Accumulation and metabolism of uneven fatty acids present in single cell protein

Liquipron and Toprina, obtained by growing yeasts (Candida maltosa and Candida lipolytica) on n-hydrocarbons, were investigated to ascertain the biological significance and possible toxicological implications of their high content of uneven fatty acids (UFA). It was confirmed that the extent to which UFA accumulate in adipose tissue of rats fed the 2 products reflects only partially their UFA contents. The presence of UFA in rat tissues does not appear to alter intermediate metabolism. The capacity of liver mitochondria ot oxidize palmitic acid was similar in control and in Liquipron-treated rats. Palmitic acid and heptadecanoic acid did not compete for oxidation when mixed at concentrations which reflect their presence in the tissues of animals fed high levels of Liquipron.     

The CTFA Evaluation of Alternatives Program: an evaluation of in vitro alternatives to the Draize primary eye irritation test. (Phase III) surfactant-based formulations

The CTFA Evaluation of Alternatives Program is an evaluation of the relationship between data from the Draize primary eye irritation test and comparable data from a selection of promising in vitro eye irritation tests. In Phase III, data from the Draize test and 41 in vitro endpoints on 25 representative surfactant-based personal care formulations were compared. As in Phase I and Phase II, regression modelling of the relationship between maximum average Draize score (MAS) and in vitro endpoint was the primary approach adopted for evaluating in vitro assay performance. The degree of confidence in prediction of MAS for a given in vitro endpoint is quantified in terms of the relative widths of prediction intervals constructed about the fitted regression curve. Prediction intervals reflect not only the error attributed to the model but also the material-specific components of variation in both the Draize and the in vitro assays. Among the in vitro assays selected for regression modeling in Phase III, the relationship between MAS and in vitro score was relatively well defined. The prediction bounds on MAS were most narrow for materials at the lower or upper end of the effective irritation range (MAS = 0-45), where variability in MAS was smallest. This, the confidence with which the MAS of surfactant-based formulations is predicted is greatest when MAS approaches zero or when MAS approaches 45 (no comment is made on prediction of MAS > 45 since extrapolation beyond the range of observed data is not possible). No single in vitro endpoint was found to exhibit relative superiority with regard to prediction of MAS. Variability associated with Draize test outcome (e.g. in MAS values) must be considered in any future comparisons of in vivo and in vitro test results if the purpose is to predict in vivo response using in vitro data.     

Challenges in Developing a Bessel-Beam Based Ultrafast Ablation Probe

Instruments and Experimental Techniques - With its elongated depth of focus, Bessel beams offer rapid and high aspect ratio ablation capability, in contrast to Gaussian beam counterparts. In this...     

A comparison of swarm-based optimization algorithms in linear antenna array synthesis

Today, the design of antenna arrays is very important in providing effective and efficient wireless communication. The purpose of antenna array synthesis is to obtain a radiation pattern with a low side lobe level (SLL) at a desired half power beam width in far-field. The amplitude and position values of the array elements can be optimized to obtain a radiation pattern with suppressed SLLs. In this paper, swarm-based metaheuristic algorithms including particle swarm optimization (PSO), artificial bee colony (ABC), mayfly algorithm (MA) and jellyfish search (JS) are compared to determine the optimal design of linear antenna arrays. Extensive experiments are conducted on designing 10-, 16-, 24- and 32-element linear arrays by determining the amplitude and positions. Experiments are repeated 30 times due to the random nature of swarm-based optimizers, and statistical results show that the performance of the novel algorithms, MA and JS, is better than that of the well-known PSO and ABC methods.