Purpose To investigate the expression of the protein of CD151 and MT1-MMP in adenocarcinoma of esophagogastric junc-tion tissues and to explore their relationship with the invasiveness and metastasis of the tumor. Methods CD151 and MT1-MMP pro-tein were detected by immunohistochemical staining respectively in 15 cases of paraneoplastic normal gastric mucosa tissue, 40 cases dysplasia and 172 cases of adenocarcinoma of esophagogastric junction tissues. Results All of the expression level of CD151 and MT1-MMP protein were increasing according to the order of normal-dysplsia-carcinoma. The expression rate of CD151 was 6. 67%, 20. 0% and 78. 3%, while the rate of MT1-MMP with 13. 3%, 22. 5% and 79. 1% in the normal, dysplasia and carcinoma subgroup. The expression rate of each protein were significant difference among the three goroups (P<0. 05). In the adenocarcinoma of esopha-gogastric junction tissues, the expression of them in the subgroup of poorly-differentiated with serosa invasion and lymph nodes metasta-sis was significantly higher than the other subgroup of well-differentiated with non serosa invasion or lymph nodes metastasis ( P <0. 05 ) . There was a positive correlation between the expression of CD151 and MT1-MMP protein in adenocarcinoma of esophagogastric junction tissues ( P<0. 05 ) . Conclusions CD151 and MT1-MMP assuredly and highly express in the adenocarcinoma of esopha-gogastric junction tissues and they have close relationships, which could involved in the invasiveness and metastasis synergistically in this tumor.

We present an analysis method of electrocardiogram (ECG) to determine patients' ventricular late potentials (VLPs) characteristics by means of wavelet packet transform and entropy (ApEn). The results indicate that the patients with VLPs tend to have higher ApEn values than do those without. So ApEn can be used as an indicator and a BP neural network for distinguishing between the two patient groups. The experiment result shows that this method has higher distinguishability.
Electrocardiography ; methods ; Entropy ; Heart Ventricles ; physiopathology ; Humans ; Neural Networks (Computer) ; Signal Processing, Computer-Assisted ; Ventricular Function