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Breast cancer is a kind of malignant tumor discovered lately, with a high incidence and a poor prognosis. The shortage of relevant biological biomarkers lead to the unsatisfactory treatment efficacy and the early diagnosis in breast cancer. Metabolomics is a new discipline that uses high-throughput analysis techniques to study the dynamic changes of endogenous metabolites under the influence of different pathological physiological stimulation or gene mutations, which has provided a novel way for biomarker screening and disease diagnosis and treatment. The overview of metabolomics and its applications in breast cancer early diagnosis, drug efficacy evaluation, and disease prognosis were summarized in this review.
RESUMO
Objective To optimize the microwave-assisted extraction process of green tea polyphenols. Methods The extraction yield of tea polyphenols was figured up by building the standard curve of gallic acid and examining the concentration of tea polyphenols in green tea extract with the introduction of a correction factor. The effects of four single factor levels of microwave extraction time, microwave output power, liquid-to-material yield, and ethanol volume fraction on the extraction yield of tea polyphenols were primarily studied in this experiment. The response surface was applied to further optimize the extraction process of green tea polyphenols after exploring the appropriate range of four single factor levels. Results The optimal extraction process was as follows: extraction time 37 s, microwave output power 350 w, material - liquid yield 1∶45 (g/ml), ethanol volume fraction 55%, and the actual extraction yield of tea polyphenols was 25.65%, which was not much different from the theoretical value. Conclusion The microwave-assisted green tea polyphenol extraction process optimized by response surface methodology is time-saving and practicable, and the extraction yield is high.