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dryad36/100

Adiponectin rescues synaptic plasticity in the dentate gyrus of a mouse model of fragile X syndrome

Fragile X Syndrome (FXS) is the most common inherited cause of intellectual disability and is the leading known single-gene cause of autism spectrum disorder. FXS patients display varied behavioural deficits that include mild to severe cognitive impairments in addition to mood disorders. Currently, there is no cure for this condition, however, there is an emerging focus on therapies that inhibit mTOR-dependent protein synthesis due to the clinical effectiveness of metformin for alleviating some behavioural symptoms in FXS. Adiponectin (APN) is a neurohormone that is released by adipocytes and provides an alternative means to inhibit mTOR activation in the brain. In these studies, we show that Fmr1 KO mice, like FXS patients, show reduced levels of circulating APN, and that both LTP and LTD in the DG (dentate gyrus) are impaired. Brief (20 min) incubation of hippocampal slices in APN (50 nM) was able to rescue both LTP and LTD in the DG and increased both the surface expression and phosphorylation of GluA1 receptors. These results provide evidence for reduced adiponectin levels in FXS playing a role in decreasing bidirectional synaptic plasticity and show that therapies that enhance adiponectin levels may have therapeutic potential for this and related conditions.

opencc-zeroMay 2024View details →

zenodo36/100

Data for Cell-type-specific alternative splicing in the cerebral cortex of a Schinzel-Giedion Syndrome patient variant mouse model

data.tar.gz contains all files from the data directory (except for sam outputs from STAR) associated with the 230926_EJ_Setbp1_AlternativeSplicing GitHub project and includes the following files:   ./marvel: - This directory contains rds and Rdata objects that were created using the MARVEL R package cell_type_goresults.rds - This is the go results split by cell type marvel_04_split_counts.Rdata - This R data includes all environment objects from MARVEL script 04, and is used for downstream plotting normalized_sj_expression.Rds - This object is the normalized splice junction expression Setbp1_marvel_aligned.rds - Final prepared MARVEL object before any SJU analyses have been run significant_tables.RData - For those who do not want to load multiple massive files, this includes all significant SJU results for each cell type sj_usage_cell_type.rds - This data object has splice junction usage calculated for each cell type sj_usage_condition.rds - This data object has splice junction usage calculated for each cell type and also split by condition   ./seurat: - This directory contains all intermediate and final Seurat single-cell gene expression objects annotated_brain_samples.rds - This is the final iteration of the processing in Seurat for a final annotated object. Please use this object for any Seurat or single-cell gene expression analyses. clustered_brain_samples.rds - This is the clustered Seurat object, before cell type annotation based on canonical markers. filtered_brain_samples_pca.rds - This is the filtered Seurat object, before clustering but after PCA. filtered_brain_samples.rds - This is the filtered Seurat object, before PCA. integrated_brain_samples.rds - This the integrated Seurat object, before other steps.   ./star: - All files in the STAR directory are outputs from STARsolo, as described in our methods. Each output directory contains the same files, so only one example is included here for brevity. Intermediate SAM files were removed to optimize space. J1/ - This directory contains outputs for brain sample J1 J13/ - This directory contains outputs for brain sample J13 J15/ - This directory contains outputs for brain sample J15 J2/ - This directory contains outputs for brain sample J2 J3/ - This directory contains outputs for brain sample J3 J4/ - This directory contains outputs for brain sample J4 K1/ - This directory contains outputs for kidney sample K1 K2/ - This directory contains outputs for kidney sample K2 K3/ - This directory contains outputs for kidney sample K3 K4/ - This directory contains outputs for kidney sample K4 K5/ - This directory contains outputs for kidney sample K5 K6/ - This directory contains outputs for kidney sample K6   ./star/genome: - This directory contains outputs from running STAR genomeGenerate. Detailed file descriptions available from<a href="https://github.com/alexdobin/STAR/blob/master/doc/STARmanual.pdf"> https://github.com/alexdobin/STAR/blob/master/doc/STARmanual.pdf</a> chrLength.txt chrNameLength.txt chrName.txt chrStart.txt exonGeTrInfo.tab exonInfo.tab geneInfo.tab Genome genomeParameters.txt Log.out SA SAindex sjdbInfo.txt sjdbList.fromGTF.out.tab sjdbList.out.tab transcriptInfo.tab   ./star/J1: - This is the head STAR directory for sample J1. It contains logs, basic QC, and gene and splice junction counts. For more information about the STAR pipeline and its outputs, please refer to the STAR documentation<a href="https://github.com/alexdobin/STAR/blob/master/doc/STARmanual.pdf"> https://github.com/alexdobin/STAR/blob/master/doc/STARmanual.pdf</a>  Log.final.out Log.out Log.progress.out SJ.out.tab Solo.out/ STARgenome/   ./star/J1/Solo.out:- This directory contains the outputs used for downstream analysis Barcodes.stats GeneFull_Ex50pAS/ SJ/   ./star/J1/Solo.out/GeneFull_Ex50pAS: - This directory contains the filtered and raw barcodes, features, and matrix files for gene expression (including introns) Features.stats filtered/ raw/ Summary.csv UMIperCellSorted.txt   ./star/J1/Solo.out/GeneFull_Ex50pAS/filtered: - This directory contains the filtered tsv and mtx gene expression files required for creating a Seurat object (or other single cell packages) barcodes.tsv.gz - This file contains filtered cell barcodes features.tsv.gz - This file contains filtered features (genes) matrix.mtx.gz - This file contains the filtered cell by gene expression count matrix   ./star/J1/Solo.out/GeneFull_Ex50pAS/raw: - This directory contains the unfiltered tsv and mtx gene expression files required for creating a Seurat object (or other single cell packages). Files are the same as previously described for filtered. barcodes.tsv features.tsv matrix.mtx   ./star/J1/Solo.out/SJ: - This directory contains the QC and raw barcodes, features, and matrix files for splice junction expression Features.stats raw/ Summary.csv   ./star/J1/Solo.out/SJ/raw: - This directory contains the raw barcodes, features, and matrix files for splice junction expression barcodes.tsv - This file contains filtered cell barcodes features.tsv - This file contains filtered features (splice junctions) matrix.mtx - This file contains the filtered cell by gene expression count matrix   ./star/J1/_STARgenome: - This directory contains the STARgenome created and used by STAR for this sample. Detailed file descriptions available from<a href="https://github.com/alexdobin/STAR/blob/master/doc/STARmanual.pdf"> https://github.com/alexdobin/STAR/blob/master/doc/STARmanual.pdf</a>  exonGeTrInfo.tab exonInfo.tab geneInfo.tab sjdbInfo.txt sjdbList.fromGTF.out.tab sjdbList.out.tab transcriptInfo.tab

