ILK Induces Cardiomyogenesis in the Human Heart

Integrin-linked kinase (ILK) is a widely conserved serine/threonine kinase that regulates diverse signal transduction pathways implicated in cardiac hypertrophy and contractility. In this study we explored whether experimental overexpression of ILK would up-regulate morphogenesis in the human fetal heart.Primary cultures of human fetal myocardial cells (19-22 weeks gestation) yielded scattered aggregates of cardioblasts positive for the early cardiac lineage marker nk × 2.5 and containing nascent sarcomeres. Cardiac cells in colonies uniformly expressed the gap junction protein connexin 43 (C × 43) and displayed a spectrum of differentiation with only a subset of cells exhibiting the late cardiomyogenic marker troponin T (cTnT) and evidence of electrical excitability. Adenovirus-mediated overexpression of ILK potently increased the number of new aggregates of primitive cardioblasts (p<0.001). The number of cardioblast colonies was significantly decreased (p<0.05) when ILK expression was knocked down with ILK targeted siRNA. Interestingly, overexpression of the activation resistant ILK mutant (ILK(R211A)) resulted in much greater increase in the number of new cell aggregates as compared to overexpression of wild-type ILK (ILK(WT)). The cardiomyogenic effects of ILK(R211A) and ILK(WT) were accompanied by concurrent activation of β-catenin (p<0.001) and increase expression of progenitor cell marker islet-1, which was also observed in lysates of transgenic mice with cardiac-specific over-expression of ILK(R211A) and ILK(WT). Finally, endogenous ILK expression was shown to increase in concert with those of cardiomyogenic markers during directed cardiomyogenic differentiation in human embryonic stem cells (hESCs).In the human fetal heart ILK activation is instructive to the specification of mesodermal precursor cells towards a cardiomyogenic lineage. Induction of cardiomyogenesis by ILK overexpression bypasses the requirement of proximal PI3K activation for transduction of growth factor- and β1-integrin-mediated differentiation signals. Altogether, our data indicate that ILK represents a novel regulatory checkpoint during human cardiomyogenesis

A Neural Computational Model of Incentive Salience

Incentive salience is a motivational property with ‘magnet-like’ qualities. When attributed to reward-predicting stimuli (cues), incentive salience triggers a pulse of ‘wanting’ and an individual is pulled toward the cues and reward. A key computational question is how incentive salience is generated during a cue re-encounter, which combines both learning and the state of limbic brain mechanisms. Learning processes, such as temporal-difference models, provide one way for stimuli to acquire cached predictive values of rewards. However, empirical data show that subsequent incentive values are also modulated on the fly by dynamic fluctuation in physiological states, altering cached values in ways requiring additional motivation mechanisms. Dynamic modulation of incentive salience for a Pavlovian conditioned stimulus (CS or cue) occurs during certain states, without necessarily requiring (re)learning about the cue. In some cases, dynamic modulation of cue value occurs during states that are quite novel, never having been experienced before, and even prior to experience of the associated unconditioned reward in the new state. Such cases can include novel drug-induced mesolimbic activation and addictive incentive-sensitization, as well as natural appetite states such as salt appetite. Dynamic enhancement specifically raises the incentive salience of an appropriate CS, without necessarily changing that of other CSs. Here we suggest a new computational model that modulates incentive salience by integrating changing physiological states with prior learning. We support the model with behavioral and neurobiological data from empirical tests that demonstrate dynamic elevations in cue-triggered motivation (involving natural salt appetite, and drug-induced intoxication and sensitization). Our data call for a dynamic model of incentive salience, such as presented here. Computational models can adequately capture fluctuations in cue-triggered ‘wanting’ only by incorporating modulation of previously learned values by natural appetite and addiction-related states.United States. Air Force Office of Scientific ResearchUnited States. National Institutes of Health (DA015188, DA017752 and MH63649