964 resultados para Computational model of emotion
Resumo:
BACKGROUND:: Voltage-gated sodium channels dysregulation is important for hyperexcitability leading to pain persistence. Sodium channel blockers currently used to treat neuropathic pain are poorly tolerated. Getting new molecules to clinical use is laborious. We here propose a drug already marketed as anticonvulsant, rufinamide. METHODS:: We compared the behavioral effect of rufinamide to amitriptyline using the Spared Nerve Injury neuropathic pain model in mice. We compared the effect of rufinamide on sodium currents using in vitro patch clamp in cells expressing the voltage-gated sodium channel Nav1.7 isoform and on dissociated dorsal root ganglion neurons to amitriptyline and mexiletine. RESULTS:: In naive mice, amitriptyline (20 mg/kg) increased withdrawal threshold to mechanical stimulation from 1.3 (0.6-1.9) (median [95% CI]) to 2.3 g (2.2-2.5) and latency of withdrawal to heat stimulation from 13.1 (10.4-15.5) to 30.0 s (21.8-31.9), whereas rufinamide had no effect. Rufinamide and amitriptyline alleviated injury-induced mechanical allodynia for 4 h (maximal effect: 0.10 ± 0.03 g (mean ± SD) to 1.99 ± 0.26 g for rufinamide and 0.25 ± 0.22 g to 1.92 ± 0.85 g for amitriptyline). All drugs reduced peak current and stabilized the inactivated state of voltage-gated sodium channel Nav1.7, with similar effects in dorsal root ganglion neurons. CONCLUSIONS:: At doses alleviating neuropathic pain, amitriptyline showed alteration of behavioral response possibly related to either alteration of basal pain sensitivity or sedative effect or both. Side-effects and drug tolerance/compliance are major problems with drugs such as amitriptyline. Rufinamide seems to have a better tolerability profile and could be a new alternative to explore for the treatment of neuropathic pain.
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Machado-Joseph disease or Spinocerebellar ataxia type 3 is a progressive fatal neurodegenerative disorder caused by the polyglutamine-expanded protein ataxin-3. Recent studies demonstrate that RNA interference is a promising approach for the treatment of Machado-Joseph disease. However, whether gene silencing at an early time-point is able to prevent the appearance of motor behavior deficits typical of the disease when initiated before onset of the disease had not been explored. Here, using a lentiviral-mediated allele-specific silencing of mutant ataxin-3 in an early pre-symptomatic cerebellar mouse model of Machado-Joseph disease we show that this strategy hampers the development of the motor and neuropathological phenotypic characteristics of the disease. At the histological level, the RNA-specific silencing of mutant ataxin-3 decreased formation of mutant ataxin-3 aggregates, preserved Purkinje cell morphology and expression of neuronal markers while reducing cell death. Importantly, gene silencing prevented the development of impairments in balance, motor coordination, gait and hyperactivity observed in control mice. These data support the therapeutic potential of RNA interference for Machado-Joseph disease and constitute a proof of principle of the beneficial effects of early allele-specific silencing for therapy of this disease.
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When individuals learn by trial-and-error, they perform randomly chosen actions and then reinforce those actions that led to a high payoff. However, individuals do not always have to physically perform an action in order to evaluate its consequences. Rather, they may be able to mentally simulate actions and their consequences without actually performing them. Such fictitious learners can select actions with high payoffs without making long chains of trial-and-error learning. Here, we analyze the evolution of an n-dimensional cultural trait (or artifact) by learning, in a payoff landscape with a single optimum. We derive the stochastic learning dynamics of the distance to the optimum in trait space when choice between alternative artifacts follows the standard logit choice rule. We show that for both trial-and-error and fictitious learners, the learning dynamics stabilize at an approximate distance of root n/(2 lambda(e)) away from the optimum, where lambda(e) is an effective learning performance parameter depending on the learning rule under scrutiny. Individual learners are thus unlikely to reach the optimum when traits are complex (n large), and so face a barrier to further improvement of the artifact. We show, however, that this barrier can be significantly reduced in a large population of learners performing payoff-biased social learning, in which case lambda(e) becomes proportional to population size. Overall, our results illustrate the effects of errors in learning, levels of cognition, and population size for the evolution of complex cultural traits. (C) 2013 Elsevier Inc. All rights reserved.
Resumo:
Determination of brain glucose transport kinetics in vivo at steady-state typically does not allow distinguishing apparent maximum transport rate (T(max)) from cerebral consumption rate. Using a four-state conformational model of glucose transport, we show that simultaneous dynamic measurement of brain and plasma glucose concentrations provide enough information for independent and reliable determination of the two rates. In addition, although dynamic glucose homeostasis can be described with a reversible Michaelis-Menten model, which is implicit to the large iso-inhibition constant (K(ii)) relative to physiological brain glucose content, we found that the apparent affinity constant (K(t)) was better determined with the four-state conformational model of glucose transport than with any of the other models tested. Furthermore, we confirmed the utility of the present method to determine glucose transport and consumption by analysing the modulation of both glucose transport and consumption by anaesthesia conditions that modify cerebral activity. In particular, deep thiopental anaesthesia caused a significant reduction of both T(max) and cerebral metabolic rate for glucose consumption. In conclusion, dynamic measurement of brain glucose in vivo in function of plasma glucose allows robust determination of both glucose uptake and consumption kinetics.
A biophysical model of atrial fibrillation ablation: what can a surgeon learn from a computer model?
