Abstract: Predicting response to adjuvant therapy or predicting disease progression in breast cancer is realized by (1) first obtaining a breast cancer test sample from a subject; (2) second obtaining clinicopathological data from said breast cancer test sample; (3) analyzing the obtained breast cancer test sample for presence or amount of (a) one or more molecular markers of hormone receptor status, one or more growth factor receptor markers, (b) one or more tumor suppression/apoptosis molecular markers; and (c) one or more additional molecular markers both proteomic and non-proteomic that are indicative of breast cancer disease processes; and then (4) correlating (a) the presence or amount of said molecular markers and, with (b) clinicopathological data from said tissue sample other than the molecular markers of breast cancer disease processes.

Abstract: The invention relates to esterases and to polynucleotides encoding the esterases. In addition methods of designing new esterase method of use thereof are also provided. The esterases have increased activity and stability at increased pH and temperature.

Abstract: To maximize both the life expectancy and quality of life of patients with operable breast cancer, it is important to predict adjuvant treatment outcome and likelihood of progression before treatment. A machine-learning based method is used to develop a cross-validated model to predict (1) the outcome of adjuvant treatment, particularly endocrine treatment outcome, and (2) likelihood of cancer progression before treatment. The model includes standard clinicopathological features, as well as molecular markers collected using standard immunohistochemistry and fluorescence in situ hybridization. The model significantly outperforms the St. Gallen Consensus guidelines and the Nottingham Prognostic Index, thus providing a clinically useful and cost-effective prognostic for breast cancer patients.

Abstract: This invention relates to a silver halide photographic element comprising a support bearing a cyan dye image forming unit comprised of at least one red sensitive silver halide emulsion, a magenta dye image forming unit comprised of at least one green sensitive silver halide emulsion, and a yellow dye image forming unit comprised of at least one blue sensitive silver halide emulsion; wherein the at least one green sensitive silver halide emulsion comprises two absorptance peaks, the first peak being between 515 and 540 nm (short wavelength peak) and the second peak being between 565 and 590 nm, (long wavelength peak) and wherein (a) the ratio of the absorptance peak value of the short wavelength peak to the absorptance peak value of the long wavelength peak is from 0.65 to 1.55; (b) the absorptance minimum between the two absorptance peaks is between 530 and 560 nm; (c) the ratio of the absorptance value at the absorptance minimum to that of the smaller absorptance peak is 0.

Abstract: Esterase enzymes derived from various Staphylothermus, Pyrodictium, Archaeoglobus, Aquifex, M11TL, Thermococcus, Teredinibacter and Sulfolobus organisms are disclosed. The enzymes are produced from native or recombinant host cells and can be utilized in pharmaceutical, agricultural and other industries.

Abstract: Esterase enzymes derived from various Staphylothermus, Pyrodictium, Archaeoglobus, Aquifex, M11TL, Thermococcus, Teredinibacter and Sulfolobus organisms are disclosed. The enzymes are produced from native or recombinant host cells and can be utilized in pharmaceutical, agricultural and other industries.

Abstract: The invention relates to esterases and to polynucleotides encoding the esterases. In addition methods of designing new esterase method of use thereof are also provided. The esterases have increased activity and stability at increased pH and temperature.

Abstract: Esterase enzymes derived from various Staphylothermus, Pyrodictium, Archaeoglobus, Aquifex, M11TL, Thermococcus, Teredinibacter and Sulfolobus organisms are disclosed. The enzymes are produced from native or recombinant host cells and can be utilized in the pharmaceutical, agricultural and other industries.