Microarray expression profiling in melanoma reveals a BRAF mutation signature

We have used microarray gene expression pro. ling and machine learning to predict the presence of BRAF mutations in a panel of 61 melanoma cell lines. The BRAF gene was found to be mutated in 42 samples (69%) and intragenic mutations of the NRAS gene were detected in seven samples (11%). No cell line carried mutations of both genes. Using support vector machines, we have built a classifier that differentiates between melanoma cell lines based on BRAF mutation status. As few as 83 genes are able to discriminate between BRAF mutant and BRAF wild-type samples with clear separation observed using hierarchical clustering. Multidimensional scaling was used to visualize the relationship between a BRAF mutation signature and that of a generalized mitogen-activated protein kinase ( MAPK) activation ( either BRAF or NRAS mutation) in the context of the discriminating gene list. We observed that samples carrying NRAS mutations lie somewhere between those with or without BRAF mutations. These observations suggest that there are gene-specific mutation signals in addition to a common MAPK activation that result from the pleiotropic effects of either BRAF or NRAS on other signaling pathways, leading to measurably different transcriptional changes.

Population inversion of a driven two-level system in a structureless bath

We derive a master equation for a driven double quantum dot damped by an unstructured phonon bath, and calculate the spectral density. We find that bath-mediated photon absorption is important at relatively strong driving, and may even dominate the dynamics, inducing population inversion of the double-dot system. This phenomenon is consistent with recent experimental observations.

Chloride as a signature indicator of soil textural and hydrologic stratigraphies in variable charge deep profiles

Soil properties that influence water movement through profiles are important for determining flow paths, reactions between soil and solute, and the ultimate destination of solutes. This is particularly important in high rainfall environments. For highly weathered deep profiles, we hypothesize that abrupt changes in the distribution of the quotient [QT = (silt + sand)/clay] reflect the boundaries between textural units or textural (TS) and hydrologic (HS) stratigraphies. As a result, QT can be used as a parameter to characterize TS and as a surrogate for HS. Secondly, we propose that if chloride distributions were correlated with QT, under non-limiting anion exchange, then chloride distributions can be used as a signature indicator of TS and HS. Soil cores to a depth of 12.5 in were taken from 16 locations in the wet tropical Johnstone River catchment of northeast Queensland, Australia. The cores belong to nine variable charge soil types and were under sugarcane (Saccharun officinarum-S) production, which included the use of potassium chloride, for several decades. The cores were segmented at I m depth increments and subsamples were analysed for chloride, pH, soil water content (theta), clay, silt and sand contents. Selected bores were capped to serve as piezometers to monitor groundwater dynamics. Depth incremented QT, theta and chloride correlated, each individually, significantly with the corresponding profile depth increments, indicating the presence of textural, hydrologic and chloride gradients in profiles. However, rapid increases in QT down the profile indicated abrupt changes in TS, suggesting that QT can be used as a parameter to characterize TS and as a surrogate for HS. Abrupt changes in chloride distributions were similar to QT, suggesting that chloride distributions can be used as a signature indicator of QT (TS) and HS. Groundwater data indicated that chloride distributions depended, at least partially, on groundwater dynamics, providing further support to our hypothesis that chloride distribution can be used as a signature indicator of HS. Copyright (c) 2005 John Wiley & Sons, Ltd.

Unidirectional inversion of ibuprofen in Caco-2 cells: Developing a suitable model for presystemic chiral inversion study

Intestinal chiral inversion of ibuprofen is still lacking direct evidence. In a preliminary experiment, ibuprofen was found to undergo inversion in Caco-2 cells. This investigation was thus conducted to determine the characteristics and influence of some biochemical factors on the chiral inversion of ibuprofen in Caco-2 cells. The effects of substrate concentration (2.5-40 mu g/ml), cell density (0.5-2 x 10(6) cells/ well), content of serum (0-20%), coexistence of S ibuprofen (corresponding doses), sodium azide (10mm), exogenous Coenzyme A (CoA) (0.1 - 0.4 mm),. and palmitic acid (5-25 mu m) on inversion were examined. A stereoselective HPLC method based on the Chromasil-CHI-TBB column was developed for quantitative analysis of the drug in cell culture medium. The inversion ratio (F-i) and elimination rate constant were calculated as the indexes of inversion extent. Inversion of ibuprofen in Caeo-2 cells was found to be both dose and cell density dependent, indicating saturable characteristics. Addition of serum significantly inhibited the inversion, to an extent of 2.7 fold decrease at 20% content. Preexistence of S enantiomer exerted a significant inhibitory effect (p < 0.01 for all tests). Sodium azide decreased the inversion ratio from 0.43 to 0.32 (p < 0.01). Exogenous CoA and palmitic acid significantly promoted the inversion at all tested doses (p < 0.01 for all tests). This research provided strong evidence to the capacity and capability of intestinal chiral inversion. Although long incubation times up to 120 h were required, Caco-2 cells should be a suitable model for chiral inversion research of 2-APAs considering the human-resourced and well-defined characteristics from the present study.

Off-line signature verification and forgery detection using fuzzy modeling

Automatic signature verification is a well-established and an active area of research with numerous applications such as bank check verification, ATM access, etc. This paper proposes a novel approach to the problem of automatic off-line signature verification and forgery detection. The proposed approach is based on fuzzy modeling that employs the Takagi-Sugeno (TS) model. Signature verification and forgery detection are carried out using angle features extracted from box approach. Each feature corresponds to a fuzzy set. The features are fuzzified by an exponential membership function involved in the TS model, which is modified to include structural parameters. The structural parameters are devised to take account of possible variations due to handwriting styles and to reflect moods. The membership functions constitute weights in the TS model. The optimization of the output of the TS model with respect to the structural parameters yields the solution for the parameters. We have also derived two TS models by considering a rule for each input feature in the first formulation (Multiple rules) and by considering a single rule for all input features in the second formulation. In this work, we have found that TS model with multiple rules is better than TS model with single rule for detecting three types of forgeries; random, skilled and unskilled from a large database of sample signatures in addition to verifying genuine signatures. We have also devised three approaches, viz., an innovative approach and two intuitive approaches using the TS model with multiple rules for improved performance. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Matching commercial clips from TV streams using a unique, robust and compact signature

One of critical challenges in automatic recognition of TV commercials is to generate a unique, robust and compact signature. Uniqueness indicates the ability to identify the similarity among the commercial video clips which may have slight content variation. Robustness means the ability to match commercial video clips containing the same content but probably with different digitalization/encoding, some noise data, and/or transmission and recording distortion. Efficiency is about the capability of effectively matching commercial video sequences with a low computation cost and storage overhead. In this paper, we present a binary signature based method, which meets all the three criteria above, by combining the techniques of ordinal and color measurements. Experimental results on a real large commercial video database show that our novel approach delivers a significantly better performance comparing to the existing methods.

Off-line signature verification and forgery detection system based on fuzzy modeling

This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (α) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system.