Dietary predictors of visceral adiposity in overweight young adults

The purpose of the present study was to determine the dietary predictors of visceral adipose tissue (VAT) area in overweight young adults. A total of 109 young adults (fifty males and fifty-nine females) ate ad libitum in a university cafeteria for 14 d. All food and beverages consumed in the cafeteria were measured using observer-recorded weighed plate waste. Food consumption outside the cafeteria (i.e. snacks) was assessed by multiple-pass 24 h recall procedures. VAT was determined using computed tomography. Stepwise regression demonstrated that the best predictor of visceral adiposity in women was total dietary fat (P# 0–05). In men, the model for predicting visceral adiposity included Ca and total dietary fat. We concluded that total dietary fat is the best predictor of VAT area in both men and women. While this relationship was independent in women, in men there was a synergistic relationship between dietary fat consumption and Ca consumption in predicting VAT

The natural history and ecology of melanism in red wolf and coyote populations of the southeastern United States – evidence for Gloger’s rule

Background: Gloger’s rule postulates that animals should be darker colored in warm and humid regions where dense vegetation and dark environments are common. Although rare in Canis populations, melanism in wolves is more common in North America than other regions globally and is believed to follow Gloger’s rule. In the temperate forests of the southeastern United States, historical records of red wolf (Canis rufus) and coyote (Canis latrans) populations document a consistent presence of melanism. Today, the melanistic phenotype is extinct in red wolves while occurring in coyotes and red wolf-coyote hybrids who occupy the red wolf’s historical range. To assess if Gloger’s rule could explain the occurrence and maintenance of melanistic phenotypes in Canis taxa, we investigated differences in morphology, habitat selection, and survival associated with pelage color using body measurements, GPS tracking data, and long-term capture-mark-recapture and radio-telemetry data collected on coyotes and hybrids across the southeastern United States. Results: We found no correlation between morphometrics and pelage color for Canis taxa. However, we observed that melanistic coyotes and hybrids experienced greater annual survival than did their gray conspecifics. Furthermore, we observed that melanistic coyotes maintained larger home ranges and exhibited greater selection for areas with dense canopy cover and wetlands than did gray coyotes. Conclusions: In the southeastern United States, pelage color influenced habitat selection by coyotes and annual survival of coyotes and hybrids providing evidence that Gloger’s rule is applicable to canids inhabiting regions with dense canopy cover and wetlands. Greater annual survival rates observed in melanistic Canis may be attributed to better concealment in areas with dense canopy cover such as coastal bottomland forests. We suggest that the larger home range sizes of melanistic coyotes may reflect the trade-off of reduced foraging efficiency in lower quality wetland habitat for improved survival. Larger home ranges and differential use of land cover by melanistic coyotes may facilitate weak assortative mating in eastern coyote populations, in which melanistic animals may have lower success of finding compatible mates in comparison to gray conspecifics. We offer that our observations provide a partial explanation for why melanism is relatively low (\u3c 10%) but consistent within coyote populations throughout southeastern parts of their range

Corrigendum "Portal protein diversity and phage ecology"

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Environmental Microbiology 13 (2011): 2832, doi:10.1111/j.1462-2920.2011.02616.x

Hemostatic Nanoparticles Increase Survival, Mitigate Neuropathology and Alleviate Anxiety in a Rodent Blast Trauma Model

Explosions account for 79% of combat related injuries and often lead to polytrauma, a majority of which include blast-induced traumatic brain injuries (bTBI). These injuries lead to internal bleeding in multiple organs and, in the case of bTBI, long term neurological deficits. Currently, there are no treatments for internal bleeding beyond fluid resuscitation and surgery. There is also a dearth of treatments for TBI. We have developed a novel approach using hemostatic nanoparticles that encapsulate an anti-inflammatory, dexamethasone, to stop the bleeding and reduce inflammation after injury. We hypothesize that this will improve not only survival but long term functional outcomes after blast polytrauma. Poly(lactic-co-glycolic acid) hemostatic nanoparticles encapsulating dexamethasone (hDNPs) were fabricated and tested following injury along with appropriate controls. Rats were exposed to a single blast wave using an Advanced Blast Simulator, inducing primary blast lung and bTBI. Survival was elevated in the hDNPs group compared to controls. Elevated anxiety parameters were found in the controls, compared to hDNPs. Histological analysis indicated that apoptosis and blood-brain barrier disruption in the amygdala were significantly increased in the controls compared to the hDNPs and sham groups. Immediate intervention is crucial to mitigate injury mechanisms that contribute to emotional deficits

Copper Accumulation and the Effect of Chelation Treatment on Cerebral Amyloid Angiopathy Compared to Parenchymal Amyloid Plaques

