directly after surgery [24].</p> <p>Snap frozen tendons in OCT were sectioned longitudinally (7 μm thickness) and stained with immunofluorescent staining for collagen 1, collagen 3, or elastin. Sections were counterstained with DAPI followed by mounting. The tissue sections were imaged under a microscope (DMi8, Leica Microsystems, Wetzlar, Germany, with a Hamamatsu Orca LT Flash sCMOS camera) where fluorescence was detected at 550 nm (secondary antibody Alexa Fluor 594), 470 nm (secondary antibody Alexa Fluor 488) and 385 nm (DAPI), and exposure time was held constant for each color channel regarding magnification and staining.</p> <p>Mapping images of the entire tendon were obtained for one section per group (n=1 per healing time, loading group and ECM matrix protein). All images were adjusted to the negative control, where the primary antibody was omitted, to correct for unspecific antibody detection.</p> <p><strong>Microscope images and description of file-names </strong></p> <p>All data is presented in the form of .tif files. Please refer to the scale bars in the images. All image-files are named using the following abbreviations, as described below. As an example, the file name “Tendon_col1_FL_1W_col1.tif” refers to a tendon section stained for collagen 1 from a rat exposed to full loading for a period of 1 week after tendon transection, where only the channel for collagen 1 is shown, whereas “Tendon_col1_FL_1W_merged.tif” includes the channels for both staining for collagen 1 and DAPI of the same section.</p> <p>Col1: Sections stained with Collagen 1 antibodies<br>Col3: Sections stained with Collagen 3 antibodies<br>Elastin: Sections stained with Elastin antibodies<br>dapi: Sections stained with 4',6-Diamidino-2-Phenylindole Dihydrochloride.<br>FL: Full loading (free cage activity),<br>RL: Reduced loading (paralysis of the calf muscle with Botox),<br>ML: Minimal loading (Botox combined with joint fixation using a steel-orthosis)<br>IT: Intact contralateral Achilles tendons, used as reference.</p> <p>1W: Healing time point 1 week after transection<br>2W: Healing time point 2 weeks after transection<br>3W: Healing time point 3 weeks after transection<br>20W: Healing time point 20 weeks after transection</p> <p><strong>Settings for brightness and contrast</strong></p> <p><em>Collagen 1</em><br>1w FL 2000-12 000, UL 4000-10 000, ML 4000-12 000<br>2w FL 2500-10 000, UL 4000-10 000, ML 5000-12 000<br>3w FL 2000-12 000, UL 3500-13 000, ML 3500-14 000<br>12w FL 3000-12 000<br>20w FL 3000-11 000<br>IT 2000-8 000</p> <p>Collagen 3<br>1w FL 3000-12 000, UL 4000-10 000, ML 4000-13 000<br>2w FL 2000 - 7 000, UL 2500-12 000, ML 2000-12 000<br>3w FL 2000-12 000, UL 3500-13 000, ML 3500-14 000<br>12w FL 3000-12 000<br>20w FL 2000-12 000<br>IT 3000-12 000</p> <p>Elastin<br>1w FL 4000-10 000, UL 5000 - 8000, ML 3500-12 000<br>2w FL 3000-12 000, UL 3000-12 000, ML 3000-12 000<br>3w FL 2500-12 000, UL 2000-12 000, ML 2500-12 000,<br>12w FL 3500-12 000<br>20w FL 3500-12 000<br>IT 2000-12 000</p>
Genome and annotations of cotton rat (Sigmodon hispidus)
<p>The chromosome level reference genome of <em>Sigmodon hispidus</em> based on third-generation high fidelity (HiFi) reads, high-throughput chromosome conformation capture (Hi-C), and second-generation sequencing techniques.</p>
Progressive ratio in protein-restricted vs. non-restricted rats
