Small-sample robust estimators of noncentrality-based and incremental model fit

Traditional estimators of fit measures based on the noncentral chi-square distribution (root mean square error of approximation [RMSEA], Steiger's , etc.) tend to overreject acceptable models when the sample size is small. To handle this problem, it is proposed to employ Bartlett's (1950), Yuan's (2005), or Swain's (1975) correction of the maximum likelihood chi-square statistic for the estimation of noncentrality-based fit measures. In a Monte Carlo study, it is shown that Swain's correction especially produces reliable estimates and confidence intervals for different degrees of model misspecification (RMSEA range: 0.000-0.096) and sample sizes (50, 75, 100, 150, 200). In the second part of the article, the study is extended to incremental fit indexes (Tucker-Lewis Index, Comparative Fit Index, etc.). For their small-sample robust estimation, use of Swain's correction is recommended only for the target model, not for the independence model. The Swain-corrected estimators only require a ratio of sample size to estimated parameters of about 2:1 (sometimes even less) and are thus strongly recommended for applied research. R software is provided for convenient use

Heritability of testosterone levels in 12-year-old twins and its relation to pubertal development

The aim of this study was to estimate the heritability of variation in testosterone levels in 12-year-old children, and to explore the overlap in genetic and environmental influences on circulating testosterone levels and androgen dependent pubertal development. Midday salivary testosterone samples were collected on two consecutive days in a sample of 183 unselected twin pairs. Androgen induced pubertal development was assessed using self report Tanner scales of pubic hair development (boys and girls) and genital development (boys). A significant contribution of genetic effects to the variance in testosterone levels was found. Heritability was approximately 50% in both boys and girls. The remaining proportion of the variance in testosterone levels could be explained by non-shared environmental influences. The relatively high correlation between testosterone levels of opposite sex dizygotic twins suggests that sex differences in genes influencing variation in testosterone levels have not yet developed in pre- and early puberty. Variance in pubertal development was explained by a large genetic component, moderate shared environmental influences, and a small non-shared environmental effect. Testosterone levels correlated moderately (r = .31) with pubertal development; the covariance between testosterone levels and pubertal development was entirely accounted for by genetic influences

Variance Decomposition Using an IRT Measurement Model

Large scale research projects in behaviour genetics and genetic epidemiology are often based on questionnaire or interview data. Typically, a number of items is presented to a number of subjects, the subjects’ sum scores on the items are computed, and the variance of sum scores is decomposed into a number of variance components. This paper discusses several disadvantages of the approach of analysing sum scores, such as the attenuation of correlations amongst sum scores due to their unreliability. It is shown that the framework of Item Response Theory (IRT) offers a solution to most of these problems. We argue that an IRT approach in combination with Markov chain Monte Carlo (MCMC) estimation provides a flexible and efficient framework for modelling behavioural phenotypes. Next, we use data simulation to illustrate the potentially huge bias in estimating variance components on the basis of sum scores. We then apply the IRT approach with an analysis of attention problems in young adult twins where the variance decomposition model is extended with an IRT measurement model. We show that when estimating an IRT measurement model and a variance decomposition model simultaneously, the estimate for the heritability of attention problems increases from 40% (based on sum scores) to 73%

Rapid shifts in Atta cephalotes fungus-garden enzyme activity after a change in fungal substrate (Attini, Formicidae)

