This image (and linked movie) shows a rotating 3D view of a vesicle that was semi-automatically segmented from a 3D TEM image reconstructed from a tilt series. A handful of seed points were placed in one slice of the image and the 3D vesicle was automatically extracted. The image also shows a very preliminary automatic segmentation of proteins extending through the vesicle wall; the extent of these proteins is currently clipped by an arbitrary global parameter setting.
The second in a series of animated videos depicting the inner workings of the human lung on a microscopic scale. “Scene 2: Clearance: A Journey” asks questions about how clearance can possibly work when the volume through which the mucus flows decreases as it moves up from the depths of the lung to the throat.
Simulated image generation in FluoroSim is fast enough to enable interaction with specimen models while watching real-time updates of the expected fluorescence image. This video shows some of FluoroSim’s main capabilities.
Cilia-driven mucus flow visualization by David Borland
David Borland developed a flow visualization technique and used the output of Brian Eastwood’s ImageTracker program to construct this visualization of cilia-driven mucus flow on a human lung cell culture video from David Hill. He overlaid the flow on the cell background determined by ImageTracker.
Flow speed is encoded both by color (blue lowest, through gray to red). Flow direction is along the lines and in the direction pointed to by the arrows.
The first in a series of animated videos depicting the inner workings of the human lung on a microscopic scale. “Scene 1: Into the Mucus River” explains how air gets into healthy lungs, how the body defends itself against harmful airborne pathogens, and how mucus and cilia interact with the air particles.
The image to the right shows one frame from a stack of images taken of a human lung epithelial cell culture. The well-separated spots were thought to be cross sections through cilia sticking out the tops of cells. There are some bright spots on the labeled cells and others (near the left of the image) that were thought to be above cells.
ImageSurfer 3D view of epithelial cells
The ImageSurfer image shown below to the right revealed that they were in fact isolated blobs of dye that were outside of the cells.
In this movie, we show a fibrin network stretched using an AFM tip and then tracked using CISMM’s video spot tracker. The distribution of fiber strains within the network is then analyzed. The goal is to understand the influence of single fiber mechanics on the properties of entire networks.
iMiJ.pdb: Native Chicken Fibrinogen rendered using broad illumination on the BASS (NIH 1S10RR023069-01)
CISMM is one of the primary users of the Biomedical Analysis and Simulation Supercomputer (BASS) system that was commissioned yesterday. One of the first uses of the machine was to construct a high-resolution rendering of fibrinogen (blood clotting molecule of interest to our thrombisis collaborators Susan Lord, John Weidel, Martin Guthold, and Alisa Wolberg). This is a prototype for the PDB rendering project in collaboration with David Banks at with the Klaus Schulten NCRR on Macromolecular Modeling and Bioinformatics.
The mitotic spindle model (Yeh et al., 2008). (a) Side-on view; (b) end-on view. Helices represent the chromatin labeled with green fluorescing protein. Experimental and noise-free simulated images in side-on orientation (c-d) and end-on orientation (e-f). Differences in background between experimental and simulated images are caused by external chromatin not accounted for in the model. Structural variation in real specimens account for shape discrepancies.
