892 resultados para emotion dysregulation


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Invasive urothelial cell carcinoma (UCC) is characterized by increased chromosomal instability and follows an aggressive clinical course in contrast to non-invasive disease. To identify molecular processes that confer and maintain an aggressive malignant phenotype, we used a high-throughput genome-wide approach to interrogate a cohort of high and low clinical risk UCC tumors. Differential expression analyses highlighted cohesive dysregulation of critical genes involved in the G(2)/M checkpoint in aggressive UCC. Hierarchical clustering based on DNA Damage Response (DDR) genes separated tumors according to a pre-defined clinical risk phenotype. Using array-comparative genomic hybridization, we confirmed that the DDR was disrupted in tumors displaying high genomic instability. We identified DNA copy number gains at 20q13.2-q13.3 (AURKA locus) and determined that overexpression of AURKA accompanied dysregulation of DDR genes in high risk tumors. We postulated that DDR-deficient UCC tumors are advantaged by a selective pressure for AURKA associated override of M phase barriers and confirmed this in an independent tissue microarray series. This mechanism that enables cancer cells to maintain an aggressive phenotype forms a rationale for targeting AURKA as a therapeutic strategy in advanced stage UCC.

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Aberrant activation of Wnt/β-catenin signaling, resulting in the expression of Wnt-regulated oncogenes, is recognized as a critical factor in the etiology of colorectal cancer. Occupancy of β-catenin at promoters of Wnt target genes drives transcription, but the mechanism of β-catenin action remains poorly understood. Here, we show that CARM1 (coactivator-associated arginine methyltransferase 1) interacts with β-catenin and positively modulates β-catenin-mediated gene expression. In colorectal cancer cells with constitutively high Wnt/β-catenin activity, depletion of CARM1 inhibits expression of endogenous Wnt/β-catenin target genes and suppresses clonal survival and anchorage-independent growth. We also identified a colorectal cancer cell line (RKO) with a low basal level of β-catenin, which is dramatically elevated by treatment with Wnt3a. Wnt3a also increased the expression of a subset of endogenous Wnt target genes, and CARM1 was required for the Wnt-induced expression of these target genes and the accompanying dimethylation of arginine 17 of histone H3. Depletion of β-catenin from RKO cells diminished the Wnt-induced occupancy of CARM1 on a Wnt target gene, indicating that CARM1 is recruited to Wnt target genes through its interaction with β-catenin and contributes to transcriptional activation by mediating events (including histone H3 methylation) that are downstream from the actions of β-catenin. Therefore, CARM1 is an important positive modulator of Wnt/β-catenin transcription and neoplastic transformation, and may thereby represent a novel target for therapeutic intervention in cancers involving aberrantly activated Wnt/β-catenin signaling.

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Research in emotion analysis of text suggest that emotion lexicon based features are superior to corpus based n-gram features. However the static nature of the general purpose emotion lexicons make them less suited to social media analysis, where the need to adopt to changes in vocabulary usage and context is crucial. In this paper we propose a set of methods to extract a word-emotion lexicon automatically from an emotion labelled corpus of tweets. Our results confirm that the features derived from these lexicons outperform the standard Bag-of-words features when applied to an emotion classification task. Furthermore, a comparative analysis with both manually crafted lexicons and a state-of-the-art lexicon generated using Point-Wise Mutual Information, show that the lexicons generated from the proposed methods lead to significantly better classi- fication performance.

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Prior research has found that affect and affective imagery strongly influence public support for global warming. This article extends this literature by exploring the separate influence of discrete emotions. Utilizing a nationally representative survey in the United States, this study found that discrete emotions were stronger predictors of global warming policy support than cultural worldviews, negative affect, image associations, or sociodemographic variables. In particular, worry, interest, and hope were strongly associated with increased policy support. The results contribute to experiential theories of risk information processing and suggest that discrete emotions play a significant role in public support for climate change policy. Implications for climate change communication are also discussed.

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Group decision making plays an important role in organizations, especially in the present-day economy that demands high-quality, yet quick decisions. Group decision-support systems (GDSSs) are interactive computer-based environments that support concerted, coordinated team efforts toward the completion of joint tasks. The need for collaborative work in organizations has led to the development of a set of general collaborative computer-supported technologies and specific GDSSs that support distributed groups (in time and space) in various domains. However, each person is unique and has different reactions to various arguments. Many times a disagreement arises because of the way we began arguing, not because of the content itself. Nevertheless, emotion, mood, and personality factors have not yet been addressed in GDSSs, despite how strongly they influence results. Our group’s previous work considered the roles that emotion and mood play in decision making. In this article, we reformulate these factors and include personality as well. Thus, this work incorporates personality, emotion, and mood in the negotiation process of an argumentbased group decision-making process. Our main goal in this work is to improve the negotiation process through argumentation using the affective characteristics of the involved participants. Each participant agent represents a group decision member. This representation lets us simulate people with different personalities. The discussion process between group members (agents) is made through the exchange of persuasive arguments. Although our multiagent architecture model4 includes two types of agents—the facilitator and the participant— this article focuses on the emotional, personality, and argumentation components of the participant agent.