<p>These data are from experiments studying motivation in protein-restricted rats using progressive ratio responding for food pellets conducted at University of Leicester, UK. These findings will be published in Chiacchierini et al. (2022) bioRxiv. Detailed methods for the experiment can be found in this paper. Full citation to a peer-reviewed publication is expected to follow. Briefly, data are from operant behavior sessions (FR1, FR3, etc) recorded on Med Associates hardware. Accompanying analysis code as a Jupyter notebook is available on Github (https://github.com/mccutcheonlab/PRPR). </p> <p>The data are provided as a compressed zip file containing the following:</p> <ul> <li>Folder with raw datafiles from experiment using nutritionally-balanced grain pellets (<strong>PRPR_exp1</strong>)</li> <li>Folder with raw datafiles from experiment using protein (35% casein) pellets (<strong>PRPR_exp2</strong>)</li> <li>Excel file with metadata to accompany each raw datafile (<strong>PRPR_metafiles.xls</strong>)</li> </ul> <p>The raw datafiles are Med Associates files in the stripped format. Timestamps of individual lever presses and reward deliveries are included in the raw datafiles and can be extracted but are not used here.</p> <p><strong>PRPR_metafiles.xls</strong> contains sheets (<em>metafile_exp1</em> and <em>metafile_exp2</em>) with the following information for each datafile:</p> <ul> <li>filename</li> <li>rat ID</li> <li>session number</li> <li>box</li> <li>diet group (NR, non-restricted or PR, protein-restricted)</li> <li>date</li> <li>ratio (FR, fixed ratio or PR, progressive ratio)</li> <li>pellet type (grain or protein)</li> <li>responses</li> <li>rewards</li> <li>breakpoint</li> </ul> <p><strong>PRPR_metafiles.xls</strong> also contains sheets (<em>freeaccess_exp1</em> and <em>freeaccess_exp2</em>) with data from the free access tests showing grams of food consumed on two consecutive days for each rat in the study.</p>
Functional MRI data from isoflurane-anesthetized macaques, marmosets, and rats
<p>This dataset contains unprocessed task-free <strong>functional MRI (fMRI)</strong> data acquired in three different mammalian species: <strong>long-tailed macaques</strong> (<em>Macaca fascicularis</em>), <strong>common marmosets</strong> (<em>Callithrix jacchus</em>), and <strong>rats</strong> (<em>Rattus Norvegicus</em>, Wistar strain). The data were obtained during <strong>isoflurane anesthesia</strong>, with the animals intubated and mechanically ventilated. All experiments were carried out in accordance with the guidelines from Directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes.</p> <p><strong>Related paper</strong></p> <p>This dataset supplements the following <a href="http://doi.org/10.7554/eLife.74813">manuscript</a>:</p> <p>Sirmpilatze N, Mylius J, Ortiz-Rios M, Baudewig J, Paasonen J, Golkowski D, Ranft A, Ilg R, Gröhn O, Boretius S. <em>Spatial signatures of anesthesia-induced burst-suppression differ between primates and rodents.</em> eLife 2022;11:e74813. DOI: https://doi.org/10.7554/eLife.74813</p> <p><strong>Data structure</strong></p> <p>The main data files are organized into four zipped folders - <em><strong>Macaque.zip, Marmoset.zip, Rat1.zip, Rat2.zip</strong></em> - each constituting a dataset formatted according to the <a href="https://bids.neuroimaging.io/">Brain Imaging Data Structure</a> specifications (BIDS v1.6.0).</p> <ul> <li>Each BIDS-formatted dataset contains subfolders for individual subjects (e.g. <em><strong>sub-01</strong>, <strong>sub-02</strong>,</em> etc.), as well as a tab-separated text file, <strong><em>participants.tsv</em></strong>, with some essential information about the subjects (e.g. age, weight, sex).</li> <li>Each subject-specific folder contains subfolders named <em><strong>func</strong> </em>and <strong><em>anat</em></strong>, storing fMRI and structural MRI data respectively. The (f)MRI data are provided in <a href="https://nifti.nimh.nih.gov/">NIfTI format</a> (suffixed with <strong><em>.nii.gz</em></strong>). Each NIfTI file is accompanied by a <strong><em>.json sidecar</em></strong> holding metadata.