Clinical correlates of social adjustment in patients with obsessive-compulsive disorder

Background: Patients with obsessive-compulsive disorder (OCD) frequently show poor social adjustment, which has been associated with OCD severity. Little is known about the effects that age at symptom onset, specific OCD symptoms, and psychiatric comorbidities have on social adjustment. The objective of this study was to investigate the clinical correlates of social functioning in OCD patients. Methods: Cross-sectional study involving 815 adults with a primary DSM-IV diagnosis of OCD participating in the Brazilian Research Consortium on Obsessive-Compulsive Spectrum Disorders. Patients were assessed with the Social Adjustment Scale, the Medical Outcomes Study 36-item Short-Form Health Survey, the Yale-Brown Obsessive-Compulsive Scale, the Dimensional Yale-Brown Obsessive-Compulsive Scale, and the Structured Clinical Interview for DSM-IV Axis I Disorders. Clinical correlates of social adjustment were assessed with generalized linear models with gamma distribution. Results: Poor overall social functioning was associated with greater OCD severity (p = 0.02); hoarding symptoms (p = 0.004); sexual/religious obsessions (p = 0.005); current major depressive disorder (p = 0.004); current post-traumatic stress disorder (p = 0.002); and current eating disorders (p = 0.02). Poor social adjustment was also associated with impaired quality of life. Conclusions: Patients with OCD have poor social functioning in domains related to personal relationships and professional performance. Hoarding symptoms and sexual/religious obsessions seem to have the strongest negative effects on social functioning. Early age at OCD symptom onset seems to be associated with professional and academic underachievement and impairment within the family unit, whereas current psychiatric comorbidity worsen overall social functioning. In comparison with quality of life, social adjustment measures seem to provide a more comprehensive overview of the OCD-related burden. (C) 2012 Elsevier Ltd. All rights reserved.

Interferon-gamma alters the phagocytic activity of the mouse trophoblast

Interferon-gamma (IFN-gamma) mediates diverse functions in bone marrow-derived phagocytes, including phagocytosis and microbe destruction. This cytokine has also been detected at implantation sites under both physiological and pathological conditions in many different species. At these particular sites, the outermost embryonic cell layer in close contact with the maternal tissues, the trophoblast exhibits intense phagocytic activity. To determine whether IFN-gamma affects phagocytosis of mouse-trophoblast cells, ectoplacental cone-derived trophoblast was cultured and evaluated for erythrophagocytosis. Phagocytic activity was monitored ultrastructurally and expressed as percentage of phagocytic trophoblast in total trophoblast cells. Conditioned medium from concanavalin-A-stimulated spleen cells significantly enhanced trophoblast phagocytosis. This effect was blocked by pre-incubation with an anti-IFN-gamma neutralizing antibody. Introduction of mouse recombinant IFN-gamma (mrIFN-gamma) to cultures did not increase cell death, but augmented the percentage of phagocytic cells in a dose-dependent manner. Ectoplacental cones from mice deficient for IFN-gamma receptor alpha-chain showed a significant decrease of the phagocytosis, even under mrIFN-gamma stimulation, suggesting that IFN-gamma-induced phagocytosis are receptor-mediated. Reverse transcriptase-PCR analyses confirmed the presence of mRNA for IFN-gamma receptor alpha and beta-chains in trophoblast cells and detected a significant increase in the mRNA levels of IFN-gamma receptor beta-chain, mainly, when cultured cells were exposed to IFN-gamma. Immunohistochemistry and Western blot analyses also revealed protein expression of the IFN-gamma receptor alpha-chain. These results suggest that IFN-gamma may participate in the phagocytic activation of the mouse trophoblast, albeit the exact mechanism was not hereby elucidated. Protective and/or nutritional fetal benefit may result from this physiological response. In addition, our data also shed some light on the understanding of trophoblast tolerance to inflammatory/immune cytokines during normal gestation.