openmit-licenseJun 2024View details →

zenodo36/100

Noscapine treatment effect in transgenic mouse model of Alzheimer's disease

Cerebrovascular dysfunction and neuroinflammation play key roles in the pathophysiology of Alzheimer’s disease (AD). The kinin-kallikrein system involving bradykinin receptor has been proposed at the nexus of beta-amyloid, vascular pathology and inflammation in patients with AD and in animal models. Here, we evaluated the effect of blocking the bradykinin receptors 1 and 2 by treatment with the bradykinin antagonist noscapine on cerebrovascular dysfunction, inflammation and amyloid pathology in a transgenic mouse model of amyloidosis. Transgenic arcAβ mice, and wild-type littermates of 14 months-of-age were either treated with noscapine (3 g/L, acidified drinking water) or received drinking water as control for three months (n = 8-11 per group). Arterial spin labeling magnetic resonance imaging showed alleviated regional hypoperfusion in noscapine-treated arcAb compared to control arcAb mice. Functional magnetic resonance imaging showed mitigated reduced regional cerebral vascular reactivity in noscapine-treated arcAb compared to control arcAb mice.

opencc-by-4.0Dec 2017View details →

zenodo36/100

Development of an imaging toolbox to assess the therapeutic potential and biodistribution of macrophages in a mouse model of multiple organ dysfunction

Data set to accompany manuscript entitled "Development of an imaging toolbox to assess the therapeutic potential and biodistribution of regenerative therapies in a mouse model of multiple organ dysfunction " which can be found on BioRxiv.

opencc-by-4.0Jul 2018View details →

zenodo36/100

Systematic spatio-temporal mapping reveals divergent cell death pathways in three mouse models of hereditary retinal degeneration

Values for immuohistochemical analysis or enzymatic analysis of various markers theorised to have roles in retinal dystrophies in three models of mouse retinal degeneration with a control. Analysis has been broken down by marker, mouseline, age and region of the retina recorded from

opencc-by-4.0Feb 2019View details →

zenodo36/100

Tau deposition is associated with imaging patterns of calcifications and immunhistochemical markers of osteogenesis in the P301L mouse model of human tauopathy

Brain calcifications are associated with several neurodegenerative proteinopathies. Here, we report a new phenotype of imaging pattern of intracranial calcifications in transgenic P301L mice overexpressing 4 repeat human tau. P301L mice (Thy1.2) of 3, 5, 9 and 18-25 months-of-age and age-matched non-transgenic littermates (n = 4-11 per group) were assessed using in vivo / ex vivo magnetic resonance imaging with a gradient recalled echo sequence and micro computed tomography. Susceptibility weighted images computed from the gradient recalled echo data revealed regional hypointensities in the hippocampus, cortex, caudate nucleus and thalamus of P301L mice, in which corresponding phase images indicated diamagnetic lesions. In the hippocampus, occurrence of diamagnetic susceptibility calcifications increased with age. Concomitantly micro computed tomography detected hyperdense lesions. Immunochemical staining of brain sections revealed osteocalcin positive nodules, which is a marker of osteogenic maturation. Furthermore, we found vessel-associated and intra-neuronal osteocalcin positivity co-localizing with phosphorylated tau (AT8 and AT100) in the hippocampus. In contrast, osteocalcin containing nodules were vessel-associated, indicating ossified vessels, in the thalamus in absence of phosphorylated tau. In summary, we demonstrated imaging pattern of intracranial calcifications, early spheroid formation containing proteins associated with ossification along with phosphorylated tau in the P301L mouse model of human tauopathy.

