[Effects of Oridonin combined with Capecitabine on the proliferaction of MDA-MB-231 human breast cancer cells].

Objective: To investigate the effects of oridonin combined with capecitabine on the proliferaction of MDA-MB-231 human breast cancer cells. Methods: Effect of different concentrations(10, 20 and 40 µmol/L)of oridonin, capecitabine and their combination on the proliferation of MDA-MB-231 cells after incubation for 24 or 48 h was studied. Then, the effect of 5 µmol/L of oridonin, capecitabine and their combination on cell colony formation was detected. Finally, influence of 20 µmol/L of oridonin, capecitabine and their combination on morphological alteration of nucleus, cell cycle and apoptosis was explored. Results: The inhibition rate on MDA-MB-231 cells after incubation with 20 µmol/L oridonin or capecitabine for 48 h was 49.5% and 58.6%, respectively, while the inhibition rate against proliferation of MDA-MB-231 cells reached 94.6% with combination of 20 µmol/L oridonin and capecitabine. Cells incubated with combination of oridonin and capecitabine formed fewer and smaller colonies (P<0.01). Meanwhile, cells in the combination group arrested at S and G2/M phases at the same time, and combination of two drugs caused more apoptotic cells (P<0.01). Conclusion: Oridonin combined with capecitabine can synergistically inhibit the proliferation of MDA-MB-231 human breast cancer cells.

[Quantitative analysis of pathological voice and identification with artificial neural network].

Objective:To discuss the characteristic of the clinical pathological voice and the feasibility of computer automatic identification of pathological voice.Method:A total of 129 clinical patients with polyp of vocal cord were selected as the pathological voice group, while a total of 125 people with normal voice were selected from the community as the control group. Praat software was used to collect and analyze the related acoustic parameter values of two groups of cases, including Jitter, Shimmer, harmonic to noise ratio (HNR), signal to noise ratio (SNR), and normalized noise energy (NNE). Pathological voice group and control group were used as training set and testing set for neural network testing, and another 140 cases of pathological voice and normal voice data were selected as a validation set. SPSS Modeler was used for artificial neural network reconstruction to calculate the identification rate of pathological voice. Result:This study found according to the calculation of groups with different genders that Jitter, Shimmer and NNE were increased in pathological voice group compared with the normal group (P< 0.05), while HNR and SNR were decreased compared with the normal group (P< 0.05). Recognition rate of artificial neural network model on pathological voice is 75.7%.Conclusion:Objective voice analysis is helpful in the identification of pathological voice. Artificial neural network has higher accuracy in recognition of pathological voice, with good clinical application value.

[The study on the standardization of adults voice acoustic parameters by objective analysis].

OBJECTIVE: To explore the characteristic of normal voice in different age-bracket of Chinese adults and to formulate the normal reference value suited to our country at voice assessment. METHOD: We divided the adults into the youth, the middle-aged and the old groups, and analyzed normal voice samples with Dr. Speech software and computer multimedia technique and compared the following 5 parameters (Jitter, Shimmer, NNE, Fo and SDFo) of different groups divided according to one's age, sex and vowel. RESULT: There is difference among the group of age, sex and vowel in most acoustic parameters in the adults. CONCLUSION: To initiate taking multi-vowels samples and using different normal reference value and multi-parameters analysis according to the difference of age-bracket, sex and vowel in the adults.