Apoptosis rate and transcriptional response of pancreatic islets exposed to the PPAR gamma agonist Pioglitazone

To explore the molecular pathways underlying thiazolidinediones effects on pancreatic islets in conditions mimicking normo- and hyperglycemia, apoptosis rate and transcriptional response to Pioglitazone at both physiological and supraphysiological glucose concentrations were evaluated. Adult rat islets were cultured at physiological (5.6 mM) and supraphysiological (23 mM) glucose concentrations in presence of 10 μM Pioglitazone or vehicle. RNA expression profiling was evaluated with the PancChip 13k cDNA microarray after 24-h, and expression results for some selected genes were validated by qRT-PCR. The effects of Pioglitazone were investigated regarding apoptosis rate after 24-, 48- and 72-h. At 5.6 mM glucose, 101 genes were modulated by Pioglitazone, while 1,235 genes were affected at 23 mM glucose. Gene networks related to lipid metabolism were identified as altered by Pioglitazone at both glucose concentrations. At 23 mM glucose, cell cycle and cell death pathways were significantly regulated as well. At 5.6 mM glucose, Pioglitazone elicited a transient reduction in islets apoptosis rate while at 23 mM, Bcl2 expression was reduced and apoptosis rate was increased by Pioglitazone. Our data demonstrate that the effect of Pioglitazone on gene expression profile and apoptosis rate depends on the glucose concentration. The modulation of genes related to cell death and the increased apoptosis rate observed at supraphysiological glucose concentration raise concerns about Pioglitazone’s direct effects in conditions of hyperglycemia and reinforce the necessity of additional studies designed to evaluate TZDs effects on the preservation of β-cell function in situations where glucotoxicity might be more relevant than lipotoxicity.

Influence of INF-gamma gene polymorphism in HTLV-1 proviral load

Financial Support FAPESP, CNPq, CTC/FUNDHERP and INCTC.

A note on the use of the generalized odds ratio in meta-analysis of association studies involving bi- and tri-allelic polymorphisms

Abstract Background The generalized odds ratio (GOR) was recently suggested as a genetic model-free measure for association studies. However, its properties were not extensively investigated. We used Monte Carlo simulations to investigate type-I error rates, power and bias in both effect size and between-study variance estimates of meta-analyses using the GOR as a summary effect, and compared these results to those obtained by usual approaches of model specification. We further applied the GOR in a real meta-analysis of three genome-wide association studies in Alzheimer's disease. Findings For bi-allelic polymorphisms, the GOR performs virtually identical to a standard multiplicative model of analysis (e.g. per-allele odds ratio) for variants acting multiplicatively, but augments slightly the power to detect variants with a dominant mode of action, while reducing the probability to detect recessive variants. Although there were differences among the GOR and usual approaches in terms of bias and type-I error rates, both simulation- and real data-based results provided little indication that these differences will be substantial in practice for meta-analyses involving bi-allelic polymorphisms. However, the use of the GOR may be slightly more powerful for the synthesis of data from tri-allelic variants, particularly when susceptibility alleles are less common in the populations (≤10%). This gain in power may depend on knowledge of the direction of the effects. Conclusions For the synthesis of data from bi-allelic variants, the GOR may be regarded as a multiplicative-like model of analysis. The use of the GOR may be slightly more powerful in the tri-allelic case, particularly when susceptibility alleles are less common in the populations.

Natural radionuclides distribution in the shelf and upper slope off southeast Brazil

In recent decades, Oceanography has been using a variety of radionuclides as tracers to understand the ocean dynamic processes, handling and disposal of sediments of seabed. In this context, the determination of natural radionuclides distributions (238U, 232Th and 40K) has been carried out with sediments samples from the shelf and upper slope off Southeast Brazil using a gamma spectrometry technique. The samples were sliced into strata of 2 cm, dried, ground and properly packed to be analysed. The concentration of activities was performed in a hyperpure Ge detector with a resolution of 1,9 keV for the peak of 1332,3 keV of 60Co, model GEM50P by EGG&ORTEC. The study area is located between latitudes 28°40'S and 23°00'S and extends from Cabo Frio (RJ) to Cabo de Santa Marta Grande (SC). The activity concentrations varied from 0,6 to 52,8 BqKg-1 for 238U, from 1,6 to 50,9BqKg-1 for 232Th and from 65,4 to 873,3 BqKg-1 for 40K. From these results it is possible to establish a correlation between the depositional area dynamics and the samples size parameters

Pseudodifferential operators on Hilbert space riggings with associated psi *-algebras and generalized Hörmander classes