opencc-by-4.0Jan 2020View details →

zenodo36/100

Craniofacial landmark coordinates of DS mouse models

<h2>DATA Description</h2> We make available the data used for craniofacial analysis of nine Down syndrome mouse models. For each DS model, one Zip file is available and contains -      a minimum of four text files with all individual coordinates by genotype (DS model or wt control) for the skull or the mandibule (Mdb): o   the first line of the text file describes the content: Cranium or mandible coordinate + wt control or DS model genotype + Sex (male or female) o   XYZ coordinates o   39L (how many landmarks) 3 (how many coordinates) 10A (how many samples) o   The list of used landmarks (see figure 1 and Tables S1-S2) o   Before the coordinate, the ID (number) of the individual is indicated  -        Tiff files for all individuals used with the model that are in two folders, one for the DS/Dp model and one for the wt controls. All Tiff files are named with the ID number of the individual.  <h2>Down Syndrome mouse models used</h2> We used the Dp(16)1Yey and Tg(Dyrk1a) (official name Dp(16Lipi-Zbtb21)1Yey and Tg(Dyrk1a)189N3Yah) models (Li et al. 2007; Guedj et al. 2012) which were maintained on the C57BL/6J genetic background. We also used the SD: CRL Dp (11Lipi-Zbtb21)1Yah (short name Dp(Rno11)) rat model generated in the lab (Birling et al. 2017) that carries a duplication of the Lipi-Zbtb21, an interval similar to the mouse Dp(16)1Yey, found on rat chromosome 11. New lines were generated via an in vivo chromosomal recombination technique, which combines a transposon system (Ruf et al. 2011) and a meiotic recombination system Cre-loxP (Hérault et al. 1998). The transposon system consists of the transposase enzyme and its substrate, the transposon. The enzyme recognizes specific repeat sequences (ITR) flanked on either side of a given DNA sequence (in this case, a vector containing a specific loxP site) (Ruf et al. 2011). Once two loxP sites bound a region of interest, successive crosses bring a transgene expressing the Cre recombinase into the same individual. In this animal, the Cre enzyme recombines the sequences of the loxP sites to produce a duplication (or partial trisomy) of the region of interest (Hérault et al. 1998; Hérault et al. 2010). The new mouse models have been developed with the following segmental duplications in the Mmu16 (Figure 1). For Dp(16Samsn1-Cldn17)7Yah (Dp(16)7Yah) we duplicated the segment between Samsn1 and Cldn17. Dp(16Tiam1-Clic6))8Yah (Dp(16)8Yah) presents a duplication between Tiam1 and Clic6. Dp(16Cldn17-Brwd1))9Yah (Dp(16)9Yah) displays a duplication in the interval between Cldn17 and Brwd1. Dp(16Tmprss15-Setd4)10Yah (Dp(16)10Yah) has the segment between Tmprss15 and Setd4 duplicated, similar to Dp(16Tmprss15-Grik1)11Yah (Dp(16)11Yah), but this model presents a region duplicated until Grik1. Dp(16Tmprss15-Zbtb21)12Yah (Dp(16)12Yah) has the duplicated region from Tmprss15 to Zfp295, and Dp(16Cldn17-Vps26c(Dyrk1aKO))13Yah (Dp(16)13Yah) from Cldn17 to Vps26c, up to the sequence of Dyrk1a which is inactivated. All lines were maintained on C57BL/6J genetic background. Figure 1 : Relative position of the duplicated interval in the DS mouse models is indicated by a line. <h2>Mouse samples from the DS mouse models</h2> To generate the data, we made cohorts of mice housed under specific pathogen-free (SPF) conditions, treated in compliance with the animal welfare policies of the French Ministry of Agriculture (law 87 848). As a major genotype effect compared to sex was previously described elsewhere independently (Redhead et al. 2023), we decided to use females. For each mouse line, about ten littermates by each genotype, DS, and wild-type (WT) were collected (n = 180).  We tried to have balanced males and females in the cohorts. For example, For the Dp(16)1Yey line, six females plus five males for the dup carrier and six males plus three females for control were used.   Nevertheless, this was not the case in all the other lines, with sometimes more female individuals collected than males, because males were used to breed the lines. <h2>Micro-computed tomography scan of the skull and mandibule of mutant and control mouse lines</h2> Animals were euthanized with the standard procedure at 14 weeks old.  Briefly, the mouse heads were dissected apart from the body. A polystyrene section was interposed between the mandible and maxilla to separate the jaws. After dissection, samples were fixed in a 4% paraformaldehyde solution (PFA), washed with water, and stored in 70% ethanol. The mouse heads were scanned using the Quantum FX micro-computed tomography imaging system (Caliper Life Sciences, Hopkinton, MA, USA) to evaluate the morphology of the skull and mandible. The images obtained were delivered in DICOM format. The scan parameters used to carry out the scanning of the samples correspond to 2 scans of every sample, anterior part, and posterior part using the mode Scan Technique Fine of 2 minutes, with a field of view (FOV) of 40 mm, the voltage 90 kV, CT 160 μA, resolution pixel size 10 µm and the capture size for live mode viewing in small, live current 80kV. Imaging Processing For each sample, two scans were obtained, one from the anterior area of the skull and one from the posterior region. FIJI software was used to unite these two scans and create a single file, performing the plugin “Stitching” and saving one file in TIFF format for each individual per model (WTs and Duplication or transgenic genotype). This format can be opened using different image processors. We make the level of raw data available here in the folder TIFF of each model. Then, Stratovan Checkpoint software (Stratovan Corporation, Sacramento, USA, Version 2018.08.07. Aug 07, 2018.) was used to place the landmarks (Table S1 and S2; Figure 2) and extract the 3D coordinates for all the landmarks in all the samples. So, for each DS model, you will find an additional text file with individuals' landmark coordinates. You will find four text files for each model, 2 for the skull and 2 for the mandible, divided into WT and DS models. Morphometrics is the quantification and statistical analysis of form. Form is the combination of size and shape of a geometric object in an arbitrary orientation and location (shape is what remains of the geometry of such an