Does prediction error during exposure relate to clinical outcomes in cognitive behavior therapy for social anxiety disorder? A study protocol.

Facing your fears, or exposure therapy, is an effective psychological intervention for anxiety disorders that is often thought to work through fear extinction learning. Fear extinction learning is a type of associative learning where fear reduces through repeated encounters with a feared situation or stimulus in the absence of aversive outcomes. Laboratory research suggests fear extinction learning is driven by threat prediction errors, defined as when fearful predictions do not eventuate. Threat prediction error and its relationship to exposure therapy outcomes haven't been studied enough in actual therapy settings. It remains unclear whether prediction error and extinction learning are central mechanisms of exposure therapy. We are conducting a longitudinal and observational study of how threat prediction error during exposure in social anxiety disorder (SAD) treatment relates to session-by-session symptom change and treatment outcome in addition to exposure surprise and learning outcome. We aim to recruit 65 adults with a primary diagnosis of SAD through an outpatient psychology clinic. Participants will receive 12 sessions of individual manualized cognitive behavioral therapy (CBT), adapted from an efficacious group protocol, that includes graded exposure. Exposure processes, including self-report measures of anxiety, threat prediction, threat outcomes, surprise, and learning outcome, will be measured with smartphone-based event-contingent ecological momentary assessments (EMAs) of all behavioral experiments completed during treatment. Clinical outcomes include self-reported social anxiety symptoms and social threat appraisals, at each session, post and 3-months after treatment. Prediction error will be operationalized as the mismatch between the threat prediction and threat outcome. The joint effect of threat prediction and threat outcome on session-by-session symptom change, treatment outcome, exposure surprise, and learning outcome will be explored using multilevel modeling. The present study will help determine whether threat prediction error during exposures in SAD treatment is related to theoretically implied clinical outcomes. This would contribute to the larger research aim of clarifying exposure therapy mechanisms.

3D Printing Latex: A Route to Complex Geometries of High Molecular Weight Polymers.

Vat photopolymerization (VP) additive manufacturing fabricates intricate geometries with excellent resolution; however, high molecular weight polymers are not amenable to VP due to concomitant high solution and melt viscosities. Thus, a challenging paradox arises between printability and mechanical performance. This report describes concurrent photopolymer and VP system design to navigate this paradox with the unprecedented use of polymeric colloids (latexes) that effectively decouple the dependency of viscosity on molecular weight. Photocrosslinking of a continuous-phase scaffold, which surrounds the latex particles, combined with in situ computer-vision print parameter optimization, which compensates for light scattering, enables high-resolution VP of high molecular weight polymer latexes as particle-embedded green bodies. Thermal post-processing promotes coalescence of the dispersed particles throughout the scaffold, forming a semi-interpenetrating polymer network without loss in part resolution. Printing a styrene-butadiene rubber latex, a previously inaccessible elastomer composition for VP, exemplified this approach and yielded printed elastomers with precise geometry and tensile extensibilities exceeding 500%.

Sewage spills are a major source of titanium dioxide engineered (nano)-particles into the environment.

Sanitary sewer overflows (SSOs) are a common problem across the United States. An estimated 23,000-75,000 SSOs occurred annually in 2004 discharging between 11 and 38 billion liters of untreated wastewater to receiving waters. SSOs release many contaminants, including engineered nanomaterials (ENMs), to receiving water bodies. Measuring ENM concentrations in environmental samples remains a key challenge in environmental nanotechnology and requires the distinction between natural and engineered particles. This distinction between natural and engineered particles is often hampered by the similarities in the intrinsic properties of natural and engineered particles such as particle size, composition, density, surface chemistry, and by the limitations of the available nanometrology tools. To overcome these challenges, we applied a multi-method approach to measure the concentrations and properties of TiO2 engineered particles (e.g., ENMs and pigments) including 1) multi-element single particle-inductively coupled plasma-mass spectrometry (ME-SP-ICP-MS) to identify elemental associations and to determine elemental ratios in natural particles, 2) total elemental concentrations and ratios calculated from total metal concentrations measured following total sample digestion to estimate engineered particle concentrations, and 3) transmission electron microscopy (TEM) to characterize engineered particle size and morphology. ME-SP-ICP-MS analysis revealed that natural TiO2 particles are often associated with at least one of the following elements Al, Fe, Ce, Si, La, Zr, Nb, Pb, Ba, Th, Ta, W and U, and that elemental ratios of Ti to these elements is typical of riverine particulates and the average crustal ratios, except for Pb likely due to anthropogenic Pb contamination. High TiO2 engineered particle concentrations up to 100 µg L-1 were found in SSOs-impacted surface waters. TEM analysis demonstrated the presence of regular-shape TiO2 particles in SSOs-impacted surface waters. This study provides a comprehensive approach for measuring TiO2 engineered particle concentrations in surface waters. The quantitative data produced in this work can be used as input for modeling studies and pave the road toward routine monitoring of ENMs in environmental systems, validation of ENM fate models, and more accurate ENM exposure and risk assessment.

