Classification of human astrocytic gliomas on the basis of gene expression: a correlated group of genes with angiogenic activity emerges as a strong predictor of subtypes.

The development of targeted treatment strategies adapted to individual patients requires identification of the different tumor classes according to their biology and prognosis. We focus here on the molecular aspects underlying these differences, in terms of sets of genes that control pathogenesis of the different subtypes of astrocytic glioma. By performing cDNA-array analysis of 53 patient biopsies, comprising low-grade astrocytoma, secondary glioblastoma (respective recurrent high-grade tumors), and newly diagnosed primary glioblastoma, we demonstrate that human gliomas can be differentiated according to their gene expression. We found that low-grade astrocytoma have the most specific and similar expression profiles, whereas primary glioblastoma exhibit much larger variation between tumors. Secondary glioblastoma display features of both other groups. We identified several sets of genes with relatively highly correlated expression within groups that: (a). can be associated with specific biological functions; and (b). effectively differentiate tumor class. One prominent gene cluster discriminating primary versus nonprimary glioblastoma comprises mostly genes involved in angiogenesis, including VEGF fms-related tyrosine kinase 1 but also IGFBP2, that has not yet been directly linked to angiogenesis. In situ hybridization demonstrating coexpression of IGFBP2 and VEGF in pseudopalisading cells surrounding tumor necrosis provided further evidence for a possible involvement of IGFBP2 in angiogenesis. The separating groups of genes were found by the unsupervised coupled two-way clustering method, and their classification power was validated by a supervised construction of a nearly perfect glioma classifier.

The neurobiological basis of prefrontal cortex impairment in the phencyclidine model of schizophrenia : convergent reduction of synaptic glutamate release, energy metabolism and cognitive performance

