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478 results for “3D data”
Research data supporting "Expanding and Optimizing 3D Bioprinting Capabilities Using Complementary Network Bioinks"
<p>Raw research data supporting:</p> <p>Ouyang L. et al., 2020, Science Advances, 6:eabc5529.</p>
Data and R code for What you see is where you go: visibility influences movement decisions of a forest bird navigating a 3D structured matrix
<p>Animal spatial behaviour is often presumed to reflect responses to visual cues. However, inference of behaviour in relation to the environment is challenged by the lack of objective methods to identify the information that effectively is available to an animal from a given location. In general, animals are assumed to have unconstrained information on the environment within a detection circle of a certain radius (the perceptual range; PR). However, visual cues are only available up to the first physical obstruction within an animal's PR, making information availability a function of an animal's location within the physical environment (the effective visual perceptual range; EVPR). By using LiDAR data and viewshed analysis, we model forest birds' EVPRs at each step along a movement path. We found that the EVPR was on average 0.063% that of an unconstrained PR and, by applying a step-selection analysis, that individuals are 1.57 times more likely to move to a tree within their EVPR than to an equivalent tree outside it. This demonstrates that behavioural choices can be substantially impacted by the characteristics of an individual's EVPR and highlights that inferences made from movement data may be improved by accounting for the EVPR.</p>
Data from: Bi-channel image registration and deep-learning segmentation (BIRDS) for efficient, versatile 3D mapping of mouse brain
<p>We have developed an open-source software called BIRDS (bi-channel image registration and deep-learning segmentation) for the mapping and analysis of 3D microscopy data and applied this to the mouse brain. The BIRDS pipeline includes image pre-processing, bi-channel registration, automatic annotation, creation of a 3D digital frame, high-resolution visualization, and expandable quantitative analysis. This new bi-channel registration algorithm is adaptive to various types of whole-brain data from different microscopy platforms and shows dramatically improved registration accuracy. Additionally, as this platform combines registration with neural networks, its improved function relative to other platforms lies in the fact that the registration procedure can readily provide training data for network construction, while the trained neural network can efficiently segment incomplete/defective brain data that is otherwise difficult to register. Our software is thus optimized to enable either minute-timescale registration-based segmentation of cross-modality, whole-brain datasets or real-time inference-based image segmentation of various brain regions of interest. Jobs can be easily submitted and implemented via a Fiji plugin that can be adapted to most computing environments.</p>
Data from: Functional and mechanistic neurotoxicity profiling using human iPSC–derived neural 3D cultures
Neurological disorders affect millions of people worldwide and appear to be on the rise. While the reason for this increase remains unknown, environmental factors are a suspected contributor. Hence, there is an urgent need to develop more complex, biologically relevant, and predictive in vitro assays to screen larger sets of compounds with the potential for neurotoxicity. Here, we employed a human induced pluripotent stem cell (iPSC)-based 3D neural platform composed of mature cortical neurons and astrocytes as a model for this purpose. The iPSC-derived human 3D cortical neuron/astrocyte co-cultures (3D neural cultures) present spontaneous synchronized, readily detectable calcium oscillations. This advanced neural platform was optimized for high-throughput screening in 384-well plates and displays highly consistent, functional performance across different wells and plates. Characterization of oscillation profiles in 3D neural cultures was performed through multi-parametric analysis that included the calcium oscillation rate and peak width, amplitude, and waveform irregularities. Cellular and mitochondrial toxicity were assessed by high-content imaging. For assay characterization, we used a set of neuromodulators with known mechanisms of action. We then explored the neurotoxic profile of a library of 87 compounds that included pharmaceutical drugs, pesticides, flame retardants, and other chemicals. Our results demonstrated that 57% of the tested compounds exhibited effects in the assay. The compounds were then ranked according to their effective concentrations based on in vitro activity. Our results show that a human iPSC-derived 3D neural culture assay platform is a promising biologically-relevant tool to assess the neurotoxic potential of drugs and environmental toxicants.
