Sialylneolacto-N-tetraose c (LSTc)-bearing Liposomal Decoys Capture Influenza A Virus

Influenza is a severe disease in humans and animals with few effective therapies available. All strains of influenza virus are prone to developing drug resistance due to the high mutation rate in the viral genome. A therapeutic agent that targets a highly conserved region of the virus could bypass resistance and also be effective against multiple strains of influenza. Influenza uses many individually weak ligand binding interactions for a high avidity multivalent attachment to sialic acid-bearing cells. Polymerized sialic acid analogs can form multivalent interactions with influenza but are not ideal therapeutics due to solubility and toxicity issues. We used liposomes as a novel means for delivery of the glycan sialylneolacto-N-tetraose c (LSTc). LSTc-bearing decoy liposomes form multivalent, polymer-like interactions with influenza virus. Decoy liposomes competitively bind influenza virus in hemagglutination inhibition assays and inhibit infection of target cells in a dose-dependent manner. Inhibition is specific for influenza virus, as inhibition of Sendai virus and respiratory syncytial virus is not observed. In contrast, monovalent LSTc does not bind influenza virus or inhibit infectivity. LSTc decoy liposomes prevent the spread of influenza virus during multiple rounds of replication in vitro and extend survival of mice challenged with a lethal dose of virus. LSTc decoy liposomes co-localize with fluorescently tagged influenza virus, whereas control liposomes do not. Considering the conservation of the hemagglutinin binding pocket and the ability of decoy liposomes to form high avidity interactions with influenza hemagglutinin, our decoy liposomes have potential as a new therapeutic agent against emerging influenza strains.     

Separating the contributions of vascular anatomy and blood viscosity to peripheral resistance and the physiological implications of interspecific resistance variation in amphibians

Amphibian pulmonary and systemic vascular circuits are arranged in parallel, with potentially important consequences for resistance (R) to blood flow. The contribution of the parallel anatomic arrangement to total vascular R (R _T), independent of blood viscosity, is unknown. We measured pulmonary (R _P) and systemic (R _S) vascular R with an in situ Ringer’s solution perfusion technique using anesthetized anuran and urodele species to determine: (1) relative contributions of vascular anatomy and blood viscosity to R _T; (2) distensibility index (%Δ flow kPa^?1) of the pulmonary and systemic vascular circuits; and (3) interspecific correlates of variation in these parameters with red blood cell size, cardiac power output, and aerobic capacities. R _P was lower than R _S in anurans, while R _P of the urodeles was greater than R _S and significantly greater than anuran R _P. Anuran R _T was lowest and did not vary interspecifically, whereas urodele R _T was significantly greater than anuran, and varied interspecifically. Pulmonary and systemic circuit distensibility differences may explain cardiac shunt patterns in toads with changes in cardiac output from rest to activity. When blood viscosity was taken into account, vascular resistance accounted for about 25 % of R _T while blood viscosity accounted for the remaining 75 %. Owing to lower R _T, terrestrial anuran species required lower cardiac power outputs when moving fluid through their vasculature compared to aquatic species. These results indicate that physical characteristics of the vasculature can account for interspecific differences in cardiovascular physiology and suggest a co-evolution of cardiac and vascular anatomy among amphibians.     

Effects of Culling on Mesopredator Population Dynamics

Anthropogenic changes in land use and the extirpation of apex predators have facilitated explosive growth of mesopredator populations. Consequently, many species have been subjected to extensive control throughout portions of their range due to their integral role as generalist predators and reservoirs of zoonotic disease. Yet, few studies have monitored the effects of landscape composition or configuration on the demographic or behavioral response of mesopredators to population manipulation. During 2007 we removed 382 raccoons (Procyon lotor) from 30 forest patches throughout a fragmented agricultural ecosystem to test hypotheses regarding the effects of habitat isolation on population recovery and role of range expansion and dispersal in patch colonization of mesopredators in heterogeneous landscapes. Patches were allowed to recolonize naturally and demographic restructuring of patches was monitored from 2008–2010 using mark-recapture. An additional 25 control patches were monitored as a baseline measure of demography. After 3 years only 40% of experimental patches had returned to pre-removal densities. This stagnant recovery was driven by low colonization rates of females, resulting in little to no within-patch recruitment. Colonizing raccoons were predominantly young males, suggesting that dispersal, rather than range expansion, was the primary mechanism driving population recovery. Contrary to our prediction, neither landscape connectivity nor measured local habitat attributes influenced colonization rates, likely due to the high dispersal capability of raccoons and limited role of range expansion in patch colonization. Although culling is commonly used to control local populations of many mesopredators, we demonstrate that such practices create severe disruptions in population demography that may be counterproductive to disease management in fragmented landscapes due to an influx of dispersing males into depopulated areas. However, given the slow repopulation rates observed in our study, localized depopulation may be effective at reducing negative ecological impacts of mesopredators in fragmented landscapes at limited spatial and temporal scales.     

