Affect-focused body psychotherapy in patients with generalized anxiety disorder: Evaluation of an integrative method.

The aim of this study was to explore the long-term effects of affect-focused body psychotherapy (ABP) for patients with generalized anxiety disorder (GAD). A group of 61 consecutive patients, 21–55 years old, were randomized to ABP and psychiatric treatment as usual (TAU). The patients were assessed before treatment and followed up 1 and 2 years after inclusion. The ABP patients received one session of treatment per week during 1 year. Three self-report questionnaires were administered; Symptom Checklist—90, Beck Anxiety Inventory, and the WHO (Ten) Well-Being Index. In both groups, there was a significant improvement. On termination, the ABP group had improved significantly more on the SCL-90 Global Symptom Index than the TAU group, whereas the differences were short of significance on the other two scales. The integration of bodily techniques with a focus on affects in a psychodynamically informed treatment seems to be a viable treatment alternative for patients with GAD. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Optimization of methods and treatment conditions for studying effects of fatty acids on cell growth

Antiproliferative properties of molecular regulators of lipid metabolism have been increasingly studied during recent years. Discussion is ongoing concerning optimal treatment conditions and assays used for monitoring proliferation and cytotoxicity. The objective of the present work was to optimize methods and treatment conditions used for studying antiproliferative effects of fatty acids and analogs, represented by palmitic acid (PA) and the β-oxidation-restricted fatty acid analog tetradecylthioacetic acid (TTA), in rat (BT4Cn) and human (D54Mg and GaMg) glioma cell lines. Changes in [³H]thymidine incorporation preceded changes in cell number in TTA-treated glioma cell cultures, and the growth inhibition was more significantly expressed by [³H]thymidine incorporation than cell number. Addition of bovine serum albumin decreased cellular fatty acid uptake and reduced the effects of TTA and PA on [³H]thymidine incorporation. Determination of the antiproliferative effect of TTA in BT4Cn cells by MTT conversion and [³H]thymidine incorporation yielded concordant results. TTA-mediated reduction in cell number corresponded to reduction in cellular protein and total DNA content in BT4Cn cells. Reduced growth potential in TTA-treated multicellular D54Mg and GaMg spheroids supported the findings from monolayer cultures. In conclusion, cell density, treatment period, fatty acid administration, and methods for growth determination may profoundly influence the outcome of cell growth experiments. Thus, experimental conditions should be carefully controlled when performing cell growth experiments, and effects on cell growth should preferably be confirmed by different methods. Karl Johan Tronstad and Kjetil Berge contributed equally to this article.     

Estimating the width of a uniform distribution when data are measured with additive normal errors with known variance

The problem of estimating the width of the symmetric uniform distribution on the line when data are measured with normal additive error is considered. The main purpose is to discuss the efficiency of the maximum likelihood estimator and the moment method estimator. It is shown that the model is regular and that the maximum likelihood estimator is more efficient than the moment method estimator. A sufficient condition is also given for the existence of both estimators.     

CFNN-PSO: An Iterative Predictive Model for Generic Parametric Design of Machining Processes

ABSTRACT

Every production process consists of a large number of dependent and independent variables, which substantially influence the quality of the machined parts. Due to the large impact of process variabilities, it is difficult to design optimal models for the machining processes. Mathematical or numerical models for production processes are resource driven, which are not cost effective approaches in terms of computation and economical production. In this paper, a new artificial neural network (ANN) based predictive model is introduced, which exploits particle swarm optimization (PSO) algorithm to minimize the root mean square errors (RMSE) for the network training. This approach can effectively obtain an optimized predictive model that can calculate precise output responses for the production processes. In order to verify the proposed approach, two case studies are considered from literature and shown to produce significant improvements. Furthermore, the proposed model is validated on abrasive water jet machining (AWJM) with industrial garnet abrasives and optimal machining conditions have been obtained with optimized responses, which are substantially improved while compared with gray relational analysis (GRA).     