Data from: Use of anisotropy, 3D segmented atlas, and computational analysis to identify gray matter subcortical lesions common to concussive injury from different sites on the cortex
Traumatic brain injury (TBI) can occur anywhere along the cortical mantel. While the cortical contusions may be random and disparate in their locations, the clinical outcomes are often similar and difficult to explain. Thus a question that arises is, do concussions at different sites on the cortex affect similar subcortical brain regions? To address this question we used a fluid percussion model to concuss the right caudal or rostral cortices in rats. Five days later, diffusion tensor MRI data were acquired for indices of anisotropy (IA) for use in a novel method of analysis to detect changes in gray matter microarchitecture. IA values from over 20,000 voxels were registered into a 3D segmented, annotated rat atlas covering 150 brain areas. Comparisons between left and right hemispheres revealed a small population of subcortical sites with altered IA values. Rostral and caudal concussions were of striking similarity in the impacted subcortical locations, particularly the central nucleus of the amygdala, laterodorsal thalamus, and hippocampal complex. Subsequent immunohistochemical analysis of these sites showed significant neuroinflammation. This study presents three significant findings that advance our understanding and evaluation of TBI: 1) the introduction of a new method to identify highly localized disturbances in discrete gray matter, subcortical brain nuclei without postmortem histology, 2) the use of this method to demonstrate that separate injuries to the rostral and caudal cortex produce the same subcortical, disturbances, and 3) the central nucleus of the amygdala, critical in the regulation of emotion, is vulnerable to concussion.
Data from: Validation of perfusion quantification with 3D gradient echo dynamic contrast-enhanced magnetic resonance imaging using a blood pool contrast agent in skeletal swine muscle
The purpose of our study was to validate perfusion quantification in a low-perfused tissue by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with shared k-space sampling using a blood pool contrast agent. Perfusion measurements were performed in a total of seven female pigs. An ultrasonic Doppler probe was attached to the right femoral artery to determine total flow in the hind leg musculature. The femoral artery was catheterized for continuous local administration of adenosine to increase blood flow up to four times the baseline level. Three different stable perfusion levels were induced. The MR protocol included a 3D gradient-echo sequence with a temporal resolution of approximately 1.5 seconds. Before each dynamic sequence, static MR images were acquired with flip angles of 5°, 10°, 20°, and 30°. Both static and dynamic images were used to generate relaxation rate and baseline magnetization maps with a flip angle method. 0.1 mL/kg body weight of blood pool contrast medium was injected via a central venous catheter at a flow rate of 5 mL/s. The right hind leg was segmented in 3D into medial, cranial, lateral, and pelvic thigh muscles, lower leg, bones, skin, and fat. The arterial input function (AIF) was measured in the aorta. Perfusion of the different anatomic regions was calculated using a one- and a two-compartment model with delay- and dispersion-corrected AIFs. The F-test for model comparison was used to decide whether to use the results of the one- or two-compartment model fit. Total flow was calculated by integrating volume-weighted perfusion values over the whole measured region. The resulting values of delay, dispersion, blood volume, mean transit time, and flow were all in physiologically and physically reasonable ranges. In 107 of 160 ROIs, the blood signal was separated, using a two-compartment model, into a capillary and an arteriolar signal contribution, decided by the F-test. Overall flow in hind leg muscles, as measured by the ultrasound probe, highly correlated with total flow determined by MRI, R = 0.89 and P = 10−7. Linear regression yielded a slope of 1.2 and a y-axis intercept of 259 mL/min. The mean total volume of the investigated muscle tissue corresponds to an offset perfusion of 4.7mL/(min ⋅ 100cm3). The DCE-MRI technique presented here uses a blood pool contrast medium in combination with a two-compartment tracer kinetic model and allows absolute quantification of low-perfused non-cerebral organs such as muscles.
Data from: Three-dimensional reconstructions come to life – interactive 3D PDF animations in functional morphology
Digital surface mesh models based on segmented datasets have become an integral part of studies on animal anatomy and functional morphology; usually, they are published as static images, movies or as interactive PDF files. We demonstrate the use of animated 3D models embedded in PDF documents, which combine the advantages of both movie and interactivity, based on the example of preserved Trigonopterus weevils. The method is particularly suitable to simulate joints with largely deterministic movements due to precise form closure. We illustrate the function of an individual screw-and-nut type hip joint and proceed to the complex movements of the entire insect attaining a defence position. This posture is achieved by a specific cascade of movements: Head and legs interlock mutually and with specific features of thorax and the first abdominal ventrite, presumably to increase the mechanical stability of the beetle and to maintain the defence position with minimal muscle activity. The deterministic interaction of accurately fitting body parts follows a defined sequence, which resembles a piece of engineering.
