6 resultados para failure time model

em Duke University


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Considerable scientific and intervention attention has been paid to judgment and decision-making systems associated with aggressive behavior in youth. However, most empirical studies have investigated social-cognitive correlates of stable child and adolescent aggressiveness, and less is known about real-time decision making to engage in aggressive behavior. A model of real-time decision making must incorporate both impulsive actions and rational thought. The present paper advances a process model (response evaluation and decision; RED) of real-time behavioral judgments and decision making in aggressive youths with mathematic representations that may be used to quantify response strength. These components are a heuristic to describe decision making, though it is doubtful that individuals always mentally complete these steps. RED represents an organization of social-cognitive operations believed to be active during the response decision step of social information processing. The model posits that RED processes can be circumvented through impulsive responding. This article provides a description and integration of thoughtful, rational decision making and nonrational impulsivity in aggressive behavioral interactions.

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Chronic human heart failure is characterized by abnormalities in beta-adrenergic receptor (betaAR) signaling, including increased levels of betaAR kinase 1 (betaARK1), which seems critical to the pathogenesis of the disease. To determine whether inhibition of betaARK1 is sufficient to rescue a model of severe heart failure, we mated transgenic mice overexpressing a peptide inhibitor of betaARK1 (betaARKct) with transgenic mice overexpressing the sarcoplasmic reticulum Ca(2+)-binding protein, calsequestrin (CSQ). CSQ mice have a severe cardiomyopathy and markedly shortened survival (9 +/- 1 weeks). In contrast, CSQ/betaARKct mice exhibited a significant increase in mean survival age (15 +/- 1 weeks; P < 0.0001) and showed less cardiac dilation, and cardiac function was significantly improved (CSQ vs. CSQ/betaARKct, left ventricular end diastolic dimension 5.60 +/- 0.17 mm vs. 4.19 +/- 0.09 mm, P < 0.005; % fractional shortening, 15 +/- 2 vs. 36 +/- 2, P < 0.005). The enhancement of the survival rate in CSQ/betaARKct mice was substantially potentiated by chronic treatment with the betaAR antagonist metoprolol (CSQ/betaARKct nontreated vs. CSQ/betaARKct metoprolol treated, 15 +/- 1 weeks vs. 25 +/- 2 weeks, P < 0.0001). Thus, overexpression of the betaARKct resulted in a marked prolongation in survival and improved cardiac function in a mouse model of severe cardiomyopathy that can be potentiated with beta-blocker therapy. These data demonstrate a significant synergy between an established heart-failure treatment and the strategy of betaARK1 inhibition.

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A model of telescoping is proposed that assumes no systematic errors in dating. Rather, the overestimation of recent occurrences of events is based on the combination of three factors: (1) Retention is greater for recent events; (2) errors in dating, though unbiased, increase linearly with the time since the dated event; and (3) intrusions often occur from events outside the period being asked about, but such intrusions do not come from events that have not yet occurred. In Experiment 1, we found that recall for colloquia fell markedly over a 2-year interval, the magnitude of errors in psychologists' dating of the colloquia increased at a rate of .4 days per day of delay, and the direction of the dating error was toward the middle of the interval. In Experiment 2, the model used the retention function and dating errors from the first study to predict the distribution of the actual dates of colloquia recalled as being within a 5-month period. In Experiment 3, the findings of the first study were replicated with colloquia given by, instead of for, the subjects.

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We introduce a dynamic directional model (DDM) for studying brain effective connectivity based on intracranial electrocorticographic (ECoG) time series. The DDM consists of two parts: a set of differential equations describing neuronal activity of brain components (state equations), and observation equations linking the underlying neuronal states to observed data. When applied to functional MRI or EEG data, DDMs usually have complex formulations and thus can accommodate only a few regions, due to limitations in spatial resolution and/or temporal resolution of these imaging modalities. In contrast, we formulate our model in the context of ECoG data. The combined high temporal and spatial resolution of ECoG data result in a much simpler DDM, allowing investigation of complex connections between many regions. To identify functionally segregated sub-networks, a form of biologically economical brain networks, we propose the Potts model for the DDM parameters. The neuronal states of brain components are represented by cubic spline bases and the parameters are estimated by minimizing a log-likelihood criterion that combines the state and observation equations. The Potts model is converted to the Potts penalty in the penalized regression approach to achieve sparsity in parameter estimation, for which a fast iterative algorithm is developed. The methods are applied to an auditory ECoG dataset.

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When the heart fails, there is often a constellation of biochemical alterations of the beta-adrenergic receptor (betaAR) signaling system, leading to the loss of cardiac inotropic reserve. betaAR down-regulation and functional uncoupling are mediated through enhanced activity of the betaAR kinase (betaARK1), the expression of which is increased in ischemic and failing myocardium. These changes are widely viewed as representing an adaptive mechanism, which protects the heart against chronic activation. In this study, we demonstrate, using in vivo intracoronary adenoviral-mediated gene delivery of a peptide inhibitor of betaARK1 (betaARKct), that the desensitization and down-regulation of betaARs seen in the failing heart may actually be maladaptive. In a rabbit model of heart failure induced by myocardial infarction, which recapitulates the biochemical betaAR abnormalities seen in human heart failure, delivery of the betaARKct transgene at the time of myocardial infarction prevents the rise in betaARK1 activity and expression and thereby maintains betaAR density and signaling at normal levels. Rather than leading to deleterious effects, cardiac function is improved, and the development of heart failure is delayed. These results appear to challenge the notion that dampening of betaAR signaling in the failing heart is protective, and they may lead to novel therapeutic strategies to treat heart disease via inhibition of betaARK1 and preservation of myocardial betaAR function.