</li> <li>The <em><strong>func</strong></em> subfolders also include tab-separated text files named as <strong><em>{sub-id}_scans.tsv</em></strong> (e.g. <em><strong>sub-01_scans.tsv</strong></em>). These files provide additional information on the fMRI runs within the <em><strong>func</strong></em> subfolder, such as the isoflurane concentration during the acquisition of the fMRI run, duration of the run, etc.</li> <li>The column names in <em><strong>participants.tsv</strong></em> and <em><strong>{sub-id}_scans.tsv</strong></em> files are explained in accompanying <em><strong>participants.json </strong></em>and <em><strong>{sub-id}_scans.json</strong></em> files.</li> </ul> <p><strong>BIDS-formatted datasets</strong></p> <p>The basic characteristics of the datasets are given below. More details can be found in the <a href="https://www.biorxiv.org/content/10.1101/2021.10.15.464515">preprint</a>.</p> <ol> <li><em><strong>Macaque</strong></em> <ul> <li><strong>Institution:<em> </em></strong>German Primate Center (Deutsches Primatenzentrum GmbH - Leibniz-Institut für Primatenforschung), Göttingen, Germany</li> <li><strong>MR system:</strong> Siemens MAGNETOM Prisma 3T</li> <li><strong>Anatomical MRI scan:</strong> T1-weighted (MPRAGE), 1 per subject</li> <li><strong>fMRI scan:</strong> GE-EPI, 1 or 2 runs per subject, run duration 600 - 1200 s</li> <li><strong>Subjects:</strong> 13 <em>Macaca fascicularis</em></li> <li><strong>Age range:</strong> 6.8 - 19.8 years</li> <li><strong>Weight range:</strong> 3.6 - 8.1 kg</li> <li><strong>Sex:</strong> all females</li> <li><strong>Ethics oversight:</strong> Lower Saxony State Office for Consumer Protection and Food Safety, Hannover, Germany (approval number 33.19-42502-04-16/2278)</li> </ul> </li> <li><em><strong>Marmoset</strong></em> <ul> <li><strong>Institution:<em> </em></strong>German Primate Center (Deutsches Primatenzentrum GmbH - Leibniz-Institut für Primatenforschung), Göttingen, Germany</li> <li><strong>MR system:</strong> Bruker BioSpec 9.4 T, equpped with B-GA 20S gradient</li> <li><strong>Anatomical MRI scan:</strong> Proton density-weighted (PDw) with magnetization transfer (MT) pulse, 1 per subject</li> <li><strong>fMRI scan:</strong> GE-EPI, 1 run per subject, run duration 600 s (except for sub-21, containing 4 runs of 300 s duration each).</li> <li><strong>Subjects:</strong> 21 <em>Callithrix jacchus</em></li> <li><strong>Age range:</strong> 1.9 - 14.2 years</li> <li><strong>Weight range:</strong> 337 - 517 g</li> <li><strong>Sex:</strong> 11 females</li> <li><strong>Ethics oversight:</strong> Lower Saxony State Office for Consumer Protection and Food Safety, Hannover, Germany (approval numbers 33.19-42502-04-17/2496 and 33.19-42502-04-17/2535)</li> </ul> </li> <li><em><strong>Rat1</strong></em> <ul> <li><strong>Institution:<em> </em></strong>German Primate Center (Deutsches Primatenzentrum GmbH - Leibniz-Institut für Primatenforschung), Göttingen, Germany</li> <li><strong>MR system:</strong> Bruker BioSpec 9.4 T, equpped with B-GA 12S2 gradient</li> <li><strong>Anatomical MRI scan:</strong> T2-weighted (TurboRARE), 1 per subject</li> <li><strong>fMRI scan:</strong> GE-EPI, 6 runs per subject (except for sub-10: 4 runs), run duration 720 s</li> <li><strong>Subjects:</strong> 11 <em>Rattus norvegicus</em>, Wistar strain</li> <li><strong>Weight range:</strong> 350 - 450 g</li> <li><strong>Sex:</strong> all females</li> <li><strong>Ethics oversight:</strong> Lower Saxony State Office for Consumer Protection and Food Safety, Hannover, Germany (approval number 33.19-42502-04-15/2042)</li> </ul> </li> <li><em><strong>Rat2</strong></em> <ul> <li><strong>Institution:<em> </em></strong>A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland</li> <li><strong>MR system:</strong> Bruker PharmaScan 7 T</li> <li><strong>Anatomical MRI scan:</strong> NOT