Exploiting symmetries for scaling loopy belief propagation and relational training

Judging by the increasing impact of machine learning on large-scale data analysis in the last decade, one can anticipate a substantial growth in diversity of the machine learning applications for “big data” over the next decade. This exciting new opportunity, however, also raises many challenges. One of them is scaling inference within and training of graphical models. Typical ways to address this scaling issue are inference by approximate message passing, stochastic gradients, and MapReduce, among others. Often, we encounter inference and training problems with symmetries and redundancies in the graph structure. A prominent example are relational models that capture complexity. Exploiting these symmetries, however, has not been considered for scaling yet. In this paper, we show that inference and training can indeed benefit from exploiting symmetries. Specifically, we show that (loopy) belief propagation (BP) can be lifted. That is, a model is compressed by grouping nodes together that send and receive identical messages so that a modified BP running on the lifted graph yields the same marginals as BP on the original one, but often in a fraction of time. By establishing a link between lifting and radix sort, we show that lifting is MapReduce-able. Still, in many if not most situations training relational models will not benefit from this (scalable) lifting: symmetries within models easily break since variables become correlated by virtue of depending asymmetrically on evidence. An appealing idea for such situations is to train and recombine local models. This breaks long-range dependencies and allows to exploit lifting within and across the local training tasks. Moreover, it naturally paves the way for the first scalable lifted training approaches based on stochastic gradients, both in an online and a MapReduced fashion. On several datasets, the online training, for instance, converges to the same quality solution over an order of magnitude faster, simply because it starts optimizing long before having seen the entire mega-example even once.     

On the communication of scientific data: The Full-Metadata Format

In this paper, we introduce a scientific format for text-based data files, which facilitates storing and communicating tabular data sets. The so-called Full-Metadata Format builds on the widely used INI-standard and is based on four principles: readable self-documentation, flexible structure, fail-safe compatibility, and searchability. As a consequence, all metadata required to interpret the tabular data are stored in the same file, allowing for the automated generation of publication-ready tables and graphs and the semantic searchability of data file collections. The Full-Metadata Format is introduced on the basis of three comprehensive examples. The complete format and syntax are given in the appendix.     

Effects of polyunsaturated fatty acids and their n-6 hydroperoxides on growth of five malignant cell lines and the significance of culture media

We examined effects of polyunsaturated fatty acids (PUFA), their corresponding hydroperoxy fatty acids (hp-PUFA), as well as various pro- and antioxidants on the growth of tumor cells in culture. When cultured in RPMI 1640 medium, A-427 and WEHI clone 13 cells were both highly sensitive to hydroperoxy docosahexaenoic acid (hp-DHA), but they were far less sensitive in minimum essential medium (MEM). In contrast, A-427 cells were also sensitive to DHA in both culture media, while WEHI clone 13 cells, as well as other cell lines, tested in their respective media, were resistant. The lower sensitivity of the cell lines to hp-DHA in MEM-medium was apparently due to a more rapid reduction of hp-DHA to the corre-sponding hydroxy-DHA in MEM-medium. Addition of glutathione (GSH) to the culture medium abolished the effects of hp-DHA, but not the effects of DHA, while depletion of intracellular GSH levels by L-buthionine-S,R-sulfoximine strongly enhanced the cytotoxic effect of hp-DHA, but not the cytotoxic effect of DHA. α-Tocopherol protected A-427 cells against the toxic effect of DHA and abolished the induced lipid peroxidation, while it did not protect against the toxic effects of hp-DHA in A-427 or WEHI clone 13 cells. Ascorbic acid reduced the cytotoxic effect of DHA, but potentiated the toxic effect of hp-DHA while selenite essentially abolished the toxicity of both DHA and hp-DHA. These results indicate that sensitivity of tumor cell lines to PUFA and their oxidation products depends on their antioxidant defense mechanisms, as well as culture conditions, and establishes hp-DHA as a major, but probably not the sole, metabolite responsible for cytotoxicity of DHA.