The present thesis is concerned with certain aspects of differential and pseudodifferential operators on infinite dimensional spaces. We aim to generalize classical operator theoretical concepts of pseudodifferential operators on finite dimensional spaces to the infinite dimensional case. At first we summarize some facts about the canonical Gaussian measures on infinite dimensional Hilbert space riggings. Considering the naturally unitary group actions in $L^2(H_-,gamma)$ given by weighted shifts and multiplication with $e^{iSkp{t}{cdot}_0}$ we obtain an unitary equivalence $F$ between them. In this sense $F$ can be considered as an abstract Fourier transform. We show that $F$ coincides with the Fourier-Wiener transform. Using the Fourier-Wiener transform we define pseudodifferential operators in Weyl- and Kohn-Nirenberg form on our Hilbert space rigging. In the case of this Gaussian measure $gamma$ we discuss several possible Laplacians, at first the Ornstein-Uhlenbeck operator and then pseudo-differential operators with negative definite symbol. In the second case, these operators are generators of $L^2_gamma$-sub-Markovian semi-groups and $L^2_gamma$-Dirichlet-forms. In 1992 Gramsch, Ueberberg and Wagner described a construction of generalized Hörmander classes by commutator methods. Following this concept and the classical finite dimensional description of $Psi_{ro,delta}^0$ ($0leqdeltaleqroleq 1$, $delta< 1$) in the $C^*$-algebra $L(L^2)$ by Beals and Cordes we construct in both cases generalized Hörmander classes, which are $Psi^*$-algebras. These classes act on a scale of Sobolev spaces, generated by our Laplacian. In the case of the Ornstein-Uhlenbeck operator, we prove that a large class of continuous pseudodifferential operators considered by Albeverio and Dalecky in 1998 is contained in our generalized Hörmander class. Furthermore, in the case of a Laplacian with negative definite symbol, we develop a symbolic calculus for our operators. We show some Fredholm-criteria for them and prove that these Fredholm-operators are hypoelliptic. Moreover, in the finite dimensional case, using the Gaussian-measure instead of the Lebesgue-measure the index of these Fredholm operators is still given by Fedosov's formula. Considering an infinite dimensional Heisenberg group rigging we discuss the connection of some representations of the Heisenberg group to pseudo-differential operators on infinite dimensional spaces. We use this connections to calculate the spectrum of pseudodifferential operators and to construct generalized Hörmander classes given by smooth elements which are spectrally invariant in $L^2(H_-,gamma)$. Finally, given a topological space $X$ with Borel measure $mu$, a locally compact group $G$ and a representation $B$ of $G$ in the group of all homeomorphisms of $X$, we construct a Borel measure $mu_s$ on $X$ which is invariant under $B(G)$.

Messung der Zerfallsasymmetrien der radiativen Hyperonzerfälle Xi 0 Lambda gamma und Xi 0 Sigma 0 gamma mit dem NA48/1-Experiment

