Risk-taking in disorders of natural and drug rewards: neural correlates and effects of probability, valence, and magnitude.

Pathological behaviors toward drugs and food rewards have underlying commonalities. Risk-taking has a fourfold pattern varying as a function of probability and valence leading to the nonlinearity of probability weighting with overweighting of small probabilities and underweighting of large probabilities. Here we assess these influences on risk-taking in patients with pathological behaviors toward drug and food rewards and examine structural neural correlates of nonlinearity of probability weighting in healthy volunteers. In the anticipation of rewards, subjects with binge eating disorder show greater risk-taking, similar to substance-use disorders. Methamphetamine-dependent subjects had greater nonlinearity of probability weighting along with impaired subjective discrimination of probability and reward magnitude. Ex-smokers also had lower risk-taking to rewards compared with non-smokers. In the anticipation of losses, obesity without binge eating had a similar pattern to other substance-use disorders. Obese subjects with binge eating also have impaired discrimination of subjective value similar to that of the methamphetamine-dependent subjects. Nonlinearity of probability weighting was associated with lower gray matter volume in dorsolateral and ventromedial prefrontal cortex and orbitofrontal cortex in healthy volunteers. Our findings support a distinct subtype of binge eating disorder in obesity with similarities in risk-taking in the reward domain to substance use disorders. The results dovetail with the current approach of defining mechanistically based dimensional approaches rather than categorical approaches to psychiatric disorders. The relationship to risk probability and valence may underlie the propensity toward pathological behaviors toward different types of rewards.This is the final version. It was first published by NPG at http://www.nature.com/npp/journal/v40/n4/full/npp2014242a.htm

Object recognition by evolutionary search

The main focus of this thesis has been considering the benefits of using evolutionary based methods for object recognition purposes. The work has tested the hypothesis that evolutionary algorithms can offer solutions to difficult machine vision object recognition problems defined as optimisation problems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

SMAD4 gene promoter mutations in patients with thyroid tumors

As a key component of the transforming growth factor beta (TGFB) pathway, which regulates the expression of thyroid-specific genes, tumor suppressor SMAD4 is crucial for thyroid development and function. Aberrant expression of SMAD4 in thyroid tumor tissue was reported and mutations affecting the coding region have been detected, but a potential role of mutations in SMAD4 gene regulatory regions remains unexplored. The aim of this study was to analyze SMAD4 gene promoters in thyroid tumors. A total of 76 thyroidectomy specimens were studied, including 42 malignant and 34 benign tumors. The presence of mutations in four SMAD4 gene promoters was analyzed in thyroid tumor tissue and peripheral blood by PCR and DNA sequencing. The expression and intracellular localization of endogenous SMAD4 protein in selected tumor samples was studied by immunostaining and confocal microscopy. Of three novel variants detected, two were within promoter A (-204T/C and -5C/T) and one in promoter D (-180delA). Unlike somatic mutations previously detected in the nearby region, germline mutation -180delA in promoter D doesn't appear to affect SMAD4 expression in the thyroid tumor tissue. However, all newly detected SMAD4 promoter variants affect predicted binding sites of transcription factors involved in cell cycle regulation and should be further characterized functionally. Although not directly involved in carcinogenesis, detected variants may alter SMAD4 transcriptional regulation to some extent. Considering that dosage dependence is of great importance for the role of SMAD4 protein as a tumor suppressor, potential clinical significance of SMAD4 gene promoter mutations is worth further investigation

An algorithm for image stitching and blending

In many clinical studies, including those of cancer, it is highly desirable to acquire images of whole tumour sections whilst retaining a microscopic resolution. A usual approach to this is to create a composite image by appropriately overlapping individual images acquired at high magnification under a microscope. A mosaic of these images can be accurately formed by applying image registration, overlap removal and blending techniques. We describe an optimised, automated, fast and reliable method for both image joining and blending. These algorithms can be applied to most types of light microscopy imaging. Examples from histology, from in vivo vascular imaging and from fluorescence applications are shown, both in 2D and 3D. The algorithms are robust to the varying image overlap of a manually moved stage, though examples of composite images acquired both with manually-driven and computer-controlled stages are presented. The overlap-removal algorithm is based on the cross-correlation method; this is used to determine and select the best correlation point between any new image and the previous composite image. A complementary image blending algorithm, based on a gradient method, is used to eliminate sharp intensity changes at the image joins, thus gradually blending one image onto the adjacent ‘composite’. The details of the algorithm to overcome both intensity discrepancies and geometric misalignments between the stitched images will be presented and illustrated with several examples