Enhanced release of palladium and platinum from catalytic converter materials exposed to ammonia and chloride bearing solutions.

The environmental levels of platinum group elements (PGEs) are steadily rising, primarily due to exhaust emissions of vehicle catalytic converter (VCC) materials containing solid PGEs. Once these VCC materials reach soil and water, the PGEs may be transported in the form of nanoparticles (dimensions 1-100 nm) or they may be mobilized by forming coordination complexes with ligands in the environment. Chloride (Cl-) and ammonia (NH3) are two ligands of particular concern due to their ubiquity as well as their potential to form the chemotherapy drug cisplatin (Pt(NH3)2Cl2) or other potentially bioactive complexes. This initial study examines the release of Pd and Pt into solutions exposed to VCC materials at pH 8 and 25 °C, using elemental analysis of metal content in post-exposure extracts. The solutions had total ammonia nitrogen concentrations (TAN, [NH4+] + [NH3]) of 0 µM, 5.56 µM, 55.6 µM and 1.13 × 105 µM (0 ppm, 0.1 ppm, 1 ppm, and 2147 ppm). The former three represent background environmental levels had a minimal effect on release. However, when combined with 1.13 × 105 µM Cl- (4000 ppm Cl-), 55.6 µM TAN induced a marked increase in metal release (∼41× for Pd). High TAN solutions induced more Pd and Pt release than equimolar NaCl solutions. Materials characterization revealed that ∼4 nm palladium-containing nanoparticles were present, spatially associated with nanoparticles of γ-Al2O3; ceria-zirconia nanoparticles were also present but did not have any metal associated with them. Platinum-containing nanoparticles were not observed.

Manganese Oxides Resembling Microbial Fabrics and Their Implications for Recognizing Inorganically Preserved Microfossils.

In the search for microfossils of early life on Earth, the demonstration of biogenicity is paramount. Traditionally, only syngenetic structures with cellular elaboration, hollow sheaths/cell walls, and indigenous kerogen have been considered bona fide fossils. Recent reports of inorganically preserved microfossils represent a shift from this practice. Such a shift, if accompanied by a robust set of biogenicity criteria, could have profound implications for the identification of biosignatures on early Earth and extraterrestrial bodies. Here, we reaffirm the conventional criteria by examining aggregates of inorganic filaments from the Pilbara region of Western Australia. These aggregates are preserved in bedded chert, and the filaments measure up to 1 µm in diameter and 100 µm in length. The aggregates superficially resemble kerogenous microbial fabrics and mycelial organisms. However, the filaments consist of manganese oxide, lack cellular elaboration, and show no evidence for hollow sheaths or cell walls. We conclude that the filaments are fibrous minerals of abiotic origin. The similarities between these pseudofossils and some filamentous fossils highlight the need for strict application of the conventional criteria for recognizing microfossils. In the absence of kerogen, morphologically simple structures should, at least, show evidence of cellular features to be considered bona fide fossils. Key Words: Fossil-Manganese oxide-Pilbara-Precambrian-Pseudofossil. Astrobiology 18, 249-258.

Discovery and ramifications of incidental Magnéli phase generation and release from industrial coal-burning.

