Prevalence of childhood obsessive-compulsive personality traits in adults with obsessive compulsive disorder versus obsessive compulsive personality disorder

Identifying risk factors of psychopathology has been an important research challenge. Prior studies examining the impact of childhood temperament on adult disorder have largely focused on under-controlled and inhibited presentations, with little study of overcontrolled traits such as obsessive-compulsive personality traits (OCPTs). We compared rates of childhood OCPTs in adults with OCD (without OCPD) (n=28) to adults with OCPD (without OCD) (n=27), adults with both OCD and OCPD (n=28), and healthy controls (HC) (n=28), using the childhood retrospective perfectionism questionnaire, a validated measure of perfectionism, inflexibility, and drive for order. Adults with OCPD (both with and without comorbid OCD) reported higher rates of all three childhood OCPTs relative to HC. Individuals with OCD (without OCPD) reported higher rates of inflexibility and drive for order relative to HC, suggesting that these traits may presage the development of OCD, independent of OCPD. Childhood OCPTs were associated with particular OCD symptom dimensions in adulthood (contamination/cleaning, doubt/checking, and symmetry/ordering), independent of OCD onset age and OCPD diagnosis. Longitudinal prospective studies evaluating OCPTs in children are needed to better understand the progression of these traits from childhood to adulthood and their ability to predict future psychopathology. (C) 2014 Elsevier Inc. All rights reserved

Efficient dynamical downscaling of general circulation models using continuous data assimilation

Continuous data assimilation (CDA) is successfully implemented for the first time for efficient dynamical downscaling of a global atmospheric reanalysis. A comparison of the performance of CDA with the standard grid and spectral nudging techniques for representing long- and short-scale features in the downscaled fields using the Weather Research and Forecast (WRF) model is further presented and analyzed. The WRF model is configured at 25km horizontal resolution and is driven by 250km initial and boundary conditions from NCEP/NCAR reanalysis fields. Downscaling experiments are performed over a one-month period in January, 2016. The similarity metric is used to evaluate the performance of the downscaling methods for large and small scales. Similarity results are compared for the outputs of the WRF model with different downscaling techniques, NCEP reanalysis, and Final Analysis. Both spectral nudging and CDA describe better the small-scale features compared to grid nudging. The choice of the wave number is critical in spectral nudging; increasing the number of retained frequencies generally produced better small-scale features, but only up to a certain threshold after which its solution gradually became closer to grid nudging. CDA maintains the balance of the large- and small-scale features similar to that of the best simulation achieved by the best spectral nudging configuration, without the need of a spectral decomposition. The different downscaled atmospheric variables, including rainfall distribution, with CDA is most consistent with the observations. The Brier skill score values further indicate that the added value of CDA is distributed over the entire model domain. The overall results clearly suggest that CDA provides an efficient new approach for dynamical downscaling by maintaining better balance between the global model and the downscaled fields

Analysis of circadian pattern reveals tissue-specific alternative transcription in leptin signaling pathway

*Background*
It has been previously reported that most mammalian genes display a circadian oscillation in their baseline expression. Consequently, the phase and amplitude of each component of a signal transduction cascade has downstream consequences. 

*Results*
We report our analysis of alternative transcripts in the leptin signaling pathway which is responsible for the systemic regulation of macronutrient storage and energy balance. We focused on the circadian expression pattern of a critical component of the leptin signaling system, suppressor of cytokine signaling 3 (SOCS3). On an Affymetrix GeneChip 430A2 microarray, this gene is represented by three probe sets targeting different regions within the 3’ end of the last exon. We demonstrate that in murine brown adipose tissue two downstream 3’ probe sets experience circadian baseline oscillation in counter-phase to the upstream probe set. Such differences in expression patterns are a telltale sign of alternative splicing within the last exon of SOCS3. In contrast, all three probe sets oscillated in a common phase in murine liver and white adipose tissue. This suggests that the regulation of SOCS3 expression in brown fat is tissue specific. Another component of the signaling pathway, Janus kinase (JAK), is directly regulated by SOCS and has alternative transcript probe sets oscillating in counter-phase in a white adipose tissue specific manner.
 
