A Functional Magnetic Resonance Imaging Predictor of Treatment Response to Venlafaxine in Generalized Anxiety Disorder

Background: Functional magnetic resonance imaging (fMRI) holds promise as a noninvasive means of identifying neural responses that can be used to predict treatment response before beginning a drug trial. Imaging paradigms employing facial expressions as presented stimuli have been shown to activate the amygdala and anterior cingulate cortex (ACC). Here, we sought to determine whether pretreatment amygdala and rostral ACC (rACC) reactivity to facial expressions could predict treatment outcomes in patients with generalized anxiety disorder (GAD).Methods: Fifteen subjects (12 female subjects) with GAD participated in an open-label venlafaxine treatment trial. Functional magnetic resonance imaging responses to facial expressions of emotion collected before subjects began treatment were compared with changes in anxiety following 8 weeks of venlafaxine administration. In addition, the magnitude of fMRI responses of subjects with GAD were compared with that of 15 control subjects (12 female subjects) who did not have GAD and did not receive venlafaxine treatment.Results The magnitude of treatment response was predicted by greater pretreatment reactivity to fearful faces in rACC and lesser reactivity in the amygdala. These individual differences in pretreatment rACC and amygdala reactivity within the GAD group were observed despite the fact that 1) the overall magnitude of pretreatment rACC and amygdala reactivity did not differ between subjects with GAD and control subjects and 2) there was no main effect of treatment on rACC-amygdala reactivity in the GAD group.Conclusions: These findings show that this pattern of rACC-amygdala responsivity could prove useful as a predictor of venlafaxine treatment response in patients with GAD.

Linear and nonlinear generalized Fourier transforms

This article presents an overview of a transform method for solving linear and integrable nonlinear partial differential equations. This new transform method, proposed by Fokas, yields a generalization and unification of various fundamental mathematical techniques and, in particular, it yields an extension of the Fourier transform method.

Involvement of phenazine-1-carboxylic acid, siderophores and hydrogen cyanide in suppression of Rhizoetonia solani and Pythium spp. damping-off by Pseudomonas oryzihabitans and Xenorhabdus nematophila

Entomopathogenic bacterial strains Pseudomonas (Flavimonas) oryzihabitans and Xenorhabdus nematophilus, both bacterial symbionts of the entomopathogenic nematodes Steinernema abbasi and S. carpocapsae have been recently used for suppression of soil-borne pathogens. Bacterial biocontrol agents (P. oryzihabitans and X nematophila) have been tested for production of secondary metabolites in vitro and their fungistatic effect,on mycelium and spore development of soil-borne pathogens. Isolates of Pythium spp. and Rhizoctonia solani, the causal agent of cotton damping-off, varied in sensitivity in vitro to the antibiotics phenazine-I-carboxylic acid (PCA), cyanide (HCN) and siderophores produced by bacterial strains shown previously to have potential for biological control of those pathogens. These findings affirm the role of the antibiotics PCA, HCN and siderophores in the biocontrol activity of these entomopathogenic strains and support earlier evidence that mechanisms of secondary metabolites are responsible for suppression of damping-off diseases. In the present studies colonies of R oryzihabitans showed production of PCA with presence of crystalline deposits after six days development and positive production where found as well in the siderophore's assay when X nematophila strain indicated HCN production in the in vitro assays. In vitro antifungal activity showed that bacteria densities of 101 to 10(6)cells/ml have antifungal activity in different media cultures. The results show further that isolates of Pythium spp. and R. solani insensitive to PCA, HCN and siderophores are present in the pathogen population and provide additional justification for the use of mixtures of entomopathogenic strains that employ different mechanisms of pathogen suppression to manage damping-off.

Biological control of Rhizoctonia solani Damping-off with a bacterium symbiotically associated with Steinernema abbasi

Rhizoctonia solani is a causal agent of damping-off of may cultivated plants. An isolate of the bacterium Pseudomonas oryzihabitans, symbiotically associated with the entomopathogenic nematode Steinernema abbasi, strongly inhibited the pathogen in vitro. The bacterium was firmly attached onto fungus mycelia and degraded the cell walls of the pathogen. In greenhouse experiments, bacterial suspension in sterile water applied in the soil, effectively controlled damping-off of radish.