Resumo:
AIMS: Surgical ablation procedures for treating atrial fibrillation have been shown to be highly successful. However, the ideal ablation pattern still remains to be determined. This article reports on a systematic study of the effectiveness of the performance of different ablation line patterns. METHODS AND RESULTS: This study of ablation line patterns was performed in a biophysical model of human atria by combining basic lines: (i) in the right atrium: isthmus line, line between vena cavae and appendage line and (ii) in the left atrium: several versions of pulmonary vein isolation, connection of pulmonary veins, isthmus line, and appendage line. Success rates and the presence of residual atrial flutter were documented. Basic patterns yielded conversion rates of only 10-25 and 10-55% in the right and the left atria, respectively. The best result for pulmonary vein isolation was obtained when a single closed line encompassed all veins (55%). Combination of lines in the right/left atrium only led to a success rate of 65/80%. Higher rates, up to 90-100%, could be obtained if right and left lines were combined. The inclusion of a left isthmus line was found to be essential for avoiding uncommon left atrial flutter. CONCLUSION: Some patterns studied achieved a high conversion rate, although using a smaller number of lines than those of the Maze III procedure. The biophysical atrial model is shown to be effective in the search for promising alternative ablation strategies.
Resumo:
Mutations in RPE65 protein is characterized by the loss of photoreceptors, although the molecular pathways triggering retinal cell death remain largely unresolved. The role of the Bcl-2 family of proteins in retinal degeneration is still controversial. However, alteration in Bcl-2-related proteins has been observed in several models of retinal injury. In particular, Bax has been suggested to play a crucial role in apoptotic pathways in murine glaucoma model as well as in retinal detachment-associated cell death. We demonstrated that Bcl-2-related signaling pathway is involved in Rpe65-dependent apoptosis of photoreceptors during development of the disease. Pro-apoptotic Bax alpha and beta isoforms were upregulated in diseased retina. This was associated with a progressive reduction of anti-apoptotic Bcl-2, reflecting imbalanced Bcl-2/Bax ratio as the disease progresses. Moreover, specific translocation of Bax beta from cytosol to mitochondria was observed in Rpe65-deficient retina. This correlated with the initiation of photoreceptor cell loss at 4 months of age, and further increased during disease development. Altogether, these data suggest that Bcl-2-apoptotic pathway plays a crucial role in Leber's congenital amaurosis disease. They further highlight a new regulatory mechanism of Bax-dependent apoptosis based on regulated expression and activation of specific isoforms of this protein.
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In this paper I present an endogenous growth model where the engine of growth is in-house R&D performed by high-tech firms. I model knowledge (patent) licensing among high-tech firms. I show that if there is knowledge licensing, high-tech firms innovate more and economic growth is higher than in cases when there are knowledge spillovers or there is no exchange of knowledge among high-tech firms. However, in case when there is knowledge licensing the number of high-tech firms is lower than in cases when there are knowledge spillovers or there is no exchange of knowledge.
Resumo:
In this paper I present an endogenous growth model where the engine of growth is in-house R&D performed by high-tech firms. I model knowledge (patent) licensing among high-tech firms. I show that if there is knowledge licensing, high-tech firms innovate more and economic growth is higher than in cases when there are knowledge spillovers or there is no exchange of knowledge among high-tech firms. However, in case when there is knowledge licensing the number of high-tech firms is lower than in cases when there are knowledge spillovers or there is no exchange of knowledge.
Resumo:
Although metabolic syndrome (MS) and systemic lupus erythematosus (SLE) are often associated, a common link has not been identified. Using the BWF1 mouse, which develops MS and SLE, we sought a molecular connection to explain the prevalence of these two diseases in the same individuals. We determined SLE- markers (plasma anti-ds-DNA antibodies, splenic regulatory T cells (Tregs) and cytokines, proteinuria and renal histology) and MS-markers (plasma glucose, non-esterified fatty acids, triglycerides, insulin and leptin, liver triglycerides, visceral adipose tissue, liver and adipose tissue expression of 86 insulin signaling-related genes) in 8-, 16-, 24-, and 36-week old BWF1 and control New-Zealand-White female mice. Up to week 16, BWF1 mice showed MS-markers (hyperleptinemia, hyperinsulinemia, fatty liver and visceral adipose tissue) that disappeared at week 36, when plasma anti-dsDNA antibodies, lupus nephritis and a pro-autoimmune cytokine profile were detected. BWF1 mice had hyperleptinemia and high splenic Tregs till week 16, thereby pointing to leptin resistance, as confirmed by the lack of increased liver P-Tyr-STAT-3. Hyperinsulinemia was associated with a down-regulation of insulin related-genes only in adipose tissue, whereas expression of liver mammalian target of rapamicyn (mTOR) was increased. Although leptin resistance presented early in BWF1 mice can slow-down the progression of autoimmunity, our results suggest that sustained insulin stimulation of organs, such as liver and probably kidneys, facilitates the over-expression and activity of mTOR and the development of SLE.
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We presented an integrated hierarchical model of psychopathology that more accurately captures empirical patterns of comorbidity between clinical syndromes and personality disorders.In order to verify the structural validity of the model proposed, this study aimed to analyze the convergence between the Restructured Clinical (RC) scales and Personality scales (PSY-5) of the MMPI-2-RF and the Clinical Syndrome and Personality Disorder scales of the MCMI-III.The MMPI-2-RF and MCMI-III were administered to a clinical sample of 377 outpatients (167 men and 210 women).The structural hypothesiswas assessed by using a Confirmatory Factor Analytic design with four common superordinate factors. An independent-cluster-basis solution was proposed based on maximum likelihood estimation and the application of several fit indices.The fit of the proposed model can be considered as good and more so if we take into account its complexity.