Fungus gardens of the basidiomycete Leucocoprinus gongylophorus sustain large colonies of leaf-cutting ants by degrading the plant material collected by the ants. Recent studies have shown that enzyme activity in these gardens is primarily targeted toward starch, proteins and the pectin matrix associated with cell walls, rather than toward structural cell wall components such as cellulose and hemicelluloses. Substrate constituents are also known to be sequentially degraded in different sections of the fungus garden. To test the plasticity in the extracellular expression of fungus-garden enzymes, we measured the changes in enzyme activity after a controlled shift in fungal substrate offered to six laboratory colonies of Atta cephalotes. An ant diet consisting exclusively of grains of parboiled rice rapidly increased the activity of endo-proteinases and some of the pectinases attacking the backbone structure of pectin molecules, relative to a pure diet of bramble leaves, and this happened predominantly in the most recently established top sections of fungus gardens. However, fungus-garden amylase activity did not significantly increase despite the substantial increase in starch availability from the rice diet, relative to the leaf diet controls. Enzyme activity in the older, bottom sections of fungus gardens decreased, indicating a faster processing of the rice substrate compared to the leaf diet. These results suggest that leaf-cutting ant fungus gardens can rapidly adjust enzyme activity to provide a better match with substrate availability and that excess starch that is not protected by cell walls may be digested by the ants rather than by the fungus-garden symbiont

Ionized and neutral gas in the peculiar star/cluster complex in NGC 6946

The characteristics of ionized and HI gas in the peculiar star/cluster complex in NGC 6946, obtained with the 6-m telescope (BTA) SAO RAS, the Gemini North telescope, and the Westerbork Synthesis Radio Telescope (WSRT), are presented. The complex is unusual as hosting a super star cluster, the most massive known in an apparently non-interacting giant galaxy. It contains a number of smaller clusters and is bordered by a sharp C-shaped rim. We found that the complex is additionally unusual in having peculiar gas kinematics. The velocity field of the ionized gas reveals a deep oval minimum, ~300 pc in size, centered 7" east of the supercluster. The Vr of the ionized gas in the dip center is 100 km/s lower than in its surroundings, and emission lines within the dip appear to be shock excited. This dip is near the center of an HI hole and a semi-ring of HII regions. The HI (and less certainly, HII) velocity fields reveal expansion, with the velocity reaching ~30 km/s at a distance about 300 pc from the center of expansion, which is near the deep minimum position. The super star cluster is at the western rim of the minimum. The sharp western rim of the whole complex is plausibly a manifestation of a regular dust arc along the complex edge. Different hypotheses about the complex and the Vr depression origins are discussed, including a HVC/dark mini-halo impact, a BCD galaxy merging, and a gas outflow due to release of energy from the supercluster stars.Comment: MN RAS, accepte

Metabolomics Profile in Depression:A Pooled Analysis of 230 Metabolic Markers in 5283 Cases With Depression and 10,145 Controls

BACKGROUND: Depression has been associated with metabolic alterations, which adversely impact cardiometabolic health. Here, a comprehensive set of metabolic markers, predominantly lipids, was compared between depressed and nondepressed persons. METHODS: Nine Dutch cohorts were included, comprising 10,145 control subjects and 5283 persons with depression, established with diagnostic interviews or questionnaires. A proton nuclear magnetic resonance metabolomics platform provided 230 metabolite measures: 51 lipids, fatty acids, and low-molecular-weight metabolites; 98 lipid composition and particle concentration measures of lipoprotein subclasses; and 81 lipid and fatty acids ratios. For each metabolite measure, logistic regression analyses adjusted for gender, age, smoking, fasting status, and lipid-modifying medication were performed within cohort, followed by random-effects meta-analyses. RESULTS: Of the 51 lipids, fatty acids, and low-molecular-weight metabolites, 21 were significantly related to depression (false discovery rate q < .05). Higher levels of apolipoprotein B, very-low-density lipoprotein cholesterol, triglycerides, diglycerides, total and monounsaturated fatty acids, fatty acid chain length, glycoprotein acetyls, tyrosine, and isoleucine and lower levels of high-density lipoprotein cholesterol, acetate, and apolipoprotein A1 were associated with increased odds of depression. Analyses of lipid composition indicators confirmed a shift toward less high-density lipoprotein and more very-low-density lipoprotein and triglyceride particles in depression. Associations appeared generally consistent across gender, age, and body mass index strata and across cohorts with depressive diagnoses versus symptoms. CONCLUSIONS: This large-scale meta-analysis indicates a clear distinctive profile of circulating lipid metabolites associated with depression, potentially opening new prevention or treatment avenues for depression and its associated cardiometabolic comorbidity