153 research outputs found

    The effect of the Cox-maze procedure for atrial fibrillation concomitant to mitral and tricuspid valve surgery

    Get PDF
    ObjectivesAtrial fibrillation (AF) is associated with less favorable outcomes in patients undergoing mitral valve and tricuspid valve surgery. Despite growing evidence on the potential benefits of surgical ablation for AF there is significant variability among surgeons in treatment of AF. The purpose of our study was to assess the effect of the Cox-maze procedure on operative and follow-up outcomes.MethodsIn our prospective study, patients who underwent isolated mitral valve or mitral valve+tricuspid valve surgery without history of AF (n = 506), with untreated AF (n = 75), or with Cox-maze procedure (n = 236) were included (N = 817). Sinus rhythm was captured according to Heart Rhythm Society guidelines. Patients who underwent the Cox-maze procedure were propensity score matched to patients without history of AF resulting in 208 pairs of patients.ResultsOperative outcomes were comparable after propensity score matching (Cox-maze procedure vs no AF) stroke/transient ischemic attack (0.5% vs 0.5%; P = 1.00), renal failure (2.9% vs 1.4%; P = .34), and operative mortality (1.4% vs 1.4%; P = 1.00). High return to sinus rhythm was documented at 6, 12, and 24 months (92%, 91%, and 86%, respectively) as well as sinus rhythm off antiarrhythmic drugs (79%, 84%, and 82%, respectively). Incidence of embolic stroke in patients who underwent Cox-maze procedure was 1.7% (4 out of 232 patients) and 5.1 cases per 1000 person-years. No difference in 4-year cumulative survival between propensity score-matched groups (91.9% vs 86.9%; log rank, 1.67; P = .20), but higher for patients who underwent Cox-maze procedure versus patients with untreated AF (hazard ratio, 2.47; P = .048). Higher additive European System for Cardiac Operative Risk Evaluation (odds ratio, 1.40; P < .001) and limited surgeon experience with Cox-maze procedure (odds ratio, 3.60; P < .001) were significant predictors for failure to perform Cox-maze procedure.ConclusionsIn our center, 76% of patients undergoing mitral valve or mitral valve+tricuspid valve surgery experiencing AF underwent concomitant Cox-maze procedure, which is considerably higher than the national average. No increased morbidity was associated with the Cox-maze procedure with the benefit of very low thromboembolic rate. These results suggest the need for performance-based education for AF surgical ablation to achieve optimal outcomes

    Altered Risk-Based Decision Making following Adolescent Alcohol Use Results from an Imbalance in Reinforcement Learning in Rats

    Get PDF
    Alcohol use during adolescence has profound and enduring consequences on decision-making under risk. However, the fundamental psychological processes underlying these changes are unknown. Here, we show that alcohol use produces over-fast learning for better-than-expected, but not worse-than-expected, outcomes without altering subjective reward valuation. We constructed a simple reinforcement learning model to simulate altered decision making using behavioral parameters extracted from rats with a history of adolescent alcohol use. Remarkably, the learning imbalance alone was sufficient to simulate the divergence in choice behavior observed between these groups of animals. These findings identify a selective alteration in reinforcement learning following adolescent alcohol use that can account for a robust change in risk-based decision making persisting into later life

    ENU Mutagenesis Identifies Mice with Morbid Obesity and Severe Hyperinsulinemia Caused by a Novel Mutation in Leptin