Coal, as one of the most economic and abundant energy sources, remains the leading fuel for producing electricity worldwide. Yet, burning coal produces more global warming CO2 relative to all other fossil fuels, and it is a major contributor to atmospheric particulate matter known to have a deleterious respiratory and cardiovascular impact in humans, especially in China and India. Here we have discovered that burning coal also produces large quantities of otherwise rare Magnéli phases (Ti x O2x-1 with 4 ≤ x ≤ 9) from TiO2 minerals naturally present in coal. This provides a new tracer for tracking solid-state emissions worldwide from industrial coal-burning. In its first toxicity testing, we have also shown that nanoscale Magnéli phases have potential toxicity pathways that are not photoactive like TiO2 phases, but instead seem to be biologically active without photostimulation. In the future, these phases should be thoroughly tested for their toxicity in the human lung.Solid-state emissions from coal burning remain an environmental concern. Here, the authors have found that TiO2 minerals present in coal are converted into titanium suboxides during burning, and initial biotoxicity screening suggests that further testing is needed to look into human lung consequences.

Asymmetric Response of Ferroelastic Domain-Wall Motion under Applied Bias.

The switching of domains in ferroelectric and multiferroic materials plays a central role in their application to next-generation computer systems, sensing applications, and memory storage. A detailed understanding of the response to electric fields and the switching behavior in the presence of complex domain structures and extrinsic effects (e.g., defects and dislocations) is crucial for the design of improved ferroelectrics. In this work, in situ transmission electron microscopy is coupled with atomistic molecular dynamics simulations to explore the response of 71° ferroelastic domain walls in BiFeO3 with various orientations under applied electric-field excitation. We observe that 71° domain walls can have intrinsically asymmetric responses to opposing biases. In particular, when the electric field has a component normal to the domain wall, forward and backward domain-wall velocities can be dramatically different for equal and opposite fields. Additionally, the presence of defects and dislocations can strongly affect the local switching behaviors through pinning or nucleation of the domain walls. These results offer insight for controlled ferroelastic domain manipulation via electric-field engineering.

Speciation Matters: Bioavailability of Silver and Silver Sulfide Nanoparticles to Alfalfa (Medicago sativa).

Terrestrial crops are directly exposed to silver nanoparticles (Ag-NPs) and their environmentally transformed analog silver sulfide nanoparticles (Ag2S-NPs) when wastewater treatment biosolids are applied as fertilizer to agricultural soils. This leads to a need to understand their bioavailability to plants. In the present study, the mechanisms of uptake and distribution of silver in alfalfa (Medicago sativa) were quantified and visualized upon hydroponic exposure to Ag-NPs, Ag2S-NPs, and AgNO3 at 3 mg total Ag/L. Total silver uptake was measured in dried roots and shoots, and the spatial distribution of elements was investigated using transmission electron microscopy (TEM) and synchrotron-based X-ray imaging techniques. Despite large differences in release of Ag(+) ions from the particles, Ag-NPs, Ag2S-NPs, and Ag(+) became associated with plant roots to a similar degree, and exhibited similarly limited (<1%) amounts of translocation of silver into the shoot system. X-ray fluorescence (XRF) mapping revealed differences in the distribution of Ag into roots for each treatment. Silver nanoparticles mainly accumulated in the (columella) border cells and elongation zone, whereas Ag(+) accumulated more uniformly throughout the root. In contrast, Ag2S-NPs remained largely adhered to the root exterior, and the presence of cytoplasmic nano-SixOy aggregates was observed. Exclusively in roots exposed to particulate silver, NPs smaller than the originally dosed NPs were identified by TEM in the cell walls. The apparent accumulation of Ag in the root apoplast determined by XRF, and the presence of small NPs in root cell walls suggests uptake of partially dissolved NPs and translocation along the apoplast.

Real-time observation of local strain effects on nonvolatile ferroelectric memory storage mechanisms.

We use in situ transmission electron microscopy to directly observe, at high temporal and spatial resolution, the interaction of ferroelectric domains and dislocation networks within BiFeO3 thin films. The experimental observations are compared with a phase field model constructed to simulate the dynamics of domains in the presence of dislocations and their resulting strain fields. We demonstrate that a global network of misfit dislocations at the film-substrate interface can act as nucleation sites and slow down domain propagation in the vicinity of the dislocations. Networks of individual threading dislocations emanating from the film-electrode interface play a more dramatic role in pinning domain motion. These dislocations may be responsible for the domain behavior in ferroelectric thin-film devices deviating from conventional Kolmogorov-Avrami-Ishibashi dynamics toward a Nucleation Limited Switching model.

