A three-dimensional virtual mouse generates synthetic training data for behavioral analysis.
Ontology highlight
ABSTRACT:
SUBMITTER: Bolanos LA
PROVIDER: S-EPMC8034498 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The data presented in this article are structures of dipeptides, tripeptides and tetrapeptides constructed from all possible combinations of 20 natural and common amino acids. In total, the data contains 168400 peptides. The structures are available in their simplified molecular-input line-entry system (SMILES) and three-dimensional (3D) formats. The type of data are text files, which could be accessed and modified either by text editor applications (e.g. Notepad++) or by molecule visualization softwares (e.g., YASARA View). These structures could be used further in virtual screening campaigns in the early stage of drug discovery projects.
| S-EPMC6806445 | biostudies-literature
Project description:The labeling and identification of long-range axonal inputs from multiple sources within densely reconstructed electron microscopy (EM) datasets from mammalian brains has been notoriously difficult because of the limited color label space of EM. Here, we report FluoEM for the identification of multi-color fluorescently labeled axons in dense EM data without the need for artificial fiducial marks or chemical label conversion. The approach is based on correlated tissue imaging and computational matching of neurite reconstructions, amounting to a virtual color labeling of axons in dense EM circuit data. We show that the identification of fluorescent light- microscopically (LM) imaged axons in 3D EM data from mouse cortex is faithfully possible as soon as the EM dataset is about 40-50 µm in extent, relying on the unique trajectories of axons in dense mammalian neuropil. The method is exemplified for the identification of long-distance axonal input into layer 1 of the mouse cerebral cortex.
| S-EPMC6158011 | biostudies-literature
Project description:The scale of biological microscopy has increased dramatically over the past ten years, with the development of new modalities supporting collection of high-resolution fluorescence image volumes spanning hundreds of microns if not millimeters. The size and complexity of these volumes is such that quantitative analysis requires automated methods of image processing to identify and characterize individual cells. For many workflows, this process starts with segmentation of nuclei that, due to their ubiquity, ease-of-labeling and relatively simple structure, make them appealing targets for automated detection of individual cells. However, in the context of large, three-dimensional image volumes, nuclei present many challenges to automated segmentation, such that conventional approaches are seldom effective and/or robust. Techniques based upon deep-learning have shown great promise, but enthusiasm for applying these techniques is tempered by the need to generate training data, an arduous task, particularly in three dimensions. Here we present results of a new technique of nuclear segmentation using neural networks trained on synthetic data. Comparisons with results obtained using commonly-used image processing packages demonstrate that DeepSynth provides the superior results associated with deep-learning techniques without the need for manual annotation.
| S-EPMC6892824 | biostudies-literature
Project description:Classical electromagnetism and quantum mechanics are both central to the modern understanding of the physical world and its ongoing technological development. Quantum simulations of electromagnetic forces have the potential to provide information about materials and systems that do not have conveniently solvable theoretical descriptions, such as those related to quantum Hall physics, or that have not been physically observed, such as magnetic monopoles. However, quantum simulations that simultaneously implement all of the principal features of classical electromagnetism have thus far proved elusive. We experimentally realize a simulation in which a charged quantum particle interacts with the knotted electromagnetic fields peculiar to a topological model of ball lightning. These phenomena are induced by precise spatiotemporal control of the spin field of an atomic Bose-Einstein condensate, simultaneously creating a Shankar skyrmion-a topological excitation that was theoretically predicted four decades ago but never before observed experimentally. Our results reveal the versatile capabilities of synthetic electromagnetism and provide the first experimental images of topological three-dimensional skyrmions in a quantum system.
| S-EPMC5834309 | biostudies-literature
Project description:Key vasculogenic (de-novo vessel forming) and angiogenic (vessel remodelling) events occur in the mouse embryo between embryonic days (E) 8.0 and 10.0 of gestation, during which time the vasculature develops from a simple circulatory loop into a complex, fine structured, three-dimensional organ. Interpretation of vascular phenotypes exhibited by signalling pathway mutants has historically been hindered by an inability to comprehensively image the normal sequence of events that shape the basic architecture of the early mouse vascular system. We have employed Optical Projection Tomography (OPT) using frequency distance relationship (FDR)-based deconvolution to image embryos immunostained with the endothelial specific marker PECAM-1 to create a high resolution, three-dimensional atlas of mouse vascular development between E8.0 and E10.0 (5 to 30 somites). Analysis of the atlas has provided significant new information regarding normal development of intersomitic vessels, the perineural vascular plexus, the cephalic plexus and vessels connecting the embryonic and extraembryonic circulation. We describe examples of vascular remodelling that provide new insight into the mechanisms of sprouting angiogenesis, vascular guidance cues and artery/vein identity that directly relate to phenotypes observed in mouse mutants affecting vascular development between E8.0 and E10.0. This atlas is freely available at http://www.mouseimaging.ca/research/mouse_atlas.html and will serve as a platform to provide insight into normal and abnormal vascular development.
