1,836 research outputs found

    Role of the mesoamygdaloid dopamine projection in emotional learning

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    Amygdala dopamine is crucially involved in the acquisition of Pavlovian associations, as measured via conditioned approach to the location of the unconditioned stimulus (US). However, learning begins before skeletomotor output, so this study assessed whether amygdala dopamine is also involved in earlier 'emotional' learning. A variant of the conditioned reinforcement (CR) procedure was validated where training was restricted to curtail the development of selective conditioned approach to the US location, and effects of amygdala dopamine manipulations before training or later CR testing assessed. Experiment 1a presented a light paired (CS+ group) or unpaired (CS- group) with a US. There were 1, 2 or 10 sessions, 4 trials per session. Then, the US was removed, and two novel levers presented. One lever (CR+) presented the light, and lever pressing was recorded. Experiment 1b also included a tone stimulus. Experiment 2 applied intra-amygdala R(+) 7-OH-DPAT (10 nmol/1.0 A mu l/side) before two training sessions (Experiment 2a) or a CR session (Experiment 2b). For Experiments 1a and 1b, the CS+ group preferred the CR+ lever across all sessions. Conditioned alcove approach during 1 or 2 training sessions or associated CR tests was low and nonspecific. In Experiment 2a, R(+) 7-OH-DPAT before training greatly diminished lever pressing during a subsequent CR test, preferentially on the CR+ lever. For Experiment 2b, R(+) 7-OH-DPAT infusions before the CR test also reduced lever pressing. Manipulations of amygdala dopamine impact the earliest stage of learning in which emotional reactions may be most prevalent

    Solving ill-posed bilevel programs

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    This paper deals with ill-posed bilevel programs, i.e., problems admitting multiple lower-level solutions for some upper-level parameters. Many publications have been devoted to the standard optimistic case of this problem, where the difficulty is essentially moved from the objective function to the feasible set. This new problem is simpler but there is no guaranty to obtain local optimal solutions for the original optimistic problem by this process. Considering the intrinsic non-convexity of bilevel programs, computing local optimal solutions is the best one can hope to get in most cases. To achieve this goal, we start by establishing an equivalence between the original optimistic problem an a certain set-valued optimization problem. Next, we develop optimality conditions for the latter problem and show that they generalize all the results currently known in the literature on optimistic bilevel optimization. Our approach is then extended to multiobjective bilevel optimization, and completely new results are derived for problems with vector-valued upper- and lower-level objective functions. Numerical implementations of the results of this paper are provided on some examples, in order to demonstrate how the original optimistic problem can be solved in practice, by means of a special set-valued optimization problem

    From error bounds to the complexity of first-order descent methods for convex functions

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    This paper shows that error bounds can be used as effective tools for deriving complexity results for first-order descent methods in convex minimization. In a first stage, this objective led us to revisit the interplay between error bounds and the Kurdyka-\L ojasiewicz (KL) inequality. One can show the equivalence between the two concepts for convex functions having a moderately flat profile near the set of minimizers (as those of functions with H\"olderian growth). A counterexample shows that the equivalence is no longer true for extremely flat functions. This fact reveals the relevance of an approach based on KL inequality. In a second stage, we show how KL inequalities can in turn be employed to compute new complexity bounds for a wealth of descent methods for convex problems. Our approach is completely original and makes use of a one-dimensional worst-case proximal sequence in the spirit of the famous majorant method of Kantorovich. Our result applies to a very simple abstract scheme that covers a wide class of descent methods. As a byproduct of our study, we also provide new results for the globalization of KL inequalities in the convex framework. Our main results inaugurate a simple methodology: derive an error bound, compute the desingularizing function whenever possible, identify essential constants in the descent method and finally compute the complexity using the one-dimensional worst case proximal sequence. Our method is illustrated through projection methods for feasibility problems, and through the famous iterative shrinkage thresholding algorithm (ISTA), for which we show that the complexity bound is of the form O(qk)O(q^{k}) where the constituents of the bound only depend on error bound constants obtained for an arbitrary least squares objective with 1\ell^1 regularization

    The influence of the frequency of periodic disturbances on the maintenance of phytoplankton diversity

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    The influence of periodic disturbances of various frequency on the maintenance of the phytoplankton diversity was studied by semicontinuous competition experiments. Disturbances consisted of dilution events, which meant both addition of fresh nutrients and elimination of organisms. The intervals between dilution events varied from 1 to 14 days. Diversity was found to increase with increasing intervals between disturbances. coexisting species belonged to different strategy types: (a) species with rapid growth under enriched conditions, (b) species with good competitive abilities under impoverished conditions, (c) species with the ability to build up storage pools of the limiting nutrient. An increase of the number of coexisting species over the number that would have coexisted in steady state was only found when the interval exceeded one generation time

    The effectiveness of problem solving therapy for stroke patients: Study protocol for a pragmatic randomized controlled trial

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    Background: Coping style is one of the determinants of health-related quality of life after stroke. Stroke patients make less use of active problem-oriented coping styles than other brain damaged patients. Coping styles can be influenced by means of intervention. The primary aim of this study is to investigate if Problem Solving Therapy is an effective group intervention for improving coping style and health-related quality of life in stroke patients. The secondary aim is to determine the effect of Problem Solving Therapy on depression, social participation, health care consumption, and to determine the cost-effectiveness of the intervention.Methods/design: We strive to include 200 stroke patients in the outpatient phase of rehabilitation treatment, using a multicenter pragmatic randomized controlled trial with one year follow-up. Patients in the intervention group will receive Problem Solving Therapy in addition to the standard rehabilitation program. The intervention will be provided in an open group design, with a continuous flow of patients. Primary outcome measures are coping style and health-related quality of life. Secondary outcome measures are depression, social participation, health care consumption, and the cost-effectiveness of the intervention.Discussion: We designed our study as close to the implementation in practice as possible, using a pragmatic randomized trial and open group design, to represent a realistic estimate of the effectiveness of the intervention. If effective, Problem Solving Therapy is an inexpensive, deliverable and sustainable group intervention for stroke rehabilitation programs.Trial registration: Nederlands Trial Register, NTR2509

