Serum Amyloid P Is a Sialylated Glycoprotein Inhibitor of Influenza A Viruses

Members of the pentraxin family, including PTX3 and serum amyloid P component (SAP), have been reported to play a role in innate host defence against a range of microbial pathogens, yet little is known regarding their antiviral activities. In this study, we demonstrate that human SAP binds to human influenza A virus (IAV) strains and mediates a range of antiviral activities, including inhibition of IAV-induced hemagglutination (HA), neutralization of virus infectivity and inhibition of the enzymatic activity of the viral neuraminidase (NA). Characterization of the anti-IAV activity of SAP after periodate or bacterial sialidase treatment demonstrated that α(2,6)-linked sialic acid residues on the glycosidic moiety of SAP are critical for recognition by the HA of susceptible IAV strains. Other proteins of the innate immune system, namely human surfactant protein A and porcine surfactant protein D, have been reported to express sialylated glycans which facilitate inhibition of particular IAV strains, yet the specific viral determinants for recognition of these inhibitors have not been defined. Herein, we have selected virus mutants in the presence of human SAP and identified specific residues in the receptor-binding pocket of the viral HA which are critical for recognition and therefore susceptibility to the antiviral activities of SAP. Given the widespread expression of α(2,6)-linked sialic acid in the human respiratory tract, we propose that SAP may act as an effective receptor mimic to limit IAV infection of airway epithelial cells.     

Signatures of Demography and Recombination at Coding Genes in Naturally-Distributed Populations of Arabidopsis Lyrata Subsp. Petraea

Demography impacts the observed standing level of genetic diversity present in populations. Distinguishing the relative impacts of demography from selection requires a baseline of expressed gene variation in naturally occurring populations. Six nuclear genes were sequenced to estimate the patterns and levels of genetic diversity in natural Arabidopsis lyrata subsp. petraea populations that differ in demographic histories since the Pleistocene. As expected, northern European populations have genetic signatures of a strong population bottleneck likely due to glaciation during the Pleistocene. Levels of diversity in the northern populations are about half of that in central European populations. Bayesian estimates of historical population size changes indicate that central European populations also have signatures of population size change since the last glacial maxima, suggesting that these populations are not as stable as previously thought. Time since divergence amongst northern European populations is higher than amongst central European populations, suggesting that the northern European populations were established before the Pleistocene and survived glaciation in small separated refugia. Estimates of demography based on expressed genes are complementary to estimates based on microsatellites and transposable elements, elucidating temporal shifts in population dynamics and confirming the importance of marker selection for tests of demography.     

WormSizer: High-throughput Analysis of Nematode Size and Shape

The fundamental phenotypes of growth rate, size and morphology are the result of complex interactions between genotype and environment. We developed a high-throughput software application, WormSizer, which computes size and shape of nematodes from brightfield images. Existing methods for estimating volume either coarsely model the nematode as a cylinder or assume the worm shape or opacity is invariant. Our estimate is more robust to changes in morphology or optical density as it only assumes radial symmetry. This open source software is written as a plugin for the well-known image-processing framework Fiji/ImageJ. It may therefore be extended easily. We evaluated the technical performance of this framework, and we used it to analyze growth and shape of several canonical Caenorhabditis elegans mutants in a developmental time series. We confirm quantitatively that a Dumpy (Dpy) mutant is short and fat and that a Long (Lon) mutant is long and thin. We show that daf-2 insulin-like receptor mutants are larger than wild-type upon hatching but grow slow, and WormSizer can distinguish dauer larvae from normal larvae. We also show that a Small (Sma) mutant is actually smaller than wild-type at all stages of larval development. WormSizer works with Uncoordinated (Unc) and Roller (Rol) mutants as well, indicating that it can be used with mutants despite behavioral phenotypes. We used our complete data set to perform a power analysis, giving users a sense of how many images are needed to detect different effect sizes. Our analysis confirms and extends on existing phenotypic characterization of well-characterized mutants, demonstrating the utility and robustness of WormSizer.     

The Dartmouth Database of Children’s Faces: Acquisition and Validation of a New Face Stimulus Set

Facial identity and expression play critical roles in our social lives. Faces are therefore frequently used as stimuli in a variety of areas of scientific research. Although several extensive and well-controlled databases of adult faces exist, few databases include children’s faces. Here we present the Dartmouth Database of Children’s Faces, a set of photographs of 40 male and 40 female Caucasian children between 6 and 16 years-of-age. Models posed eight facial expressions and were photographed from five camera angles under two lighting conditions. Models wore black hats and black gowns to minimize extra-facial variables. To validate the images, independent raters identified facial expressions, rated their intensity, and provided an age estimate for each model. The Dartmouth Database of Children’s Faces is freely available for research purposes and can be downloaded by contacting the corresponding author by email.     

Developing Prediction Equations and a Mobile Phone Application to Identify Infants at Risk of Obesity

Background

Advancements in knowledge of obesity aetiology and mobile phone technology have created the opportunity to develop an electronic tool to predict an infant’s risk of childhood obesity. The study aims were to develop and validate equations for the prediction of childhood obesity and integrate them into a mobile phone application (App).

Methods and Findings

Anthropometry and childhood obesity risk data were obtained for 1868 UK-born White or South Asian infants in the Born in Bradford cohort. Logistic regression was used to develop prediction equations (at 6±1.5, 9±1.5 and 12±1.5 months) for risk of childhood obesity (BMI at 2 years >91^st centile and weight gain from 0–2 years >1 centile band) incorporating sex, birth weight, and weight gain as predictors. The discrimination accuracy of the equations was assessed by the area under the curve (AUC); internal validity by comparing area under the curve to those obtained in bootstrapped samples; and external validity by applying the equations to an external sample. An App was built to incorporate six final equations (two at each age, one of which included maternal BMI). The equations had good discrimination (AUCs 86–91%), with the addition of maternal BMI marginally improving prediction. The AUCs in the bootstrapped and external validation samples were similar to those obtained in the development sample. The App is user-friendly, requires a minimum amount of information, and provides a risk assessment of low, medium, or high accompanied by advice and website links to government recommendations.

Conclusions

Prediction equations for risk of childhood obesity have been developed and incorporated into a novel App, thereby providing proof of concept that childhood obesity prediction research can be integrated with advancements in technology.     

A single major QTL controls expression of larval Cry1F resistance trait in Ostrinia nubilalis (Lepidoptera: Crambidae) and is independent of midgut receptor genes

The European corn borer, Ostrinia nubilalis (Lepidoptera: Crambidae), is an introduced crop pest in North America that causes major damage to corn and reduces yield of food, feed, and biofuel materials. The Cry1F toxin from Bacillus thuringiensis (Bt) expressed in transgenic hybrid corn is highly toxic to O. nubilalis larvae and effective in minimizing feeding damage. A laboratory colony of O. nubilalis was selected for high levels of Cry1F resistance (>12,000-fold compared to susceptible larvae) and is capable of survival on transgenic hybrid corn. Genetic linkage maps with segregating AFLP markers show that the Cry1F resistance trait is controlled by a single quantitative trait locus (QTL) on linkage group 12. The map position of single nucleotide polymorphism (SNP) markers indicated that midgut Bt toxin-receptor genes, alkaline phosphatase, aminopeptidase N, and cadherin, are not linked with the Cry1F QTL. Evidence suggests that genes within this genome interval may give rise to a novel Bt toxin resistance trait for Lepidoptera that appears independent of known receptor-based mechanisms of resistance.