Induced Anticlinic Ordering and Nanophase Segregation of Bow-Shaped Molecules in a Smectic Solvent

Recent experiments indicate that doping low concentrations of bent-core molecules into calamitic smectic solvents can induce anticlinic and biaxial smectic phases. We have carried out Monte Carlo (MC) simulations of mixtures of rodlike molecules (hard spherocylinders with length/breadth ratio $L_{\rm rod}/D = 5$) and bow- or banana-shaped molecules (hard spherocylinder dimers with length/breadth ratio $L_{ban}/D = 5$ or 2.5 and opening angle $\psi$) to probe the molecular-scale organization and phase behavior of rod/banana mixtures. We find that a low concentration (3%) of $L_{ban}/D = 5$ dimers induces anticlinic (SmC$_A$) ordering in an untilted smectic (SmA) phase for $100^\circ \le \psi < 150^\circ$. For smaller $\psi$, half of each bow-shaped molecule is nanophase segregated between smectic layers, and the smectic layers are untilted. For $L_{ban}/D = 2.5$, no tilted phases are induced. However, with decreasing $\psi$ we observe a sharp transition from {\sl intralamellar} nanophase segregation (bow-shaped molecules segregated within smectic layers) to {\sl interlamellar} nanophase segregation (bow-shaped molecules concentrated between smectic layers) near $\psi = 130^\circ$. These results demonstrate that purely entropic effects can lead to surprisingly complex behavior in rod/banana mixtures.Comment: 5 pages Revtex, 7 postscript figure

Direct sequencing of the human microbiome readily reveals community differences

Future sequencing of the human microbiota will require greater breadth rather than depth

Transkingdom Networks: A Systems Biology Approach to Identify Causal Members of Host-Microbiota Interactions

Improvements in sequencing technologies and reduced experimental costs have resulted in a vast number of studies generating high-throughput data. Although the number of methods to analyze these "omics" data has also increased, computational complexity and lack of documentation hinder researchers from analyzing their high-throughput data to its true potential. In this chapter we detail our data-driven, transkingdom network (TransNet) analysis protocol to integrate and interrogate multi-omics data. This systems biology approach has allowed us to successfully identify important causal relationships between different taxonomic kingdoms (e.g. mammals and microbes) using diverse types of data

The role of parental achievement goals in predicting autonomy-supportive and controlling parenting

Although autonomy-supportive and controlling parenting are linked to numerous positive and negative child outcomes respectively, fewer studies have focused on their determinants. Drawing on achievement goal theory and self-determination theory, we propose that parental achievement goals (i.e., achievement goals that parents have for their children) can be mastery, performance-approach or performance-avoidance oriented and that types of goals predict mothers' tendency to adopt autonomy-supportive and controlling behaviors. A total of 67 mothers (aged 30-53 years) reported their goals for their adolescent (aged 13-16 years; 19.4 % girls), while their adolescent evaluated their mothers' behaviors. Hierarchical regression analyses showed that parental performance-approach goals predict more controlling parenting and prevent acknowledgement of feelings, one autonomy-supportive behavior. In addition, mothers who have mastery goals and who endorse performance-avoidance goals are less likely to use guilt-inducing criticisms. These findings were observed while controlling for the effect of maternal anxiety

The Challenge of Informed Consent and Return of Results in Translational Genomics: Empirical Analysis and Recommendations

As exome and genome sequencing move into clinical application, questions surround how to elicit consent and handle potential return of individual genomic results. This study analyzes nine consent forms used in NIH-funded sequencing studies. Content analysis reveals considerable heterogeneity, including in defining results that may be returned, identifying potential benefits and risks of return, protecting privacy, addressing placement of results in the medical record, and data-sharing. In response to lack of consensus, we offer recommendations

Predicting growth curves of early childhood externalizing problems: Differential susceptibility of children with difficult temperament

Using an accelerated longitudinal design, the development of externalizing problems from age 2 to 5 years was investigated in relation to maternal psychopathology, maternal parenting, gender, child temperament, and the presence of siblings. The sample consisted of 150 children selected at age 2-3 years for having high levels of externalizing problems. Parenting was measured using observational methods, and maternal reports were used for the other variables. Overall, mean levels of externalizing problems decreased over time, and higher initial levels (intercept) were related to a stronger decrease (negative slope) in externalizing problems. Results showed that higher levels of maternal psychopathology were related to less decrease in early childhood externalizing problems. Parental sensitive behavior predicted a stronger decrease in externalizing problems, but only for children with difficult temperaments. A stronger decrease of externalizing problems in children with older siblings also pertained only to children with difficult temperaments. Thus, temperamentally difficult children appear to be more susceptible to environmental influences on the development of externalizing behaviors. Our results indicate that the role of siblings in early childhood externalizing problems deserves more research attention, and that intervention efforts need to take into account temperamental differences in children's susceptibility to environmental influences. © 2009 Springer Science+Business Media, LLC

Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community’s functional capabilities. Here we describe PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this ‘predictive metagenomic’ approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available