The role of learning-related dopamine signals in addiction vulnerability

Dopaminergic signals play a mathematically precise role in reward-related learning, and variations in dopaminergic signaling have been implicated in vulnerability to addiction. Here, we provide a detailed overview of the relationship between theoretical, mathematical, and experimental accounts of phasic dopamine signaling, with implications for the role of learning-related dopamine signaling in addiction and related disorders. We describe the theoretical and behavioral characteristics of model-free learning based on errors in the prediction of reward, including step-by-step explanations of the underlying equations. We then use recent insights from an animal model that highlights individual variation in learning during a Pavlovian conditioning paradigm to describe overlapping aspects of incentive salience attribution and model-free learning. We argue that this provides a computationally coherent account of some features of addiction.

Robust meta-analytic-predictive priors in clinical trials with historical control information.

Historical information is always relevant for clinical trial design. Additionally, if incorporated in the analysis of a new trial, historical data allow to reduce the number of subjects. This decreases costs and trial duration, facilitates recruitment, and may be more ethical. Yet, under prior-data conflict, a too optimistic use of historical data may be inappropriate. We address this challenge by deriving a Bayesian meta-analytic-predictive prior from historical data, which is then combined with the new data. This prospective approach is equivalent to a meta-analytic-combined analysis of historical and new data if parameters are exchangeable across trials. The prospective Bayesian version requires a good approximation of the meta-analytic-predictive prior, which is not available analytically. We propose two- or three-component mixtures of standard priors, which allow for good approximations and, for the one-parameter exponential family, straightforward posterior calculations. Moreover, since one of the mixture components is usually vague, mixture priors will often be heavy-tailed and therefore robust. Further robustness and a more rapid reaction to prior-data conflicts can be achieved by adding an extra weakly-informative mixture component. Use of historical prior information is particularly attractive for adaptive trials, as the randomization ratio can then be changed in case of prior-data conflict. Both frequentist operating characteristics and posterior summaries for various data scenarios show that these designs have desirable properties. We illustrate the methodology for a phase II proof-of-concept trial with historical controls from four studies. Robust meta-analytic-predictive priors alleviate prior-data conflicts ' they should encourage better and more frequent use of historical data in clinical trials.

Distortion-free enhancement of terahertz signals measured by electro-optic sampling. I. Theory

We present three methods for the distortion-free enhancement of THz signals measured by electro-optic sampling in zinc blende-type detector crystals, e.g., ZnTe or GaP. A technique commonly used in optically heterodyne-detected optical Kerr effect spectroscopy is introduced, which is based on two measurements at opposite optical biases near the zero transmission point in a crossed polarizer detection geometry. In contrast to other techniques for an undistorted THz signal enhancement, it also works in a balanced detection scheme and does not require an elaborate procedure for the reconstruction of the true signal as the two measured waveforms are simply subtracted to remove distortions. We study three different approaches for setting an optical bias using the Jones matrix formalism and discuss them also in the framework of optical heterodyne detection. We show that there is an optimal bias point in realistic situations where a small fraction of the probe light is scattered by optical components. The experimental demonstration will be given in the second part of this two-paper series [J. Opt. Soc. Am. B, doc. ID 204877 (2014, posted online)].

Distortion-free enhancement of terahertz signals measured by electro-optic sampling. II. Experiment

Three methods for distortion-free enhancement of electro-optic sampling measurements of terahertz signals are tested. In the first part of this two-paper series [J. Opt. Soc. Am B 31, 904–910 (2014)], the theoretical framework for describing the signal enhancement was presented and discussed. As the applied optical bias is decreased, individual signal traces become enhanced but distorted. Here we experimentally show that nonlinear signal components that distort the terahertz electric field measurement can be removed by subtracting traces recorded with opposite optical bias values. In all three methods tested, we observe up to an order of magnitude increase in distortion-free signal enhancement, in agreement with the theory, making possible measurements of small terahertz-induced transient birefringence signals with increased signal-to-noise ratio.

Defensive weapons and defense signals in plants: Some metabolites serve both roles

The defense of plants against herbivores and pathogens involves the participation of an enormous range of different metabolites, some of which act directly as defensive weapons against enemies (toxins or deterrents) and some of which act as components of the complex internal signaling network that insures that defense is timed to enemy attack. Recent work reveals a surprising trend: The same compounds may act as both weapons and signals of defense. For example, two groups of well-studied defensive weapons, glucosinolates and benzoxazinoids, trigger the accumulation of the protective polysaccharide callose as a barrier against aphids and pathogens. In the other direction, several hormones acting in defense signaling (and their precursors and products) exhibit activity as weapons against pathogens. Knowing which compounds are defensive weapons, which are defensive signals and which are both is vital for understanding the functioning of plant defense systems.

The block numerical range of analytic operator functions

We introduce the block numerical range Wn(L) of an operator function L with respect to a decomposition H = H1⊕. . .⊕Hn of the underlying Hilbert space. Our main results include the spectral inclusion property and estimates of the norm of the resolvent for analytic L . They generalise, and improve, the corresponding results for the numerical range (which is the case n = 1) since the block numerical range is contained in, and may be much smaller than, the usual numerical range. We show that refinements of the decomposition entail inclusions between the corresponding block numerical ranges and that the block numerical range of the operator matrix function L contains those of its principal subminors. For the special case of operator polynomials, we investigate the boundedness of Wn(L) and we prove a Perron-Frobenius type result for the block numerical radius of monic operator polynomials with coefficients that are positive in Hilbert lattice sense.