Microstructural changes in CdSe-coated ZnO nanowires evaluated by in situ annealing in transmission electron microscopy and x-ray diffraction.

We report on the crystallite growth and phase change of electrodeposited CdSe coatings on ZnO nanowires during annealing. Both in situ transmission electron microscopy (TEM) and x-ray diffraction (XRD) reveal that the nanocrystal size increases from ∼3 to ∼10 nm upon annealing at 350 °C for 1 h and then to more than 30 nm during another 1 h at 400 °C, exhibiting two distinct growth regimes. Nanocrystal growth occurs together with a structural change from zinc blende to wurtzite. The structural transition begins at 350 °C, which results in the formation of stacking faults. Increased crystallite size, comparable to the coating thickness, can improve charge separation in extremely thin absorber solar cells. We demonstrate a nearly two-fold improvement in power conversion efficiency upon annealing.

QTL linkage analysis of connected populations using ancestral marker and pedigree information.

The common assumption in quantitative trait locus (QTL) linkage mapping studies that parents of multiple connected populations are unrelated is unrealistic for many plant breeding programs. We remove this assumption and propose a Bayesian approach that clusters the alleles of the parents of the current mapping populations from locus-specific identity by descent (IBD) matrices that capture ancestral marker and pedigree information. Moreover, we demonstrate how the parental IBD data can be incorporated into a QTL linkage analysis framework by using two approaches: a Threshold IBD model (TIBD) and a Latent Ancestral Allele Model (LAAM). The TIBD and LAAM models are empirically tested via numerical simulation based on the structure of a commercial maize breeding program. The simulations included a pilot dataset with closely linked QTL on a single linkage group and 100 replicated datasets with five linkage groups harboring four unlinked QTL. The simulation results show that including parental IBD data (similarly for TIBD and LAAM) significantly improves the power and particularly accuracy of QTL mapping, e.g., position, effect size and individuals' genotype probability without significantly increasing computational demand.

Identity-by-descent matrix decomposition using latent ancestral allele models.

Genetic linkage and association studies are empowered by proper modeling of relatedness among individuals. Such relatedness can be inferred from marker and/or pedigree information. In this study, the genetic relatedness among n inbred individuals at a particular locus is expressed as an n x n square matrix Q. The elements of Q are identity-by-descent probabilities, that is, probabilities that two individuals share an allele descended from a common ancestor. In this representation the definition of the ancestral alleles and their number remains implicit. For human inspection and further analysis, an explicit representation in terms of the ancestral allele origin and the number of alleles is desirable. To this purpose, we decompose the matrix Q by a latent class model with K classes (latent ancestral alleles). Let P be an n x K matrix with assignment probabilities of n individuals to K classes constrained such that every element is nonnegative and each row sums to 1. The problem then amounts to approximating Q by PP(T), while disregarding the diagonal elements. This is not an eigenvalue problem because of the constraints on P. An efficient algorithm for calculating P is provided. We indicate the potential utility of the latent ancestral allele model. For representative locus-specific Q matrices constructed for a set of maize inbreds, the proposed model recovered the known ancestry.

Mixed model approaches for the identification of QTLs within a maize hybrid breeding program.

Two outlines for mixed model based approaches to quantitative trait locus (QTL) mapping in existing maize hybrid selection programs are presented: a restricted maximum likelihood (REML) and a Bayesian Markov Chain Monte Carlo (MCMC) approach. The methods use the in-silico-mapping procedure developed by Parisseaux and Bernardo (2004) as a starting point. The original single-point approach is extended to a multi-point approach that facilitates interval mapping procedures. For computational and conceptual reasons, we partition the full set of relationships from founders to parents of hybrids into two types of relations by defining so-called intermediate founders. QTL effects are defined in terms of those intermediate founders. Marker based identity by descent relationships between intermediate founders define structuring matrices for the QTL effects that change along the genome. The dimension of the vector of QTL effects is reduced by the fact that there are fewer intermediate founders than parents. Furthermore, additional reduction in the number of QTL effects follows from the identification of founder groups by various algorithms. As a result, we obtain a powerful mixed model based statistical framework to identify QTLs in genetic backgrounds relevant to the elite germplasm of a commercial breeding program. The identification of such QTLs will provide the foundation for effective marker assisted and genome wide selection strategies. Analyses of an example data set show that QTLs are primarily identified in different heterotic groups and point to complementation of additive QTL effects as an important factor in hybrid performance.

