CONTRIBUTION OF NUCLEUS ACCUMBENS CORE TO IMPULSIVE CHOICE: ROLE OF DOPAMINE AND GLUTAMATE SYSTEMS

Impulsive choice refers to the inability to delay gratification and is associated with increased drug abuse vulnerability. Understanding the underlying neural mechanisms linking impulsive choice and drug abuse can contribute to improved treatment options for individuals with substance use disorders. Evidence suggests a major role for nucleus accumbens core (NAcc) in impulsive choice and the reinforcing effects of drugs of abuse. The neurotransmitters glutamate (Glu) and dopamine (DA) are implicated in the neural adaptations observed in drug addiction; however, the role of intra-NAcc Glu and DA in impulsive choice is unclear. Rats were trained in a delay discounting task, in which animals chose between a small, immediate reinforcer and large, delayed reinforcer. Consistently choosing the small, immediate reinforcer was considered to reflect increased impulsivity. Following delay discounting, in vitro receptor autoradiography was performed to quantify the number of N-methyl-D-aspartate (NMDA) receptors and dopamine transporters (DAT) in NAcc and nucleus accumbens shell (NAcSh). In a separate experiment, rats were trained in delay discounting and were implanted with guide cannulae into NAcc. Following surgery, rats received microinfusions of either a) the Glu-selective ligands MK-801 (noncompetitive NMDA receptor channel blocker; 0, 0.3, and 1.0 μg), AP-5 (competitive NMDA receptor antagonist; 0, 0.3, and 1.0 μg), ifenprodil (NMDA NR2B subunit antagonist; 0, 0.3, and 1.0 μg), and CNQX (AMPA receptor antagonist; 0, 0.2, and 0.5 μg) or b) the DA-selective ligands SKF 38393 (D1-like receptor agonist; 0, 0.03, and 0.1 μg), SCH 23390 (D1-like receptor antagonist; 0, 0.3, and 1.0 μg), quinpirole (D2-like receptor agonist; 0, 0.3, and 1.0 μg), and eticlopride (D2-like receptor antagonist; 0, 0.3, and 1.0 μg). In NAcc and NAcSh, NMDA receptor and DAT expression did not differ between high and low impulsive rats. Furthermore, intra-NAcc administration of NDMA and DA receptor ligands did not significantly alter impulsive choice. These results suggest that Glu and DA systems within NAcc do not directly mediate impulsive decision making. Future work is needed to determine the precise role of NAcc in mediating impulsive choice

Reusing Data and Metadata to Create New Metadata Through Machine-Learning & Other Programmatic Methods

Recent improvements in natural language processing (NLP) enable metadata to be created programmatically from reused original metadata or even the dataset itself. Transfer-learning applied to NLP has greatly improved performance and reduced training data requirements. In this talk, well compare machine-generated metadata to human-generated metadata and discuss characteristics of metadata and data archives that affect suitability for machine-learning reuse of metadata. Where as human-generated metadata is often populated once, populated from the perspective of data supplier, populated by many individuals with different words for the same thing, and limited in length, machine-generated metadata can be updated any number of times, generated from the perspective of any user, constrained to a standardized set of terms that can be evolved over time, and be any length required. Machine-learning generated metadata offers benefits but also additional needs in terms of version control, process transparency, human-computer interaction, and IT requirements. As a successful example, well discuss how a dataset of abstracts and associated human-tagged keywords from a standardized list of several thousand keywords were used to create a machine-learning model that predicted keyword metadata for open-source code projects on code.nasa.gov. Well also discuss a less successful example from data.nasa.gov to show how data archive architecture and characteristics of initial metadata can be strong controls on how easy it is to leverage programmatic methods to reuse metadata to create additional metadata

Predicting the critical density of topological defects in O(N) scalar field theories

O(N) symmetric $\lambda \phi^4$ field theories describe many critical phenomena in the laboratory and in the early Universe. Given N and $D\leq 3$, the dimension of space, these models exhibit topological defect classical solutions that in some cases fully determine their critical behavior. For N=2, D=3 it has been observed that the defect density is seemingly a universal quantity at T_c. We prove this conjecture and show how to predict its value based on the universal critical exponents of the field theory. Analogously, for general N and D we predict the universal critical densities of domain walls and monopoles, for which no detailed thermodynamic study exists. This procedure can also be inverted, producing an algorithm for generating typical defect networks at criticality, in contrast to the canonical procedure, which applies only in the unphysical limit of infinite temperature.Comment: 4 pages, 3 figures, uses RevTex, typos in Eq.(11) and (14) correcte

The causal relationship between gastro-oesophageal reflux disease and idiopathic pulmonary fibrosis: a bidirectional two-sample Mendelian randomisation study

Background: Gastro-oesophageal reflux disease (GORD) is associated with idiopathic pulmonary fibrosis (IPF) in observational studies. It is not known if this association arises because GORD causes IPF or because IPF causes GORD, or because of confounding by factors, such as smoking, associated with both GORD and IPF. We used bidirectional Mendelian randomisation (MR), where genetic variants are used as instrumental variables to address issues of confounding and reverse causation, to examine how, if at all, GORD and IPF are causally related. Methods: A bidirectional two-sample MR was performed to estimate the causal effect of GORD on IPF risk and of IPF on GORD risk, using genetic data from the largest GORD (78 707 cases and 288 734 controls) and IPF (4125 cases and 20 464 controls) genome-wide association meta-analyses currently available. Results: GORD increased the risk of IPF, with an OR of 1.6 (95% CI 1.04–2.49; p=0.032). There was no evidence of a causal effect of IPF on the risk of GORD, with an OR of 0.999 (95% CI 0.997–1.000; p=0.245). Conclusions: We found that GORD increases the risk of IPF, but found no evidence that IPF increases the risk of GORD. GORD should be considered in future studies of IPF risk and interest in it as a potential therapeutic target should be renewed. The mechanisms underlying the effect of GORD on IPF should also be investigated