object once it is standardized for size). Various approaches can be employed when conducting morphometric analysis. The method of interest in this study is the landmark-based method, which is a conventional approach that relies on phenotypic measurements such as linear distances, angles, weights, and areas. In this case, we used 61 landmarks, 39 in the skull and 22 in the mandible (Figure 2), to obtain the 3D coordinates of the structure (Hallgrimsson et al. 2015). Figure 2. Landmark positions for the skull and mandibule analysis. Based on 3D coordinates, Euclidean Distance Matrix Analysis (EDMA) is one of the principal tools for analyzing landmark-based morphometric data (Lele et Richtsmeier 2001). This method builds a matrix of linear distances between all possible pairs of landmarks for each specimen (Lele et Richtsmeier 1991). Morphological differences between groups can be pinpointed to specific linear distances on an object through pairwise comparisons of mean form or shape matrices, followed by bootstrapping to estimate the significance of these differences (Lele et Richtsmeier 2001). In this study, two tests were done for each group of samples, first to analyze the form of the skull and mandibles with form difference matrix (FDM) and then the shape with the shape difference matrix (SDM). In addition, to track the landmarks associated with a significant change and understand where they are located in the CF structures, “EDMA FORM or SHAPE Influence landmark analysis” was performed (Cole et Richtsmeier 1998). The purpose of this test is to search which landmarks present a Relative Euclidean distance (RED) > 1.05 or < 0.95 (outside of the confidence interval 97,8%), meaning, which landmarks show a bigger difference in linear distances between every landmark and in what direction. Another way to handle landmark-based data is using a multivariate statistical analysis of form, geometric morphometric. This method relies on the superimposition of landmark coordinate data to place individuals into a common morpho-space. The most used superimposition form is the Generalized Procrustes (GP) method and Principal Component Analysis (PCA). This method places multiple individual specimens into the same shape space by scaling, translating, and rotating the landmark coordinates around the centroid of every sample (Rohlf et Slice 1990). As an alternative, we took advantage of Stratovan Checkpoint (Stratovan Corporation, Sacramento, USA) to create population average models and perform a voxel-based analysis, where we can observe directly in 3D models the changes between populations. Finally, using the 3dMD Vultus® software, we created Procrustes average models created in Checkpoint to perform a landmarking calculation. References Birling, Marie-Christine, Laurence Schaeffer, Philippe André, Loic Lindner, Damien Maréchal, Abdel Ayadi, Tania Sorg, Guillaume Pavlovic, et Yann Hérault. 2017. « Efficient and Rapid Generation of Large Genomic Variants in Rats and Mice Using CRISMERE ». Scientific Reports 7 (1): 43331. https://doi.org/10.1038/srep43331. Cole, T. M., et J. T. Richtsmeier. 1998. « A Simple Method for Visualization of Influential Landmarks When Using Euclidean Distance Matrix Analysis ». American Journal of Physical Anthropology 107 (3): 273‑83. https://doi.org/10.1002/(SICI)1096-8644(199811)107:3<273::AID-AJPA4>3.0.CO;2-1. Guedj, Fayçal, Patricia Lopes Pereira, Sonia Najas, Maria-Jose Barallobre, Caroline Chabert, Benoit Souchet, Catherine Sebrie, et al. 2012. « DYRK1A: A master regulatory protein controlling brain growth ». Neurobiology of Disease 46 (1): 190‑203. https://doi.org/10.1016/j.nbd.2012.01.007. Hallgrimsson, Benedikt, Christopher J. Percival, Rebecca Green, Nathan M. Young, Washington Mio, et Ralph Marcucio. 2015. « Chapter Twenty - Morphometrics, 3D Imaging, and Craniofacial Development ». In Current Topics in Developmental Biology, édité par Yang Chai, 115:561‑97. Craniofacial Development. Academic Press. https://doi.org/10.1016/bs.ctdb.2015.09.003. Hérault, Y., M. Rassoulzadegan, F. Cuzin, et D. Duboule. 1998. « Engineering Chromosomes in Mice through Targeted Meiotic Recombination (TAMERE) ». Nature Genetics 20 (4): 381‑84. https://doi.org/10.1038/3861. Hérault, Yann, Arnaud Duchon, Damien Maréchal, Matthieu Raveau, Patricia L. Pereira, Emilie Dalloneau, et Véronique Brault. 2010. « Controlled Somatic and Germline Copy Number Variation in the Mouse Model ». Current Genomics 11 (6): 470‑80. https://doi.org/10.2174/138920210793176038. Lele, Subhash R., et Joan T. Richtsmeier. 2001. An Invariant Approach to Statistical Analysis of Shapes. CRC Press. Li, Zhongyou, Tao Yu, Masae Morishima, Annie Pao, Jeffrey LaDuca, Jeffrey Conroy, Norma Nowak, Sei-Ichi Matsui, Isao Shiraishi, et Y. Eugene Yu. 2007. « Duplication of the Entire 22.9 Mb Human Chromosome 21 Syntenic Region on Mouse Chromosome 16 Causes Cardiovascular and Gastrointestinal Abnormalities ». Human Molecular Genetics 16 (11): 1359‑66. https://doi.org/10.1093/hmg/ddm086. Redhead, Yushi, Dorota Gibbins, Eva Lana-Elola, Sheona Watson-Scales, Lisa Dobson, Matthias Krause, Karen J. Liu, Elizabeth M. C. Fisher, Jeremy B. A. Green, et Victor L. J. Tybulewicz. 2023. « Craniofacial dysmorphology in Down syndrome is caused by increased dosage of Dyrk1a and at least three other genes ». Development 150 (8): dev201077. https://doi.org/10.1242/dev.201077. Rohlf, F. James, et Dennis Slice. 1990. « Extensions of the Procrustes Method for the Optimal Superimposition of Landmarks ». Systematic Biology 39 (1): 40‑59. https://doi.org/10.2307/2992207. Ruf, Sandra, Orsolya Symmons, Veli Vural Uslu, Dirk Dolle, Chloé Hot, Laurence Ettwiller, et François Spitz. 2011. « Large-Scale Analysis of the Regulatory Architecture of the Mouse Genome with a Transposon-Associated Sensor ». Nature Genetics 43 (4): 379‑86. https://doi.org/10.1038/ng.790.   