    Get PDF
    BACKGROUND: Obesity is a multifactorial disease that arises from complex interactions between genetic predisposition and environmental factors. Leptin is central to the regulation of energy metabolism and control of body weight in mammals. METHODOLOGY/PRINCIPAL FINDINGS: To better recapitulate the complexity of human obesity syndrome, we applied N-ethyl-N-nitrosourea (ENU) mutagenesis in combination with a set of metabolic assays in screening mice for obesity. Mapping revealed linkage to the chromosome 6 within a region containing mouse Leptin gene. Sequencing on the candidate genes identified a novel T-to-A mutation in the third exon of Leptin gene, which translates to a V145E amino acid exchange in the leptin propeptide. Homozygous Leptin(145E/145E) mutant mice exhibited morbid obesity, accompanied by adipose hypertrophy, energy imbalance, and liver steatosis. This was further associated with severe insulin resistance, hyperinsulinemia, dyslipidemia, and hyperleptinemia, characteristics of human obesity syndrome. Hypothalamic leptin actions in inhibition of orexigenic peptides NPY and AgRP and induction of SOCS1 and SOCS3 were attenuated in Leptin(145E/145E) mice. Administration of exogenous wild-type leptin attenuated hyperphagia and body weight increase in Leptin(145E/145E) mice. However, mutant V145E leptin coimmunoprecipitated with leptin receptor, suggesting that the V145E mutation does not affect the binding of leptin to its receptor. Molecular modeling predicted that the mutated residue would form hydrogen bond with the adjacent residues, potentially affecting the structure and formation of an active complex with leptin receptor within that region. CONCLUSIONS/SIGNIFICANCE: Thus, our evolutionary, structural, and in vivo metabolic information suggests the residue 145 as of special function significance. The mouse model harboring leptin V145E mutation will provide new information on the current understanding of leptin biology and novel mouse model for the study of human obesity syndrome

    Speed/Accuracy Trade-Off between the Habitual and the Goal-Directed Processes

    Get PDF
    Instrumental responses are hypothesized to be of two kinds: habitual and goal-directed, mediated by the sensorimotor and the associative cortico-basal ganglia circuits, respectively. The existence of the two heterogeneous associative learning mechanisms can be hypothesized to arise from the comparative advantages that they have at different stages of learning. In this paper, we assume that the goal-directed system is behaviourally flexible, but slow in choice selection. The habitual system, in contrast, is fast in responding, but inflexible in adapting its behavioural strategy to new conditions. Based on these assumptions and using the computational theory of reinforcement learning, we propose a normative model for arbitration between the two processes that makes an approximately optimal balance between search-time and accuracy in decision making. Behaviourally, the model can explain experimental evidence on behavioural sensitivity to outcome at the early stages of learning, but insensitivity at the later stages. It also explains that when two choices with equal incentive values are available concurrently, the behaviour remains outcome-sensitive, even after extensive training. Moreover, the model can explain choice reaction time variations during the course of learning, as well as the experimental observation that as the number of choices increases, the reaction time also increases. Neurobiologically, by assuming that phasic and tonic activities of midbrain dopamine neurons carry the reward prediction error and the average reward signals used by the model, respectively, the model predicts that whereas phasic dopamine indirectly affects behaviour through reinforcing stimulus-response associations, tonic dopamine can directly affect behaviour through manipulating the competition between the habitual and the goal-directed systems and thus, affect reaction time

    Temporal-Difference Reinforcement Learning with Distributed Representations

    Get PDF
    Temporal-difference (TD) algorithms have been proposed as models of reinforcement learning (RL). We examine two issues of distributed representation in these TD algorithms: distributed representations of belief and distributed discounting factors. Distributed representation of belief allows the believed state of the world to distribute across sets of equivalent states. Distributed exponential discounting factors produce hyperbolic discounting in the behavior of the agent itself. We examine these issues in the context of a TD RL model in which state-belief is distributed over a set of exponentially-discounting “micro-Agents”, each of which has a separate discounting factor (γ). Each µAgent maintains an independent hypothesis about the state of the world, and a separate value-estimate of taking actions within that hypothesized state. The overall agent thus instantiates a flexible representation of an evolving world-state. As with other TD models, the value-error (δ) signal within the model matches dopamine signals recorded from animals in standard conditioning reward-paradigms. The distributed representation of belief provides an explanation for the decrease in dopamine at the conditioned stimulus seen in overtrained animals, for the differences between trace and delay conditioning, and for transient bursts of dopamine seen at movement initiation. Because each µAgent also includes its own exponential discounting factor, the overall agent shows hyperbolic discounting, consistent with behavioral experiments

    A computational psychiatry approach identifies how alpha-2A noradrenergic agonist Guanfacine affects feature-based reinforcement learning in the macaque