Describing long-term trends in precipitation using generalized additive models

With the current concern over climate change, descriptions of how rainfall patterns are changing over time can be useful. Observations of daily rainfall data over the last few decades provide information on these trends. Generalized linear models are typically used to model patterns in the occurrence and intensity of rainfall. These models describe rainfall patterns for an average year but are more limited when describing long-term trends, particularly when these are potentially non-linear. Generalized additive models (GAMS) provide a framework for modelling non-linear relationships by fitting smooth functions to the data. This paper describes how GAMS can extend the flexibility of models to describe seasonal patterns and long-term trends in the occurrence and intensity of daily rainfall using data from Mauritius from 1962 to 2001. Smoothed estimates from the models provide useful graphical descriptions of changing rainfall patterns over the last 40 years at this location. GAMS are particularly helpful when exploring non-linear relationships in the data. Care is needed to ensure the choice of smooth functions is appropriate for the data and modelling objectives. (c) 2008 Elsevier B.V. All rights reserved.

A family study of co-morbidity between generalized social phobia and generalized anxiety disorder in a non-clinic sample

Background: High rates of co-morbidity between Generalized Social Phobia (GSP) and Generalized Anxiety Disorder (GAD) have been documented. The reason for this is unclear. Family studies are one means of clarifying the nature of co-morbidity between two disorders. Methods: Six models of co-morbidity between GSP and GAD were investigated in a family aggregation study of 403 first-degree relatives of non-clinical probands: 37 with GSP, 22 with GAD, 15 with co-morbid GSP/GAD, and 41 controls with no history of GSP or GAD. Psychiatric data were collected for probands and relatives. Mixed methods (direct and family history interviews) were utilised. Results: Primary contrasts (against controls) found an increased rate of pure GSP in the relatives of both GSP probands and co-morbid GSP/GAD probands, and found relatives of co-morbid GSP/GAD probands to have an increased rate of both pure GAD and comorbid GSP/GAD. Secondary contrasts found (i) increased GSP in the relatives of GSP only probands compared to the relatives of GAD only probands; and (ii) increased GAD in the relatives of co-morbid GSP/GAD probands compared to the relatives of GSP only probands. Limitations: The study did not directly interview all relatives, although the reliability of family history data was assessed. The study was based on an all-female proband sample. The implications of both these limitations are discussed. Conclusions: The results were most consistent with a co-morbidity model indicating independent familial transmission of GSP and GAD. This has clinical implications for the treatment of patients with both disorders. (C) 2006 Elsevier B.V. All fights reserved.

Design of redundant drive joint with adjustable stiffness and damping mechanism to improve joint admittance

Improving admittance of robotic joints is the key issue for making rehabilitation robots safe. This paper describes a design of Redundant Drive Joint (RD-Joint) which allows greater flexibility in the design of robotic mechanisms. The design strategy of the RD-Joint employs a systematic approach which consists of 1) adopting a redundant joint mechanism with internal kinematical redundancy to reduce effective joint inertia, and 2) adopting an adjustable admittance mechanism with a novel Cross link Reduction Mechanism and mechanical springs and dampers as a passive second actuator. First, the basic concepts used to construct the redundant drive joint mechanism are explained, in particular the method that allows a reduction in effective inertia at the output joint. The basic structure of the RD-Joint is introduced based on the idea of reduced inertia along with a method to include effective stiffness and damping. Then, the basic design of the adjustable admittance mechanism is described. Finally, a prototype of RD-joint is described and its expected characteristics are discussed.

Identification of nonlinear systems using generalized kernel models

Nonlinear system identification is considered using a generalized kernel regression model. Unlike the standard kernel model, which employs a fixed common variance for all the kernel regressors, each kernel regressor in the generalized kernel model has an individually tuned diagonal covariance matrix that is determined by maximizing the correlation between the training data and the regressor using a repeated guided random search based on boosting optimization. An efficient construction algorithm based on orthogonal forward regression with leave-one-out (LOO) test statistic and local regularization (LR) is then used to select a parsimonious generalized kernel regression model from the resulting full regression matrix. The proposed modeling algorithm is fully automatic and the user is not required to specify any criterion to terminate the construction procedure. Experimental results involving two real data sets demonstrate the effectiveness of the proposed nonlinear system identification approach.