    Temporal variance of disturbance did not affect diversity and structure of a marine fouling community in north-eastern New Zealand

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    Natural heterogeneity in ecological parameters, like population abundance, is more widely recognized and investigated than variability in the processes that control these parameters. Experimental ecologists have focused mainly on the mean intensity of predictor variables and have largely ignored the potential to manipulate variances in processes, which can be considered explicitly in experimental designs to explore variation in causal mechanisms. In the present study, the effect of the temporal variance of disturbance on the diversity of marine assemblages was tested in a field experiment replicated at two sites on the northeast coast of New Zealand. Fouling communities grown on artificial settlement substrata experienced disturbance regimes that differed in their inherent levels of temporal variability and timing of disturbance events, while disturbance intensity was identical across all levels. Additionally, undisturbed assemblages were used as controls. After 150 days of experimental duration, the assemblages were then compared with regard to their species richness, abundance and structure. The disturbance effectively reduced the average total cover of the assemblages, but no consistent effect of variability in the disturbance regime on the assemblages was detected. The results of this study were corroborated by the outcomes from simultaneous replicate experiments carried out in each of eight different biogeographical regions around the world

    Quantitative RT-PCR analysis of differentially expressed genes in Quercus suber in response to Phytophthora cinnamomi infection

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    cDNA-AFLP methodology was used to gain insight into gene fragments differentially present in the mRNA profiles of Quercus suber roots infected with zoospores of Phytophthora cinnamomi at different post challenge time points. Fifty-three transcript-derived fragments (TDFs) were identified and sequenced. Six candidate genes were selected based on their expression patterns and homology to genes known to play a role in defence. They encode a cinnamyl alcohol dehydrogenase2 (QsCAD2), a protein disulphide isomerase (QsPDI), a CC-NBS-LRR resistance protein (QsRPc), a thaumatin-like protein (QsTLP), a chitinase (QsCHI) and a 1,3-β-glucanase (QsGlu). Evaluation of the expression of these genes by quantitative polymerase chain reaction (qPCR) revealed that transcript levels of QsRPc, QsCHI, QsCAD2 and QsPDI increased during the first 24 h post-inoculation, while those of thaumatin-like protein decreased. No differential expression was observed for 1,3-β-glucanase (QsGlu).Four candidate reference genes, polymerase II (QsRPII), eukaryotic translation initiation factor 5A (QsEIF-5A), β-tubulin (QsTUB) and a medium subunit family protein of clathrin adaptor complexes (QsCACs) were assessed to determine the most stable internal references for qRT-PCR normalization in the Phytophthora-Q. suber pathosystem in root tissues. Those found to be more stable, QsRPII and QsCACs, were used as internal reference in the present work.Knowledge on the Quercus defence mechanisms against biotic stress is scarce. This study provides an insight into the gene profiling of a few important genes of Q. suber in response to P. cinnamomi infection contributing to the knowledge of the molecular interactions involving Quercus and root pathogens that can be useful in the future to understand the mechanisms underlying oak resistance to soil-borne oomycetes.Peer Reviewe

    Experience-based utility and own health state valuation for a health state classification system: why do it and how to do it

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    In the estimation of population value sets for health state classification systems such as the EQ-5D, there is increasing interest in asking respondents to value their own health state, sometimes referred to as "experienced-based utility values" or more correctly ownrather than hypothetical health states. Own health state values differ to hypothetical health state values, and this may be attributed to many reasons. This paper critically examines: whose values matter; why there is a difference between own and hypothetical values; how to measure own health state values; and why to use own health state values. Finally, the paper also examines other ways that own health state values can be taken into account, such as including the use of informed general population preferences that may better take into account experience-based values

    A systematic, large-scale comparison of transcription factor binding site models

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    Background The modelling of gene regulation is a major challenge in biomedical research. This process is dominated by transcription factors (TFs) and mutations in their binding sites (TFBSs) may cause the misregulation of genes, eventually leading to disease. The consequences of DNA variants on TF binding are modelled in silico using binding matrices, but it remains unclear whether these are capable of accurately representing in vivo binding. In this study, we present a systematic comparison of binding models for 82 human TFs from three freely available sources: JASPAR matrices, HT-SELEX-generated models and matrices derived from protein binding microarrays (PBMs). We determined their ability to detect experimentally verified “real” in vivo TFBSs derived from ENCODE ChIP-seq data. As negative controls we chose random downstream exonic sequences, which are unlikely to harbour TFBS. All models were assessed by receiver operating characteristics (ROC) analysis. Results While the area- under-curve was low for most of the tested models with only 47 % reaching a score of 0.7 or higher, we noticed strong differences between the various position-specific scoring matrices with JASPAR and HT-SELEX models showing higher success rates than PBM-derived models. In addition, we found that while TFBS sequences showed a higher degree of conservation than randomly chosen sequences, there was a high variability between individual TFBSs. Conclusions Our results show that only few of the matrix-based models used to predict potential TFBS are able to reliably detect experimentally confirmed TFBS. We compiled our findings in a freely accessible web application called ePOSSUM (http:/mutationtaster.charite.de/ePOSSUM/) which uses a Bayes classifier to assess the impact of genetic alterations on TF binding in user-defined sequences. Additionally, ePOSSUM provides information on the reliability of the prediction using our test set of experimentally confirmed binding sites
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