Tables <table> <tbody> <tr> <td> Landmarks Cranium </td> </tr> <tr> <td> 1 </td> <td> Nasale: Intersection of nasal bones, rostral point </td> </tr> <tr> <td> 2 </td> <td> Nasion: Intersection of nasal bones, caudal point    </td> </tr> <tr> <td> 3 </td> <td> Bregma: intersection of frontal bones and parietal bones at midline </td> </tr> <tr> <td> 4 </td> <td> Intersection of parietal bones with anterior aspect of interparietal bone at midline </td> </tr> <tr> <td> 5 </td> <td> Intersection of interparietal bones with squamous portion of occipital bone at midline </td> </tr> <tr> <td> 6 </td> <td> Opisthion, midsagittal point on the posterior margin of the foramen magnum </td> </tr> <tr> <td> 7 </td> <td> Center of alveolar ridge over maxillary incisor, right side </td> </tr> <tr> <td> 8 </td> <td> Anterior Intersection of frontal process of maxilla with frontal bone, right side. </td> </tr> <tr> <td> 9 </td> <td> Anterior notch on frontal process lateral to infraorbital fissure, right side </td> </tr> <tr> <td> 10 </td> <td> Intersection of frontal process of maxilla with frontal and lacrimal bones, right side </td> </tr> <tr> <td> 11 </td> <td> Frontal-squasmosal intersection at temporal crest, right side </td> </tr> <tr> <td> 12 </td> <td> Intersection of zygoma (jugal) with zygomatic process of temporal, superior aspect, left side </td> </tr> <tr> <td> 13 </td> <td> Intersection of zygoma (jugal) with zygomatic process of temporal, inferior aspect, left side </td> </tr> <tr> <td> 14 </td> <td> Most posteroinferior point on the superior portion of the tympanic ring, right side </td> </tr> <tr> <td> 15 </td> <td> Center of alveolar ridge over maxillary incisor, left side </td> </tr> <tr> <td> 16 </td> <td> Anterior Intersection of frontal process of maxilla with frontal bone, left side. </td> </tr> <tr> <td> 17 </td> <td> Anterior notch on frontal process lateral to infraorbital fissure, left side </td> </tr> <tr> <td> 18 </td> <td> Intersection of frontal process of maxilla with frontal and lacrimal bones, left side </td> </tr> <tr> <td> 19 </td> <td> Frontal-squasmosal intersection at temporal crest, left side </td> </tr> <tr> <td> 20 </td> <td> Intersection of zygoma (jugal) with zygomatic process of temporal, superior aspect, right side </td> </tr> <tr> <td> 21 </td> <td> Intersection of zygoma (jugal) with zygomatic process of temporal, inferior aspect, right side </td> </tr> <tr> <td> 22 </td> <td> Most poteroinferior point on the superior portion of the tympanic ring, left side </td> </tr> <tr> <td> 23 </td> <td> Most anterior point of the anterior palatine foramen, right side </td> </tr> <tr> <td> 24 </td> <td> Most posterior point of the anterior palatine foramen, right side </td> </tr> <tr> <td> 25 </td> <td> Most infero lateral point on premaxilla-maxilla suture, right side </td> </tr> <tr> <td> 26 </td> <td> The anterior most point on the central ant/post axis of the right molar alveolus </td> </tr> <tr> <td> 27 </td> <td> Intersection of zygomatic process of maxilla with zygoma (jugal), inferior surface, right side </td> </tr> <tr> <td> 28 </td> <td> Lateral intersection of maxilla and palatine bone posterior to the third molar, right side </td> </tr> <tr> <td> 29 </td> <td> Joining of squasmosal body to zygomatic process of squasmosal, right side </td> </tr> <tr> <td> 30 </td> <td> Most inferior aspect of posterior tip of medial pterygoid process, right side </td> </tr> <tr> <td> 31 </td> <td> Most anterior point of the anterior palatine foramen, left side </td> </tr> <tr> <td> 32 </td> <td> Most posterior point of the anterior palatine foramen, left side </td> </tr> <tr> <td> 33 </td> <td> Most infero lateral point on premaxilla-maxilla suture, left side </td> </tr> <tr> <td> 34 </td> <td> The anterio most point on the central ant/post axis of the left molar alveolus </td> </tr> <tr> <td> 35 </td> <td> Intersection of zygomatic process of maxilla with zygoma (jugal), inferior surface, left side </td> </tr> <tr> <td> 36 </td> <td> Lateral intersection of maxilla and palatine bone posterior to the third molar, left side </td> </tr> <tr> <td> 37 </td> <td> Joining of squasmosal body to zygomatic process of squasmosal, left side </td> </tr> <tr> <td> 38 </td> <td> Most inferior aspect of posterior tip of medial pterygoid process, left side </td> </tr> <tr> <td> 39 </td> <td> Basion, midsagittal point on the anterior margin of the foramen magnum </td> </tr> </tbody> </table>  Table S1: 39 Skull Landmarks.   <table> <tbody> <tr> <td> Landmarks Mandible </td> </tr> <tr> <td> 1 </td> <td> Apex of coronoid process, Right side </td> </tr> <tr> <td> 2 </td> <td> Intersection of molar alveolar rim and base of coronoid process, Right side </td> </tr> <tr> <td> 3 </td> <td> Anterior edge of alveolar process where first molar hits alveolus at the midline, Right side </td> </tr> <tr> <td> 4 </td> <td> Superior-most point on incisor alveolar rim at midline (at bone-tooth junctions), Right side </td> </tr> <tr> <td> 5 </td> <td> Inferior-most point on incisor alveolar rim at midline (at bone-tooth junction), Right side </td> </tr> <tr> <td> 6 </td> <td> Inferior point on mandibular symphysis, Right side </td> </tr> <tr> <td> 7 </td> <td> Anterior edge of the coalescence of curve of masseteric ridge with post-symphyseal rugged area, Right side </td> </tr> <tr> <td> 8 </td> <td> Tip of mandibular angle, Right side </td> </tr> <tr> <td> 9 </td> <td> Posterior midline point on condyle, Right side </td> </tr> <tr> <td> 10 </td> <td> Anterior midline point on condyle, Right side </td> </tr> <tr> <td> 11 </td> <td> Anterior edge of the mental foramen, Right side </td> </tr> <tr> <td> 12 </td> <td> Apex of the coronoid process, left side </td> </tr> <tr> <td> 13 </td> <td> Intersection of molar alveolar rim and base of coronoid process, left side </td> </tr> <tr> <td> 14 </td> <td> Anterior edge of alveolar process where first molar hits alveolus at the midline, left side </td> </tr> <tr> <td> 15 </td> <td> Superior-most point on incisor alveolar rim at midline (at bone-tooth junctions), left side </td> </tr> <tr> <td> 16 </td> <td> Inferior-most point on incisor alveolar rim at midline (at bone-tooth junction), left side </td> </tr> <tr> <td> 17 </td> <td> Inferior point on mandibular symphysis, left side </td> </tr> <tr> <td> 18 </td> <td> Anterior edge of the coalescence of curve of masseteric ridge with post-symphyseal rugged area, left side </td> </tr> <tr> <td> 19 </td> <td> Tip of mandibular angle, left side </td> </tr> <tr> <td> 20 </td> <td> Posterior midline point on condyle, left side </td> </tr> <tr> <td> 21 </td> <td> Anterior midline point on condyle, left side </td> </tr> <tr> <td> 22 </td> <td> Anterior edge of the mental foramen, left side </td> </tr> </tbody> </table>  Table S2: 22 mandible Landmarks.