Extent and Degree of Shoreline Oiling: Deepwater Horizon Oil Spill,Gulf of Mexico,USA

The oil from the 2010 Deepwater Horizon spill in the Gulf of Mexico was documented by shoreline assessment teams as stranding on 1,773 km of shoreline. Beaches comprised 50.8%, marshes 44.9%, and other shoreline types 4.3% of the oiled shoreline. Shoreline cleanup activities were authorized on 660 km, or 73.3% of oiled beaches and up to 71 km, or 8.9% of oiled marshes and associated habitats. One year after the spill began, oil remained on 847 km; two years later, oil remained on 687 km, though at much lesser degrees of oiling. For example, shorelines characterized as heavily oiled went from a maximum of 360 km, to 22.4 km one year later, and to 6.4 km two years later. Shoreline cleanup has been conducted to meet habitat-specific cleanup endpoints and will continue until all oiled shoreline segments meet endpoints. The entire shoreline cleanup program has been managed under the Shoreline Cleanup Assessment Technique (SCAT) Program, which is a systematic, objective, and inclusive process to collect data on shoreline oiling conditions and support decision making on appropriate cleanup methods and endpoints. It was a particularly valuable and effective process during such a complex spill.     

Predicting Essential Metabolic Genome Content of Niche-Specific Enterobacterial Human Pathogens during Simulation of Host Environments

Microorganisms have evolved to occupy certain environmental niches, and the metabolic genes essential for growth in these locations are retained in the genomes. Many microorganisms inhabit niches located in the human body, sometimes causing disease, and may retain genes essential for growth in locations such as the bloodstream and urinary tract, or growth during intracellular invasion of the hosts’ macrophage cells. Strains of Escherichia coli (E. coli) and Salmonella spp. are thought to have evolved over 100 million years from a common ancestor, and now cause disease in specific niches within humans. Here we have used a genome scale metabolic model representing the pangenome of E. coli which contains all metabolic reactions encoded by genes from 16 E. coli genomes, and have simulated environmental conditions found in the human bloodstream, urinary tract, and macrophage to determine essential metabolic genes needed for growth in each location. We compared the predicted essential genes for three E. coli strains and one Salmonella strain that cause disease in each host environment, and determined that essential gene retention could be accurately predicted using this approach. This project demonstrated that simulating human body environments such as the bloodstream can successfully lead to accurate computational predictions of essential/important genes.     

Drone and Worker Brood Microclimates Are Regulated Differentially in Honey Bees,Apis mellifera

Background

Honey bee (Apis mellifera) drones and workers show differences in morphology, physiology, and behavior. Because the functions of drones are more related to colony reproduction, and those of workers relate to both survival and reproduction, we hypothesize that the microclimate for worker brood is more precisely regulated than that of drone brood.

Methodology/Principal Findings

We assessed temperature and relative humidity (RH) inside honey bee colonies for both drone and worker brood throughout the three-stage development period, using digital HOBO^® Data Loggers. The major findings of this study are that 1) both drone and worker castes show the highest temperature for eggs, followed by larvae and then pupae; 2) temperature in drones are maintained at higher precision (smaller variance) in drone eggs and larvae, but at a lower precision in pupae than the corresponding stages of workers; 3) RH regulation showed higher variance in drone than workers across all brood stages; and 4) RH regulation seems largely due to regulation by workers, as the contribution from empty honey combs are much smaller compared to that from adult workers.

Conclusions/Significance

We conclude that honey bee colonies maintain both temperature and humidity actively; that the microclimate for sealed drone brood is less precisely regulated than worker brood; and that combs with honey contribute very little to the increase of RH in honey bee colonies. These findings increase our understanding of microclimate regulation in honey bees and may have implications for beekeeping practices.     

Redrawing the US Obesity Landscape: Bias-Corrected Estimates of State-Specific Adult Obesity Prevalence

Background

State-level estimates from the Centers for Disease Control and Prevention (CDC) underestimate the obesity epidemic because they use self-reported height and weight. We describe a novel bias-correction method and produce corrected state-level estimates of obesity and severe obesity.

Methods

Using non-parametric statistical matching, we adjusted self-reported data from the Behavioral Risk Factor Surveillance System (BRFSS) 2013 (n = 386,795) using measured data from the National Health and Nutrition Examination Survey (NHANES) (n = 16,924). We validated our national estimates against NHANES and estimated bias-corrected state-specific prevalence of obesity (BMI≥30) and severe obesity (BMI≥35). We compared these results with previous adjustment methods.

Results

Compared to NHANES, self-reported BRFSS data underestimated national prevalence of obesity by 16% (28.67% vs 34.01%), and severe obesity by 23% (11.03% vs 14.26%). Our method was not significantly different from NHANES for obesity or severe obesity, while previous methods underestimated both. Only four states had a corrected obesity prevalence below 30%, with four exceeding 40%–in contrast, most states were below 30% in CDC maps.

Conclusions

Twelve million adults with obesity (including 6.7 million with severe obesity) were misclassified by CDC state-level estimates. Previous bias-correction methods also resulted in underestimates. Accurate state-level estimates are necessary to plan for resources to address the obesity epidemic.