| S-EPMC2478714 | biostudies-literature
Project description:Visualization and characterization of [Formula: see text]-amyloid deposits is a fundamental task in pre-clinical study of Alzheimer's disease (AD) to assess its evolution and monitor the efficiency of new therapeutic strategies. While the cerebellum is one of the brain areas most underestimated in the context of AD, renewed interest in cerebellar lesions has recently arisen as they may link to motor and cognitive alterations. Thus, we quantitatively investigated three-dimensional plaque morphology in the cerebellum in APP/PS1 transgenic mouse, as a model of AD. In order to obtain a complete high-resolution three-dimensional view of the investigated tissue, we exploited synchrotron X-ray phase contrast tomography (XPCT), providing virtual slices with histology-matching resolution. We found the formation of plaques elongated in shape, and with a specific orientation in space depending on the investigated region of the cerebellar cortex. Remarkably, a similar shape is observed in human cerebellum from demented patients. Our findings demonstrate the capability of XPCT in volumetric quantification, supporting the current knowledge about plaque morphology in the cerebellum and the fundamental role of the surrounding tissue in driving their evolution. A good correlation with the human neuropathology is also reported.
| S-EPMC7343834 | biostudies-literature
Project description:BACKGROUND:Genome-wide association studies (GWAS) are typically visualized using a two-dimensional Manhattan plot, displaying chromosomal location of SNPs along the x-axis and the negative log-10 of their p-value on the y-axis. This traditional plot provides a broad overview of the results, but offers little opportunity for interaction or expansion of specific regions, and is unable to show additional dimensions of the dataset. RESULTS:We created BigTop, a visualization framework in virtual reality (VR), designed to render a Manhattan plot in three dimensions, wrapping the graph around the user in a simulated cylindrical room. BigTop uses the z-axis to display minor allele frequency of each SNP, allowing for the identification of allelic variants of genes. BigTop also offers additional interactivity, allowing users to select any individual SNP and receive expanded information, including SNP name, exact values, and gene location, if applicable. BigTop is built in JavaScript using the React and A-Frame frameworks, and can be rendered using commercially available VR headsets or in a two-dimensional web browser such as Google Chrome. Data is read into BigTop in JSON format, and can be provided as either JSON or a tab-separated text file. CONCLUSIONS:Using additional dimensions and interactivity options offered through VR, we provide a new, interactive, three-dimensional representation of the traditional Manhattan plot for displaying and exploring GWAS data.
| S-EPMC6995189 | biostudies-literature
Project description:The analysis of single molecule imaging experiments is complicated by the stochastic nature of single molecule events, by instrument noise and by the limited information which can be gathered about any individual molecule observed. Consequently, it is important to cross check experimental results using a model simulating single molecule dynamics (e.g. movements and binding events) in a virtual cell-like environment. The output of such a model should match the real data format allowing researchers to compare simulated results with the real experiments. The proposed model exploits the advantages of 'object-oriented' computing. First of all, the ability to create and manipulate a number of classes, each containing an arbitrary number of single molecule objects. These classes may include objects moving within the 'cytoplasm'; objects moving at the 'plasma membrane'; and static objects located inside the 'body'. The objects of a given class can interact with each other and/or with the objects of other classes according to their physical and chemical properties. Each model run generates a sequence of images, each containing summed images of all fluorescent objects emitting light under given illumination conditions with realistic levels of noise and emission fluctuations. The model accurately reproduces reported single molecule experiments and predicts the outcome of future experiments.
| S-EPMC4233692 | biostudies-literature
Project description:Facial appearance transfer from donor to recipient in face transplantation is a concern. Previous studies of facial appearance transfer and facial appearance persistence (preservation of the recipient's facial likeness) in face transplants simulated using two-dimensional photographic manipulations found low facial appearance transfer (2.6 percent) and high facial appearance persistence (66 percent). Three-dimensional computer simulation of complex facial transplant patterns may improve the accuracy of facial appearance transfer and facial appearance persistence estimations.Three-dimensional virtual models of human faces were generated from deidentified computed tomographic angiographs and used as "donors" or "recipients" for virtual face transplantation. Surgical planning software was used to perform 73 virtual face transplantations by creating specific facial defects (mandibular, midface, or large) in the recipient models and restoring them with allografts extracted from the donor models. Twenty independent reviewers evaluated the resemblance of each resulting posttransplant model to the donor (facial appearance transfer) and recipient (facial appearance persistence). The results were analyzed using tests for equal results with one-sample and pairwise Rao-Scott Pearson chi-square testing, correcting for clustering and multiple testing.Overall rates of facial appearance persistence and facial appearance transfer were high (69.2 percent) and low (32.4 percent), respectively. The mandibular pattern had the highest rates of facial appearance persistence and lowest rates of facial appearance transfer. Facial appearance persistence and transfer were similar across sexes.Facial appearance persistence is high and facial appearance transfer is low after virtual face transplantation. Appearance transfer and persistence after virtual face transplantation are more dependent on the anatomy than on the size of transplanted facial aesthetic units. This information may reassure recipients of partial face transplants and donor families.
| S-EPMC3788837 | biostudies-literature
Project description:In anatomical education three-dimensional (3D) visualization technology allows for active and stereoscopic exploration of anatomy and can easily be adopted into medical curricula along with traditional 3D teaching methods. However, most often knowledge is still assessed with two-dimensional (2D) paper-and-pencil tests. To address the growing misalignment between learning and assessment, this viewpoint commentary highlights the development of a virtual 3D assessment scenario and perspectives from students and teachers on the use of this assessment tool: a 10-minute session of anatomical knowledge assessment with real-time interaction between assessor and examinee, both wearing a HoloLens and sharing the same stereoscopic 3D augmented reality model. Additionally, recommendations for future directions, including implementation, validation, logistic challenges, and cost-effectiveness, are provided. Continued collaboration between developers, researchers, teachers, and students is critical to advancing these processes.
| S-EPMC8252734 | biostudies-literature