Sex and pubertal variation in reward-related behavior and neural activation in early adolescents.

This study aimed to characterize the role of sex and pubertal markers in reward motivation behavior and neural processing in early adolescence. We used baseline and two-year follow-up data from the Adolescent Brain and Cognitive DevelopmentSM study (15844 observations; 52% from boys; age 9-13). Pubertal development was measured with parent-reported Pubertal Development Scale, and DHEA, testosterone, and estradiol levels. Reward motivation behavior and neural processing at anticipation and feedback stages were assessed with the Monetary Incentive Delay task. Boys had higher reward motivation than girls, demonstrating greater accuracy difference between reward and neutral trials and higher task earnings. Girls had lower neural activation during reward feedback than boys in the nucleus accumbens, caudate, rostral anterior cingulate, medial orbitofrontal cortex, superior frontal gyrus and posterior cingulate. Pubertal stage and testosterone levels were positively associated with reward motivation behavior, although these associations changed when controlling for age. There were no significant associations between pubertal development and neural activation during reward anticipation and feedback. Sex differences in reward-related processing exist in early adolescence, signaling the need to understand their impact on typical and atypical functioning as it unfolds into adulthood.

Sex and pubertal influences on the neurodevelopmental underpinnings of schizophrenia: A case for longitudinal research on adolescents.

Sex is a significant source of heterogeneity in schizophrenia, with more negative symptoms in males and more affective symptoms and internalizing comorbidity in females. In this narrative review, we argue that there are likely sex differences in the pathophysiological mechanisms of schizophrenia-spectrum disorders (SZ) that originate during puberty and relate to the sex-specific impacts of pubertal maturation on brain development. Pubertal maturation might also trigger underlying (genetic or other) vulnerabilities in at-risk individuals, influencing brain development trajectories that contribute to the emergence of SZ. This review is the first to integrate links between pubertal development and neural development with cognitive neuroscience research in SZ to form and evaluate these hypotheses, with a focus on the frontal-striatal and frontal-limbic networks and their hypothesized contribution to negative and mood symptoms respectively. To test these hypotheses, longitudinal research with human adolescents is needed that examines the role of sex and pubertal development using large cohorts or high risk samples. We provide recommendations for such studies, which will integrate the fields of psychiatry, developmental cognitive neuroscience, and developmental endocrinology towards a more nuanced understanding of the role of pubertal factors in the hypothesized sex-specific pathophysiological mechanisms of schizophrenia.

Model Fit after Pairwise Maximum Likelihood.

Maximum likelihood factor analysis of discrete data within the structural equation modeling framework rests on the assumption that the observed discrete responses are manifestations of underlying continuous scores that are normally distributed. As maximizing the likelihood of multivariate response patterns is computationally very intensive, the sum of the log-likelihoods of the bivariate response patterns is maximized instead. Little is yet known about how to assess model fit when the analysis is based on such a pairwise maximum likelihood (PML) of two-way contingency tables. We propose new fit criteria for the PML method and conduct a simulation study to evaluate their performance in model selection. With large sample sizes (500 or more), PML performs as well the robust weighted least squares analysis of polychoric correlations.

Measurement bias detection through Bayesian factor analysis.

Measurement bias has been defined as a violation of measurement invariance. Potential violators-variables that possibly violate measurement invariance-can be investigated through restricted factor analysis (RFA). The purpose of the present paper is to investigate a Bayesian approach to estimate RFA models with interaction effects, in order to detect uniform and nonuniform measurement bias. Because modeling nonuniform bias requires an interaction term, it is more complicated than modeling uniform bias. The Bayesian approach seems especially suited for such complex models. In a simulation study we vary the type of bias (uniform, nonuniform), the type of violator (observed continuous, observed dichotomous, latent continuous), and the correlation between the trait and the violator (0.0, 0.5). For each condition, 100 sets of data are generated and analyzed. We examine the accuracy of the parameter estimates and the performance of two bias detection procedures, based on the DIC fit statistic, in Bayesian RFA. Results show that the accuracy of the estimated parameters is satisfactory. Bias detection rates are high in all conditions with an observed violator, and still satisfactory in all other conditions.

Cause of heart murmurs in 57 apparently healthy cats.

Heart murmurs are caused by turbulent blood flow or by vibration of cardiac structures. Turbulent blood flow may originate from structural heart disease or from physiological phenomena. The aims of this study were to establish the cause of heart murmurs in apparently healthy adult cats and to determine whether a heart murmur is a reliable indicator of heart disease. In this retrospective study, we reviewed the medical records of cats in which a heart murmur was detected during physical examination by one of the authors in the period January 2008 to December 2009. Cats younger than 6 months and those with systemic disease were excluded. Timing, grade, and point of maximum intensity of the murmur were determined by one observer (MD) before 2D-, M-mode and Doppler echocardiography. Fifty-seven cats (median age 76 months, range 6-194) were included, 30 neutered females and 27 neutered males. All murmurs were systolic and varied in intensity from 2/6 to 5/6. The point of maximum intensity was the left or right parasternal region in 34/57 (61%) of murmurs. Murmurs were caused by dynamic left ventricular outflow tract obstruction in 25/57 (44%) cats, dynamic right ventricular outflow tract obstruction in 9/57 (16%) cats, and combined dynamic left and right outflow tract obstruction in 11/57 (19%) cats. In 5 (9%) cats the cause of the murmur could not be identified. Heart disease was present in 50 (88%) cats, namely, left ventricular hypertrophy in 44 (77%) and congenital defects in 6 (11%) cats. In conclusion, most heart murmurs in apparently healthy cats are detected in the left or right parasternal region and are caused by dynamic left and right ventricular outflow tract obstruction. Because most cats (88%) with a heart murmur had heart disease in this study, if a heart murmur is detected in an apparently healthy cat, echocardiography is recommended to determine the cause of the heart murmur and the presence of heart disease.

Analysis of the inheritance of white spotting and the evaluation of KIT and EDNRB as spotting loci in Dutch boxer dogs.

The genetic basis of the white spotting pattern in Dutch boxer dogs is not known. We studied whether the segregation of white spotting in boxers follows a Mendelian inheritance pattern. Blood samples were collected, along with digital photographs in standard directions of (grand)parents (n=16) and offspring (n=52) from eight litters of Dutch boxers. In order to select heterozygous parents, we selected nonuniform litters, in which at least one puppy was extreme white. On the basis of criteria for the location, the extent of white spotting, and the mean percentage of pigmented area of the foot soles, we classified 10 dogs as solid colored, 27 as flashy, and 15 as extreme white. This was not a significant deviation from the expected 1:2:1 ratio. Because the flashy phenotype seems to be an intermediate between the two homozygotes, white spotting in the Dutch boxer can be considered to be due to a single gene effect, with incomplete dominance. We have evaluated candidate genes c-KIT (KIT) and EDNRB for segregation with white spotting phenotype in these litters. Using polymorphic markers, very near the KIT and EDNRB genes, we found that segregation of the white spotting pattern did not coincide with segregation of these polymorphic markers. Thus neither KIT nor EDNRB are likely to be responsible for white spotting in the Dutch population of boxers.