Accumulation of fibrillar amyloid β-protein (Aβ) in parenchymal plaques and in blood vessels of the brain, the latter condition known as cerebral amyloid angiopathy (CAA), are hallmark pathologies of Alzheimer\u27s disease (AD) and related disorders. Cerebral amyloid deposits have been reported to accumulate various metals, most notably copper and zinc. Here we show that, in human AD, copper is preferentially accumulated in amyloid-containing brain blood vessels compared to parenchymal amyloid plaques. In light of this observation, we evaluated the effects of reducing copper levels in Tg2576 mice, a transgenic model of AD amyloid pathologies. The copper chelator, tetrathiomolybdate (TTM), was administered to twelve month old Tg2576 mice for a period of five months. Copper chelation treatment significantly reduced both CAA and parenchymal plaque load in Tg2576 mice. Further, copper chelation reduced parenchymal plaque copper content but had no effect on CAA copper levels in this model. These findings indicate that copper is associated with both CAA deposits and parenchymal amyloid plaques in humans, but less in Tg2576 mice. TTM only reduces copper levels in plaques in Tg2576 mice. Reducing copper levels in the brain may beneficially lower amyloid pathologies associated with AD

Semi-supervised Learning for Photometric Supernova Classification

We present a semi-supervised method for photometric supernova typing. Our approach is to first use the nonlinear dimension reduction technique diffusion map to detect structure in a database of supernova light curves and subsequently employ random forest classification on a spectroscopically confirmed training set to learn a model that can predict the type of each newly observed supernova. We demonstrate that this is an effective method for supernova typing. As supernova numbers increase, our semi-supervised method efficiently utilizes this information to improve classification, a property not enjoyed by template based methods. Applied to supernova data simulated by Kessler et al. (2010b) to mimic those of the Dark Energy Survey, our methods achieve (cross-validated) 95% Type Ia purity and 87% Type Ia efficiency on the spectroscopic sample, but only 50% Type Ia purity and 50% efficiency on the photometric sample due to their spectroscopic follow-up strategy. To improve the performance on the photometric sample, we search for better spectroscopic follow-up procedures by studying the sensitivity of our machine learned supernova classification on the specific strategy used to obtain training sets. With a fixed amount of spectroscopic follow-up time, we find that deeper magnitude-limited spectroscopic surveys are better for producing training sets. For supernova Ia (II-P) typing, we obtain a 44% (1%) increase in purity to 72% (87%) and 30% (162%) increase in efficiency to 65% (84%) of the sample using a 25th (24.5th) magnitude-limited survey instead of the shallower spectroscopic sample used in the original simulations. When redshift information is available, we incorporate it into our analysis using a novel method of altering the diffusion map representation of the supernovae. Incorporating host redshifts leads to a 5% improvement in Type Ia purity and 13% improvement in Type Ia efficiency.Comment: 16 pages, 11 figures, accepted for publication in MNRA

Deactivation of metastable single-crystal silicon hyperdoped with sulfur

Silicon supersaturated with sulfur by ion implantation and pulsed laser melting exhibits broadband optical absorption of photons with energies less than silicon's band gap. However, this metastable, hyperdoped material loses its ability to absorb sub-band gap light after subsequent thermal treatment. We explore this deactivation process through optical absorption and electronic transport measurements of sulfur-hyperdoped silicon subject to anneals at a range of durations and temperatures. The deactivation process is well described by the Johnson-Mehl-Avrami-Kolmogorov framework for the diffusion-mediated transformation of a metastable supersaturated solid solution, and we find that this transformation is characterized by an apparent activation energy of E[subscript A] = 1.7 ± 0.1  eV. Using this activation energy, the evolution of the optical and electronic properties for all anneal duration-temperature combinations collapse onto distinct curves as a function of the extent of reaction. We provide a mechanistic interpretation of this deactivation based on short-range thermally activated atomic movements of the dopants to form sulfur complexes.Center for Clean Water and Clean Energy at MIT and KFUPMNational Science Foundation (U.S.) (Energy, Power, and Adaptive Systems Grant Contract ECCS-1102050)National Science Foundation (U.S.) (United States. Dept. of Energy Contract EEC-1041895

The Richardson's Law in Large-Eddy Simulations of Boundary Layer flows

Relative dispersion in a neutrally stratified planetary boundary layer (PBL) is investigated by means of Large-Eddy Simulations (LES). Despite the small extension of the inertial range of scales in the simulated PBL, our Lagrangian statistics turns out to be compatible with the Richardson $t^3$ law for the average of square particle separation. This emerges from the application of nonstandard methods of analysis through which a precise measure of the Richardson constant was also possible. Its values is estimated as $C_2\sim 0.5$ in close agreement with recent experiments and three-dimensional direct numerical simulations.Comment: 15 LaTex pages, 4 PS figure

Synthesis of monodisperse chitosan nanoparticles

The objectives of this study were to evaluate the effects of the initial concentrations of chitosan (CS) and sodium tripolyphosphate (TPP), the CS:TPP mass ratio, the CS molecular weight (MW) and pH on the synthesis of CS nanoparticles (CS NPs). The particle size of the synthesised CS NPs was significantly affected (P 300 nm. While both native CS and CS NPs showed antimicrobial activity, no significant antimicrobial enhancement was observed for the NP form. The findings of this study have shown that monodisperse CS NPs can be obtained using a combination of bottom-up and top-down techniques and the unique physiochemical properties of these nanomaterials have the potential for applications in developing of antimicrobial active packaging materials