Evidence of a diurnal rhythm in implicit reward learning

Many aspects of hedonic behavior, including self-administration of natural and drug rewards, as well as human positive affect, follow a diurnal cycle that peaks during the species-specific active period. This variation has been linked to circadian modulation of the mesolimbic dopamine system, and is hypothesized to serve an adaptive function by driving an organism to engage with the environment during times where the opportunity for obtaining rewards is high. However, relatively little is known about whether more complex facets of hedonic behavior – in particular, reward learning – follow the same diurnal cycle. The current study aimed to address this gap by examining evidence for diurnal variation in reward learning on a well-validated probabilistic reward learning task (PRT). PRT data from a large normative sample (N = 516) of non-clinical individuals, recruited across eight studies, were examined for the current study. The PRT uses an asymmetrical reinforcement ratio to induce a behavioral response bias, and reward learning was operationalized as the strength of this response bias across blocks of the task. Results revealed significant diurnal variation in reward learning, however in contrast to patterns previously observed in other aspects of hedonic behavior, reward learning was lowest in the middle of the day. Although a diurnal pattern was also observed on a measure of more general task performance (discriminability), this did not account for the variation observed in reward learning. Taken together, these findings point to a distinct diurnal pattern in reward learning that differs from that observed in other aspects of hedonic behavior. The results of this study have important implications for our understanding of clinical disorders characterized by both circadian and reward learning disturbances, and future research is needed to confirm whether this diurnal variation has a truly circadian origin.     

Mapping elasticity moduli of atherosclerotic plaque in situ via atomic force microscopy

Several studies have suggested that evolving mechanical stresses and strains drive atherosclerotic plaque development and vulnerability. Especially, stress distribution in the plaque fibrous capsule is an important determinant for the risk of vulnerable plaque rupture. Knowledge of the stiffness of atherosclerotic plaque components is therefore of critical importance. In this work, force mapping experiments using atomic force microscopy (AFM) were conducted in apolipoprotein E-deficient (ApoE(-/-)) mouse, which represents the most widely used experimental model for studying mechanisms underlying the development of atherosclerotic lesions. To obtain the elastic material properties of fibrous caps and lipidic cores of atherosclerotic plaques, serial cross-sections of aortic arch lesions were probed at different sites. Atherosclerotic plaque sub-structures were subdivided into cellular fibrotic, hypocellular fibrotic and lipidic rich areas according to histological staining. Hertz's contact mechanics were used to determine elasticity (Young's) moduli that were related to the underlying histological plaque structure. Cellular fibrotic regions exhibit a mean Young modulus of 10.4±5.7kPa. Hypocellular fibrous caps were almost six-times stiffer, with average modulus value of 59.4±47.4kPa, locally rising up to ～250kPa. Lipid rich areas exhibit a rather large range of Young's moduli, with average value of 5.5±3.5kPa. Such precise quantification of plaque stiffness heterogeneity will allow investigators to have prospectively a better monitoring of atherosclerotic disease evolution, including arterial wall remodeling and plaque rupture, in response to mechanical constraints imposed by vascular shear stress and blood pressure.     

NF-kappaB-mediated modulation of inducible nitric oxide synthase activity controls induction of the Epstein-Barr virus productive cycle by transforming growth factor beta 1

Transforming growth factor beta 1 (TGF-β1) signal transduction has been implicated in many second-messenger pathways, including the NF-κB pathway. We provide evidence of a novel TGF-β1-mediated pathway that leads to extracellular signal-regulated kinase (ERK) 1/2 phosphorylation, which in turn induces expression of an Epstein-Barr virus (EBV) protein, ZEBRA, that is responsible for the induction of the viral lytic cycle. This pathway includes two unexpected steps, both of which are required to control ERK 1/2 phosphorylation: first, a quick and transient activation of NF-κB, and second, downregulation of inducible nitric oxide synthase (iNOS) activity that requires the participation of NF-κB activity. Although necessary, NF-κB alone is not sufficient to produce downregulation of iNOS, suggesting that another uncharacterized event(s) is involved in this pathway. Dissection of the steps involved in the switch from the EBV latent cycle to the lytic cycle will be important to understand how virus-host relationships modulate the innate immune system.     

Epicardial fat: from the biomolecular aspects to the clinical practice

Epicardial fat is the visceral fat depot of heart. It is a metabolically active organ with anatomical and functional contiguity to the myocardium. A dichotomous role has been attributed to the epicardial fat. Under physiological conditions, epicardial fat displays biochemical and thermogenic cardio-protective properties. Under pathological circumstances epicardial fat can locally affect the heart and coronary arteries through vasocrine or paracrine secretion of pro-inflammatory cytokines. Epicardial fat can be measured with imaging techniques. Epicardial fat thickness reflects intra-abdominal and myocardial fat and correlates with metabolic syndrome and coronary artery disease. Epicardial fat measurement may play a role in the stratification of the cardio-metabolic risk and serve as therapeutic target. Weight loss and anti-inflammatory drugs targeting the fat may modulate epicardial fat. Because epicardial and myocardial tissues share the same coronary arterial supply it is reasonable to hypothesize that improved local vascularisation may resume epicardial fat to its physiological role.     