Defect Formation and Critical Dynamics in the Early Universe

We study the nonequilibrium dynamics leading to the formation of topological defects in a symmetry-breaking phase transition of a quantum scalar field with \lambda\Phi^4 self-interaction in a spatially flat, radiation-dominated Friedmann-Robertson-Walker Universe. The quantum field is initially in a finite-temperature symmetry-restored state and the phase transition develops as the Universe expands and cools. We present a first-principles, microscopic approach in which the nonperturbative, nonequilibrium dynamics of the quantum field is derived from the two-loop, two-particle-irreducible closed-time-path effective action. We numerically solve the dynamical equations for the two-point function and we identify signatures of topological defects in the infrared portion of the momentum-space power spectrum. We find that the density of topological defects formed after the phase transition scales as a power law with the expansion rate of the Universe. We calculate the equilibrium critical exponents of the correlation length and relaxation time for this model and show that the power law exponent of the defect density, for both overdamped and underdamped evolution, is in good agreement with the "freeze-out" scenario of Zurek. We introduce an analytic dynamical model, valid near the critical point, that exhibits the same power law scaling of the defect density with the quench rate. By incorporating the realistic quench of the expanding Universe, our approach illuminates the dynamical mechanisms important for topological defect formation. The observed power law scaling of the defect density with the quench rate, observered here in a quantum field theory context, provides evidence for the "freeze-out" scenario in three spatial dimensions.Comment: 31 pages, RevTex, 8 figures in EPS forma

The Functioning of the Drosophila CPEB Protein Orb Is Regulated by Phosphorylation and Requires Casein Kinase 2 Activity

The Orb CPEB protein regulates translation of localized mRNAs in Drosophila ovaries. While there are multiple hypo- and hyperphosphorylated Orb isoforms in wild type ovaries, most are missing in orbF303, which has an amino acid substitution in a buried region of the second RRM domain. Using a proteomics approach we identified a candidate Orb kinase, Casein Kinase 2 (CK2). In addition to being associated with Orb in vivo, we show that ck2 is required for orb functioning in gurken signaling and in the autoregulation of orb mRNA localization and translation. Supporting a role for ck2 in Orb phosphorylation, we find that the phosphorylation pattern is altered when ck2 activity is partially compromised. Finally, we show that the Orb hypophosphorylated isoforms are in slowly sedimenting complexes that contain the translational repressor Bruno, while the hyperphosphorylated isoforms assemble into large complexes that co-sediment with polysomes and contain the Wisp poly(A) polymerase

Semantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery.

Electronic Health Record (EHR) systems typically define laboratory test results using the Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast Healthcare Interoperability Resource (FHIR) standards. LOINC has not yet been semantically integrated with computational resources for phenotype analysis. Here, we provide a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to Human Phenotype Ontology (HPO) terms. We annotated the medical implications of 2923 commonly used laboratory tests with HPO terms. Using these annotations, our software assesses laboratory test results and converts each result into an HPO term. We validated our approach with EHR data from 15,681 patients with respiratory complaints and identified known biomarkers for asthma. Finally, we provide a freely available SMART on FHIR application that can be used within EHR systems. Our approach allows readily available laboratory tests in EHR to be reused for deep phenotyping and exploits the hierarchical structure of HPO to integrate distinct tests that have comparable medical interpretations for association studies

Point Mutations in Aβ Result in the Formation of Distinct Polymorphic Aggregates in the Presence of Lipid Bilayers

A hallmark of Alzheimer's disease (AD) is the rearrangement of the β-amyloid (Aβ) peptide to a non-native conformation that promotes the formation of toxic, nanoscale aggregates. Recent studies have pointed to the role of sample preparation in creating polymorphic fibrillar species. One of many potential pathways for Aβ toxicity may be modulation of lipid membrane function on cellular surfaces. There are several mutations clustered around the central hydrophobic core of Aβ near the α-secretase cleavage site (E22G Arctic mutation, E22K Italian mutation, D23N Iowa mutation, and A21G Flemish mutation). These point mutations are associated with hereditary diseases ranging from almost pure cerebral amyloid angiopathy (CAA) to typical Alzheimer's disease pathology with plaques and tangles. We investigated how these point mutations alter Aβ aggregation in the presence of supported lipid membranes comprised of total brain lipid extract. Brain lipid extract bilayers were used as a physiologically relevant model of a neuronal cell surface. Intact lipid bilayers were exposed to predominantly monomeric preparations of Wild Type or different mutant forms of Aβ, and atomic force microscopy was used to monitor aggregate formation and morphology as well as bilayer integrity over a 12 hour period. The goal of this study was to determine how point mutations in Aβ, which alter peptide charge and hydrophobic character, influence interactions between Aβ and the lipid surface. While fibril morphology did not appear to be significantly altered when mutants were prepped similarly and incubated under free solution conditions, aggregation in the lipid membranes resulted in a variety of polymorphic aggregates in a mutation dependent manner. The mutant peptides also had a variable ability to disrupt bilayer integrity

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe