Protein Kinase C–Dependent Mobilization of the α6β4 Integrin from Hemidesmosomes and Its Association with Actin-Rich Cell Protrusions Drive the Chemotactic Migration of Carcinoma Cells

We explored the hypothesis that the chemotactic migration of carcinoma cells that assemble hemidesmosomes involves the activation of a signaling pathway that releases the α6β4 integrin from these stable adhesion complexes and promotes its association with F-actin in cell protrusions enabling it to function in migration. Squamous carcinoma-derived A431 cells were used because they express α6β4 and migrate in response to EGF stimulation. Using function-blocking antibodies, we show that the α6β4 integrin participates in EGF-stimulated chemotaxis and is required for lamellae formation on laminin-1. At concentrations of EGF that stimulate A431 chemotaxis (∼1 ng/ml), the α6β4 integrin is mobilized from hemidesmosomes as evidenced by indirect immunofluorescence microscopy using mAbs specific for this integrin and hemidesmosomal components and its loss from a cytokeratin fraction obtained by detergent extraction. EGF stimulation also increased the formation of lamellipodia and membrane ruffles that contained α6β4 in association with F-actin. Importantly, we demonstrate that this mobilization of α6β4 from hemidesmosomes and its redistribution to cell protrusions occurs by a mechanism that involves activation of protein kinase C-α and that it is associated with the phosphorylation of the β4 integrin subunit on serine residues. Thus, the chemotactic migration of A431 cells on laminin-1 requires not only the formation of F-actin–rich cell protrusions that mediate α6β4-dependent cell movement but also the disruption of α6β4-containing hemidesmosomes by protein kinase C

Final Report: Closeout of the Award NO. DE-FG02-98ER62618 (M.S. Fox-Rabinovitz, P.I.)

The final report describes the study aimed at exploring the variable-resolution stretched-grid (SG) approach to decadal regional climate modeling using advanced numerical techniques. The obtained results have shown that variable-resolution SG-GCMs using stretched grids with fine resolution over the area(s) of interest, is a viable established approach to regional climate modeling. The developed SG-GCMs have been extensively used for regional climate experimentation. The SG-GCM simulations are aimed at studying the U.S. regional climate variability with an emphasis on studying anomalous summer climate events, the U.S. droughts and floods

Kinetics of Intramolecular Chemical Exchange by Initial Growth Rates of Spin Saturation Transfer Difference Experiments (SSTD NMR)

We report here the Initial Growth Rates SSTD NMR method, as a new powerful tool to obtain the kinetic parameters of intramolecular chemical exchange in challenging small organic and organometallic molecules

Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images

Dermoscopy is a non-invasive skin imaging technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. One of the most important features for the diagnosis of melanoma in dermoscopy images is the blue-white veil (irregular, structureless areas of confluent blue pigmentation with an overlying white "ground-glass" film). In this article, we present a machine learning approach to the detection of blue-white veil and related structures in dermoscopy images. The method involves contextual pixel classification using a decision tree classifier. The percentage of blue-white areas detected in a lesion combined with a simple shape descriptor yielded a sensitivity of 69.35% and a specificity of 89.97% on a set of 545 dermoscopy images. The sensitivity rises to 78.20% for detection of blue veil in those cases where it is a primary feature for melanoma recognition

Orthotopic liver transplantation for alcoholic liver disease

Alcohol abuse is the most common cause of end‐stage liver disease in the United States, but many transplant centers are unwilling to accept alcoholic patients because of their supposed potential for recidivism, poor compliance with the required immunosuppression regimen and resulting failure of the allograft. There is also concern that alcohol‐induced injury in other organs will preclude a good result. From July 1, 11982, to April 30, 1988, 73 patients received orthotopic liver transplants at the University of Pittsburgh for end‐stage alcoholic liver disease. Fifty‐two (71%) of these were alive at 25 ± 9 mo (mean ± S. D.) after transplantation, when a phone survey of these patients, their wives/husbands, and their physicians was performed to evaluate their subsequent use of alcohol, current medical condition and employment. Data obtained were compared with those for nonalcoholic patients selected as transplant controls. The recidivism rate has been 11.5%, with most patients drinking only socially. Fifty‐four percent of the survivors are employed, 21% classify themselves as homemakers and only 11 (21%) are unable to work. Twenty‐one patients died after transplantation; the most frequent cause of death was sepsis (43%), and intraoperative death was the next most common cause (28.6%). These data demonstrate that alcoholic patients can be transplanted successfully and achieve good health not significantly different from that of individuals transplanted for other causes. Thus orthotopic liver transplantation is a therapeutic option that should be considered for individuals with end‐stage alcoholic liver disease who desire such therapy. Copyright © 1990 American Association for the Study of Liver Disease

Dark homogeneous streak dermoscopic pattern correlating with specific KIT mutations in melanoma

Mutations driving melanoma growth have diagnostic, prognostic, and therapeutic implications. Traditional classification systems do not correlate optimally with underlying melanoma growth-promoting mutations. Our objective was to determine whether unique dermoscopic growth patterns directly correlate with driving mutations. OBSERVATIONS: We evaluated common driving mutations in 4 different dermoscopic patterns (rhomboidal, negative pigmented network, polygonal, and dark homogeneous streaks) of primary cutaneous melanomas; 3 melanomas per pattern were tested. Three of the 4 patterns lacked common mutations in BRAF, NRAS, KIT, GNAQ, and HRAS. One pattern, the dark homogeneous streaks pattern, had unique KIT mutations in the second catalytic domain of KIT in exon 17 for all 3 samples tested. Two tumors with the dark homogeneous streaks pattern turned out to be different primary melanomas from the same patient and had different sequence mutations but had an impact on the same KIT domain. CONCLUSIONS AND RELEVANCE: While future study is required, these results have multiple implications. (1) The underlying melanoma-driving mutations may give rise to specific dermoscopic growth patterns, (2) BRAF/NRAS mutations in early melanomas may not be as common as previously thought, and (3) patients may be predisposed to developing specific driving mutations giving rise to melanomas or nevi of similar growth patterns

Fast and Accurate Border Detection in Dermoscopy Images Using Statistical Region Merging

Copyright 2007 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.As a result of advances in skin imaging technology and the development of suitable image processing techniques during the last decade, there has been a significant increase of interest in the computer-aided diagnosis of melanoma. Automated border detection is one of the most important steps in this procedure, since the accuracy of the subsequent steps crucially depends on it. In this paper, a fast and unsupervised approach to border detection in dermoscopy images of pigmented skin lesions based on the Statistical Region Merging algorithm is presented. The method is tested on a set of 90 dermoscopy images. The border detection error is quantified by a metric in which a set of dermatologist-determined borders is used as the ground-truth. The proposed method is compared to six state-of-the-art automated methods (optimized histogram thresholding, orientation-sensitive fuzzy c-means, gradient vector flow snakes, dermatologist-like tumor extraction algorithm, meanshift clustering, and the modified JSEG method) and borders determined by a second dermatologist. The results demonstrate that the presented method achieves both fast and accurate border detection in dermoscopy images.http://dx.doi.org/10.1117/12.70907

A Comparison of Two Shallow Water Models with Non-Conforming Adaptive Grids: classical tests

In an effort to study the applicability of adaptive mesh refinement (AMR) techniques to atmospheric models an interpolation-based spectral element shallow water model on a cubed-sphere grid is compared to a block-structured finite volume method in latitude-longitude geometry. Both models utilize a non-conforming adaptation approach which doubles the resolution at fine-coarse mesh interfaces. The underlying AMR libraries are quad-tree based and ensure that neighboring regions can only differ by one refinement level. The models are compared via selected test cases from a standard test suite for the shallow water equations. They include the advection of a cosine bell, a steady-state geostrophic flow, a flow over an idealized mountain and a Rossby-Haurwitz wave. Both static and dynamics adaptations are evaluated which reveal the strengths and weaknesses of the AMR techniques. Overall, the AMR simulations show that both models successfully place static and dynamic adaptations in local regions without requiring a fine grid in the global domain. The adaptive grids reliably track features of interests without visible distortions or noise at mesh interfaces. Simple threshold adaptation criteria for the geopotential height and the relative vorticity are assessed.Comment: 25 pages, 11 figures, preprin

Bounded Model Checking of Concurrent Data Types on Relaxed Memory Models: A Case Study

Many multithreaded programs employ concurrent data types to safely share data among threads. However, highly-concurrent algorithms for even seemingly simple data types are difficult to implement correctly, especially when considering the relaxed memory ordering models commonly employed by today’s multiprocessors. The formal verification of such implementations is challenging as well because the high degree of concurrency leads to a large number of possible executions. In this case study, we develop a SAT-based bounded verification method and apply it to a representative example, a well-known two-lock concurrent queue algorithm. We first formulate a correctness criterion that specifically targets failures caused by concurrency; it demands that all concurrent executions be observationally equivalent to some serial execution. Next, we define a relaxed memory model that conservatively approximates several common shared-memory multiprocessors. Using commit point specifications, a suite of finite symbolic tests, a prototype encoder, and a standard SAT solver, we successfully identify two failures of a naive implementation that can be observed only under relaxed memory models. We eliminate these failures by inserting appropriate memory ordering fences into the code. The experiments confirm that our approach provides a valuable aid for desigining and implementing concurrent data types

Analysis of Globule Types in Malignant Melanoma

Objective: To identify and analyze subtypes of globules based on size, shape, network connectedness, pigmentation, and distribution to determine which globule types and globule distributions are most frequently associated with a diagnosis of malignant melanoma. Design: Retrospective case series of dermoscopy images with globules. Setting: Private dermatology practices. Participants: Patients in dermatology practices. Intervention: Observation only. Main Outcome Measure: Association of globule types with malignant melanoma. Results: The presence of large globules (odds ratio [OR], 5.25) and globules varying in size (4.72) or shape (5.37) had the highest ORs for malignant melanoma among all globule types and combinations studied. Classical globules (dark, discrete, convex, and 0.10-0.20 mm) had a higher risk (OR, 4.20) than irregularly shaped globules (dark, discrete, and not generally convex) (2.89). Globules connected to other structures were not significant in the diagnosis of malignant melanoma. Of the different configurations studied, asymmetric clusters have the highest risk (OR, 3.02). Conclusions: The presence of globules of varying size or shape seems to be more associated with a diagnosis of malignant melanoma than any other globule type or distribution in this study. Large globules are of particular importance in the diagnosis of malignant melanoma