Speaker overestimation of communication effectiveness and fear of negative evaluation: being realistic is unrealistic.

Speakers systematically overestimate their communication effectiveness (Keysar & Henly, 2002). We argue that doing so is adaptive, reducing the risk of social anxiety and withdrawal from social situations. This hypothesis was tested by having speakers who scored low and high for fear of negative evaluation (FNE), a hallmark of social phobia, attempt to convey a specific meaning of ambiguous statements to a listener and then estimate their communication effectiveness. Low-FNE speakers consistently overestimated their effectiveness, expecting the listener to understand their intended meaning more often than listeners actually did. In contrast, high-FNE speakers' estimates of communication effectiveness were consistent with the listener's actual understanding. Signal detection analysis revealed that low- and high-FNE speakers were equally able to discriminate communication success from failure, but low-FNE speakers exhibited a stronger positive response bias. In conclusion, overestimating one's communication effectiveness is adaptive, and accurate estimation is associated with dysfunction.

Expert face coding: configural and component coding of own-race and other-race faces.

Configural and holistic coding are hallmarks of face perception. Although recent studies have shown that own-race faces are coded more holistically than other-race faces, the evidence for better configural coding of own-race faces is equivocal. We directly measured configural and component coding of own- and other-race male faces in Caucasian and Chinese participants. We manipulated individual features (components) or their spatial relations (configurations) using a novel morphing method to vary difficulty parametrically and tested sensitivity to these changes in a sequential matching task. Both configural and component coding were better for upright own-race than for upright other-race faces. Inversion impaired detection of configural changes more than it did detection of component changes, but also impaired performance more for easier discriminations, independent of type of change. These results challenge explanations of face expertise that rely solely on configural and holistic processing, and also call into question the widespread interpretation of large inversion decrements as diagnostic of configural coding.

Perceptual adaptation affects attractiveness of female bodies.

We investigated whether short durations (5 minutes) of exposure to distorted bodies can change subsequent perceptions of attractiveness and normality. Participants rated 110 female bodies, varying in width, on either their attractiveness or normality before and after exposure to either extremely narrow (-50% of original width in Experiments 1 and 2) or extremely wide bodies (+50% of original width in Experiment 1, and +70% of original width in Experiment 2). In both experiments, the most attractive and most normal looking bodies became significantly and substantially narrower after exposure to narrow bodies. The most normal looking body changed significantly after exposure to wide bodies, but the most attractive body did not. These results show that perceptions of body attractiveness can be influenced by experience, but that there is an asymmetry between the effects of exposure to narrow and wide bodies. We consider a possible mechanism for this unexpected asymmetry, as well as possible implications for the effects of media exposure on body-image. The most attractive body shape was consistently narrower than the most normal looking body shape. Substantial changes in what looked normal were accompanied by congruent changes in what looked attractive, suggesting that a normal or average body shape may function as a reference point against which body attractiveness is judged.

On the determination of recombination rates in intermated recombinant inbred populations.

The recurrent intermating of F(2) individuals for some number of generations followed by several generations of inbreeding produces an intermated recombinant inbred (IRI) population. Such populations are currently being developed in the plant-breeding community because linkage associations present in an F(2) population are broken down and a population of fixed inbred lines is also created. The increased levels of recombination enable higher-resolution mapping in IRI populations relative to F(2) populations. Herein we derive relationships, under several limiting assumptions, for determining the expected recombination fraction in IRI populations from the crossover rate per meiosis. These relationships are applicable to situations where the inbreeding component of IRI population development is by either self-fertilization or full-sib mating. Additionally, we show that the derived equations can be solved for the crossover rate per meiosis if the recombination fraction is known for the IRI population. Thus, the observed recombination fraction in any IRI population can be expressed on an F(2) basis. The implications of this work on the expansion of genetic maps in IRI populations and limits for detecting linkage between markers are also considered.