provided</li> <li><strong>fMRI scan:</strong> GE-EPI, 6 runs per subject (except for sub-10: 4 runs), run duration 720 s</li> <li><strong>Subjects:</strong> 6 <em>Rattus norvegicus</em>, Wistar strain</li> <li><strong>Weight range:</strong> 265 - 350 g</li> <li><strong>Sex:</strong> all males</li> <li><strong>Ethics oversight:</strong> Animal Ethics Committee of the Provincial Government of Southern Finland</li> </ul> </li> </ol> <p><strong>Example data</strong></p> <p>Before you commit to downloading the BIDS-formatted datasets, we encourage you to examine the example data that we provide in the root folder. These include one anatomical (stuctural MRI) and one functional (fMRI) scan from each of the four datasets (Rat2 contains functional scans only), with their respecitve <strong><em>.json sidecars</em></strong>. A preview of these example scans is provided by <em><strong>0_preview.pdf.</strong></em></p>
3D Nuclei annotations and StarDist 3D model(s) (rat brain)
<p><strong>Name</strong>: 3D Nuclei annotations and StarDist3D model(s) (rat brain)</p> <p><strong><em>Images: </em></strong>From a large tiling acquisition ( https://doi.org/10.5281/zenodo.6646128 ) individual Tile (xyz : 1024x1024x62) were downsampled and cropped (128x128x62). Four crops, from different tiles (./annotations_BIOP/images/) were manually annotated with ITK-SNAP (./annotations_BIOP/masks/)</p> <p>These four images, and their corresponding masks, were cropped into four quadrants (./crops_BIOP_v1/) in order to get 16 different images (64x64x62).</p> <p><strong><em>Conda environment</em></strong><em>: </em>A conda environment was created using the yml file <em>stardist0.8_TF1.15.yml</em></p> <p><strong><em>Training : </em></strong>Training was performed using the jupyter notebook <em>1-Training_notebook.ipynb</em>.<br> Three different trainings (with the same random seed, same anisotropy, patch size and grid) were performed and produced three different models (./models/)</p> <p>Validation images (from the random seed used) were exported to ease the visual inspection of the results(./val_rdm42/).</p> <p><strong><em>Validation: </em></strong>To save metrics in a csv file and compare predictions to the annotations the jupyter notebook <em>2-QC_notebook.ipynb </em>can be used on the validation folder.</p> <p><strong>Large images</strong>: To test the model on larger images one can use Whole_ds441.tif (or Crop_ds441.tif )<br> These images were obtained using the plugin <a href="https://imagej.net/plugins/bigstitcher/">BigSticher </a>on the raw data ( https://doi.org/10.5281/zenodo.6646128 ), resaved as h5 and exported the downsample by 4 version.</p> <p> </p> <p> </p>
Semi-automated Quantitative Morphometric Analysis of E18 Rat Hippocampal Neurons from 0.5 to 6 Days In Vitro
<p>This is the dataset presented in "Semi-automated quantitatve evaluation of neuron developmental morphology <em>in vitro</em> using the change-point test" by AS Liao, W Cui, VS Webster-Wood, and YJ Zhang (submitted to Neuroinformatics 2022).</p>
Multiple Particle Tracking Data from Neonatal Organotypic Rat Brain Slices
<p>The data includes statistical features generated from raw multiple particle tracking data from videos collected during three independent experiments: (1) 5 different brain regions, (2) 3 different treatment conditions in the brain, and (3) 5 different brain ages. </p> <p> </p> <table> <thead> <tr> <th scope="col">Feature</th> <th scope="col">Model Abbreviation</th> <th scope="col">Description</th> </tr> </thead> <tbody> <tr> <td>alpha</td> <td>alpha</td> <td>Exponent of the anomalous diffusion equation.</td> </tr> <tr> <td>Effective diffusion coefficient</td> <td>D_fit</td> <td>Coefficient of the anomalous diffusion equation</td> </tr> <tr> <td>Kurtosis</td> <td>kurtosis</td> <td>The fourth moment of the projected positions on the dominant eigenvector of the radius gyration tensor (T).