*Conclusion*
We hypothesize that differential oscillation of alternative transcripts may provide a mechanism to maintain steady levels of expression in spite of circadian baseline variation

A Robot Model of OC-Spectrum Disorders : Design Framework, Implementation and First Experiments

© 2019 Massachusetts Institute of TechnologyComputational psychiatry is increasingly establishing itself as valuable discipline for understanding human mental disorders. However, robot models and their potential for investigating embodied and contextual aspects of mental health have been, to date, largely unexplored. In this paper, we present an initial robot model of obsessive-compulsive (OC) spectrum disorders based on an embodied motivation-based control architecture for decision making in autonomous robots. The OC family of conditions is chiefly characterized by obsessions (recurrent, invasive thoughts) and/or compulsions (an urge to carry out certain repetitive or ritualized behaviors). The design of our robot model follows and illustrates a general design framework that we have proposed to ground research in robot models of mental disorders, and to link it with existing methodologies in psychiatry, and notably in the design of animal models. To test and validate our model, we present and discuss initial experiments, results and quantitative and qualitative analysis regarding the compulsive and obsessive elements of OC-spectrum disorders. While this initial stage of development only models basic elements of such disorders, our results already shed light on aspects of the underlying theoretical model that are not obvious simply from consideration of the model.Peer reviewe

Metagenomic approach for identification of the pathogens associated with diarrhea in stool specimens

The potential to rapidly capture the entire microbial community structure and/or gene content makes metagenomic sequencing an attractive tool for pathogen identification and the detection of resistance/virulence genes in clinical settings. Here, we assessed the consistency between PCR from a diagnostic laboratory, quantitative PCR (qPCR) from a research laboratory, 16S rRNA gene sequencing, and metagenomic shotgun sequencing (MSS) for Clostridium difficile identification in diarrhea stool samples. Twenty-two C. difficile-positive diarrhea samples identified by PCR and qPCR and five C. difficile-negative diarrhea controls were studied. C. difficile was detected in 90.9% of C. difficile-positive samples using 16S rRNA gene sequencing, and C. difficile was detected in 86.3% of C. difficile-positive samples using MSS. CFU inferred from qPCR analysis were positively correlated with the relative abundance of C. difficile from 16S rRNA gene sequencing (r(2) = -0.60) and MSS (r(2) = -0.55). C. difficile was codetected with Clostridium perfringens, norovirus, sapovirus, parechovirus, and anellovirus in 3.7% to 27.3% of the samples. A high load of Candida spp. was found in a symptomatic control sample in which no causative agents for diarrhea were identified in routine clinical testing. Beta-lactamase and tetracycline resistance genes were the most prevalent (25.9%) antibiotic resistance genes in these samples. In summary, the proof-of-concept study demonstrated that next-generation sequencing (NGS) in pathogen detection is moderately correlated with laboratory testing and is advantageous in detecting pathogens without a priori knowledge. J Clin Microbiol 2016 Feb; 54(2):368-75

Maximal height statistics for 1/f^alpha signals

Numerical and analytical results are presented for the maximal relative height distribution of stationary periodic Gaussian signals (one dimensional interfaces) displaying a 1/f^alpha power spectrum. For 0<alpha<1 (regime of decaying correlations), we observe that the mathematically established limiting distribution (Fisher-Tippett-Gumbel distribution) is approached extremely slowly as the sample size increases. The convergence is rapid for alpha>1 (regime of strong correlations) and a highly accurate picture gallery of distribution functions can be constructed numerically. Analytical results can be obtained in the limit alpha -> infinity and, for large alpha, by perturbation expansion. Furthermore, using path integral techniques we derive a trace formula for the distribution function, valid for alpha=2n even integer. From the latter we extract the small argument asymptote of the distribution function whose analytic continuation to arbitrary alpha > 1 is found to be in agreement with simulations. Comparison of the extreme and roughness statistics of the interfaces reveals similarities in both the small and large argument asymptotes of the distribution functions.Comment: 17 pages, 8 figures, RevTex