Multinational Tagging Efforts Illustrate Regional Scale of Distribution and Threats for East Pacific Green Turtles (Chelonia mydas agassizii)

To further describe movement patterns and distribution of East Pacific green turtles (Chelonia mydas agassizii) and to determine threat levels for this species within the Eastern Pacific. In order to do this we combined published data from existing flipper tagging and early satellite tracking studies with data from an additional 12 satellite tracked green turtles (1996-2006). Three of these were tracked from their foraging grounds in the Gulf of California along the east coast of the Baja California peninsula to their breeding grounds in Michoacán (1337-2928 km). In addition, three post-nesting females were satellite tracked from Colola beach, Michoacán to their foraging grounds in southern Mexico and Central America (941.3-3020 km). A further six turtles were tracked in the Gulf of California within their foraging grounds giving insights into the scale of ranging behaviour. Turtles undertaking long-distance migrations showed a tendency to follow the coastline. Turtles tracked within foraging grounds showed that foraging individuals typically ranged up to 691.6 km (maximum) from release site location. Additionally, we carried out threat analysis (using the cumulative global human impact in the Eastern Pacific) clustering pre-existing satellite tracking studies from Galapagos, Costa Rica, and data obtained from this study; this indicated that turtles foraging and nesting in Central American waters are subject to the highest anthropogenic impact. Considering that turtles from all three rookeries were found to migrate towards Central America, it is highly important to implement conservation plans in Central American coastal areas to ensure the survival of the remaining green turtles in the Eastern Pacific. Finally, by combining satellite tracking data from this and previous studies, and data of tag returns we created the best available distributional patterns for this particular sea turtle species, which emphasized that conservation measures in key areas may have positive consequences on a regional scale.     

Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset

For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.     

Impact of Protein Palmitoylation on the Virulence Potential of Cryptococcus neoformans

The localization and specialized function of Ras-like proteins are largely determined by posttranslational processing events. In a highly regulated process, palmitoyl groups may be added to C-terminal cysteine residues, targeting these proteins to specific membranes. In the human fungal pathogen Cryptococcus neoformans, Ras1 protein palmitoylation is essential for growth at high temperature but is dispensable for sexual differentiation. Ras1 palmitoylation is also required for localization of this protein on the plasma membrane. Together, these results support a model in which specific Ras functions are mediated from different subcellular locations. We therefore hypothesize that proteins that activate Ras1 or mediate Ras1 localization to the plasma membrane will be important for C. neoformans pathogenesis. To further characterize the Ras1 signaling cascade mediating high-temperature growth, we have identified a family of protein S-acyltransferases (PATs), enzymes that mediate palmitoylation, in the C. neoformans genome database. Deletion strains for each candidate gene were generated by homogenous recombination, and each mutant strain was assessed for Ras1-mediated phenotypes, including high-temperature growth, morphogenesis, and sexual development. We found that full Ras1 palmitoylation and function required one particular PAT, Pfa4, and deletion of the PFA4 gene in C. neoformans resulted in altered Ras1 localization to membranes, impaired growth at 37°C, and reduced virulence.     

A Quantitative Diffuse Reflectance Imaging (QDRI) System for Comprehensive Surveillance of the Morphological Landscape in Breast Tumor Margins