</td> </tr> <tr> <td>Asymmetry1</td> <td>asymmetry1</td> <td>Characterizes the asymmetry of the trajectory. Asymmetry1 equals 0 for circularly symmetric trajectories and 1 for linear trajectories.</td> </tr> <tr> <td>Asymmetry2</td> <td>asymmetry2</td> <td>The ratio of the smaller to larger principal radius of gyration.</td> </tr> <tr> <td>Asymmetry3</td> <td>asymmetry3</td> <td>An asymmetry feature that accounts for non-cylindrically symmetric point distributions.</td> </tr> <tr> <td>Aspect ratio</td> <td>AR</td> <td>The ratio of the kong and short side of the trajectory's minimum bounding rectangle. Perfectly symmetric trajectories have an aspect ratio of 1, and aspect ratio increases as trajectories become more elongated. </td> </tr> <tr> <td>Elongation</td> <td>elongation</td> <td>An estimation of amount of extension of the trajectory from its centroid. </td> </tr> <tr> <td>Boundedness</td> <td>boundedness</td> <td>Boundedness quantifies how much a particle with diffusion coefficient <em>D<sub>eff</sub></em> is restricted by a circular confinement of radius <em>r</em> when diffusing for a period of time <span class="math-tex">\(N\Delta t \)</span></td> </tr> <tr> <td>Fractal Dimension</td> <td>fractal_dim</td> <td>Fractal dimension is a measure of how "complicated" a self similar figure is. </td> </tr> <tr> <td>Trappedness</td> <td>trappedness</td> <td>The probability (<span class="math-tex">\(\textit{P}_{\textit{t}} \)</span>) that a particle with duffusion coefficient <em>D<sub>eff</sub></em> is trapped in a region (<em>r<sub>0</sub></em>) for a period of time <span class="math-tex">\(N\Delta t \)</span>. </td> </tr> <tr> <td>Efficiency</td> <td>efficiency</td> <td>The ratio of the squared net displacement to the sum of step lengths. </td> </tr> <tr> <td>Straightness</td> <td>straightness</td> <td>The ratio of the net displacement to the sum of step lengths. </td> </tr> <tr> <td>MSD Ratio</td> <td>MSD_ratio</td> <td>MSD ratio characterizes the shape of the MSD curve. For Brownian motion, it is 0; For restricted motion it is < 0; For directed motion it is > 0. </td> </tr> <tr> <td>Frames</td> <td>frames</td> <td>The total number of frames the trajectory spans. </td> </tr> <tr> <td>Effective Diffusion Coefficient 1</td> <td>Deff1</td> <td>Effective diffusion coefficient at 0.33 s.</td> </tr> <tr> <td>Effective Diffusion Coefficient 2</td> <td>Deff2</td> <td>Effective diffusion coefficient at 3.3s. </td> </tr> </tbody> </table> <p>Mean values were calculated based on surrounding datapoints for alpha, D_fit, kurtosis, asymmetry1, asymmetry2, asymmetry3, AR, elongation, boundedness, fractal_dim, trappedness, efficiency, straightness, MSD_ratio, Deff2, and Deff2. </p> <p> </p>
Diffusion weighted MR imaging of post-mortem rat brain to allow reconstruction of the cortical connectome
<h2>Brief description</h2> <p> </p> <p>These data accompany the article by Sinke et al. (Sinke et al., 2018). It contains the dMRI image volumes of 10 rats, a subset of these data was used for the tractography procedures described in the article. In addition high-resolution 3D balanced SSFP data are provided with high contrast between grey and white matter and CBF. The data are also accompanied by T<sub>1</sub> weighted 3D spoiled gradient echo volumes at three different echo times (5,10 and 15 ms) which can be used for T<sub>2</sub>* measurements.</p> <h2>Animals</h2> <p> </p> <p>All animal procedures were approved by the Animal Experiments Committee of the University Medical Center Utrecht and Utrecht University. Experiments were performed in accordance with the guidelines of the European Communities Council Directive. Ten healthy adult (12–13 weeks old) male Wistar rats have been used and are described in the RCR_table.csv file. Animals were sacrificed and their brains were fixed with transcardial perfusion-fixation. Brains were extracted scanned.