RÉSUMÉ : Le traitement répété à la phencyclidine (PCP), un bloqueur du récepteur NMDA (NMDAR), reproduit chez les rongeurs une partie de la symptomatologie typique de la schizophrénie. Le blocage prolongé du NMDAR par la PCP mime une hypofunction du NMDAR, une des principales altérations supposées exister dans les cerveaux des patients schizophréniques. Le but de notre étude était d'examiner les conséquences neurochimiques, métaboliques et fonctionnelles du traitement répété à la phencyclidine in vivo, au niveau du cortex préfrontal (cpf), une région cérébrale qui joue un rôle dans les déficits cognitifs observés chez les patients schizophréniques. Pour répondre à cette question, les rats ou les souris ont reçu chaque jour une injection soit de PCP (5 mg/kg), soit de solution saline, pendant 7 ou 14 jours. Les animaux ont ensuite été sacrifiés au moins 24 heures après le dernier traitement. Des tranches aiguës du cpf ont été préparées rapidement, puis stimulées avec une concentration élevée de KCI, de manière à induire une libération de glutamate à partir des terminaisons synaptiques excitatrices. Les résultats montrent que les tranches du cpf des animaux traités à la PCP ont libéré une quantité de glutamate significativement inférieure par rapport à celles des animaux contrôle. Ce déficit de libération a persisté 72 heures après la fin du traitement, tandis qu'il n'était pas observé dans le cortex visuel primaire, une autre région corticale. En outre, le traitement avec des antipsychotiques, l'halopéridol ou l'olanzapine, a supprimé le déficit induit par la PCP. Le même déficit de libération a été remarqué sur des synaptosomes obtenus à partir du cpf des animaux traités à la phenryclidine. Cette observation indique que la PCP induit une modification plastique adaptative du mécanisme qui contrôle la libération du glutamate dans les terminaisons synaptiques. Nous avons découvert que cette modification implique la sous-régulation d'un NMDAR présynaptique, qui serait doué d'un rôle d'autorécepteur stimulateur de la libération du glutamate. Grâce à des tests comportementaux conduits en parallèle et réalisés pour évaluer la fonctionnalité du cpf, nous avons observé chez les souris traitées à la PCP une flexibilité comportementale réduite lors d'un test de discrimination de stimuli visuels/tactiles. Le déficit cognitif était encore présent 4 jours après la dernière administration de PCP. La technique de l'autoradiographie quantitative du [14C]2-deoxyglucose a permis d'associer ce déficit à une réduction de l'activité métabolique cérébrale pendant le déroulement du test, particulièrement au niveau du cpf. Dans l'ensemble, nos résultats suggèrent que le blocage prolongé du NMDAR lors de l'administration répétée de PCP produit un déficit de libération du glutamate au niveau des terminaisons synaptiques excitatrices du cpf. Un tel déficit pourrait être provoqué par la sousrégulation d'un NMDAR présynaptique, qui aurait une fonction de stimulateur de libération; la transmission excitatrice du cpf s'en trouverait dans ce cas réduite. Ce résultat est en ligne avec l'activité métabolique et fonctionnelle réduite du cpf et l'observation de déficits cognitifs induits lors de l'administration de la PCP. ABSTRACT : Sub-chronic treatment with phencyclidine (PCP), an NMDA receptor (NMDAR) channel blocker, reproduces in rodents part of the symptomatology associated to schizophrenia in humans. Prolonged pharmacological blockade of NMDAR with PCP mimics NMDAR hypofunction, one of the main alterations thought to take place in the brains of schizophrenics. Our study was aimed at investigating the neurochemical, metabolic and behavioral consequences of repeated PCP administration in vivo, focusing on the functioning of the prefrontal cortex (pfc), a brain region highly relevant for the cognitive deficits observed in schizophrenic patients. Rats or mice received a daily administration of either PCP (5 mg/kg) or saline for 7 or 14 days. At least 24 hours after the last treatment the animals were sacrificed. Acute slices of the pfc were quickly prepared and challenged with high KCl to induce synaptic glutamate release. Pfc slices from PCP-treated animals released significantly less glutamate than slices from salinetreated animals. The deficit persisted 72 hours after the end of the treatment, while it was not observed in another cortical region: the primary visual cortex. Interestingly, treatment with antipsychotic drugs, either haloperidol or olanzapine, reverted the glutamate release defect induced by PCP treatment. The same release defect was observed in synaptosomes prepared from the pfc of PCP-treated animals, indicating that PCP induces a plastic adaptive change in the mechanism controlling glutamate release in the glutamatergic terminals. We discovered that such change most likely involves the down-regulation of a newly identified, pre-synaptic NMDAR with stimulatory auto-receptor function on glutamate release. In parallel sets of behavioral experiments challenging pfc function, mice sub-chronically treated with PCP displayed reduced behavioral flexibility (reversal learning) in a visual/tactile-cued discrimination task. The cognitive deficit was still evident 4 days after the last PCP administration and was associated to reduced brain metabolic activity during the performance of the behavioral task, notably in the pfc, as determined by [14C]2-deoxyglucose quantitative autoradiography. Clverall, our findings suggest that prolonged NMDAR blockade by repeated PCP administration results in a defect of glutamate release from excitatory afferents in the pfc, possibly ascribed to down-regulation of apre-synaptic stimulatory NMDAR. Deficient excitatory neurotransmission in the pfc is consistent with the reduced metabolic and functional activation of this area and the observed PCP-induced cognitive deficits.

Proximate basis of the covariation between a melanin-based female ornament and offspring quality.

