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The neuroarchitecture of Acoela has been at the center of morphological debates. Some authors, using immunochemical tools, suggest that the nervous system in Acoela is organized as a commissural brain that bears little resemblance to the central, ganglionic type brain of other flatworms, and bilaterians in general. Others, who used histological staining on paraffin sections, conclude that it is a compact structure (an endonal brain; e.g., Raikova 2004; von Graff 1891; Delage Arch Zool Exp Gén 4:109-144, 1886). To address this question with modern tools, we have obtained images from serial transmission electron microscopic sections of the entire hatchling of Symsagittifera roscoffensis. In addition, we obtained data from wholemounts of hatchlings labeled with markers for serotonin and tyrosinated tubulin. Our data show that the central nervous system of a juvenile S. roscoffensis consists of an anterior compact brain, formed by a dense, bilobed mass of neuronal cell bodies surrounding a central neuropile. The neuropile flanks the median statocyst and contains several types of neurites, classified according to their types of synaptic vesicles. The neuropile issues three pairs of nerve cords that run at different dorso-ventral positions along the whole length of the body. Neuronal cell bodies flank the cords, and neuromuscular synapses are abundant. The TEM analysis also reveals different classes of peripheral sensory neurons and provides valuable information about the spatial relationships between neurites and other cell types within the brain and nerve cords. We conclude that the acoel S. roscoffensis has a central brain that is comparable in size and architecture to the brain of other (rhabditophoran) flatworms.
Pubmed ID: 20549514 RIS Download
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An ImageJ plugin for morphological data mining, three-dimensional modeling and image stitching, registration, editing and annotation. Two independent modalities exist: either XML-based projects, working directly with the file system, or database-based projects, working on top of a local or remote PostgreSQL database. What can you do with it? * Semantic segmentation editor: order segmentations in tree hierarchies, whose template is exportable for reuse in other, comparable projects. * Model, visualize and export 3D. * Work from your laptop on your huge, remote image storage. * Work with an endless number of images, limited only by the hard drive capacity. Dozens of formats supported thanks to LOCI Bioformats and ImageJ. * Import stacks and even entire grids (montages) of images, automatically stitch them together and homogenize their histograms for best montaging quality. * Add layers conveniently. A layer represents, for example, one 50 nm section (for TEM) or a confocal section. Each layer has its own Z coordinate and thickness, and contains images, labels, areas, nodes of 3d skeletons, profiles... * Insert layer sets into layers: so your electron microscopy serial sections can live inside your optical microscopy sections. * Run any ImageJ plugin on any image. * Measure everything: areas, volumes, pixel intensities, etc. using both built-in data structures and segmentation types, and standard ImageJ ROIs. And with double dissectors! * Visualize RGB color channels changing the opacity of each on the fly, non-destructively. * Annotate images non-destructively with floating text labels, which you can rotate/scale on the fly and display in any color. * Montage/register/stitch/blend images manually with transparencies, semiautomatically, or fully automatically within and across sections, with translation, rigid, similarity and affine models with automatically extracted SIFT features. * Correct the lens distortion present in the images, like those generated in transmission electron microscopy. * Add alpha masks to images using ROIs, for example to split images in two or more parts, or to remove the borders of an image or collection of images. * Model neuronal arbors with 3D skeletons (with areas or radiuses), and synapses with connectors. * Undo all steps. And much more...
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