Observation and applications of single-electron charge signals in the XENON100 experiment

The XENON100 dark matter experiment uses liquid xenon in a time projection chamber (TPC) to measure xenon nuclear recoils resulting from the scattering of dark matter weakly interacting massive particles (WIMPs). In this paper, we report the observation of single-electron charge signals which are not related to WIMP interactions. These signals, which show the excellent sensitivity of the detector to small charge signals, are explained as being due to the photoionization of impurities in the liquid xenon and of the metal components inside the TPC. They are used as a unique calibration source to characterize the detector. We explain how we can infer crucial parameters for the XENON100 experiment: the secondary-scintillation gain, the extraction yield from the liquid to the gas phase and the electron drift velocity.

Ephrin-B1 transduces signals to activate integrin-mediated migration, attachment and angiogenesis.

Ephrin-B/EphB family proteins are implicated in bidirectional signaling and were initially defined through the function of their ectodomain sequences in activating EphB receptor tyrosine kinases. Ephrin-B1-3 are transmembrane proteins sharing highly conserved C-terminal cytoplasmic sequences. Here we use a soluble EphB1 ectodomain fusion protein (EphB1/Fc) to demonstrate that ephrin-B1 transduces signals that regulate cell attachment and migration. EphB1/Fc induced endothelial ephrin-B1 tyrosine phosphorylation, migration and integrin-mediated (alpha(v)beta(3) and alpha(5)beta(1)) attachment and promoted neovascularization, in vivo, in a mouse corneal micropocket assay. Activation of ephrin-B1 by EphB1/Fc induced phosphorylation of p46 JNK but not ERK-1/2 or p38 MAPkinases. By contrast, mutant ephrin-B1s bearing either a cytoplasmic deletion (ephrin-B1DeltaCy) or a deletion of four C-terminal amino acids (ephrin-B1DeltaPDZbd) fail to activate p46 JNK. Transient expression of intact ephin-B1 conferred EphB1/Fc migration responses on CHO cells, whereas the ephrin-B1DeltaCy and ephrin-B1DeltaPDZbd mutants were inactive. Thus ephrin-B1 transduces 'outside-in' signals through C-terminal protein interactions that affect integrin-mediated attachment and migration.

Plant elicitor peptides are conserved signals regulating direct and indirect antiherbivore defense

Insect-induced defenses occur in nearly all plants and are regulated by conserved signaling pathways. As the first described plant peptide signal, systemin regulates antiherbivore defenses in the Solanaceae, but in other plant families, peptides with analogous activity have remained elusive. In the current study, we demonstrate that a member of the maize (Zea mays) plant elicitor peptide (Pep) family, ZmPep3, regulates responses against herbivores. Consistent with being a signal, expression of the ZmPROPEP3 precursor gene is rapidly induced by Spodoptera exigua oral secretions. At concentrations starting at 5 pmol per leaf, ZmPep3 stimulates production of jasmonic acid, ethylene, and increased expression of genes encoding proteins associated with herbivory defense. These include proteinase inhibitors and biosynthetic enzymes for production of volatile terpenes and benzoxazinoids. In accordance with gene expression data, plants treated with ZmPep3 emit volatiles similar to those from plants subjected to herbivory. ZmPep3-treated plants also exhibit induced accumulation of the benzoxazinoid phytoalexin 2-hydroxy-4,7-dimethoxy-1,4-benzoxazin-3-one glucoside. Direct and indirect defenses induced by ZmPep3 contribute to resistance against S. exigua through significant reduction of larval growth and attraction of Cotesia marginiventris parasitoids. ZmPep3 activity is specific to Poaceous species; however, peptides derived from PROPEP orthologs identified in Solanaceous and Fabaceous plants also induce herbivory-associated volatiles in their respective species. These studies demonstrate that Peps are conserved signals across diverse plant families regulating antiherbivore defenses and are likely to be the missing functional homologs of systemin outside of the Solanaceae.

The Martian Gas-Analytic Package for the Landing Platform Experiments of the ExoMars 2018

The paper describes the architecture of the Martian Gas Analytic Package, which is proposed for the Russian ExoMars Lander 2018.

Widespread Signals of Convergent Adaptation to High Altitude in Asia and America

Living at high altitude is one of the most difficult challenges that humans had to cope with during their evolution. Whereas several genomic studies have revealed some of the genetic bases of adaptations in Tibetan, Andean, and Ethiopian populations, relatively little evidence of convergent evolution to altitude in different continents has accumulated. This lack of evidence can be due to truly different evolutionary responses, but it can also be due to the low power of former studies that have mainly focused on populations from a single geographical region or performed separate analyses on multiple pairs of populations to avoid problems linked to shared histories between some populations. We introduce here a hierarchical Bayesian method to detect local adaptation that can deal with complex demographic histories. Our method can identify selection occurring at different scales, as well as convergent adaptation in different regions. We apply our approach to the analysis of a large SNP data set from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high-altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia.

Chow–Liu trees are sufficient predictive models for reproducing key features of functional networks of periictal EEG time-series

Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.