Proteomic expression profiling of thyroid neoplasms

Thyroid cancer is the most common endocrine neoplasm with multiple histologic subtypes, each associated with different treatments and outcomes. Differentiating benign neoplasms such as follicular adenomas from malignant entities such as follicular carcinomas and papillary carcinoma can be challenging. To define the proteomic profile of different thyroid tumors, we screened an antibody array of 330 features against five thyroid neoplasms: follicular adenoma, follicular carcinoma, papillary carcinoma, anaplastic carcinoma, and medullary carcinoma as well as normal thyroid epithelium. Eight candidate biomarkers; c-erbB-2, Stat5a, Annexin IV, IL-11, RARα, FGF7, Caspase 9, and phospho-c-myc were identified as differentially expressed on the antibody array, and validated with immunohistochemistry on tissue microarrays, with a total of 144 samples of the same variety of thyroid neoplasms. Analysis revealed c-erbB-2, Annexin IV, and Stat5a have potential clinical utility to differentiate follicular adenoma, follicular carcinoma, and papillary carcinoma from each other. By using an antibody array as a discovery platform and a tissue microarray as a first step in validation on a large number of specimens, we have identified new markers that have potential utility in the diagnosis of thyroid neoplasms.     

Probabilistic fusion of stereo with color and contrast for bilayer segmentation

This paper describes models and algorithms for the real-time segmentation of foreground from background layers in stereo video sequences. Automatic separation of layers from color/contrast or from stereo alone is known to be error-prone. Here, color, contrast, and stereo matching information are fused to infer layers accurately and efficiently. The first algorithm, layered dynamic programming (LDP), solves stereo in an extended six-state space that represents both foreground/background layers and occluded regions. The stereo-match likelihood is then fused with a contrast-sensitive color model that is learned on-the-fly and stereo disparities are obtained by dynamic programming. The second algorithm, layered graph cut (LGC), does not directly solve stereo. Instead, the stereo match likelihood is marginalized over disparities to evaluate foreground and background hypotheses and then fused with a contrast-sensitive color model like the one used in LDP. Segmentation is solved efficiently by ternary graph cut. Both algorithms are evaluated with respect to ground truth data and found to have similar performance, substantially better than either stereo or color/contrast alone. However, their characteristics with respect to computational efficiency are rather different. The algorithms are demonstrated in the application of background substitution and shown to give good quality composite video output.     

Simple Algorithm for Partial Quantum Search

Quite often in database search, we only need to extract portion of the information about the satisfying item. We consider this problem in the following form: the database of N items is separated into K blocks of size b = N / K elements each and an algorithm has just to find the block containing the item of interest. The queries are exactly the same as in the standard database search problem. We present a quantum algorithm for this problem of partial search that takes about 0.34 fewer iterations than the quantum search algorithm.     

Ion-cyclotron resonance study of elementary stages of the catalytic oxidation of CO by N2O in the presence of VIA-group metal ions

Gas phase reactions of Mo⁺ and W⁺ ions with the molecules of various oxidants (NO, O₂, N₂O, CH₂O, C₂H₄O) were studied using ion cyclotron resonance. In oxidation with N₂O the mono-, di- and trioxide metal cations are formed consecutively. The trioxide MO₃ ⁺ ions of both metals react with CO to form CO₂ and MO₂ ⁺ ions. In this way, catalytic reaction N₂O + CO N₂ + CO₂ occurs in the gas phase with MoO₃ ⁺ /MoO₂ ⁺ and WO₃ ⁺/WO₂ ⁺ couples as catalysts. The rate constants have been measured for both stages of the catalytic cycle as well as for the stages of the catalyst preparation. Metal-oxygen bond energies were estimated for MoO_x ⁺ and WO_x ⁺ species with various x. The mechanism of CO oxidation with MoO_x ⁺ and WO_x ⁺ cations as catalysts in the gas phase is discussed in comparison with that for the oxidation over classical solid oxide catalysts.     

On the self-erasing nature of errors of prediction.

82 female undergraduates were assigned to 1 of 4 experimental groups—predict-request, information-request, predict only, and request only—in which requested tasks involved writing a counterattitudinal essay or singing over the telephone. In 3 experiments, Ss overpredicted the degree to which their behavior would be socially desirable and these errors of prediction proved to be self-erasing. Having mispredicted a given behavior, Ss were likely to have these predictions confirmed in later behavior, indicating that prediction of a behavioral sequence evokes a specific cognitive representation of that sequence which is subsequently accessed. Results demonstrate the strong effects on behavior of engaging in prebehavioral cognitive work. (27 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Water productivity and water footprint: misguided concepts or useful tools in water management and policy?

Water productivity (WP) and water footprint (WFP) are popular concepts in research and discourses on water management. Yet there are concerns about their theoretical validity and practical value. This paper shows that the water production function, the concept with a sound theoretical foundation, is the basis for WP. Total WFP is the reciprocal of WP. The practical value of WP and WFP depends on the context of water use and stress. Maximizing WP, not a panacea to all water problems, mainly suits arid rainfed areas. In other regions, economic and marginal WP for increasing overall production should take precedence in water management and policy decisions.     

Probabilistic resource allocation in heterogeneous distributed systems with random failures

The problem of finding efficient workload distribution techniques is becoming increasingly important today for heterogeneous distributed systems where the availability of compute nodes may change spontaneously over time. Resource-allocation policies designed for such systems should maximize the performance and, at the same time, be robust against failure and recovery of compute nodes. Such a policy, based on the concepts of the Derman–Lieberman–Ross theorem, is proposed in this work, and is applied to a simulated model of a dedicated system composed of a set of heterogeneous image processing servers. Assuming that each image results in a “reward” if its processing is completed before a certain deadline, the goal for the resource allocation policy is to maximize the expected cumulative reward. An extensive analysis was done to study the performance of the proposed policy and compare it with the performance of some existing policies adapted to this environment. Our experiments conducted for various types of task-machine heterogeneity illustrate the potential of our method for solving resource allocation problems in a broad spectrum of distributed systems that experience high failure rates.     

Incompetence and impact of training in bimatrix games

The concept of games with incompetence has been introduced to better represent games where players may not be capable of executing strategies that they select. In particular this paper introduces incompetence into bimatrix games and investigates the properties of such games. The results obtained describe both the general dependence of “extreme Nash equilibrium payoffs” on incompetence and special behaviour arising in particular cases. The dependence of the payoffs can be complex and include non-linearities and transition points. Transition points occur when kernels change and may result in the number of “extreme Nash equilibria” changing. Understanding these changes allows the determination of the benefits of regimes that seek to decrease a player’s incompetence. While the games we consider are normally static, in our context there is a hidden dynamics resulting from the fact that players will strive to improve their equilibrium payoffs by changing their incompetence levels. This might require training, in the case of games like tennis, or it might require the purchase of new equipment costing billions of dollars, in the case of military applications.