Der radiative Zerfall eines Hyperons in ein leichteres Hyperon und ein Photon erlaubt eine Untersuchung der Struktur der elektroschwachen Wechselwirkung von Hadronen. Dazu wird die Zerfallsasymmetrie $alpha$ betrachtet. Sie beschreibt die Verteilung des Tochterhyperons bezüglich der Polarisation $vec{P}$ des Mutterhyperons mit $dN / d cos(Theta) propto 1 + alpha |vec{P}| cos(Theta)$, wobei $Theta$ der Winkel zwischen $vec{P}$ und dem Impuls des Tochterhyperons ist. Von besonderem Interesse ist der radiative Zerfall $Xi^0 to Lambda gamma$, für den alle Rechnungen auf Quarkniveau eine positive Asymmetrie vorhersagen, wohingegen bisher eine negative Asymmetrie von $alpha_{Lambda gamma} = -0,73 +- 0,17$ gemessen wurde. Ziel dieser Arbeit war es, die bisherigen Messungen zu überprüfen und die Asymmetrie mit einer deutlich höheren Präzision zu bestimmen. Ferner wurden die Zerfallsasymmetrie des radiativen Zerfalls $Xi^0 to Sigma^0 gamma$ ermittelt und zum Test der angewandten Analysemethode der gut bekannte Zerfall $Xi^0 to Lambda pi^0$ herangezogen. Während der Datennahme im Jahr 2002 zeichnete das NA48/1-Experiment am CERN gezielt seltene $K_S$- und Hyperonzerfälle auf. Damit konnte der weltweit größte Datensatz an $Xi^0$-Zerfällen gewonnen werden, aus dem etwa 52.000 $Xi^0 to Lambda gamma$-Zerfälle, 15.000 $Xi^0 to Sigma^0 gamma$-Zerfälle und 4 Mill. $Xi^0 to Lambda pi^0$-Zerfälle mit nur geringem Untergrund extrahiert wurden. Ebenso wurden die entsprechenden $antiXi$-Zerfälle mit etwa einem Zehntel der obigen Ereigniszahlen registriert. Die Bestimmung der Zerfallsasymmetrien erfolgte durch den Vergleich der gemessene Daten mit einer detaillierten Detektorsimulation und führte zu den folgenden Resultaten dieser Arbeit: $alpha_{Lambda gamma} = -0,701 +- 0,019_{stat} +- 0,064_{sys}$, $alpha_{Sigma^0 gamma} = -0,683 +- 0,032_{stat} +- 0,077_{sys}$, $alpha_{Lambda pi^0} = -0,439 +- 0,002_{stat} +- 0,056_{sys}$, $alpha_{antiLambda gamma} = 0,772 +- 0,064_{stat} +- 0,066_{sys}$, $alpha_{antiSigma^0 gamma} = 0,811 +- 0,103_{stat} +- 0,135_{sys}$, $alpha_{antiLambda pi^0} = 0,451 +- 0,005_{stat} +- 0,057_{sys}$. Somit konnte die Unsicherheit der $Xi^0 to Lambda gamma$-Zerfallsasymmetrie auf etwa ein Drittel reduziert werden. Ihr negatives Vorzeichen und damit der Widerspruch zu den Vorhersagen der Quarkmodellrechnungen ist so zweifelsfrei bestätigt. Mit den zum ersten Mal gemessenen $antiXi$-Asymmetrien konnten zusätzlich Grenzen auf eine mögliche CP-Verletzung in den $Xi^0$-Zerfällen, die $alpha_{Xi^0} neq -alpha_{antiXi}$ zur Folge hätte, bestimmt werden.

Orthogonal gamma-based expansions for volatility option prices under jump-diffusion dynamics

In my work I derive closed-form pricing formulas for volatility based options by suitably approximating the volatility process risk-neutral density function. I exploit and adapt the idea, which stands behind popular techniques already employed in the context of equity options such as Edgeworth and Gram-Charlier expansions, of approximating the underlying process as a sum of some particular polynomials weighted by a kernel, which is typically a Gaussian distribution. I propose instead a Gamma kernel to adapt the methodology to the context of volatility options. VIX vanilla options closed-form pricing formulas are derived and their accuracy is tested for the Heston model (1993) as well as for the jump-diffusion SVJJ model proposed by Duffie et al. (2000).

New Results Concerning Probability Distributions with Increasing Generalized Failure Rates

The generalized failure rate of a continuous random variable has demonstrable importance in operations management. If the valuation distribution of a product has an increasing generalized failure rate (that is, the distribution is IGFR), then the associated revenue function is unimodal, and when the generalized failure rate is strictly increasing, the global maximum is uniquely specified. The assumption that the distribution is IGFR is thus useful and frequently held in recent pricing, revenue, and supply chain management literature. This note contributes to the IGFR literature in several ways. First, it investigates the prevalence of the IGFR property for the left and right truncations of valuation distributions. Second, we extend the IGFR notion to discrete distributions and contrast it with the continuous distribution case. The note also addresses two errors in the previous IGFR literature. Finally, for future reference, we analyze all common (continuous and discrete) distributions for the prevalence of the IGFR property, and derive and tabulate their generalized failure rates.

Posterior Simulation in the Generalized Linear Model with Semiparmetric Random Effects

Generalized linear mixed models with semiparametric random effects are useful in a wide variety of Bayesian applications. When the random effects arise from a mixture of Dirichlet process (MDP) model, normal base measures and Gibbs sampling procedures based on the Pólya urn scheme are often used to simulate posterior draws. These algorithms are applicable in the conjugate case when (for a normal base measure) the likelihood is normal. In the non-conjugate case, the algorithms proposed by MacEachern and Müller (1998) and Neal (2000) are often applied to generate posterior samples. Some common problems associated with simulation algorithms for non-conjugate MDP models include convergence and mixing difficulties. This paper proposes an algorithm based on the Pólya urn scheme that extends the Gibbs sampling algorithms to non-conjugate models with normal base measures and exponential family likelihoods. The algorithm proceeds by making Laplace approximations to the likelihood function, thereby reducing the procedure to that of conjugate normal MDP models. To ensure the validity of the stationary distribution in the non-conjugate case, the proposals are accepted or rejected by a Metropolis-Hastings step. In the special case where the data are normally distributed, the algorithm is identical to the Gibbs sampler.