In contradiction to sexual selection theory, several studies showed that although the expression of melanin-based ornaments is usually under strong genetic control and weakly sensitive to the environment and body condition, they can signal individual quality. Covariation between a melanin-based ornament and phenotypic quality may result from pleiotropic effects of genes involved in the production of melanin pigments. Two categories of genes responsible for variation in melanin production may be relevant, namely those that trigger melanin production (yes or no response) and those that determine the amount of pigments produced. To investigate which of these two hypotheses is the most likely, I reanalysed data collected from barn owls ( Tyto alba). The underparts of this bird vary from immaculate to heavily marked with black spots of varying size. Published cross-fostering experiments have shown that the proportion of the plumage surface covered with black spots, a eumelanin composite trait so-called "plumage spottiness", in females positively covaries with offspring humoral immunocompetence, and negatively with offspring parasite resistance (i.show $132#e. the ability to reduce fecundity of ectoparasites) and fluctuating asymmetry of wing feathers. However, it is unclear which component of plumage spottiness causes these relationships, namely genes responsible for variation in number of spots or in spot diameter. Number of spots reflects variation in the expression of genes triggering the switch from no eumelanin production to production, whereas spot diameter reflects variation in the expression of genes determining the amount of eumelanin produced per spot. In the present study, multiple regression analyses, performed on the same data sets, showed that humoral immunocompetence, parasite resistance and wing fluctuating asymmetry of cross-fostered offspring covary with spot diameter measured in their genetic mother, but not with number of spots. This suggests that genes responsible for variation in the quantity of eumelanin produced per spot are responsible for covariation between a melanin ornament and individual attributes. In contrast, genes responsible for variation in number of black spots may not play a significant role. Covariation between a eumelanin female trait and offspring quality may therefore be due to an indirect effect of melanin production.

Towards the identification of a genetic basis for Landau-Kleffner syndrome.

OBJECTIVE: To establish the genetic basis of Landau-Kleffner syndrome (LKS) in a cohort of two discordant monozygotic (MZ) twin pairs and 11 isolated cases. METHODS: We used a multifaceted approach to identify genetic risk factors for LKS. Array comparative genomic hybridization (CGH) was performed using the Agilent 180K array. Whole genome methylation profiling was undertaken in the two discordant twin pairs, three isolated LKS cases, and 12 control samples using the Illumina 27K array. Exome sequencing was undertaken in 13 patients with LKS including two sets of discordant MZ twins. Data were analyzed with respect to novel and rare variants, overlapping genes, variants in reported epilepsy genes, and pathway enrichment. RESULTS: A variant (cG1553A) was found in a single patient in the GRIN2A gene, causing an arginine to histidine change at site 518, a predicted glutamate binding site. Following copy number variation (CNV), methylation, and exome sequencing analysis, no single candidate gene was identified to cause LKS in the remaining cohort. However, a number of interesting additional candidate variants were identified including variants in RELN, BSN, EPHB2, and NID2. SIGNIFICANCE: A single mutation was identified in the GRIN2A gene. This study has identified a number of additional candidate genes including RELN, BSN, EPHB2, and NID2. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.