    Get PDF
    [EN] Noradrenaline is believed to support cognitive flexibility through the alpha 2A noradrenergic receptor (a2A-NAR) acting in prefrontal cortex. Enhanced flexibility has been inferred from improved working memory with the a2A-NA agonist Guanfacine. But it has been unclear whether Guanfacine improves specific attention and learning mechanisms beyond working memory, and whether the drug effects can be formalized computationally to allow single subject predictions. We tested and confirmed these suggestions in a case study with a healthy nonhuman primate performing a feature-based reversal learning task evaluating performance using Bayesian and Reinforcement learning models. In an initial dose-testing phase we found a Guanfacine dose that increased performance accuracy, decreased distractibility and improved learning. In a second experimental phase using only that dose we examined the faster feature-based reversal learning with Guanfacine with single-subject computational modeling. Parameter estimation suggested that improved learning is not accounted for by varying a single reinforcement learning mechanism, but by changing the set of parameter values to higher learning rates and stronger suppression of non-chosen over chosen feature information. These findings provide an important starting point for developing nonhuman primate models to discern the synaptic mechanisms of attention and learning functions within the context of a computational neuropsychiatry framework.This research was supported by grants from the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Ontario Ministry of Economic Development and Innovation (MEDI). We thank Dr. Hongying Wang for invaluable help with drug administration and animal careHassani, SA.; Oemisch, M.; Balcarras, M.; Westendorff, S.; Ardid-Ramírez, JS.; Van Der Meer, MA.; Tiesinga, P.... (2017). A computational psychiatry approach identifies how alpha-2A noradrenergic agonist Guanfacine affects feature-based reinforcement learning in the macaque. Scientific Reports. 7:1-19. https://doi.org/10.1038/srep40606S1197Arnsten, A. F., Wang, M. J. & Paspalas, C. D. Neuromodulation of thought: flexibilities and vulnerabilities in prefrontal cortical network synapses. Neuron 76, 223–239 (2012).Arnsten, A. F. & Dudley, A. G. Methylphenidate improves prefrontal cortical cognitive function through alpha2 adrenoceptor and dopamine D1 receptor actions: Relevance to therapeutic effects in Attention Deficit Hyperactivity Disorder. Behav Brain Funct 1, 2 (2005).Clark, K. L. & Noudoost, B. The role of prefrontal catecholamines in attention and working memory. Front Neural Circuits 8, 33 (2014).Wang, M. et al. Neuronal basis of age-related working memory decline. Nature 476, 210–213 (2011).Wang, M. et al. Alpha2A-adrenoceptors strengthen working memory networks by inhibiting cAMP-HCN channel signaling in prefrontal cortex. Cell 129, 397–410 (2007).Aston-Jones, G. & Cohen, J. D. An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. Annu Rev Neurosci 28, 403–450 (2005).Yu, A. J. & Dayan, P. Uncertainty, neuromodulation, and attention. Neuron 46, 681–692 (2005).Mather, M., Clewett, D., Sakaki, M. & Harley, C. W. Norepinephrine ignites local hot spots of neuronal excitation: How arousal amplifies selectivity in perception and memory. Behav Brain Sci, 1–100, doi: 10.1017/S0140525X15000667 (2015).Amemiya, S. & Redish, A. D. Manipulating Decisiveness in Decision Making: Effects of Clonidine on Hippocampal Search Strategies. J Neurosci 36, 814–827 (2016).Doya, K. Metalearning and neuromodulation. Neural Netw 15, 495–506 (2002).Uhlen, S., Muceniece, R., Rangel, N., Tiger, G. & Wikberg, J. E. Comparison of the binding activities of some drugs on alpha 2A, alpha 2B and alpha 2C-adrenoceptors and non-adrenergic imidazoline sites in the guinea pig. Pharmacology & toxicology 76, 353–364 (1995).Mao, Z. M., Arnsten, A. F. & Li, B. M. Local infusion of an alpha-1 adrenergic agonist into the prefrontal cortex impairs spatial working memory performance in monkeys. Biological psychiatry 46, 1259–1265 (1999).Arnsten, A. F. & Goldman-Rakic, P. S. Analysis of alpha-2 adrenergic agonist effects on the delayed nonmatch-to-sample performance of aged rhesus monkeys. Neurobiol Aging 11, 583–590 (1990).Franowicz, J. S. & Arnsten, A. F. The alpha-2a noradrenergic agonist, guanfacine, improves delayed response performance in young adult rhesus monkeys. Psychopharmacology 136, 8–14 (1998).Caetano, M. S. et