951 resultados para Factor Beta
Resumo:
Conformational energy calculations were carried out on penicillin α-and Β-sulfoxides and δ2- and δ3-cephalosporins, in order to identify the structural features governing their biological activity. Results on penicillin Β-sulfoxide indicated that in its favoured conformation, the orientation of the aminoacyl group was different from the one required for biological activity. Penicillin α sulfoxide, like penicillin sulfide, favoured two conformations of nearly equal energies, but separated by a much higher energy barrier. The reduced activity of the sulfoxides despite the nonplanarity of their lactam peptide indicated that the orientations of the aminoacyl and carboxyl groups might also govern biological activity. δ3-cephalosporins favoured two conformations of nearly equal energies, whereas δ2-cephalosporins favoured only one conformation. The lactam peptide was moderately nonplanÄr in the former, but nearly planar in the latter. The differences in the.preferred orientations of the carboxyl group between penicillins and cephalosporins were correlated with the resistance of cephalosporins to penicillinases.
Resumo:
A Monte Carlo study along with experimental uptake measurements of 1,2,3-trimethyl benzene, 1,2,4-trimethyl benzene and 1,3,5-trimethyl benzene (TMB) in beta zeolite is reported. The TraPPE potential has been employed for hydrocarbon interaction and harmonic potential of Demontis for modeling framework of the zeolite. Structure, energetics and dynamics of TMB in zeolite beta from Monte Carlo runs reveal interesting information about the diameter, properties of these isomers on confinement. Of the three isomers, 135TMB is supposed to have the largest diameter. It is seen TraPPE with Demontis potential predicts a restricted motion of 135TMB in the channels of zeolite beta.Experimentally, 135TMB has the highest transport diffusivity whereas MID results suggest this has the lowest self diffusivity. (C) 2009 Elsevier Inc. Ail rights reserved.
Resumo:
The present study describes the seminal plasma proteome of Bos indicus bulls. Fifty-six, 24-month old Australian Brahman sires were evaluated and subjected to electroejaculation. Seminal plasma proteins were separated by 2-D SDS-PAGE and identified by mass spectrometry. The percentage of progressively motile and morphologically normal sperm of the bulls were 70.4±2.3 and 64±3.2%, respectively. A total of 108 spots were identified in the 2-D maps, corresponding to 46 proteins. Binder of sperm proteins accounted for 55.8% of all spots detected in the maps and spermadhesins comprised the second most abundant constituents. Other proteins of the Bos indicus seminal plasma include clusterin, albumin, transferrin, metalloproteinase inhibitor 2, osteopontin, epididymal secretory protein E1, apolipoprotein A-1, heat shock 70kDa protein, glutathione peroxidase 3, cathelicidins, alpha-enolase, tripeptidyl-peptidase 1, zinc-alpha-2-glycoprotein, plasma serine protease inhibitor, beta 2-microglobulin, proteasome subunit beta type-4, actin, cathepsins, nucleobinding-1, protein S100-A9, hemoglobin subunit alpha, cadherin-1, angiogenin-1, fibrinogen alpha and beta chain, ephirin-A1, protein DJ-1, serpin A3-7, alpha-2-macroglobulin, annexin A1, complement factor B, polymeric immunoglobulin receptor, seminal ribonuclease, ribonuclease-4, prostaglandin-H2 D-isomarase, platelet-activating factor acetylhydrolase, and phosphoglycerate kinase In conclusion, this work uniquely portrays the Bos indicus seminal fluid proteome, based on samples from a large set of animals representing the Brahman cattle of the tropical Northern Australia. Based on putative biochemical attributes, seminal proteins act during sperm maturation, protection, capacitation and fertilization.
Resumo:
Hendra virus causes sporadic but typically fatal infection in horses and humans in eastern Australia. Fruit-bats of the genus Pteropus (commonly known as flying-foxes) are the natural host of the virus, and the putative source of infection in horses; infected horses are the source of human infection. Effective treatment is lacking in both horses and humans, and notwithstanding the recent availability of a vaccine for horses, exposure risk mitigation remains an important infection control strategy. This study sought to inform risk mitigation by identifying spatial and environmental risk factors for equine infection using multiple analytical approaches to investigate the relationship between plausible variables and reported Hendra virus infection in horses. Spatial autocorrelation (Global Moran’s I) showed significant clustering of equine cases at a distance of 40 km, a distance consistent with the foraging ‘footprint’ of a flying-fox roost, suggesting the latter as a biologically plausible basis for the clustering. Getis-Ord Gi* analysis identified multiple equine infection hot spots along the eastern Australia coast from far north Queensland to central New South Wales, with the largest extending for nearly 300 km from southern Queensland to northern New South Wales. Geographically weighted regression (GWR) showed the density of P. alecto and P. conspicillatus to have the strongest positive correlation with equine case locations, suggesting these species are more likely a source of infection of Hendra virus for horses than P. poliocephalus or P. scapulatus. The density of horses, climate variables and vegetation variables were not found to be a significant risk factors, but the residuals from the GWR suggest that additional unidentified risk factors exist at the property level. Further investigations and comparisons between case and control properties are needed to identify these local risk factors.
Resumo:
Reputation systems are employed to measure the quality of items on the Web. Incorporating accurate reputation scores in recommender systems is useful to provide more accurate recommendations as recommenders are agnostic to reputation. The ratings aggregation process is a vital component of a reputation system. Reputation models available do not consider statistical data in the rating aggregation process. This limitation can reduce the accuracy of generated reputation scores. In this paper, we propose a new reputation model that considers previously ignored statistical data. We compare our proposed model against state-of the-art models using top-N recommender system experiment.