MARCKS is a natively unfolded protein with an inaccessible actin-binding site: evidence for long-range intramolecular interactions

Myristoylated alanine-rich C kinase substrate (MARCKS) is an unfolded protein that contains well characterized actin-binding sites within the phosphorylation site domain (PSD), yet paradoxically, we now find that intact MARCKS does not bind to actin. Intact MARCKS also does not bind as well to calmodulin as does the PSD alone. Myristoylation at the N terminus alters how calmodulin binds to MARCKS, implying that, despite its unfolded state, the distant N terminus influences binding events at the PSD. We show that the free PSD binds with site specificity to MARCKS, suggesting that long-range intramolecular interactions within MARCKS are also possible. Because of the unusual primary sequence of MARCKS with an overall isoelectric point of 4.2 yet a very basic PSD (overall charge of +13), we speculated that ionic interactions between oppositely charged domains of MARCKS were responsible for long-range interactions within MARCKS that sterically influence binding events at the PSD and that explain the observed differences between properties of the PSD and MARCKS. Consistent with this hypothesis, chemical modifications of MARCKS that neutralize negatively charged residues outside of the PSD allow the PSD to bind to actin and increase the affinity of MARCKS for calmodulin. Similarly, both myristoylation of MARCKS and cleavage of MARCKS by calpain are shown to increase the availability of the PSD so as to activate its actin-binding activity. Because abundant evidence supports the conclusion that MARCKS is an important protein in regulating actin dynamics, our data imply that post-translational modifications of MARCKS are necessary and sufficient to regulate actin-binding activity.     

Correction for Inhibition Leads to an Allosteric Co-Agonist Model for Pentobarbital Modulation and Activation of α1β3γ2L GABAA Receptors

BackgroundPentobarbital, like propofol and etomidate, produces important general anesthetic effects through GABA_A receptors. Photolabeling also indicates that pentobarbital binds to some of the same sites where propofol and etomidate act. Quantitative allosteric co-agonist models for propofol and etomidate account for modulatory and agonist effects in GABA_A receptors and have proven valuable in establishing drug site characteristics and for functional analysis of mutants. We therefore sought to establish an allosteric co-agonist model for pentobarbital activation and modulation of α1β3γ2L receptors, using a novel approach to first correct pentobarbital activation data for inhibitory effects in the same concentration range.MethodsUsing oocyte-expressed α1β3γ2L GABA_A receptors and two-microelectrode voltage-clamp, we quantified modulation of GABA responses by a low pentobarbital concentration and direct effects of high pentobarbital concentrations, the latter displaying mixed agonist and inhibitory effects. We then isolated and quantified pentobarbital inhibition in activated receptors using a novel single-sweep “notch” approach, and used these results to correct steady-state direct activation for inhibition.ResultsCombining results for GABA modulation and corrected direct activation, we estimated receptor open probability and optimized parameters for a Monod-Wyman-Changeux allosteric co-agonist model. Inhibition by pentobarbital was consistent with two sites with IC₅₀s near 1 mM, while co-agonist model parameters suggest two allosteric pentobarbital agonist sites characterized by K_PB ≈ 5 mM and high efficacy. The results also indicate that pentobarbital may be a more efficacious agonist than GABA.ConclusionsOur novel approach to quantifying both inhibitory and co-agonist effects of pentobarbital provides a basis for future structure-function analyses of GABA_A receptor mutations in putative pentobarbital binding sites.     

Computer‐aided biochemical programming of synthetic microreactors as diagnostic devices

Biological systems have evolved efficient sensing and decision‐making mechanisms to maximize fitness in changing molecular environments. Synthetic biologists have exploited these capabilities to engineer control on information and energy processing in living cells. While engineered organisms pose important technological and ethical challenges, de novo assembly of non‐living biomolecular devices could offer promising avenues toward various real‐world applications. However, assembling biochemical parts into functional information processing systems has remained challenging due to extensive multidimensional parameter spaces that must be sampled comprehensively in order to identify robust, specification compliant molecular implementations. We introduce a systematic methodology based on automated computational design and microfluidics enabling the programming of synthetic cell‐like microreactors embedding biochemical logic circuits, or protosensors, to perform accurate biosensing and biocomputing operations in vitro according to temporal logic specifications. We show that proof‐of‐concept protosensors integrating diagnostic algorithms detect specific patterns of biomarkers in human clinical samples. Protosensors may enable novel approaches to medicine and represent a step toward autonomous micromachines capable of precise interfacing of human physiology or other complex biological environments, ecosystems, or industrial bioprocesses.     

Quality and quantity of genetic relatedness data affect the analysis of social structure

Kinship plays a fundamental role in the evolution of social systems and is considered a key driver of group living. To understand the role of kinship in the formation and maintenance of social bonds, accurate measures of genetic relatedness are critical. Genotype‐by‐sequencing technologies are rapidly advancing the accuracy and precision of genetic relatedness estimates for wild populations. The ability to assign kinship from genetic data varies depending on a species’ or population's mating system and pattern of dispersal, and empirical data from longitudinal studies are crucial to validate these methods. We use data from a long‐term behavioural study of a polygynandrous, bisexually philopatric marine mammal to measure accuracy and precision of parentage and genetic relatedness estimation against a known partial pedigree. We show that with moderate but obtainable sample sizes of approximately 4,235 SNPs and 272 individuals, highly accurate parentage assignments and genetic relatedness coefficients can be obtained. Additionally, we subsample our data to quantify how data availability affects relatedness estimation and kinship assignment. Lastly, we conduct a social network analysis to investigate the extent to which accuracy and precision of relatedness estimation improve statistical power to detect an effect of relatedness on social structure. Our results provide practical guidance for minimum sample sizes and sequencing depth for future studies, as well as thresholds for post hoc interpretation of previous analyses.