opencc-by-4.0Sep 2024View details →

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Data and Code from: Dysregulation of zebrin-II cell subtypes is a shared feature across polyglutamine ataxia mouse models and human patients

<div> <div> <div> Abstract Spinocerebellar ataxia type 7 (SCA7) is a genetic neurodegenerative disorder caused by a CAG- polyglutamine repeat expansion. Purkinje cells (PCs) are central to the pathology of ataxias, but their low abundance in the cerebellum underrepresents their transcriptomes in sequencing assays. To address this issue, we developed a PC enrichment protocol and sequenced individual nuclei from mice and patients with SCA7. Single-nucleus RNA sequencing in SCA7-266Q mice revealed dysregulation of cell identity genes affecting glia and PCs. Specifically, genes marking zebrin-II PC subtypes accounted for the highest proportion of DEGs in symptomatic SCA7-266Q mice. These transcriptomic changes in SCA7-266Q mice were associated with increased numbers of inhibitory synapses as quantified by immunohistochemistry and reduced spiking of PCs in acute brain slices. Dysregulation of zebrin-II cell subtypes was the predominant signal in PCs of SCA7-266Q mice and was associated with the loss of zebrin-II striping in the cerebellum at motor symptom onset. We furthermore demonstrated zebrin-II stripe degradation in additional mouse models of polyglutamine ataxia and observed decreased zebrin-II expression in cerebellum of patients with SCA7. Our results suggest that a breakdown of zebrin subtype regulation is a shared pathological feature of polyglutamine ataxias. Data and Code Availability Here you will find data and code associated with our manuscript "Dysregulation of zebrin-II cell subtypes is a shared feature across polyglutamine ataxia mouse models and human patients", Bartelt et al., Sci. Trans. Med. 16, eadn5449 (2024). The data file labeled "HuCb_filtered.rds" is a processed and annotated single-nucleus RNA-seq Seurat object, containing the gene-level count data for the multiplexed snRNA-seq experiment performed on post-mortem human cerebellar tissues from patients with SCA7 and unaffected controls. Data obtained from WT and SCA7-266Q mice as described in our paper can be accessed in the NIH Gene Expression Omnibus under accession number GSE269430. There are three code files numbered 00 through 02 which contain analysis code for snRNA-seq data applied to both the mouse and human datasets. These files are sequential and will take the user from CellRanger output, to filtered and annotated Seurat objects, and include details for subclustering analysis as well as our pseudobulk DEseq2 differential expression approach. There are places where the user may need to modify the code based on their computer system, version of R or Seurat, and whether they are processing the 5 week, 8 week, or human data sets; these locations in the code are marked with comments. <ul> <li>The first file, 00_Preprocessing_MULTIseq, begins with CellRanger filtered_feature_barcode_matrix output, extracts cell barcodes, utilizes the MULTIseq deMULTIplex software to match cell barcodes to oligo barcodes from MULTIseq fastq files, and annotates the Seurat file with metadata. Cell type identification and annotation also takes place in this file. Note: the deMULTIplex step will likely need to be run on a high performance compute cluster.</li> <li>The second file, 01_Seurat_Analysis, uses the filtered and annotated Seurat file to calculate useful QC metrics, investigate disease signals, and perform cell type subclustering analyses.</li> <li>The third file, 02_Pseudobulk_DEseq2, contains custom analysis code to extract raw counts for each cell type and each animal from the Seurat file, and uses the DEseq2 package to calculate DEGs, taking into account biological replicates, and raw read count differences between control and SCA7 animals.</li> </ul> </div> </div> </div>

opencc-by-4.0Nov 2024View details →

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DAPI images, molecules and segmentation boundaries for: A Spatiotemporal Atlas of Mouse Gastrulation and Early Organogenesis to Explore Axial Patterning and Project In Vitro Models onto In Vivo Space

<div> </div> Data Description <ol> <li>Stitched & rotated DAPI images - tiff file format filename indicates sample and optical z-slice position, i.e. embryo3_z5.tif is the DAPI image for embryo 3 in optical z-slice 5. Also provided in PNG format.</li> <li>Detected molecules and cell segmentation in MoleculeExperiment objects - RDS files to read data using the MoleculeExperiment format in R/Bioconductor. Filename embryo3_z5.Rds indicates MoleculeExperiment RDS file for embryo 3 in optical z-slice 5. Coordinates are provided in microns. Note that z-slices 2 and 5 are only provided for embryos 1,2,3 as they were originally provided in Lohoff et al, Nature Biotechnology, 2023.</li> <li>Pixels-to-microns conversion - pixelSize.R Simple R script/text to indicate the size of each pixel in the DAPI images, this is to align the coordinate systems between the DAPI images and molecules. <div> <h4>Project Abstract</h4> </div> At the onset of murine gastrulation, pluripotent epiblast cells migrate through the primitive streak, generating mesodermal and endodermal precursors, while the ectoderm arises from the remaining epiblast. Together, these germ layers establish the body plan, defining major body axes and initiating organogenesis. Although comprehensive single cell transcriptional atlases of dissociated mouse embryos across embryonic stages have provided valuable insights during gastrulation, the spatial context for cell differentiation and tissue patterning remain underexplored. In this study, we employed spatial transcriptomics to measure gene expression in mouse embryos at E6.5 and E7.5 and integrated these datasets with previously published E8.5 spatial transcriptomics and a scRNA-seq atlas spanning E6.5 to E9.5. This approach resulted in a comprehensive spatiotemporal atlas, comprising over 150,000 cells with 88 refined cell type annotations as well as genome-wide transcriptional imputation during mouse gastrulation and early organogenesis. The atlas facilitates exploration of gene expression dynamics along anterior-posterior and dorsal-ventral axes at cell type, tissue, and organismal scales, revealing insights into mesodermal fate decisions within the primitive streak. Moreover, we developed a bioinformatics pipeline to project additional scRNA-seq datasets into a spatiotemporal framework and demonstrate its utility by analysing cardiovascular models of gastrulation3. To maximise impact, the atlas is publicly accessible via a user-friendly web portal empowering the wider developmental and stem cell biology communities to explore mechanisms of early mouse development in a spatiotemporal context. </li> </ol>

opencc-by-4.0Oct 2024View details →

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Metabolic Derangement in Polycystic Kidney Disease Mouse Models Is Ameliorated by Mitochondrial-Targeted Antioxidants

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressively enlarging cysts. Here we elucidate the interplay between oxidative stress, mitochondrial dysfunction, and metabolic derangement using two mouse models of PKD1 mutation, PKD1RC/null and PKD1RC/RC. Mouse kidneys with PKD1 mutation have decreased mitochondrial complexes activity. Targeted proteomics analysis shows a significant decrease in proteins involved in the TCA cycle, fatty acid oxidation (FAO), respiratory complexes, and endogenous antioxidants. Overexpressing mitochondrial-targeted catalase (mCAT) using adeno-associated virus reduces mitochondrial ROS, oxidative damage, ameliorates the progression of PKD and partially restores expression of proteins involved in FAO and the TCA cycle. In human ADPKD cells, inducing mitochondrial ROS increased ERK1/2 phosphorylation and decreased AMPK phosphorylation, whereas the converse was observed with increased scavenging of ROS in the mitochondria. Treatment with the mitochondrial protective peptide, SS31, recapitulates the beneficial effects of mCAT, supporting its potential application as a novel therapeutic for ADPKD.

opencc-by-4.0Sep 2021View details →

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Data of Figure 5 from "Inhibition of IL-1beta improves Glycaemia in a Mouse Model for Gestational Diabetes"

