The interaction between monoamine oxidase A and punitive discipline in the development of antisocial behavior: Mediation by maladaptive social information processing.

Previous studies demonstrate that boys' monoamine oxidase A (MAOA) genotype interacts with adverse rearing environments in early childhood, including punitive discipline, to predict later antisocial behavior. Yet the mechanisms by which MAOA and punitive parenting interact during childhood to amplify risk for antisocial behavior are not well understood. In the present study, hostile attributional bias and aggressive response generation during middle childhood, salient aspects of maladaptive social information processing, were tested as possible mediators of this relation in a sample of 187 low-income men followed prospectively from infancy into early adulthood. Given racial-ethnic variation in MAOA allele frequencies, analyses were conducted separately by race. In both African American and Caucasian men, those with the low-activity MAOA allele who experienced more punitive discipline at age 1.5 generated more aggressive responses to perceived threat at age 10 relative to men with the high-activity variant. In the African American subsample only, formal mediation analyses indicated a marginally significant indirect effect of maternal punitiveness on adult arrest records via aggressive response generation in middle childhood. The findings suggest that maladaptive social information processing may be an important mechanism underlying the association between MAOA × Parenting interactions and antisocial behavior in early adulthood. The present study extends previous work in the field by demonstrating that MAOA and harsh parenting assessed in early childhood interact to not only predict antisocial behavior in early adulthood, but also predict social information processing, a well-established social-cognitive correlate of antisocial behavior

Interactions between empathy and resting heart rate in early adolescence predict violent behavior in late adolescence and early adulthood.

BackgroundAlthough resting heart rate (RHR) and empathy are independently and negatively associated with violent behavior, relatively little is known about the interplay between these psychophysiological and temperament-related risk factors.MethodsUsing a sample of 160 low-income, racially diverse men followed prospectively from infancy through early adulthood, this study examined whether RHR and empathy during early adolescence independently and interactively predict violent behavior and related correlates in late adolescence and early adulthood.ResultsControlling for child ethnicity, family income, and child antisocial behavior at age 12, empathy inversely predicted moral disengagement and juvenile petitions for violent crimes, while RHR was unrelated to all measures of violent behavior. Interactive effects were also evident such that among men with lower but not higher levels of RHR, lower empathy predicted increased violent behavior, as indexed by juvenile arrests for violent offenses, peer-reported violent behavior at age 17, self-reported moral disengagement at age 17, and self-reported violent behavior at age 20.ConclusionsImplications for prevention and intervention are considered. Specifically, targeting empathic skills among individuals at risk for violent behavior because of specific psychophysiological profiles may lead to more impactful interventions

The variation of relative magnetic helicity around major flares

We have investigated the variation of magnetic helicity over a span of several days around the times of 11 X-class flares which occurred in seven active regions (NOAA 9672, 10030, 10314, 10486, 10564, 10696, and 10720) using the magnetograms taken by the Michelson Doppler Imager (MDI) on board the Solar and Heliospheric Observatory (SOHO). As a major result we found that each of these major flares was preceded by a significant helicity accumulation over a long period (0.5 to a few days). Another finding is that the helicity accumulates at a nearly constant rate and then becomes nearly constant before the flares. This led us to distinguish the helicity variation into two phases: a phase of monotonically increasing helicity and the following phase of relatively constant helicity. As expected, the amount of helicity accumulated shows a modest correlation with time-integrated soft X-ray flux during flares. However, the average helicity change rate in the first phase shows even stronger correlation with the time-integrated soft X-ray flux. We discuss the physical implications of this result and the possibility that this characteristic helicity variation pattern can be used as an early warning sign for solar eruptions

Sustainability of multi-field inflation and bound on string scale

We study the effects of the interaction terms between the inflaton fields on the inflationary dynamics in multi-field models. With power law type potential and interactions, the total number of e-folds may get considerably reduced and can lead to unacceptably short period of inflation. Also we point out that this can place a bound on the characteristic scale of the underlying theory such as string theory. Using a simple multi-field chaotic inflation model from string theory, the string scale is constrained to be larger than the scale of grand unified theory.Comment: (v1) 9 pages, 1 figure;(v2) 10 pages, references added; (v3) 15 pages, 4 figures, more discussions about parameters and observable quantities, references added, to appear in Modern Physics Letters

Strange meson-nucleon states in the quark potential model

The quark potential model and resonating group method are used to investigate the $\bar{K}N$ bound states and/or resonances. The model potential consists of the t-channel and s-channel one-gluon exchange potentials and the confining potential with incorporating the QCD renormalization correction and the spin-orbital suppression effect in it. It was shown in our previous work that by considering the color octet contribution, use of this model to investigate the $KN$ low energy elastic scattering leads to the results which are in pretty good agreement with the experimental data. In this paper, the same model and method are employed to calculate the masses of the $\bar{K}N$ bound systems. For this purpose, the resonating group equation is transformed into a standard Schr\"odinger equation in which a nonlocal effective $\bar{K}N$ interaction potential is included. Solving the Schr\"odinger equation by the variational method, we are able to reproduce the masses of some currently concerned $\bar{K}N$ states and get a view that these states possibly exist as $\bar{K}N$ molecular states. For the $KN$ system, the same calculation gives no support to the existence of the resonance $\Theta ^{+}(1540)$ which was announced recently.Comment: 15 pages, 4 figure

QCD at non-zero temperature and density from the lattice

The study of systems as diverse as the cores of neutron stars and heavy-ion collision experiments requires the understanding of the phase structure of QCD at non-zero temperature, T, and chemical potential, mu_q. We review some of the difficulties of performing lattice simulations of QCD with non-zero mu_q, and outline the re-weighting method used to overcome this problem. This method is used to determine the critical endpoint of QCD in the (mu_q,T) plane. We study the pressure and quark number susceptibility at small mu_q.Comment: 5 pages, talk presented by C.R. Allton at the QCD Downunder Conference, Barossa Valley and Adelaide, March 200

Preferred analysis methods for Affymetrix GeneChips revealed by a wholly defined control dataset

BACKGROUND: As more methods are developed to analyze RNA-profiling data, assessing their performance using control datasets becomes increasingly important. RESULTS: We present a 'spike-in' experiment for Affymetrix GeneChips that provides a defined dataset of 3,860 RNA species, which we use to evaluate analysis options for identifying differentially expressed genes. The experimental design incorporates two novel features. First, to obtain accurate estimates of false-positive and false-negative rates, 100-200 RNAs are spiked in at each fold-change level of interest, ranging from 1.2 to 4-fold. Second, instead of using an uncharacterized background RNA sample, a set of 2,551 RNA species is used as the constant (1x) set, allowing us to know whether any given probe set is truly present or absent. Application of a large number of analysis methods to this dataset reveals clear variation in their ability to identify differentially expressed genes. False-negative and false-positive rates are minimized when the following options are chosen: subtracting nonspecific signal from the PM probe intensities; performing an intensity-dependent normalization at the probe set level; and incorporating a signal intensity-dependent standard deviation in the test statistic. CONCLUSIONS: A best-route combination of analysis methods is presented that allows detection of approximately 70% of true positives before reaching a 10% false-discovery rate. We highlight areas in need of improvement, including better estimate of false-discovery rates and decreased false-negative rates