</p> <p> </p> <h2>MR acquisition</h2> <p> </p> <p>MRI was performed on a 9.4 T horizontal bore MR system (Varian, Palo Alto, CA, USA) equipped with a 6 cm ID gradient insert with gradients up to 1 T/m. A custom made solenoid coil with an internal diameter of 2.6 cm was used for excitation and reception of the MR signal. The perfusion-fixed brains were inserted with the skulls intact in a custom-made holder and immersed in non-magnetic oil (Fomblin, Solvay Solexis). Diffusion MR used a 3D diffusion-weighted spin-echo sequence with an isotropic spatial resolution of 150 mm, where the read- and phase- encode direction were acquired using 8-shot EPI encoding and the second phase direction was linearly phase-encoded (TR/TE 500/32.4 ms, 220*128*108 matrix, FOV 33*19.2*16 mm<sup>3</sup>, D/d 15/4 ms, b 1031,2078,3994,6038,7756 s/mm<sup>2</sup>, 60 diffusion-weighted images in non-collinear directions and 24 images without diffusion weighting (b=0), number of averages 1, total number of images 325). Four 3D BSSFP images were acquired with an isotropic spatial resolution of 100 mm (TR/TE 15.4/7.7 ms, flip angle 40°, 320*160*190 matrix, FOV 32*16*19 mm<sup>3</sup>, 6 averages, pulse angle shift 0°, 90°, 180° and 270°). The four images were added as complex images to obtain a single BSSFP image with reduced banding artifacts in the brain. If scanning time allowed, three spoiled gradient-echo acquisitions were also performed with varying echotimes of 15, 10 and 5 ms respectively and TR 20 ms (flip angle 40°, 320*160*190 matrix, FOV 32*16*19 mm<sup>3</sup>, 24 averages, pulse angle shift 117°).</p> <h2>Data structure</h2> <p> </p> <p>The repository contains the following data:</p> <p>- READ_ME.txt: this file</p> <p>- RCR_table.csv : Table containing acquisition dates and numbers for the scanned animals.</p> <p>- rawdata.zip : Zipped data directory ‘rawdata’ containing acquired images in NIfTI data format per animal. Data can be unzipped using the ‘unzip’ command. Directory rawdata contains subdirectories RCR01 to RCR10 (individual rat directories). Each rat directory contains the following NIfTI files:</p> <p>o bal.nii.gz and balsumcom.nii.gz : The separate acquisitions of the BSSFP experiment and the complex summation of the data respectively.</p> <p>o dtitot.nii.gz : The diffusion weighted volumes in the order that they were acquired.</p> <p>o bvals and bvecs : Text files containing the b-values and b-vectors in the order that they were acquired, so this corresponds with the dtitot.nii.gz file.</p> <p>o zerob: Text file containing the image numbers where images with no diffusion weighting were acquired.</p> <p>o ubal1.nii.gz, ubal2.nii.gz and ubal3.nii.gz : The three 3D spoiled gradient acquisitions with TE 15,10, and 5 ms respectively.</p> <p>- derivatives.zip : Zipped data directory ‘derivatives’ containing calculated images of the diffusion parameters after application of FMRIB’s diffusion toolbox DTIfit. In addition it contains a file dti3D_b0.nii.gz which is a summation of all the b0-images and a file mask.nii.gz containing the ‘brain’ mask used for application of DTIfit.</p> <p>- Sinke_BrainStructureFunction2018.pdf : The article based on (part) of these data.</p>
Supplementary Document to "Design Guidelines and Applications for Dual-Band Rat-Race Couplers and Gysel Power Dividers with Unequal Amplitude Imbalances"