Pharmacokinetics and excretion of gamma-hydroxybutyrate (GHB) in healthy subjects

In Europe and the United States, the recreational use of gamma-hydroxy butyric acid (GHB) at dance clubs and "rave" parties has increased substantially. In addition, GHB is used to assist in the commission of sexual assaults. The aim of this controlled clinical study was to acquire pharmacokinetic profiles, detection times, and excretion rates in human subjects. Eight GHB-naïve volunteers were administered a single 25-mg/kg body weight oral dose of GHB, and plasma, urine, and oral fluid specimens were analyzed by using gas chromatography-mass spectrometry (GC-MS). Liquid-liquid extraction was performed after acid conversion of GHB to gamma-butyrolactone. Limits of quantitation of 0.1 (oral fluid), 0.2 (urine), and 0.5 microg/mL (plasma) could be achieved in the selected ion monitoring mode. GHB plasma peaks of 39.4 +/- 25.2 microg/mL (mean +/- SEM) occurred 20-45 min after administration. The terminal plasma elimination half-life was 30.4 +/- 2.45 min, the distribution volume 52.7 +/- 15.0 L, and the total clearance 1228 +/- 233 microL/min. In oral fluid, GHB could be detected up to 360 min, with peak concentrations of 203 +/- 92.4 microg/mL in the 10-min samples. In urine, 200 +/- 71.8 and 230 +/- 86.3 microg/mL, were the highest GHB levels measured at 30 and 60 min, respectively. Only 1.2 +/- 0.2% of the dose was excreted, resulting in a detection window of 720 min. Common side-effects were confusion, sleepiness, and dizziness; euphoria and change of vital functions were not observed. GHB is extensively metabolized and rapidly eliminated in urine and oral fluid. Consequently, samples should be collected as soon as possible after ingestion.

Generalized fuzzy clustering for segmentation of multi-spectral magnetic resonance images.

An integrated approach for multi-spectral segmentation of MR images is presented. This method is based on the fuzzy c-means (FCM) and includes bias field correction and contextual constraints over spatial intensity distribution and accounts for the non-spherical cluster's shape in the feature space. The bias field is modeled as a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of intensity are added into the FCM cost functions. To reduce the computational complexity, the contextual regularizations are separated from the clustering iterations. Since the feature space is not isotropic, distance measure adopted in Gustafson-Kessel (G-K) algorithm is used instead of the Euclidean distance, to account for the non-spherical shape of the clusters in the feature space. These algorithms are quantitatively evaluated on MR brain images using the similarity measures.

Empirical Analysis of Credit Risk Regime Switching and Temporal Conditional Default Correlation in Credit Default Swap Valuation: The Market liquidity effect

In this paper, we extend the debate concerning Credit Default Swap valuation to include time varying correlation and co-variances. Traditional multi-variate techniques treat the correlations between covariates as constant over time; however, this view is not supported by the data. Secondly, since financial data does not follow a normal distribution because of its heavy tails, modeling the data using a Generalized Linear model (GLM) incorporating copulas emerge as a more robust technique over traditional approaches. This paper also includes an empirical analysis of the regime switching dynamics of credit risk in the presence of liquidity by following the general practice of assuming that credit and market risk follow a Markov process. The study was based on Credit Default Swap data obtained from Bloomberg that spanned the period January 1st 2004 to August 08th 2006. The empirical examination of the regime switching tendencies provided quantitative support to the anecdotal view that liquidity decreases as credit quality deteriorates. The analysis also examined the joint probability distribution of the credit risk determinants across credit quality through the use of a copula function which disaggregates the behavior embedded in the marginal gamma distributions, so as to isolate the level of dependence which is captured in the copula function. The results suggest that the time varying joint correlation matrix performed far superior as compared to the constant correlation matrix; the centerpiece of linear regression models.

Bayesian generalized linear models for meta-analysis of diagnostic tests

With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^