Keyword: boron nitride nanotubesBoron nitride nanotubes (BNNTs) are desired for their exceptional mechanical, electronic, thermal, structural, textural, optical, and quantum properties. Golberg [1] gives an excellent review of possible applications. To date, BNNTs have been grown by a number of techniques which can be divided roughly into two categories based on the class of material produced.One is the high temperature category in which energy is concentrated into a B or BN target at a level which can vaporize elemental boron. BNNTs form in the deposits of the liberated vapors. The energy is input by laser [2][3][4][5][6] or by arc discharge [7][8][9] . Only small quantities (mg's) of material have been produced by this method, but the tubes are high quality. They have one or just a few walls, and most importantly, the tube walls are low in defects and parallel to the axis of the nanotube. The second category is low temperature synthesis, between about 600 C and 1700 C, well below the vaporization temperature of pure boron (~4000 C). These low temperature synthesis methods can be further divided into two catagories. In the first category, ball-milled precursor powders of boron and catalyst are annealed in a nitrogen or ammonia gas atmosphere, sprouting nanostructures on their

BackgroundGenomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction.MethodsDeregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values.ResultsAccuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied.ConclusionsThese results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.

Recently, hepatic peroxisome proliferator-activated receptor (PPAR)γ has been implicated in hepatic lipid accumulation. We found that the C3H mouse strain does not express PPARγ in the liver and, when subject to a high-fat diet, is resistant to hepatic steatosis, compared with C57BL/6 (B6) mice. Adenoviral PPARγ2 injection into B6 and C3H mice caused hepatic steatosis, and microarray analysis demonstrated that hepatic PPARγ2 expression is associated with genes involved in fatty acid transport and the triglyceride synthesis pathway. In particular, hepatic PPARγ2 expression significantly increased the expression of monoacylglycerol O-acyltransferase 1 (MGAT1). Promoter analysis by luciferase assay and electrophoretic mobility shift assay as well as chromatin immunoprecipitation assay revealed that PPARγ2 directly regulates the MGAT1 promoter activity. The MGAT1 overexpression in cultured hepatocytes enhanced triglyceride synthesis without an increase of PPARγ expression. Importantly, knockdown of MGAT1 in the liver significantly reduced hepatic steatosis in 12-wk-old high-fat-fed mice as well as ob/ob mice, accompanied by weight loss and improved glucose tolerance. These results suggest that the MGAT1 pathway induced by hepatic PPARγ is critically important in the development of hepatic steatosis during dietinduced obesity.nonalcoholic fatty liver disease | adenoviral expression | SREBP1c | ChREBP | TLR4

We present results from the largest contiguous narrow-band survey in the near-infrared. We have used WIRCam/CFHT and the lowOH2 filter (1.187 ± 0.005 µm) to survey ≈10 deg 2 of contiguous extragalactic sky in the SA22 field. A total of ∼ 6000 candidate emission-line galaxies are found. We use deep ugrizJK data to obtain robust photometric redshifts. We combine our data with the High-redshift Emission Line Survey (HiZELS), explore spectroscopic surveys (VVDS, VIPERS) and obtain our own spectroscopic follow-up with KMOS, FMOS and MOSFIRE to derive large samples of high-redshift emission-line selected galaxies: 3471 Hα emitters at z = 0.8, 1343 [OIII]+Hβ emitters at z = 1.4 and 572 [OII] emitters at z = 2.2. We probe co-moving volumes of > 10 6 Mpc 3 and find significant over-densities, including an 8.5 σ (spectroscopically confirmed) over-density of Hα emitters at z = 0.81. We derive Hα, [OIII]+Hβ and [OII] luminosity functions at z = 0.8, 1.4, 2.2, respectively, and present implications for future surveys such as Euclid. Our uniquely large volumes/areas allow us to sub-divide the samples in thousands of randomised combinations of areas and provide a robust empirical measurement of sample/cosmic variance. We show that surveys for star-forming/emission-line galaxies at a depth similar to ours can only overcome cosmicvariance (errors < 10%) if they are based on volumes > 5 × 10 5 Mpc 3 ; errors on L * and φ * due to sample (cosmic) variance on surveys probing ∼ 10 4 Mpc 3 and ∼ 10 5 Mpc 3 are typically very high: ∼ 300% and ∼ 40 − 60%, respectively.