<p>This document presented additional results generated using a CAD application [1] developed for the submitted paper [2]. The CAD application is freely available under Creative Commons Attribution 4.0 International. The application can be downloaded from https://zenodo.org/records/11199141.</p> <p>REFERENCES<br>[1] R. Sinha, “Single/ Dual band Rat-race Coupler and Gysel Power Divider with unequal power division ratio,” May 2024. [Online]. Available:<br>https://doi.org/10.5281/zenodo.11199141<br>[2] ——, “Design guidelines and application of dual-band rat-race couplers and Gysel power dividers with unequal amplitude imbalances [application notes],”<br>IEEE Microwave Magazine, vol. vv, no. nn, p. pp, 2024.</p>
Raw data (RF) provided for : Sensing Ultrasound Localization Microscopy reveals glomeruli in rats and humans
<p><strong>Abstract :</strong> Estimation of glomerular function is a key element in the diagnosis of kidney disease. However, the study of glomeruli in the clinic remains indirect through urine and blood tests. Recent imaging technique called Ultrasound Localization Microscopy (ULM) originated from the ability to record continuous movements of individual microbubbles in the bloodstream. Although it improved the resolution of vascular imaging up to tenfold, the imaging of the smallest vessels had yet to be reported.</p> <p>We acquired ultrasound sequences from living humans and rats and then applied filtering dividing the data set into slow-moving and fast-moving microbubbles. We performed a double tracking to highlight and characterize this new population of microbubbles with singular behaviors: we called this technique “sensing ULM” (sULM). We used post-mortem micro-CT for side-by-side confirmation in rats.</p> <p>In this study, we report the observation of microbubbles flowing in capillaries bundles, i.e. the glomeruli, in the kidney in living humans and rats. We introduce a set of analysis tools dedicated to extracting quantitative information from individual microbubbles, like the remanence time or the normalized distance.</p> <p>As glomeruli play a key role in kidney function, their observation could yield a deeper understanding of kidney diseases and provide a diagnostic tool for patients. More generally, it will bring imaging capabilities closer to the functional units of organs, which is one of the keys to understanding most diseases, like cancers, diabetes, or kidney failures. </p> <p><strong>Academic reference to be cited : </strong>Denis, Bodard, Hingot, Chavignon, Battaglia, Renault, Lager, Aissani, Hélénon, Correas, and Couture. <em>Sensing Ultrasound Localization Microscopy reveals glomeruli in rats and humans,</em> eBioMedicine, 2023.</p> <p><strong>Article</strong> : <a href="https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(23)00143-3/fulltext">https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(23)00143-3/fulltext</a></p> <p><strong>Related scripts and software application</strong> : <a href="https://github.com/EngineerJB/akebia">https://github.com/EngineerJB/akebia</a></p> <p><strong>Beamformed dataset</strong> : <a href="../record/6811910#.ZA9dV3bMLid">https://zenodo.org/record/6811910#.ZA9dV3bMLid</a></p> <p><strong>Corresponding authors : </strong></p> <ul> <li>Article : Louise Denis, <a href="mailto:louise.denis@sorbonne-universite.fr">louise.denis@sorbonne-universite.fr</a>, Sylvain Bodard, <a href="mailto:sylvain.bodard@aphp.fr">sylvain.bodard@aphp.fr</a></li> <li>Scripts, and codes : Louise Denis, <a href="mailto:louise.denis@sorbonne-universite.fr">louise.denis@sorbonne-universite.fr</a>, Jacques Battaglia, <a href="mailto:jacques.battaglia@sorbonne-universite.fr">jacques.battaglia@sorbonne-universite.fr</a></li> <li>Materials, collaborations, rights and others: Olivier Couture, <a href="mailto:olivier.couture@sorbonne-universite.fr">olivier.couture@sorbonne-universite.fr</a></li> </ul>
ScienceDex guides
Understand access before you commit
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.