Knapsack sets for cryptography

The basic goal of this study is to extend old and propose new ways to generate knapsack sets suitable for use in public key cryptography. The knapsack problem and its cryptographic use are reviewed in the introductory chapter. Terminology is based on common cryptographic vocabulary. For example, solving the knapsack problem (which is here a subset sum problem) is termed decipherment. Chapter 1 also reviews the most famous knapsack cryptosystem, the Merkle Hellman system. It is based on a superincreasing knapsack and uses modular multiplication as a trapdoor transformation. The insecurity caused by these two properties exemplifies the two general categories of attacks against knapsack systems. These categories provide the motivation for Chapters 2 and 4. Chapter 2 discusses the density of a knapsack and the dangers of having a low density. Chapter 3 interrupts for a while the more abstract treatment by showing examples of small injective knapsacks and extrapolating conjectures on some characteristics of knapsacks of larger size, especially their density and number. The most common trapdoor technique, modular multiplication, is likely to cause insecurity, but as argued in Chapter 4, it is difficult to find any other simple trapdoor techniques. This discussion also provides a basis for the introduction of various categories of non injectivity in Chapter 5. Besides general ideas of non injectivity of knapsack systems, Chapter 5 introduces and evaluates several ways to construct such systems, most notably the "exceptional blocks" in superincreasing knapsacks and the usage of "too small" a modulus in the modular multiplication as a trapdoor technique. The author believes that non injectivity is the most promising direction for development of knapsack cryptosystema. Chapter 6 modifies two well known knapsack schemes, the Merkle Hellman multiplicative trapdoor knapsack and the Graham Shamir knapsack. The main interest is in aspects other than non injectivity, although that is also exploited. In the end of the chapter, constructions proposed by Desmedt et. al. are presented to serve as a comparison for the developments of the subsequent three chapters. Chapter 7 provides a general framework for the iterative construction of injective knapsacks from smaller knapsacks, together with a simple example, the "three elements" system. In Chapters 8 and 9 the general framework is put into practice in two different ways. Modularly injective small knapsacks are used in Chapter 9 to construct a large knapsack, which is called the congruential knapsack. The addends of a subset sum can be found by decrementing the sum iteratively by using each of the small knapsacks and their moduli in turn. The construction is also generalized to the non injective case, which can lead to especially good results in the density, without complicating the deciphering process too much. Chapter 9 presents three related ways to realize the general framework of Chapter 7. The main idea is to join iteratively small knapsacks, each element of which would satisfy the superincreasing condition. As a whole, none of these systems need become superincreasing, though the development of density is not better than that. The new knapsack systems are injective but they can be deciphered with the same searching method as the non injective knapsacks with the "exceptional blocks" in Chapter 5. The final Chapter 10 first reviews the Chor Rivest knapsack system, which has withstood all cryptanalytic attacks. A couple of modifications to the use of this system are presented in order to further increase the security or make the construction easier. The latter goal is attempted by reducing the size of the Chor Rivest knapsack embedded in the modified system. '

Selection of patients for myocardial perfusion scintigraphy based on fuzzy sets theory applied to clinical-epidemiological data and treadmill test results

Coronary artery disease (CAD) is a worldwide leading cause of death. The standard method for evaluating critical partial occlusions is coronary arteriography, a catheterization technique which is invasive, time consuming, and costly. There are noninvasive approaches for the early detection of CAD. The basis for the noninvasive diagnosis of CAD has been laid in a sequential analysis of the risk factors, and the results of the treadmill test and myocardial perfusion scintigraphy (MPS). Many investigators have demonstrated that the diagnostic applications of MPS are appropriate for patients who have an intermediate likelihood of disease. Although this information is useful, it is only partially utilized in clinical practice due to the difficulty to properly classify the patients. Since the seminal work of Lotfi Zadeh, fuzzy logic has been applied in numerous areas. In the present study, we proposed and tested a model to select patients for MPS based on fuzzy sets theory. A group of 1053 patients was used to develop the model and another group of 1045 patients was used to test it. Receiver operating characteristic curves were used to compare the performance of the fuzzy model against expert physician opinions, and showed that the performance of the fuzzy model was equal or superior to that of the physicians. Therefore, we conclude that the fuzzy model could be a useful tool to assist the general practitioner in the selection of patients for MPS.

Microbial perchlorate reduction: A precise laboratory determination of the chlorine isotope fractionation and its possible biochemical basis

Perchlorate-reducing bacteria fractionate chlorine stable isotopes giving a powerful approach to monitor the extent of microbial consumption of perchlorate in contaminated sites undergoing remediation or natural perchlorate containing sites. This study reports the full experimental data and methodology used to re-evaluate the chlorine isotope fractionation of perchlorate reduction in duplicate culture experiments of Azospira suillum strain PS at 37 degrees C (Delta Cl-37(Cr)--ClO4-) previously reported, without a supporting data set by Coleman et al. [Coleman, M.L., Ader, M., Chaudhuri, S., Coates,J.D., 2003. Microbial Isotopic Fractionation of Perchlorate Chlorine. Appl. Environ. Microbiol. 69, 4997-5000] in a reconnaissance study, with the goal of increasing the accuracy and precision of the isotopic fractionation determination. The method fully described here for the first time, allows the determination of a higher precision Delta Cl-37(Cl)--ClO4- value, either from accumulated chloride content and isotopic composition or from the residual perchlorate content and isotopic composition. The result sets agree perfectly, within error, giving average Delta Cl-37(Cl)--ClO4- = -14.94 +/- 0.15%omicron. Complementary use of chloride and perchlorate data allowed the identification and rejection of poor quality data by applying mass and isotopic balance checks. This precise Delta Cl-37(Cl)--ClO4-, value can serve as a reference point for comparison with future in situ or microcosm studies but we also note its similarity to the theoretical equilibrium isotopic fractionation between a hypothetical chlorine species of redox state +6 and perchlorate at 37 degrees C and suggest that the first electron transfer during perchlorate reduction may occur at isotopic equilibrium between art enzyme-bound chlorine and perchlorate. (C) 2008 Elsevier B.V. All rights reserved.