al. Noradrenergic control of error perseveration in medial prefrontal cortex. Frontiers in Integrative Neuroscience 6, 125 (2012).Kim, S., Bobeica, I., Gamo, N. J., Arnsten, A. F. & Lee, D. Effects of alpha-2A adrenergic receptor agonist on time and risk preference in primates. Psychopharmacology 219, 363–375 (2012).Seu, E., Lang, A., Rivera, R. J. & Jentsch, J. D. Inhibition of the norepinephrine transporter improves behavioral flexibility in rats and monkeys. Psychopharmacology 202, 505–519 (2009).Kawaura, K., Karasawa, J., Chaki, S. & Hikichi, H. Stimulation of postsynapse adrenergic alpha2A receptor improves attention/cognition performance in an animal model of attention deficit hyperactivity disorder. Behav Brain Res 270, 349–356 (2014).Aoki, C., Go, C. G., Venkatesan, C. & Kurose, H. Perikaryal and synaptic localization of alpha 2A-adrenergic receptor-like immunoreactivity. Brain Res 650, 181–204 (1994).Barth, A. M., Vizi, E. S., Zelles, T. & Lendvai, B. Alpha2-adrenergic receptors modify dendritic spike generation via HCN channels in the prefrontal cortex. J Neurophysiol 99, 394–401 (2008).Ji, X. H., Ji, J. Z., Zhang, H. & Li, B. M. Stimulation of alpha2-adrenoceptors suppresses excitatory synaptic transmission in the medial prefrontal cortex of rat. Neuropsychopharmacology 33, 2263–2271 (2008).Yi, F., Liu, S. S., Luo, F., Zhang, X. H. & Li, B. M. Signaling mechanism underlying alpha2A -adrenergic suppression of excitatory synaptic transmission in the medial prefrontal cortex of rats. Eur J Neurosci 38, 2364–2373 (2013).Engberg, G. & Eriksson, E. Effects of alpha 2-adrenoceptor agonists on locus coeruleus firing rate and brain noradrenaline turnover in N-ethoxycarbonyl-2-ethoxy-1,2-dihydroquinoline (EEDQ)-treated rats. Naunyn-Schmiedeberg’s archives of pharmacology 343, 472–477 (1991).Jakala, P. et al. Guanfacine, but not clonidine, improves planning and working memory performance in humans. Neuropsychopharmacology 20, 460–470 (1999).Jakala, P. et al. Guanfacine and clonidine, alpha 2-agonists, improve paired associates learning, but not delayed matching to sample, in humans. Neuropsychopharmacology 20, 119–130 (1999).Muller, U. et al. Lack of effects of guanfacine on executive and memory functions in healthy male volunteers. Psychopharmacology 182, 205–213 (2005).Scahill, L. et al. A placebo-controlled study of guanfacine in the treatment of children with tic disorders and attention deficit hyperactivity disorder. The American journal of psychiatry 158, 1067–1074 (2001).Huys, Q. J. M., Maia, T. V. & Frank, M. J. Computational psychiatry as a bridge from neuroscience to clinical applications. Nat Neurosci 19, 404–413 (2016).Stephan, K. E. et al. Computational neuroimaging strategies for single patient predictions. NeuroImage in press (2015).Arnsten, A. F., Cai, J. X. & Goldman-Rakic, P. S. The alpha-2 adrenergic agonist guanfacine improves memory in aged monkeys without sedative or hypotensive side effects: evidence for alpha-2 receptor subtypes. J Neurosci 8, 4287–4298 (1988).Callado, L. F. & Stamford, J. A. Alpha2A- but not alpha2B/C-adrenoceptors modulate noradrenaline release in rat locus coeruleus: voltammetric data. Eur J Pharmacol 366, 35–39 (1999).Millan, M. J. et al. Cognitive dysfunction in psychiatric disorders: characteristics, causes and the quest for improved therapy. Nature reviews. Drug discovery 11, 141–168 (2012).Niv, Y. et al. Reinforcement learning in multidimensional environments relies on attention mechanisms. J Neurosci 35, 8145–8157 (2015).Balcarras, M., Ardid, S., Kaping, D., Everling, S. & Womelsdorf, T. Attentional Selection Can Be Predicted by Reinforcement Learning of Task-relevant Stimulus Features Weighted by Value-independent Stickiness. J Cogn Neurosci 28, 333–349 (2016).Redish, A. D., Jensen, S., Johnson, A. & Kurth-Nelson, Z. Reconciling reinforcement learning models with behavioral extinction and renewal: implications for addiction, relapse, and problem gambling. Psychol Rev 114, 784–805 (2007).Nassar, M. R. et al. Rational regulation of learning dynamics by pupil-linked arousal systems. Nat Neurosci 15, 1040–1046 (2012).O’Reilly, J. X. et al. Dissociable effects of surprise and model update in parietal and anterior cingulate cortex. Proc Natl Acad Sci USA 110, 3660–3669 (2013).Shenhav, A., Botvinick, M. M. & Cohen, J. D. The expected value of control: an integrative theory of anterior cingulate cortex function. Neuron 79, 217–240 (2013).Womelsdorf, T. & Everling, S. Long-Range