Inhibitory effect of Periplaneta Americana extract on 3LL lung cancer in mice / 中国肺癌杂志

<p><b>BACKGROUND</b>It has been known that Kangfuxin, a drug derived from Periplaneta Americana, can induce cell apoptosis of many cancer cell lines in vitro. The aim of this study is to investigate the inhibitory effect and mechanism of Periplaneta Americana extract (PAE) on 3LL lung cancer in mice.</p><p><b>METHODS</b>The C57BL/6J mice transplanted with 3LL lung cancer were divided into normal saline (NS), PAE high dose (PAE-H) and PAE low dose (PAE-L) groups. The body weight changes and inhibitory rate of tumor growth in each group were observed. In addition, the cell cycle, apoptosis index (AI) and the expression of apoptosis associated genes were analysed by flow cytometry (FCM).</p><p><b>RESULTS</b>The body weights were decreased in PAE-L and PAE-H treated group compared with NS group and the inhibitive rate of tumor growth was 41.24% and 81.08% respectively. FCM assay indicated that PAE could induce apoptosis of lung cancer cell, and the apoptosis rate was concentration-dependent. At the same time, the number of S and G2/M phase cells was decreased, most of the cells were arrested in G1/G1 phase. The result of TUNEL showed that there were apoptosis and necrosis associated with upregulated expression of Fas, FasR and p53 genes, and downregulated expression of Bcl-2.</p><p><b>CONCLUSIONS</b>PAE may inhibit the growth of 3LL lung cancer in mice and induce apoptosis of 3LL lung cancer cells. It might be related to its effects on the regulation of apoptotic gene expression.</p>

A novel ROI extracting technique based on wavelet transform for the detection of micro-calcifications in mammograms / 生物医学工程学杂志

In order to preprocess mammograms for diagnosing the early cases of breast cancer and improving the computational efficiency in the computer-aided detection of micro-calcifications in mammograms, we have advanced a novel processing technique for the extraction of micro-calcification region of interest (MROI). The proposed method is based on a three-step procedure: (1) the mammogram is divided into sub-images of the same size; (2) the wavelet multi-resolution method is conducted on the sub-images, and the parameters related to wavelet transform and threshold T are discussed according to rho; (3) the classification of sub-images is determined by T. It is tested with 20 mammograms and the results show that the method can achieve a true positive rate as high as 89.7% with a false positive rate as low as 2.1%.