The purpose of this study is to analyze the effect of site-specific tau phosphorylation on cellular microfilaments networks. We examined cell images to study tau’s interaction with microfilaments in both wild type full-length (2N4R) tau and pathological human tau (PH-tau) when expressed in Chinese hamster ovarian fibroblasts (CHO). A custom ImageJ plugin was developed to provide quantitative analysis of the immunofluorescently labeled polymerized actin in cells expressing either of the above mentioned tau vectors. Using histograms of the pixel intensities of images, with userdefined thresholds, the code calculates the integrated densities and creates an output image to visualize the considered areas (those outside the thresholds are displayed as well). The data demonstrated the presence of an inverse correlation between the level of PH-tau expressed and the amount of total actin polymerization. Additionally, actin polymerization was not only interrupted by the presence of PH-tau but also punctate staining was also detected (as opposed to the normal fibril structure). These observations were not detected in cells expressing wild type tau. The visualization helped reveal some image acquisition anomalies such as varying levels of fluorescent staining as well as standardized image collection. The results should aid in a further understanding the mechanism of cellular degeneration induced by the hyperphosphorylation of MAP tau. Keywords: Microfilaments, Medical
Multiple Sclerosis (MS) lesions are known to change over time. The location, size and shape characteristics of lesions
are often used to diagnose and to track disease progression. We have improved our lesion-browsing tool that allows
users to automatically locate successive significant lesions in a MRI stack. In addition, an automatic alignment feature
was implemented to facilitate comparisons across stacks. A lesion stack is formed that can be browsed independently or
in tandem with the image windows. Lesions of interest can then be measured, rendered and rotated. Multiple windows
allow the viewer to compare the size and shape of lesions from the MRI images of the same patient taken at different
Multiple Sclerosis (MS) is an inflammatory and demyelinating disorder of the central nervous system with a presumed immune-mediated etiology. For treatment of MS, the measurements of white matter (WM), gray matter (GM), and cerebral spinal fluid (CSF) are often used in conjunction with clinical evaluation to provide a more objective measure of MS burden. In this paper, we apply a new unifying automatic mixture-based algorithm for segmentation of brain tissues to quantitatively analyze MS. The method takes into account the following effects that commonly appear in MR imaging: 1) The MR data is modeled as a stochastic process with an inherent inhomogeneity effect of smoothly varying intensity; 2) A new partial volume (PV) model is built in establishing the maximum a posterior (MAP) segmentation scheme; 3) Noise artifacts are minimized by a priori Markov random field (MRF) penalty indicating neighborhood correlation from tissue mixture. The volumes of brain tissues (WM, GM) and CSF are extracted from the mixture-based segmentation. Experimental results of feasibility studies on quantitative analysis of MS are presented.
We have developed a set of tools to build 3D images of vascular structures from contiguous slices. Slices were obtained from plastic-filled vascular casts. Major vascular branches on each slice were revealed and observed under the optical microscope. A series of video images of the branches on contiguous slices were then digitized. Each image was processed to isolate the vessels of interest. A user interface was built to select diameters, depths, and branching angles. A 3D image can then be viewed from any angle.