Attention Networks: Circuit Motifs Underlying Endogenously Controlled Stimulus Selection. Trends Neurosci 38, 682–700 (2015).Yang, Y. et al. Nicotinic alpha7 receptors enhance NMDA cognitive circuits in dorsolateral prefrontal cortex. Proc Natl Acad Sci USA 110, 12078–12083 (2013).Aston-Jones, G., Rajkowski, J. & Cohen, J. Role of locus coeruleus in attention and behavioral flexibility. Biological psychiatry 46, 1309–1320 (1999).Cole, B. J. & Robbins, T. W. Forebrain norepinephrine: role in controlled information processing in the rat. Neuropsychopharmacology 7, 129–142 (1992).Dalley, J. W., Cardinal, R. N. & Robbins, T. W. Prefrontal executive and cognitive functions in rodents: neural and neurochemical substrates. Neuroscience and biobehavioral reviews 28, 771–784 (2004).Devauges, V. & Sara, S. J. Activation of the noradrenergic system facilitates an attentional shift in the rat. Behav Brain Res 39, 19–28 (1990).Connor, D. F., Arnsten, A. F., Pearson, G. S. & Greco, G. F. Guanfacine extended release for the treatment of attention-deficit/hyperactivity disorder in children and adolescents. Expert opinion on pharmacotherapy 15, 1601–1610 (2014).Sallee, F. R. et al. Guanfacine extended release in children and adolescents with attention-deficit/hyperactivity disorder: a placebo-controlled trial. J Am Acad Child Adolesc Psychiatry 48, 155–165 (2009).Steere, J. C. & Arnsten, A. F. The alpha-2A noradrenergic receptor agonist guanfacine improves visual object discrimination reversal performance in aged rhesus monkeys. Behav Neurosci 111, 883–891 (1997).Doya, K. Modulators of decision making. Nat Neurosci 11, 410–416 (2008).Wang, X. J. & Krystal, J. H. Computational psychiatry. Neuron 84, 638–654 (2014).Wiecki, T. V. et al. A Computational Cognitive Biomarker for Early-Stage Huntington’s Disease. PLoS One 11, e0148409, doi: 10.1371/journal.pone.0148409 (2016).Huys, Q. J., Pizzagalli, D. A., Bogdan, R. & Dayan, P. Mapping anhedonia onto reinforcement learning: a behavioural meta-analysis. Biol Mood Anxiety Disord 3, 12 (2013).Gershman, S. J. & Niv, Y. Learning latent structure: carving nature at its joints. Curr Opin Neurobiol 20, 251–256 (2010).Voon, V. et al. Disorders of compulsivity: a common bias towards learning habits. Mol Psychiatry 20, 345–352 (2015).Maia, T. V. & Frank, M. J. From reinforcement learning models to psychiatric and neurological disorders. Nature Neuroscience 14, 154–162 (2011).Adams, R. A., Huys, Q. J. M. & Roiser, J. P. Computational Psychiatry: towards a mathematically informed understanding of mental illness. Journal of Neurology, Neurosurgery, and Psychiatry 87, 53–63 (2015).Schlagenhauf, F. et al. Striatal dysfunction during reversal learning in unmedicated schizophrenia patients. NeuroImage 89, 171–180 (2014).Harlé, K. M. et al. Bayesian neural adjustment of inhibitory control predicts emergence of problem stimulant use. Brain 138, 3413–3426 (2015).Zhang, J. et al. Different decision deficits impair response inhibition in progressive supranuclear palsy and Parkinson’s disease. Brain 139, 161–173 (2016).Frank, M. J. et al. fMRI and EEG Predictors of Dynamic Decision Parameters during Human Reinforcement Learning. Journal of Neuroscience 35, 485–494 (2015).Smith, A. C. & Brown, E. N. Estimating a state-space model from point process observations. Neural Comput 15, 965–991 (2003).Wilson, R. C. & Niv, Y. Inferring relevance in a changing world. Frontiers in human neuroscience 5, 189 (2011).Rämä, P. et al. Medetomidine, atipamezole, and guanfacine in delayed response performance of aged monkeys. Pharmacology Biochemistry and Behavior 55, 415–422 (1996).Arnsten, A. F. T. & Contant, T. A. Alpha-2 adrenergic agonists decrease distractibility in aged monkeys performing the delayed response task. Psychopharmacology 108, 159–169 (1992).O’Neill, J. et al. Effects of guanfacine on three forms of distraction in the aging macaque. Life Sciences 67, 877–885 (2000).Wang, M., Ji, J.-Z. & Li, B.-M. The α2A-Adrenergic Agonist Guanfacine Improves Visuomotor Associative Learning in Monkeys. Neuropsychopharmacology 29, 86–92 (2004).Witte, E. a. & Marrocco, R. T. Alteration of brain noradrenergic activity in rhesus monkeys affects the alerting component of covert orienting. Psychopharmacology 132, 315–323 (1997).Decamp, E., Clark, K. & Schneider, J. S. Effects of the alpha-2 adrenoceptor agonist guanfacine on attention and working memory in aged non-human primates. European Journal of Neuroscience 34, 1018–1022 (2011)

