Screening of the Appropriate Proportion on Anti-Breast Cancer Activity of Prunellae spica Combined with Taraxaci herba and Its Anti-Tumor Research in Vivo / 中国药学杂志

OBJECTIVE: To screen optimal ratio of Prunella vulgaris(PV) and Taraxacum mongolicum(TM) as a synergetic combination for anti-breast cancer treatment in vitro based on combination index(CI) and to investigate the effects of PV and TM on cell proliferation and apoptosis under the optimized ratio in tumor-bearing(4T1) female BALB/c mice in vivo. METHODS: Cell proliferation was assayed by MTT method. The dose-effect of PV combined with TM was evaluated by CI method, The combination has a synergistic effect when the CI value is less than 1. Breast cancer model was established by subcutaneous injection of 4T1 cells in BABL/c mice, the mice were given medicated feed daily for 25 d. Body weight and tumor growth were measured every three days. Histological change and cell apoptosis in tumor tissue from breast cancer mice were evaluated via HE and TUNEL methods. RESULTS: The results indicated that cell proliferation of MCF-7 and MDA-MB-231 treated with PV and TM in combination was markedly inhibited. The combination index of PV and TM was 0.199 8 and 0.407 at a ratio of 4:3, which showed a synergistic effect. In addition, PV+TM treatment significantly reduced tumor volume without affecting body weight in breast cancer mice. HE staining showed that the infiltration of inflammatory cells appeared around the tumors and the areas of necrosis. TUNEL staining showed the induced apoptosis in tumor cells from breast cancer mice. CONCLUSION: PV+TM combination has a significant anti-breast cancer activity possibly by boosting immunity and promoting apoptosis in tumor cells, which suggests that PV+TM combination might be a novel potent therapy for the treatment of breast cancer.

Application of random forest algorithm in fingerprint of Chinese medicine: different brands of Xiasangju granules as example / 中国中药杂志

To establish a random forest algorithm for identifying and classifying different brands of Xiasangju granules, and provide effective reference for identifying multi-index complex fingerprint. HPLC method was used to collect the fingerprint of 83 batches of Xiasangju granules from different manufacturers. The classification of Xiasangju granules samples based on chromatographic fingerprints was identified by chemometric methods including principal component analysis (PCA), partial least squares discriminate analysis (PLS-DA) and random forest analysis (RF). The superiority of the above three chemometric methods was compared. The results showed that the fingerprints of 83 batches of Xiasangju granules were established in this study. PCA could only explicate 56.52% variance contribution rate and could not completely classify the samples; PLS-DA analysis was superior to PCA, explicating 63.43% variance contribution rate and could obtain certain separation; RF could well classify the samples into 3 types, and the predication accuracy of the proposed method was 96.5%. Therefore, The results indicate that RF combined with HPLC fingerprint could effectively construct traditional Chinese medicine quality control and analysis system.