Data from: A versatile pipeline for the multi-scale digital reconstruction and quantitative analysis of 3D tissue architecture
A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness.
Data from: Sharing is caring? measurement error and the issues arising from combining 3D morphometric datasets
Geometric morphometrics is routinely used in ecology and evolution and morphometric datasets are increasingly shared among researchers, allowing for more comprehensive studies and higher statistical power (as a consequence of increased sample size). However, sharing of morphometric data opens up the question of how much nonbiologically relevant variation (i.e., measurement error) is introduced in the resulting datasets and how this variation affects analyses. We perform a set of analyses based on an empirical 3D geometric morphometric dataset. In particular, we quantify the amount of error associated with combining data from multiple devices and digitized by multiple operators and test for the presence of bias. We also extend these analyses to a dataset obtained with a recently developed automated method, which does not require human-digitized landmarks. Further, we analyze how measurement error affects estimates of phylogenetic signal and how its effect compares with the effect of phylogenetic uncertainty. We show that measurement error can be substantial when combining surface models produced by different devices and even more among landmarks digitized by different operators. We also document the presence of small, but significant, amounts of nonrandom error (i.e., bias). Measurement error is heavily reduced by excluding landmarks that are difficult to digitize. The automated method we tested had low levels of error, if used in combination with a procedure for dimensionality reduction. Estimates of phylogenetic signal can be more affected by measurement error than by phylogenetic uncertainty. Our results generally highlight the importance of landmark choice and the usefulness of estimating measurement error. Further, measurement error may limit comparisons of estimates of phylogenetic signal across studies if these have been performed using different devices or by different operators. Finally, we also show how widely held assumptions do not always hold true, particularly that measurement error affects inference more at a shallower phylogenetic scale and that automated methods perform worse than human digitization.
Data and Code for "3D flightpaths reveal the development of spatial memory in wild hummingbirds"
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Raw data for the article: 3D Culture and Interferon-? Priming Modulates Characteristics of Mesenchymal Stromal/Stem Cells by Modifying the Expression of Both Intracellular and Exosomal microRNAs
<p>Mesenchymal stromal/stem cells (MSCs) have emerged as a therapeutic tool in regenerative medicine. Recent studies have shown that exosome (EXO)-derived microRNAs (miRNAs) play a crucial role in mediating MSC functions. Additionally, intracellular miRNAs have been found to regulate MSC therapeutic capacities. However, the molecular mechanisms underlying miRNA-mediated MSC effects are not fully understood. We used 3D culture and IFN-γ to prime/enhance the MSC therapeutic effects in terms of functional miRNAs. After priming, our analysis revealed stable variations in intracellular miRNA among the MSC biological replicates. Conversely, a significant variability of miRNA was observed among EXOs released from biological replicates of the priming treatment. For each priming, we observed distinct miRNA expression profiles between the MSCs and their EXOs. Moreover, in both types of priming, gene ontology (GO) analysis of deregulated miRNAs highlighted their involvement in tissue repair/regeneration pathways. In particular, the 3D culture enhanced angiogenic properties in both MSCs and EXOs, while IFN-γ treatment enriched miRNAs associated with immunomodulatory pathways. These findings suggest that 3D culture and IFN-γ treatment are promising strategies for enhancing the therapeutic potential of MSCs by modulating miRNA expression. Additionally, the identified miRNAs may contribute to understanding the molecular mechanisms underlying the miRNA-mediated therapeutic effects of MSCs.</p>
Datasets for '3D Reconstruction of Equatorial Plasma Bubbles Using EOF and GNSS Radio Occultation Data From MSS-1 and COSMIC-2'