Vibrational energy levels for the electronic ground state of the diazocarbene (CNN) molecule

The vibrational energy levels of diazocarbene (diazomethylene) in its electronic ground state, (X) over tilde (3) Sigma(-) CNN, have been predicted using the variational method. The potential energy surfaces of (X) over tilde (3) A" CNN were determined by employing ab initio single reference coupled cluster with single and double excitations (CCSD), CCSD with perturbative triple excitations [CCSD(T)], multi-reference complete active space self-consistent-field (CASSCF), and internally contracted multi-reference configuration interaction (ICMRCI) methods. The correlation-consistent polarised valence quadruple zeta (cc-pVQZ) basis set was used. Four sets of vibrational energy levels determined from the four distinct analytical potential functions have been compared with the experimental values from the laser-induced fluorescence measurements of Wurfel et al. obtained in 1992. The CCSD, CCSD(T), and CASSCF potentials have not provided satisfactory agreement with the experimental observations. In this light, the importance of both non-dynamic (static) and dynamic correlation effects in describing the ground state of CNN is emphasised. Our best theoretical fundamental frequencies at the cc-pVQZ ICMRCI level of theory, v(1) = 1230, v(2) = 394, and v(3) = 1420 cm(-1) are in excellent agreement with the experimental values of v(1) = 1235, v(2) = 396, and v(3) = 1419cm(-1) and the mean absolute deviation between the 23 calculated and experimental vibrational energy levels is only 7.4 cm(-1). It is shown that the previously suggested observation of the v(3) frequency at about 2847cm(-1) was in fact the first overtone 2v(3).

Nonlinear system identification using particle swarm optimisation tuned radial basis function models

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.

On combination of SMOTE and particle swarm optimization based radial basis function classifier for imbalanced problems

The combination of the synthetic minority oversampling technique (SMOTE) and the radial basis function (RBF) classifier is proposed to deal with classification for imbalanced two-class data. In order to enhance the significance of the small and specific region belonging to the positive class in the decision region, the SMOTE is applied to generate synthetic instances for the positive class to balance the training data set. Based on the over-sampled training data, the RBF classifier is constructed by applying the orthogonal forward selection procedure, in which the classifier structure and the parameters of RBF kernels are determined using a particle swarm optimization algorithm based on the criterion of minimizing the leave-one-out misclassification rate. The experimental results on both simulated and real imbalanced data sets are presented to demonstrate the effectiveness of our proposed algorithm.

Inferring the biggest and best: a measurement model for applying recognition to evoke consideration sets and judge between multiple alternatives

It has long been supposed that preference judgments between sets of to-be-considered possibilities are made by means of initially winnowing down the most promising-looking alternatives to form smaller “consideration sets” (Howard, 1963; Wright & Barbour, 1977). In preference choices with >2 options, it is standard to assume that a “consideration set”, based upon some simple criterion, is established to reduce the options available. Inferential judgments, in contrast, have more frequently been investigated in situations in which only two possibilities need to be considered (e.g., which of these two cities is the larger?) Proponents of the “fast and frugal” approach to decision-making suggest that such judgments are also made on the basis of limited, simple criteria. For example, if only one of two cities is recognized and the task is to judge which city has the larger population, the recognition heuristic states that the recognized city should be selected. A multinomial processing tree model is outlined which provides the basis for estimating the extent to which recognition is used as a criterion in establishing a consideration set for inferential judgments between three possible options.