    Early onset MSI-H colon cancer with MLH1 promoter methylation, is there a genetic predisposition?

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>To investigate the etiology of <it>MLH1 </it>promoter methylation in mismatch repair (MMR) mutation-negative early onset MSI-H colon cancer. As this type of colon cancer is associated with high ages, young patients bearing this type of malignancy are rare and could provide additional insight into the etiology of sporadic MSI-H colon cancer.</p> <p>Methods</p> <p>We studied a set of 46 MSI-H colon tumors cases with <it>MLH1 </it>promoter methylation which was enriched for patients with an age of onset below 50 years (n = 13). Tumors were tested for CIMP marker methylation and mutations linked to methylation: <it>BRAF, KRAS</it>, <it>GADD45A </it>and the <it>MLH1 </it>-93G>A polymorphism. When available, normal colon and leukocyte DNA was tested for <it>GADD45A </it>mutations and germline <it>MLH1 </it>methylation. SNP array analysis was performed on a subset of tumors.</p> <p>Results</p> <p>We identified two cases (33 and 60 years) with <it>MLH1 </it>germline promoter methylation. <it>BRAF </it>mutations were less frequent in colon cancer patients below 50 years relative to patients above 50 years (p-value: 0.044). CIMP-high was infrequent and related to <it>BRAF </it>mutations in patients below 50 years. In comparison with published controls the G>A polymorphism was associated with our cohort. Although similar distribution of the pathogenic A allele was observed in the patients with an age of onset above and below 50 years, the significance for the association was lost for the group under 50 years. <it>GADD45A </it>sequencing yielded an unclassified variant. Tumors from both age groups showed infrequent copy number changes and loss-of-heterozygosity.</p> <p>Conclusion</p> <p>Somatic or germline <it>GADD45A </it>mutations did not explain sporadic MSI-H colon cancer. Although germline <it>MLH1 </it>methylation was found in two individuals, locus-specific somatic <it>MLH1 </it>hypermethylation explained the majority of sporadic early onset MSI-H colon cancer cases. Our data do not suggest an intrinsic tendency for CpG island hypermethylation in these early onset MSI-H tumors other than through somatic mutation of <it>BRAF</it>.</p
    corecore