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Latent 3D Graph Diffusion -- AE_geom_cond_weights_and_data
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Latent 3D Graph Diffusion -- AE_topo_weights_and_data
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Data from: Sex-determining 3D regulatory hubs revealed by genome spatial auto-correlation analysis
<p>Mammalian sex is determined by opposing networks of ovarian and testicular genes that are well characterized. However, its epigenetic regulation is still largely unknown, thus limiting our understanding of a fundamental process for species propagation. Here we explore the 3D chromatin landscape of sex determination <em>in vivo</em>, using <em>METALoci</em>, a novel genome spatial auto-correlation analysis.</p> <p><strong>Extended Data File 1: Coordinates for HH metaloci in each sample.</strong></p> <p>The EDFile1_H3K27ac_HH_metaloci_per_gene.zip file contains four files named:</p> <ul> <li>XX10.5_H3K27ac_HH_metaloci_per_gene.bed</li> <li>XX13.5_H3K27ac_HH_metaloci_per_gene.bed</li> <li>XY10.5_H3K27ac_HH_metaloci_per_gene.bed</li> <li>XY13.5_H3K27ac_HH_metaloci_per_gene.bed</li> </ul> <p>Each BED file contains the following columns tab separated:</p> <ul> <li>chr Chromosome</li> <li>start Start coordinates</li> <li>end End coordinates</li> <li>MetaLociBinNumber Number of the bin in the METALoci layout</li> <li>GeneSymbol Gene symbol</li> </ul> <p> </p> <p><strong>Extended Data File 2: Coordinates bins in METALoci with ATAC-seq accessible peak targeted by TF.</strong></p> <p>The EDFile2_TF_ATAC_ML_Sites.zip file contains four files named:</p> <ul> <li>XX10.5_TF_ATAC_ML_Sites.tsv</li> <li>XX13.5_TF_ATAC_ML_Sites.tsv</li> <li>XY10.5_TF_ATAC_ML_Sites.tsv</li> <li>XY13.5_TF_ATAC_ML_Sites.tsv</li> </ul> <p>Each TSV file contains the following columns tab separated:</p> <ul> <li>chr Motif site chromosome </li> <li>start Motif site start coordinates </li> <li>end Motif site end coordinates</li> <li>bin Hi-C bin number</li> <li>pchr ATAC site chromosome</li> <li>pstart ATAC site start coordinates</li> <li>pend ATAC site end coordinates</li> <li>gene Gene symbol</li> </ul>
3D_data_files_STAGE_NEBULIZER_DOUBLE_newEXTRUDER_Extension
<p>Version 2.2.1: 3D Dataset of the STAGE and the NEBULIZER new Extruder, using Controller Board + Extension </p>
3D reconstruction of a Mycoplasma pneumoniae cell from cryo-electron tomography data
<p>3D reconstruction of a Mycoplasma pneumoniae cell from cryo-electron tomography data in EMPIAR-10499.</p>
3D reconstruction of HIV virus-like particles from cryo-electron tomography data
<p>3D reconstruction of HIV virus-like particles from cryo-electron tomography data in EMPIAR-10164 and associated particle poses.</p>
3D-MSNet: A point cloud based deep learning model for untargeted feature detection and quantification in profile LC-HRMS data
<p>Supplementary data of 3D-MSNet</p>
Data from: Ellipsoid segmentation model for analyzing light-attenuated 3D confocal image stacks of fluorescent multi-cellular spheroids
In oncology, two-dimensional in-vitro culture models are the standard test beds for the discovery and development of cancer treatments, but in the last decades, evidence emerged that such models have low predictive value for clinical efficacy. Therefore they are increasingly complemented by more physiologically relevant 3D models, such as spheroid micro-tumor cultures. If suitable fluorescent labels are applied, confocal 3D image stacks can characterize the structure of such volumetric cultures and, for example, cell proliferation. However, several issues hamper accurate analysis. In particular, signal attenuation within the tissue of the spheroids prevents the acquisition of a complete image for spheroids over 100 micrometers in diameter. And quantitative analysis of large 3D image data sets is challenging, creating a need for methods which can be applied to large-scale experiments and account for impeding factors. We present a robust, computationally inexpensive 2.5D method for the segmentation of spheroid cultures and for counting proliferating cells within them. The spheroids are assumed to be approximately ellipsoid in shape. They are identified from information present in the Maximum Intensity Projection (MIP) and the corresponding height view, also known as Z-buffer. It alerts the user when potential bias-introducing factors cannot be compensated for and includes a compensation for signal attenuation.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.