A radial basis function network classifier to maximise leave-one-out mutual information

tWe develop an orthogonal forward selection (OFS) approach to construct radial basis function (RBF)network classifiers for two-class problems. Our approach integrates several concepts in probabilisticmodelling, including cross validation, mutual information and Bayesian hyperparameter fitting. At eachstage of the OFS procedure, one model term is selected by maximising the leave-one-out mutual infor-mation (LOOMI) between the classifier’s predicted class labels and the true class labels. We derive theformula of LOOMI within the OFS framework so that the LOOMI can be evaluated efficiently for modelterm selection. Furthermore, a Bayesian procedure of hyperparameter fitting is also integrated into theeach stage of the OFS to infer the l2-norm based local regularisation parameter from the data. Since eachforward stage is effectively fitting of a one-variable model, this task is very fast. The classifier construc-tion procedure is automatically terminated without the need of using additional stopping criterion toyield very sparse RBF classifiers with excellent classification generalisation performance, which is par-ticular useful for the noisy data sets with highly overlapping class distribution. A number of benchmarkexamples are employed to demonstrate the effectiveness of our proposed approach.

Transreal arithmetic as a consistent basis for paraconsistent logics

Paraconsistent logics are non-classical logics which allow non-trivial and consistent reasoning about inconsistent axioms. They have been pro- posed as a formal basis for handling inconsistent data, as commonly arise in human enterprises, and as methods for fuzzy reasoning, with applica- tions in Artificial Intelligence and the control of complex systems. Formalisations of paraconsistent logics usually require heroic mathe- matical efforts to provide a consistent axiomatisation of an inconsistent system. Here we use transreal arithmetic, which is known to be consis- tent, to arithmetise a paraconsistent logic. This is theoretically simple and should lead to efficient computer implementations. We introduce the metalogical principle of monotonicity which is a very simple way of making logics paraconsistent. Our logic has dialetheaic truth values which are both False and True. It allows contradictory propositions, allows variable contradictions, but blocks literal contradictions. Thus literal reasoning, in this logic, forms an on-the- y, syntactic partition of the propositions into internally consistent sets. We show how the set of all paraconsistent, possible worlds can be represented in a transreal space. During the development of our logic we discuss how other paraconsistent logics could be arithmetised in transreal arithmetic.

The statistical downscaling model-decision centric (SDSM-DC): conceptual basis and applications

Regional climate downscaling has arrived at an important juncture. Some in the research community favour continued refinement and evaluation of downscaling techniques within a broader framework of uncertainty characterisation and reduction. Others are calling for smarter use of downscaling tools, accepting that conventional, scenario-led strategies for adaptation planning have limited utility in practice. This paper sets out the rationale and new functionality of the Decision Centric (DC) version of the Statistical DownScaling Model (SDSM-DC). This tool enables synthesis of plausible daily weather series, exotic variables (such as tidal surge), and climate change scenarios guided, not determined, by climate model output. Two worked examples are presented. The first shows how SDSM-DC can be used to reconstruct and in-fill missing records based on calibrated predictor-predictand relationships. Daily temperature and precipitation series from sites in Africa, Asia and North America are deliberately degraded to show that SDSM-DC can reconstitute lost data. The second demonstrates the application of the new scenario generator for stress testing a specific adaptation decision. SDSM-DC is used to generate daily precipitation scenarios to simulate winter flooding in the Boyne catchment, Ireland. This sensitivity analysis reveals the conditions under which existing precautionary allowances for climate change might be insufficient. We conclude by discussing the wider implications of the proposed approach and research opportunities presented by the new tool.

Optimization of Radial Basis Function neural network employed for prediction of surface roughness in hard turning process using Taguchi's orthogonal arrays

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)