994 resultados para Multi-functionality


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Many studies comparing the effects of single- and multi-strain probiotics on pathogen inhibition compare treatments with different concentrations. They also do not examine the possibility of inhibition between probiotic strains with a mixture. We tested the ability of 14 single-species probiotics to inhibit each other using a cross-streak assay, and agar spot test. We then tested the ability of 15 single-species probiotics and 5 probiotic mixtures to inhibit C. difficile, E. coli and S. Typhimurium, using the agar spot test. Testing was done with mixtures created in two ways: one group contained component species incubated together, the other group of mixtures was made using component species which had been incubated separately, equalised to equal optical density, and then mixed in equal volumes. Inhibition was observed for all combinations of probiotics, suggesting that when used as such there may be inhibition between probiotics, potentially reducing efficacy of the mixture. Significant inter-species variation was seen against each pathogen. When single species were tested against mixtures, the multi-species preparations displayed significantly (p<0.05 or less) greater inhibition of pathogens in 12 out of 24 cases. Despite evidence that probiotic species will inhibit each other when incubated together in vitro, in many cases a probiotic mixture was more effective at inhibiting pathogens than its component species when tested at approximately equal concentrations of biomass. This suggests that using a probiotic mixture might be more effective at reducing gastrointestinal infections, and that creating a mixture using species with different effects against different pathogens may have a broader spectrum of action that a single provided by a single strain.

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The observed dramatic decrease in September sea ice extent (SIE) has been widely discussed in the scientific literature. Though there is qualitative agreement between observations and ensemble members of the Third Coupled Model Intercomparison Project (CMIP3), it is concerning that the observed trend (1979–2010) is not captured by any ensemble member. The potential sources of this discrepancy include: observational uncertainty, physical model limitations and vigorous natural climate variability. The latter has received less attention and is difficult to assess using the relatively short observational sea ice records. In this study multi-centennial pre-industrial control simulations with five CMIP3 climate models are used to investigate the role that the Arctic oscillation (AO), the Atlantic multi-decadal oscillation (AMO) and the Atlantic meridional overturning circulation (AMOC) play in decadal sea ice variability. Further, we use the models to determine the impact that these sources of variability have had on SIE over both the era of satellite observation (1979–2010) and an extended observational record (1953–2010). There is little evidence of a relationship between the AO and SIE in the models. However, we find that both the AMO and AMOC indices are significantly correlated with SIE in all the models considered. Using sensitivity statistics derived from the models, assuming a linear relationship, we attribute 0.5–3.1%/decade of the 10.1%/decade decline in September SIE (1979–2010) to AMO driven variability.