Infant neural sensitivity to dynamic eye gaze is associated with later emerging autism

Autism spectrum disorders (henceforth autism) are diagnosed in around 1% of the population [1]. Familial liability confers risk for a broad spectrum of difficulties including the broader autism phenotype (BAP) [2, 3]. There are currently no reliable predictors of autism in infancy, but characteristic behaviors emerge during the second year, enabling diagnosis after this age [4, 5]. Because indicators of brain functioning may be sensitive predictors, and atypical eye contact is characteristic of the syndrome [6-9] and the BAP [10, 11], we examined whether neural sensitivity to eye gaze during infancy is associated with later autism outcomes [12, 13]. We undertook a prospective longitudinal study of infants with and without familial risk for autism. At 6-10 months, we recorded infants' event-related potentials (ERPs) in response to viewing faces with eye gaze directed toward versus away from the infant [14]. Longitudinal analyses showed that characteristics of ERP components evoked in response to dynamic eye gaze shifts during infancy were associated with autism diagnosed at 36 months. ERP responses to eye gaze may help characterize developmental processes that lead to later emerging autism. Findings also elucidate the mechanisms driving the development of the social brain in infancy.     

Evolutionary optimization of fluorescent proteins for intracellular FRET

Fluorescent proteins that exhibit Forster resonance energy transfer (FRET) have made a strong impact as they enable measurement of molecular-scale distances through changes in fluorescence. FRET-based approaches have enabled otherwise intractable measurements of molecular concentrations, binding interactions and catalytic activity, but are limited by the dynamic range and sensitivity of the donor-acceptor pair. To address this problem, we applied a quantitative evolutionary strategy using fluorescence-activated cell sorting to optimize a cyan-yellow fluorescent protein pair for FRET. The resulting pair, CyPet-YPet, exhibited a 20-fold ratiometric FRET signal change, as compared to threefold for the parental pair. The optimized FRET pair enabled high-throughput flow cytometric screening of cells undergoing caspase-3-dependent apoptosis. The CyPet-YPet energy transfer pair provides substantially improved sensitivity and dynamic range for a broad range of molecular imaging and screening applications.     

Spotiton: a prototype for an integrated inkjet dispense and vitrification system for cryo-TEM

Over the last three decades, Cryo-TEM has developed into a powerful technique for high-resolution imaging of biological macromolecules in their native vitrified state. However, the method for vitrifying specimens onto EM grids is essentially unchanged - application of ～3 μL sample to a grid, followed by blotting and rapid plunge freezing into liquid ethane. Several trials are often required to obtain suitable thin (few hundred nanometers or less) vitrified layers amenable for cryo-TEM imaging, which results in waste of precious sample and resources. While commercially available instruments provide some level of automation to control the vitrification process in an effort to increase quality and reproducibility, obtaining satisfactory vitrified specimens remains a bottleneck in the Cryo-TEM pipeline. We describe here a completely novel method for EM specimen preparation based on small volume (picoliter to nanoliter) dispensing using inkjet technology. A first prototype system (Spotiton v0.5) demonstrates feasibility of this new approach for specimen vitrification. A piezo-electric inkjet dispenser is integrated with optical real-time cameras (100 Hz frame rate) to analyze picoliter to nanoliter droplet profiles in-flight and spreading dynamics on the grid, and thus provides a method to optimize timing of the process. Using TEM imaging and biochemical assays we demonstrate that the piezo-electric inkjet mechanism does not disrupt the structural or functional integrity of macromolecules. These preliminary studies provide insight into the factors and components that will need further development to enable a robust and repeatable technique for specimen vitrification using this novel approach.     

Serendipitous syntheses of Rh(H)2Cl(PRPh2)3 complexes, and their crystal structures, where R = Me, Cy (cyclohexyl)

Reactions of RhCl(cod)(THP) (cod = 1,5-cyclooctadiene; THP = P(CH₂OH)₃) with PMePh₂ or PCyPh₂ (Cy = cyclohexyl) in acetone/MeOH solution under H₂ surprisingly form the complexes cis, mer-Rh(H)₂Cl(PRPh₂)₃ (R = Me or Cy); both complexes are characterized by crystallography (the first structures in which the hydride ligands of such dihydrido-chloro-trisphosphine complexes have been located), and by detailed ¹H and ³¹P NMR spectroscopy. The key role of the THP in the observed chemistry is discussed.     

Dendritic cells and cytokines in human inflammatory and autoimmune diseases

Dendritic cells (DCs) produce cytokines and are susceptible to cytokine-mediated activation. Thus, interaction of resting immature DCs with TLR ligands, for example nucleic acids, or with microbes leads to a cascade of pro-inflammatory cytokines and skewing of T cell responses. Conversely, several cytokines are able to trigger DC activation (maturation) via autocrine, for example TNF and plasmacytoid DCs, and paracrine, for example type I IFN and myeloid DCs, pathways. By controlling DC activation, cytokines regulate immune homeostasis and the balance between tolerance and immunity. The increased production and/or bioavailability of cytokines and associated alterations in DC homeostasis have been implicated in various human inflammatory and autoimmune diseases. Targeting these cytokines with biological agents as already is the case with TNF and IL-1 represents a success of immunology and the coming years will expand the range of cytokines as therapeutic targets in autoinflammatory and autoimmune pathology.     

Large-scale production of a therapeutic protein in transgenic tobacco plants: effect of subcellular targeting on quality of a recombinant dog gastric lipase

A recombinant dog gastric lipase with therapeutic potential for the treatment of exocrine pancreatic insufficiency was expressed in transgenic tobacco plants. We targeted the protein using two different signal sequences for either vacuolar retention or secretion. In both cases, an active glycosylated recombinant protein was obtained. The recombinant enzymes and the native enzyme displayed similar properties including acid resistance and acidic optimum pH. The proteolytic maturation and the specific activity of the recombinant proteins, however, were found to be dependent on subcellular compartmentalization. Expression levels of recombinant dog gastric lipase were about 5% and 7% of acid extractable plant proteins for vacuolar retention and secretion respectively. This expression system already has allowed the production of tens of grams of purified lipase through open-field culture of transgenic tobacco plants.     

An eco-informatics tool for microbial community studies: supervised classification of Amplicon Length Heterogeneity (ALH) profiles of 16S rRNA

Support vector machines (SVM) and K-nearest neighbors (KNN) are two computational machine learning tools that perform supervised classification. This paper presents a novel application of such supervised analytical tools for microbial community profiling and to distinguish patterning among ecosystems. Amplicon length heterogeneity (ALH) profiles from several hypervariable regions of 16S rRNA gene of eubacterial communities from Idaho agricultural soil samples and from Chesapeake Bay marsh sediments were separately analyzed. The profiles from all available hypervariable regions were concatenated to obtain a combined profile, which was then provided to the SVM and KNN classifiers. Each profile was labeled with information about the location or time of its sampling. We hypothesized that after a learning phase using feature vectors from labeled ALH profiles, both these classifiers would have the capacity to predict the labels of previously unseen samples. The resulting classifiers were able to predict the labels of the Idaho soil samples with high accuracy. The classifiers were less accurate for the classification of the Chesapeake Bay sediments suggesting greater similarity within the Bay's microbial community patterns in the sampled sites. The profiles obtained from the V1+V2 region were more informative than that obtained from any other single region. However, combining them with profiles from the V1 region (with or without the profiles from the V3 region) resulted in the most accurate classification of the samples. The addition of profiles from the V 9 region appeared to confound the classifiers. Our results show that SVM and KNN classifiers can be effectively applied to distinguish between eubacterial community patterns from different ecosystems based only on their ALH profiles.