Epidermal penetration of a therapeutic peptide by lipid conjugation; Stereo-selective peptide availability of a topical diastereomeric lipopeptide

In inflammatory disorders (e.g. psoriasis), local concentrations of human neutrophil elastase (HNE), also known as polymorphonuclear leukocyte elastase (HLE), possibly overwhelm its natural inhibitors leading to extracellular matrix degradation. Elevated levels of HNE have been reported in a variety of inflammatory disorders, including psoriasis. Peptidic HNE inhibitors have a common hydrophobic sequence (Ala-Ala-Pro-Val). This peptide sequence inhibits HNE competitively; however the stratum corneum presents an effective barrier to the delivery of this tetrapeptide across the skin. The current work investigates the delivery of the modified peptide whereby the tetrapeptide was lipidated to enhance its ability to penetrate the stratum The tetrapeptide Was Coupled to a racaemic mixture of a short chain lipoamino acid (LAA) resulting in two diastereomers of the lipoamino acid-modified tetrapeptide. The penetration of the lipopeptide mixture was assessed across human epidermis in vitro. The percentage of applied dose penetrating to the receptor over 8 h following administration was 2.53% for the D-LAA conjugate and 1.47% for the L-diastereomer, compared to 0% for the peptide. The D-diastereomer appears to be relatively stable but the L-diastereomer appears to degrade releasing possibly the tetrapeptide and peptide fragment(s). Therefore the results clearly indicate that coupling the tetrapeptide to a short chain LAA enhances its delivery across human epidermis.

Fast stereo matching by iterated dynamic programming and quadtree subregioning

The application of energy minimisation methods for stereo matching has been demonstrated to produce high quality disparity maps. However the majority of these methods are known to be computationally expensive, requiring minutes or even hours of computation. We propose a fast minimisation scheme that produces strongly competitive results for significantly reduced computation, requiring only a few seconds of computation. In this paper, we present our iterated dynamic programming algorithm along with a quadtree subregioning process for fast stereo matching.

Multiple paths extraction in images using a constrained expanded trellis

Single shortest path extraction algorithms have been used in a number of areas such as network flow and image analysis. In image analysis, shortest path techniques can be used for object boundary detection, crack detection, or stereo disparity estimation. Sometimes one needs to find multiple paths as opposed to a single path in a network or an image where the paths must satisfy certain constraints. In this paper, we propose a new algorithm to extract multiple paths simultaneously within an image using a constrained expanded trellis (CET) for feature extraction and object segmentation. We also give a number of application examples for our multiple paths extraction algorithm.

Automatic building detection using the Dempster-Shafer algorithm

An approach and strategy for automatic detection of buildings from aerial images using combined image analysis and interpretation techniques is described in this paper. It is undertaken in several steps. A dense DSM is obtained by stereo image matching and then the results of multi-band classification, the DSM, and Normalized Difference Vegetation Index (NDVI) are used to reveal preliminary building interest areas. From these areas, a shape modeling algorithm has been used to precisely delineate their boundaries. The Dempster-Shafer data fusion technique is then applied to detect buildings from the combination of three data sources by a statistically-based classification. A number of test areas, which include buildings of different sizes, shape, and roof color have been investigated. The tests are encouraging and demonstrate that all processes in this system are important for effective building detection.

Dynamic breast MRI: Image registration and its impact on enhancement curve estimation

A novel algorithm for performing registration of dynamic contrast-enhanced (DCE) MRI data of the breast is presented. It is based on an algorithm known as iterated dynamic programming originally devised to solve the stereo matching problem. Using artificially distorted DCE-MRI breast images it is shown that the proposed algorithm is able to correct for movement and distortions over a larger range than is likely to occur during routine clinical examination. In addition, using a clinical DCE-MRI data set with an expertly labeled suspicious region, it is shown that the proposed algorithm significantly reduces the variability of the enhancement curves at the pixel level yielding more pronounced uptake and washout phases.