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Involving groups in important management processes such as decision making has several advantages. By discussing and combining ideas, counter ideas, critical opinions, identified constraints, and alternatives, a group of individuals can test potentially better solutions, sometimes in the form of new products, services, and plans. In the past few decades, operations research, AI, and computer science have had tremendous success creating software systems that can achieve optimal solutions, even for complex problems. The only drawback is that people don’t always agree with these solutions. Sometimes this dissatisfaction is due to an incorrect parameterization of the problem. Nevertheless, the reasons people don’t like a solution might not be quantifiable, because those reasons are often based on aspects such as emotion, mood, and personality. At the same time, monolithic individual decisionsupport systems centered on optimizing solutions are being replaced by collaborative systems and group decision-support systems (GDSSs) that focus more on establishing connections between people in organizations. These systems follow a kind of social paradigm. Combining both optimization- and socialcentered approaches is a topic of current research. However, even if such a hybrid approach can be developed, it will still miss an essential point: the emotional nature of group participants in decision-making tasks. We’ve developed a context-aware emotion based model to design intelligent agents for group decision-making processes. To evaluate this model, we’ve incorporated it in an agent-based simulator called ABS4GD (Agent-Based Simulation for Group Decision), which we developed. This multiagent simulator considers emotion- and argument based factors while supporting group decision-making processes. Experiments show that agents endowed with emotional awareness achieve agreements more quickly than those without such awareness. Hence, participant agents that integrate emotional factors in their judgments can be more successful because, in exchanging arguments with other agents, they consider the emotional nature of group decision making.

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Current explanatory models for binge eating in binge eating disorder (BED) mostly rely onmodels for bulimianervosa (BN), although research indicates different antecedents for binge eating in BED. This studyinvestigates antecedents and maintaining factors in terms of positive mood, negative mood and tension in asample of 22 women with BED using ecological momentary assessment over a 1-week. Values for negativemood were higher and those for positive mood lower during binge days compared with non-binge days.During binge days, negative mood and tension both strongly and significantly increased and positive moodstrongly and significantly decreased at the first binge episode, followed by a slight though significant, andlonger lasting decrease (negative mood, tension) or increase (positive mood) during a 4-h observation periodfollowing binge eating. Binge eating in BED seems to be triggered by an immediate breakdown of emotionregulation. There are no indications of an accumulation of negative mood triggering binge eating followed byimmediate reinforcing mechanisms in terms of substantial and stable improvement of mood as observed inBN. These differences implicate a further specification of etiological models and could serve as a basis fordeveloping new treatment approaches for BED.

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Human decision-making has consistently demonstrated deviation from "pure" rationality. Emotions are a primary driver of human actions and the current study investigates how perceived emotions and personality traits may affect decision-making during the Ultimatum Game (UG). We manipulated emotions by showing images with emotional connotation while participants decided how to split money with a second player. Event-related potentials (ERPs) from scalp electrodes were recorded during the whole decision-making process. We observed significant differences in the activity of central and frontal areas when participants offered money with respect to when they accepted or rejected an offer. We found that participants were more likely to offer a higher amount of money when making their decision in association with negative emotions. Furthermore, participants were more likely to accept offers when making their decision in association with positive emotions. Honest, conscientious, and introverted participants were more likely to accept offers. Our results suggest that factors others than a rational strategy may predict economic decision-making in the UG.

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The purpose of this study was to explore the frequency of risk behaviours among Swiss adolescents and their links with risk perception, impulsivity and emotion regulation abilities, operationalized with the concepts of alexithymia and emo- tional openness. We recruited 144 subjects (aged 14-20), who completed the Risk Involvement and Perception Scale (RIPS-R), the UPPS Impulsive Behavior Scale, the 20-item Toronto Alexithymia Scale (TAS-20), and the 20-item Dimensions of Openness to Emotional Experiences (DOE-20) questionnaire. Findings revealed that a greater perception of benefits and a higher level of sensation seeking were associated with more involvement in risk behaviours, which are essentially socially accepted behaviours. Notably, the path model indicated that the perception of benefits was a mediator in the relationship between sensation seeking and risk behaviours. The results add to the psychological understanding of factors associated with risk behaviours in adolescence. The limitations and implications of these results for developmental theories, research, and prevention are stated.