In an ongoing effort to address the clear clinical unmet needs surrounding breast conserving surgery (BCS), our group has developed a next-generation multiplexed optical-fiber-based tool to assess breast tumor margin status during initial surgeries. Specifically detailed in this work is the performance and clinical validation of a research-grade intra-operative tool for margin assessment based on diffuse optical spectroscopy. Previous work published by our group has illustrated the proof-of-concept generations of this device; here we incorporate a highly optimized quantitative diffuse reflectance imaging (QDRI) system utilizing a wide-field (imaging area = 17cm²) 49-channel multiplexed fiber optic probe, a custom raster-scanning imaging platform, a custom dual-channel white LED source, and an astronomy grade imaging CCD and spectrograph. The system signal to noise ratio (SNR) was found to be greater than 40dB for all channels. Optical property estimation error was found to be less than 10%, on average, over a wide range of absorption (μ_a = 0–8.9cm^-1) and scattering (μ_s’ = 7.0–9.7cm^-1) coefficients. Very low inter-channel and CCD crosstalk was observed (2% max) when used on turbid media (including breast tissue). A raster-scanning mechanism was developed to achieve sub-pixel resolution and was found to be optimally performed at an upsample factor of 8, affording 0.75mm spatially resolved diffuse reflectance images (λ = 450–600nm) of an entire margin (area = 17cm²) in 13.8 minutes (1.23cm²/min). Moreover, controlled pressure application at the probe-tissue interface afforded by the imaging platform reduces repeated scan variability, providing <1% variation across repeated scans of clinical specimens. We demonstrate the clinical utility of this device through a pilot 20-patient study of high-resolution optical parameter maps of the ratio of the β-carotene concentration to the reduced scattering coefficient. An empirical cumulative distribution function (eCDF) analysis is used to reduce optical property maps to quantitative distributions representing the morphological landscape of breast tumor margins. The optimizations presented in this work provide an avenue to rapidly survey large tissue areas on intra-operative time scales with improved sensitivity to regions of focal disease that may otherwise be overlooked.     

Two CDC42 paralogues modulate Cryptococcus neoformans thermotolerance and morphogenesis under host physiological conditions

The precise regulation of morphogenesis is a key mechanism by which cells respond to a variety of stresses, including those encountered by microbial pathogens in the host. The polarity protein Cdc42 regulates cellular morphogenesis throughout eukaryotes, and we explore the role of Cdc42 proteins in the host survival of the human fungal pathogen Cryptococcus neoformans. Uniquely, C. neoformans has two functional Cdc42 paralogues, Cdc42 and Cdc420. Here we investigate the contribution of each paralogue to resistance to host stress. In contrast to non‐pathogenic model organisms, C. neoformans Cdc42 proteins are not required for viability under non‐stress conditions but are required for resistance to high temperature. The paralogues play differential roles in actin and septin organization and act downstream of C. neoformans Ras1 to regulate its morphogenesis sub‐pathway, but not its effects on mating. Cdc42, and not Cdc420, is upregulated in response to temperature stress and is required for virulence in a murine model of cryptococcosis. The C. neoformans Cdc42 proteins likely perform complementary functions with other Rho‐like GTPases to control cell polarity, septin organization and hyphal transitions that allow survival in the environment and in the host.     

Discovery of a novel series of potent S1P1 agonists

The discovery of a novel series of S1P1 agonists is described. Starting from a micromolar HTS positive, iterative optimization gave rise to several single-digit nanomolar S1P1 agonists. The compounds were able to induce internalization of the S1P1 receptor, and a selected compound was shown to be able to induce lymphopenia in mice after oral dosing.     

Effect of Size,Quaternary Structure and Translational Error on the Static and Dynamic Heterogeneity of β-Galactosidase and Measurement of Electrophoretic Dynamic Heterogeneity

Single enzyme molecule assays were performed using capillary electrophoresis-based protocols on β-galactosidase from Lactobacillus delbrueckii, Lactobacillus reuteri, Lactobacillus helveticus and Bacillus circulans. The enzyme was found to show static heterogeneity with respect to catalytic rate and the variance in rate increased with protein size. This is consistent with the proposal that random errors in translation may be an important underlying component of enzyme heterogeneity. Additionally these enzymes were found to show static heterogeneity with respect to electrophoretic mobility. Comparison of wild-type and rpsL E. coli β-galactosidase expressed in the presence and absence of streptomycin suggested that increases in error do not result in detectable increases in the dynamic heterogeneity of activity with increasing temperature. Finally, a method was developed to measure the dynamic heterogeneity in electrophoretic mobility.