Quantifying and visualizing the shape of developing biological tissues provide information about the morphogenetic processes in multicellular organisms. The size and shape of biological tissues depend on the number, size, shape, and arrangement of the constituting cells. To better understand the mechanisms that guide tissues into their final shape, it is important to investigate the cellular arrangement within tissues. Here we present a data processing pipeline to generate 3D volumetric surface models of epithelial tissues, as well as geometric descriptions of the tissues’ apical cell cross-sections. The data processing pipeline includes image acquisition, editing, processing and analysis, 2D cell mesh generation, 3D contourbased surface reconstruction, cell mesh projection, followed by geometric calculations and color-based visualization of morphological parameters. In their first utilization we have applied these procedures to construct a 3D volumetric surface model at cellular resolution of the wing imaginal disc of Drosophila melanogaster. The ultimate goal of the reported effort is to produce tools for the creation of detailed 3D geometric models of the individual cells in epithelial tissues. To date, 3D volumetric surface models of the whole wing imaginal disc have been created, and the apicolateral cell boundaries have been identified, allowing for the calculation and visualization of cell parameters, e.g. apical cross-sectional area of cells. The calculation and visualization of morphological parameters show position-dependent patterns of cell shape in the wing imaginal disc. Our procedures should offer a general data processing pipeline for the construction of 3D volumetric surface models of a wide variety of epithelial tissues.
The ear relies on nonlinear amplification to enhance its sensitivity and frequency selectivity. It has been suggested that this active process results from dynamical systems which oscillate spontaneously.
In the bullfrog sacculus, hair bundles, which are the mechanosensitive elements of sensory hair cells display noisy oscillations. These oscillations can be described in a simple model which takes into account the properties of mechanosensitive ion channels coupled to motor proteins which are regulated by inflowing Ca2+ ions. The role of fluctuations can be studied by adding random forcing terms with characteristic amplitudes that result from the number and properties of ion channels and motor molecules. This description can account quantitatively for the experimentally measured linear and nonlinear response functions and reveals the relevance of fluctuations for signal detection.
Conference Committee Involvement (1)
Fluctuations and Noise in Biological, Biophysical, and Biomedical Systems II
26 May 2004 | Maspalomas, Gran Canaria Island, Spain