Data of Figure 5 from “Inhibition of IL-1beta improves Glycaemia in a Mouse Model for Gestational Diabetes” Dataset (doi: 10.1038/s41598-020-59701-0) contains the original publication as PDF-format (10.1038_s41598-020-59701-0). Corresponding raw data obtained from LC-MS/MS analysis provided as two files in CSV format (31003A-179400_10.1038_s41598-020-59701-0_DW_4-1.csv, 31003A-179400_10.1038_s41598-020-59701-0_DW_4-2.csv). All further experiment related information provided as three meta-data-files (31003A-179400_10.1038_s41598-020-59701-0_DW _4-1_M_1.PDF, 31003A-179400_10.1038_s41598-020-59701-0_DW _4-2_M_1.PDF, 31003A-179400_10.1038_s41598-020-59701-0_DW _4_1-2_M_2.pdf) as PDF format.

opencc-by-4.0Feb 2020View details →

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Lung microbiota analyses in asthma mouse model

Background: Asthma is a frequent chronic inflammatory bronchial disease affecting more than 300 million patients worldwide, 70% of whom secondary to allergy. The diversity of asthmatic endotypes contributes to their complexity. Many factors, such as the environment, allergen sensitization pathways associate with microbiota, influence asthma natural course and explain its phenotypic heterogeneity. Here, we compared a mouse model of house dust mite (HDM)-induced allergic asthma sensitized via various routes for the clinical features of asthma, immune responses, the lung barrier and dysbiosis. Method: Mice were sensitized HDM by oral, nasal or percutaneous routes. Lung function, barrier integrity, immune response and microbiota composition were analyzed. Results: Severe impairment of respiratory function was observed in the mice sensitized by the nasal and cutaneous paths. It was associated with epithelial dysfunction characterized by an increased permeability secondary to junction protein disruption. Conversely, such sensitization paths induced a mixed eosinophilic and neutrophilic inflammatory response with high IL-17 airways secretion. In contrast, oral sensitized mice showed a mild impairment of respiratory function. Epithelial dysfunction was lighter with increased mucus production but conserved epithelial junctions. Lung Th2 and eosinophilic inflammation were observed. Considering lung microbiota, sensitization provoked a significant loss diversity. At the genus level, Cutibacterium, Acinetobacter, Streptococcus and Lactobacillus were found to be modulated according to the sensitization pathway. An increase in anti-inflammatory microbiota metabolites was observed in the oral group. Conclusion: Our study highlights the strong involvement of the sensitization route in allergic asthma physiopathology and the critical phenotypic diversity in a mouse model.

opencc-zeroDec 2022View details →

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Dataset related to: Therapeutic Small Interfering RNA Targeting Complement C3 in a Mouse Model of C3 Glomerulopathy

The files contain all the dataset included in the manuscript divided by figures.   Abstract Alternative pathway complement dysregulation with abnormal glomerular C3 deposits and glomerular damage is a key mechanism of pathology in C3 glomerulopathy (C3G). No disease-specific treatments are currently available for C3G. Therapeutics inhibiting complement are emerging as a potential strategy for the treatment of C3G. In this study, we investigated the effects of N-acetylgalactosamine (GalNAc) conjugated small interfering RNA (siRNA) targeting the C3 component of complement that inhibits liver C3 expression in the C3G model of mice with heterozygous deficiency of factor H (Cfh+/- mice). We showed a duration of action for GalNAc-conjugated C3 siRNA in reducing the liver C3 gene expression in Cfh+/- mice that were dosed s.c. once a month for up to 7 mo. C3 siRNA limited fluid-phase alternative pathway activation, reducing circulating C3 fragmentation and activation of factor B. Treatment with GalNAc-conjugated C3 siRNA reduced glomerular C3d deposits in Cfh+/- mice to levels similar to those of wild-type mice. Ultrastructural analysis further revealed the efficacy of the C3 siRNA in slowing the formation of mesangial and subendothelial electron-dense deposits. The present data indicate that RNA interference mediated C3 silencing in the liver may be a relevant therapeutic strategy for treating patients with C3G associated with the haploinsufficiency of complement factor H.

opencc-by-4.0Mar 2022View details →

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KidDO project update - quantitative proteomic and metabolomic analysis of five mouse models with chronic kidney disease

Chronic kidney disease (CKD) is one of the most deadly diseases faced by patients and is a major global health and socioeconomic burden.CKD increases cardiovascular morbidity and premature mortality and decreases quality of life. Hypertension (HTN) and type 2 diabetes mellitus (T2DM), which are reaching epidemic levels, are major risk factors for CKD. CKD diagnosis and progression is based on estimated GFR (eGFR) and urinary albumin excretion. However, eGFR only has a predictive value in advanced disease and there is risk of progressive CKD in non-albuminuric individuals. Thus, there is an urgent need for new approaches for early detection of the most “at risk” individuals and identification of CKD signatures to aid in designing novel drugs and preventive measures that could ameliorate progression of CKD. Our overarching goal is to identify metabolites that predict kidney cell phenotypes during CKD and how crosstalk of these metabolites with the proteome drive CKD progression. We will integrate metabolomics and proteomic information from animal models of CKD with human CKD patient biopsies to identify common signatures in the tubulointerstitium that correlate with human pathophysiology. Here we provide quantitative proteomic and metabolomic datasets, as well as plasma and urine electrolyte measurements on five CKD mouse models.

opencc-by-4.0Jan 2023View details →

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3D bioprinted alginate-gelatin hydrogel patches containing cardiac spheroids recover heart function in a mouse model of myocardial infarction

Datasets for Roche et al (2023), '3D bioprinted alginate-gelatin hydrogel patches containing cardiac spheroids recover heart function in a mouse model of myocardial infarction'.

opencc-by-4.0Feb 2023View details →

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Ex vivo 100 μm isotropic diffusion MRI‐based tractography of connectivity changes in the end‐stage R6/2 mouse model of Huntington's disease

