This study used Lactobacillus casei 334e, an erythromycin-resistant derivative of ATCC 334, as a model to evaluate viability and acid resistance of probiotic L. casei in low-fat Cheddar cheese and yogurt. Cheese and yogurt were made by standard methods and the probiotic L. casei adjunct was added at approximately 10(7) CFU/g with the starter cultures. Low-fat cheese and yogurt samples were stored at 8 and 2 degrees C, respectively, and numbers of the L. casei adjunct were periodically determined by plating on MRS agar that contained 5 microg/mL of erythromycin. L. casei 334e counts in cheese and yogurt remained at 10(7) CFU/g over 3 mo and 3 wk, respectively, indicating good survival in both products. Acid challenge studies in 8.7 mM phosphoric acid (pH 2) at 37 degrees C showed numbers of L. casei 334e in yogurt dropped from 10(7) CFU/g to less than 10(1) CFU/g after 30 min, while counts in cheese samples dropped from 10(7) CFU/g to about 10(5) after 30 min, and remained near 10(4) CFU/g after 120 min. As a whole, these data showed that low-fat Cheddar cheese is a viable delivery food for probiotic L. casei because it allowed for good survival during storage and helped protect cells against the very low pH that will be encountered during stomach transit.

Vanilla beans have been shown to contain over 200 compounds, which can vary in concentration depending on the region where the beans are harvested. Several compounds including vanillin, p-hydroxybenzaldehyde, guaiacol, and anise alcohol have been found to be important for the aroma profile of vanilla. Our objective was to evaluate the performance of selected ion flow tube mass spectrometry (SIFT-MS) and Fourier-transform infrared (FTIR) spectroscopy for rapid discrimination and characterization of vanilla bean extracts. Vanilla extracts were obtained from different countries including Uganda, Indonesia, Papua New Guinea, Madagascar, and India. Multivariate data analysis (soft independent modeling of class analogy, SIMCA) was utilized to determine the clustering patterns between samples. Both methods provided differentiation between samples for all vanilla bean extracts. FTIR differentiated on the basis of functional groups, whereas the SIFT-MS method provided more specific information about the chemical basis of the differentiation. SIMCA's discriminating power showed that the most important compounds responsible for the differentiation between samples by SIFT-MS were vanillin, anise alcohol, 4-methylguaiacol, p-hydroxybenzaldehyde/trimethylpyrazine, p-cresol/anisole, guaiacol, isovaleric acid, and acetic acid. ATR-IR spectroscopy analysis showed that the classification of samples was related to major bands at 1523, 1573, 1516, 1292, 1774, 1670, 1608, and 1431 cm(-1) , associated with vanillin and vanillin derivatives.

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Class-specific optimizations are compiler optimizations specified by the class implementor to the compiler. They allow the compiler to take advantage of the semantics of the particular class so as to produce better code. Optimizations of interest include the strength reduction of class:: array address calculations, elimination of large temporaries, and the placement of asynchronous send/recv calls so as to achieve computation/communication overlap. We will outline our progress towards the implementation of a C++ compiler capable of incorporating class-specific optimizations.

Mel Gibson's movie Braveheart tells the story of the life of William Wallace, one of Scodand's great national heroes. Originally released in the late spring of 1995, the film received predominandy glowing reviews, and later in the year enjoyed a second run in theatres as Paramount Studios began marketing the film for consideration in the many end-of-the-year awards shows. Early in 1996 Mel Gibson was honoured at the Golden Globe Awards as the year's Best Director, and in March of the same year, Braveheart won five Academy Awards, including another Best Director award for Gibson as well as the award for Best Motion Picture of the Year.