Effects of biological clock gene Bmal1 on the expression of cell cycle-associated genes in chondrocytes / 基础医学与临床

Objective To explore the intrinsic relationship between circadian clock and cell cycle in osteoarthritis(OA)chondrocytes,especially the regulation of cell cycle-related genes by the clock gene Bmal1.Methods The chondroid ATDC5 cells induced by insulin-transfering-selenium(ITS)were divided into control group,OA group and LV-Bmal1 group.The cell viability of each group was detected by CCK8 method.The expression of Bmal1,Per1,Wee1,Cdk1,Ccnb1 and Mmp13 mRNA in each group was detected by RT-qPCR.The expression of BMAL1,PER1,WEE1,CDK1,CCNB1 and MMP13 protein in each group was detected by Western blot.The effects of Bmal1 on different stages of cell cycle and apoptosis was analyzed by flow cytometry.The regulation of Bmal1 on Per1,Wee1,Cdk1,Ccnb1 and Mmp13 and their roles in OA were analyzed.Results Compared with the normal group,the cell viability of the OA group was increased,the relative mRNA expression of Bmal1 and Wee1 in the OA group decreased,and the relative mRNA expression of Per1,Cdk1,Ccnb1 and Mmp13 increased signif-icantly.The cell viability of LV-Bmal1 group decreased,the relative expression of Bmal1 and Wee1 mRNA in-creased,and the relative expression of Per1,Cdk1,Ccnb1 and Mmp13 mRNA decreased(P＜0.05).Correlation analysis showed that Bmal1 was positively correlated with Wee1 and they were negatively correlated with Per1,Cdk1,Ccnb1 or Mmp13.The results of Western blot showed that protein expression in different groups were con-sistent with the trend of PCR.The results of cell cycle and apoptosis showed that compared with the normal group,the S phase and G2/M phase of the OA group were shortened,the proportion of cells decreased significantly,and the proportion of early and late apoptosis increased.The S phase and G2/M phase of the LV-Bmal1 group were prolonged,the proportion of cells was increased,and the proportion of early and late apoptosis was decreased.Conclusions Circadian clock gene Bmal1 in inflammatory chondrocytes might regulate the expression of cell cycle-related genes.

R-wave detection of ECG signal by using wavelet transform / 生物医学工程学杂志

The detection of R-wave of ECG is essential to the analysis of the heart rate variability (HRV). In this paper, an R-wave detection method using wavelet transform(WT) is presented in line with the principle of discrete wavelet transform(DWT) and multi-resolution technique (MRT). We made use of the special properties of dbl wavelet in time-domain, decomposed the original ECG signals into 3-level detailed signals on different frequency bands by using DWT with Mallat algorithm, and got appropriate threshold values in different high frequency bands to distinguish R-wave. It is concluded that the algorithm had significant effects on it, which is verified by MIT/BIH (Massachusetts Institute of Technology/Boston's Beth Israel Hospital) ECG Database. The results show that R-wave could be detected accurately and localized precisely by this method, even when the patient was seriously sick or the signal was disturbed by noise. Consequently the method has a quite high locating precision (its error is not more than two sampled points and about 85 percent of the points of R-wave in ECG signal are localized precisely) and the correct detection rate of R-wave is 99.8% by using wavelet transform, so this method is quite feasible.

Exercise ECG signal de-noising using unbiased risk estimate and wavelet transform / 生物医学工程学杂志

In this paper a filtering method for EECG (Exercise ECG) signal is proposed which is based on wavelet transform (WT) and Stein's unbiased risk estimate (SURE). This algorithm was used to decompose original EECG signals into detail signals on different frequency bands by using WT and get different thresholds with SURE. According to EECG signal features and by using the above thresholds, the method amended several detail signals so that the main interferences in EECG signal can be removed efficiently. The authors also put forward two indexes to estimate the validity of such algorithms. Our experimental results demonstrate that this is an efficient de-noising method for EECG.