<div> <div> <div> <div> Background: Huntington's disease is a progressive neurodegenerative disorder. Brain atrophy, as measured by volumetric magnetic resonance imaging (MRI), is a downstream consequence of neurodegeneration, but microstructural changes within brain tissue are expected to precede this volumetric decline. The tissue microstructure can be assayed non-invasively using diffusion MRI, which also allows a tractographic analysis of brain connectivity. Methods: We here used ex vivo diffusion MRI (11.7T) to measure microstructural changes in different brain regions of end‐stage (14 weeks of age) wild type and R6/2 mice (male and female) modeling Huntington's disease. To probe the microstructure of different brain regions, reduce partial volume effects and measure connectivity between different regions, a 100 μm isotropic voxel resolution was acquired. Results: Although fractional anisotropy did not reveal any difference between wild‐type controls and R6/2 mice, mean, axial, and radial diffusivity were increased in female R6/2 mice and decreased in male R6/2 mice. Whole brain streamlines were only reduced in male R6/2 mice, but streamline density was increased. Region‐to‐region tractography indicated reductions in connectivity between the cortex, hippocampus, and thalamus with the striatum, as well as within the basal ganglia (striatum—globus pallidus—subthalamic nucleus—substantia nigra—thalamus). Conclusions: Biological sex and left/right hemisphere affected tractographic results, potentially reflecting different stages of disease progression. This proof‐of‐principle study indicates that diffusion MRI and tractography potentially provide novel biomarkers that connect volumetric changes across different brain regions. In a translation setting, these measurements constitute a novel tool to assess the therapeutic impact of interventions such as neuroprotective agents in transgenic models, as well as patients with Huntington's disease. </div> </div> </div> </div>

opencc-zeroMar 2023View details →

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Data from: Small molecule inhibitor of tau self-association in a mouse model of tauopathy: A preventive study in P301L tau JNPL3 mice

Advances in tau biology and the difficulties of amyloid-directed immunotherapeutics have heightened interest in tau as a target for small molecule drug discovery for neurodegenerative diseases. Here, we evaluated OLX-07010, a small molecule inhibitor of tau self-association, for the prevention of tau aggregation. The primary endpoint of the study was statistically significant reduction of insoluble tau aggregates in treated JNPL3 mice compared with Vehicle-control mice. Secondary endpoints were dose-dependent reduction of insoluble tau aggregates, reduction of phosphorylated tau, and reduction of soluble tau. This study was performed in JNPL3 mice, which are representative of inherited forms of 4-repeat tauopathies with the P301L tau mutation (eg, progressive supranuclear palsy and frontotemporal dementia). The P301L mutation makes tau prone to aggregation; therefore, JNPL3 mice present a more challenging target than mouse models of human tau without mutations. JNPL3 mice were treated from 3 to 7 months of age with Vehicle, 30 mg/kg compound dose, or 40 mg/kg compound dose. Biochemical methods were used to evaluate self-associated tau, insoluble tau aggregates, total tau, and phosphorylated tau in the hindbrain, cortex, and hippocampus. The Vehicle group had higher levels of insoluble tau in the hindbrain than the Baseline group; treatment with 40 mg/kg compound dose prevented this increase. In the cortex, the levels of insoluble tau were similar in the Baseline and Vehicle groups, indicating that the pathological phenotype of these mice was beginning to emerge at the study endpoint and that there was a delay in the development of the phenotype of the model as originally characterized. No drug-related adverse effects were observed during the 4-month treatment period.

opencc-zeroJun 2023View details →

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Raw video and pose estimation data of top view open field mouse behavior recordings of acute and chronic stress models

This repository contains raw data for 411 different open field recordings of mice. these include top view raw video .mp4 files (Videos.zip) and the corresponding .csv pose estimation data (data.zip) obtained with DeepLabCut. The data is from multiple different experiments. The METADATA.csv or METADATA.xlsx files contain all grouping variables and help linking the pose estimation files (located in multiple subfolders of /data) to the video files. Visit https://github.com/ETHZ-INS/BehaviorFlow to find out more about how this data has be used by us.

opencc-by-4.0Jul 2023View details →

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Data from: Investigating the human and non-obese diabetic mouse MHC class II immunopeptidome using protein language modelling.

Background: Identifying peptides associated with the major histocompability complex class II (MHCII) is a central task in the evaluation of the immunoregulatory function of therapeutics and drug prototypes. MHCII-peptide presentation prediction has multiple biopharmaceutical applications, including the safety assessment of biologics and engineered derivatives in silico, or the fast progression of antigen-specific immunomodulatory drug discovery programs in immune disease and cancer. This has resulted in the collection of large–scale data sets on adaptive immune receptor antigenic responses and MHC-associated peptide proteomics. In parallel, recent deep learning algorithmic advances in natural language processing (NLP) and protein language modelling (PLM) have shown potential in leveraging large collections of sequence data and improve MHC presentation prediction. Methodology: We trained a compact transformer model (AEGIS) on human and mouse MHCII immunopeptidome data, including a preclinical murine model, and evaluated its performance on the peptide presentation prediction task. Data: The data and models used in AEGIS are contained in the uploaded tar files. Results: The transformer performs on par with existing deep learning algorithms and that combining datasets from multiple organisms increases model performance (see preprint). We trained variants of the model with and without MHCII information. In both alternatives, the inclusion of peptides presented by the I-Ag7 MHC class II molecule expressed by the non-obese diabetic (NOD) mice enabled the in silico prediction of presented peptides in a preclinical type 1 diabetes model organism, which has promising therapeutic applications.

opencc-by-4.0Aug 2022View details →

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Late gene therapy limits the restoration of retinal function in a mouse model of retinitis pigmentosa

Retinitis pigmentosa is an inherited photoreceptor degeneration that begins with rod loss followed by cone loss. This cell loss greatly diminishes vision, with most patients becoming legally blind. Gene therapies are being developed, but it is unknown how retinal function depends on the time of intervention. To uncover this dependence, we utilize a mouse model of retinitis pigmentosa capable of artificial genetic rescue. This model enables a benchmark of best-case gene therapy by removing variables that complicate the ability to answer this vital question. Complete genetic rescue was performed at 25%, 50%, and 70% rod loss (early, mid, and late, respectively). Here we show early- and mid-treatment restores retinal function to near wild-type levels, specifically the sensitivity and signal fidelity of retinal ganglion cells, the output neurons of the retina. However, some anatomical defects persist. Late treatment retinas exhibit continued, albeit slowed, loss of sensitivity and signal fidelity among retinal ganglion cells, as well as persistent gliosis. We conclude that gene replacement therapies delivered after 50% rod loss are unlikely to restore visual function to normal. This is critical information for administering gene therapies to rescue vision.

opencc-zeroAug 2023View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record