1.Expression of canstatin gene in human lymphocytes and its inhibitory effect on growth and metastasis of Lewis lung carcinoma.
Weizhong LU ; Xiwen WANG ; Guijun HUANG ; Yuying LI ; Shicang YU ; Jin LI ; Guisheng QIAN
Chinese Journal of Lung Cancer 2006;9(3):245-249
BACKGROUNDIn recent years, many progresses have been made in molecular target therapy for lung cancer, in which anti-angiogenic target therapy is a hot spot drawing researchers' attention. The aim of this study is to explore the expression of canstatin gene transfected into human lymphocytes and its inhibitory effect on growth and metastasis of Lewis lung carcinoma.
METHODSThe eukaryotic expression vector of pCMV-Script and the recombinant pCMV-Script/Canstatin vector were separately transfected into lymphocytes by electroporation. The expression of canstatin protein in supernatant of lymphocyues was examined by SDS-PAGE assay. Furthermore, Lewis lung carcinoma cells were subcutaneously inoculated to C57BL mice to make animal model of tumor. When the transplanted tumors on the mice developed to 1cm³, the 30 mice were randomized into 3 groups, which were injected with 0.2mL supernatant of lymphocytes transfected with recombinant vector or naked vector, or 0.2mL NS respectively. After the treatment for 14 days, the size and pathological section of subcutaneous tumors were observed, and the number of pulmonary metastatic node was calculated.
RESULTSCanstatin protein was found in supernatant of the lymphocytes in the recombinant vector group by SDS-PAGE assay. After the treatment, the tumor size in the recombinant vector group (1.49cm³±0.18cm³) was significantly smaller than that in the naked vector group (2.44cm³± 0.19cm³) and NS group (2.53cm³±0.18cm³) (P=0.000). The numbers of pulmonary metastatic node were 3.40±1.14, 7.60±2.61 and 7.60±2.41 in the recombinant vector group, naked vector group and NS group respectively (recombinant vector group vs the other two groups, P=0.013).
CONCLUSIONSThe pCMV-Script/Canstatin vector can express canstatin protein in human lymphocytes. Canstatin has strongly inhibitory effect on growth and metastasis of mouse Lewis lung carcinoma.
2.Effects of canstatin gene transfection on growth and apoptosis of lung cancer A549 cells and HUV-ECC cells.
Weizhong LU ; Guijun HUANG ; Guisheng QIAN ; Yuying LI ; Shicang YU ; Jin LI
Chinese Journal of Lung Cancer 2005;8(2):95-98
BACKGROUNDAngiogenesis is essential for tumor's growth and metastasis. Canstatin, a newly found potent endogenous angiogenesis inhibitor, has drawn researcher's attention to its powerful biological activities on endothelial cells. The aim of this experiment is to explore the expression and effects of canstatin gene in lung cancer A549 cells and HUV-ECC cells.
METHODSExpression vector of pCMV- Script/Canstatin was transfected into A549 and ECC cells by electroporation, and the positive clone was screened by G418. Growth characteristics of the two cell lines were compared before and after transfection. Expression of canstatin protein in supernatant was examined by SDS-PAGE assay, and cell cycles of the two cell lines were analysed by flow cytometry.
RESULTSThe expression of canstatin gene was found in supernatant of the transfected A549 cells and ECC cells. The apoptotic rate in the transfected ECC cells (16.04%) was significantly increased compared with that of the naked plasmid control group (0.43%) and parental cell group (2.92%) (P < 0.01). The growth of the transfected ECC cells was significantly inhibited (P < 0.01). The apoptotic rate in the transfected A549 cells (0.19%) showed no marked difference from the naked plasmid control group (0.13%) and parental cell group (0.07%) (P > 0.05). No significant difference in cell growth was found among the transfected A549 cell, naked plasmid control and parental cell groups.
CONCLUSIONSThe results indicate that canstatin gene can express in lung cancer A549 cell line and HUV-ECC cell line, and it can specifically inhibit proliferation of endothelial cell and induce its apoptosis.
3.Application of artificial intelligence teaching-picture system to improve the bone marrow cell morphological reading ability of clinical medical students
Lei GAO ; Xiangui PENG ; Wucheng YANG ; Yanqi ZHANG ; Cheng ZHANG ; Yao LIU ; Peiyan KONG ; Li GAO ; Shicang YU ; Xi ZHANG
Chinese Journal of Medical Education Research 2020;19(5):569-573
Objective:To explore the effect of artificial intelligence teaching-picture system in training the bone marrow cell morphological reading ability of clinical medical students.Methods:A total of 110 five-year undergraduate students were divided into experimental group (artificial intelligence picture teaching method) and control group (traditional teaching method) in the bone marrow cell morphology reading ability training. On the basis of multimedia teaching, the experimental group was given the teaching by using the bone marrow cell morphology picture storage and transmission system for retrieval, learning and computer adaptive test. Then objective evaluation of image recognition ability and questionnaire were used to compare the teaching effect.Results:The image recognition ability was significantly better in the experimental group than in the control group [(89.6±5.7) vs. (81.4±4.9), P<0.01]. Furthermore, the experimental group showed more obvious advantages in cell morphology recognition [(74.7±4.0) vs. (68.7±4.9)] and diagnosis of hematological diseases [(14.9±3.0) vs. (12.9±2.4)] than the control group (both P<0.01). Questionnaire survey showed that the students expressed their affirmation and support for the artificial intelligence teaching-picture system in the bone marrow cell morphological reading ability training. Conclusion:The application of artificial intelligence teaching-picture system can greatly improve the teaching effect, mobilize students' learning enthusiasm and expand learning resources, which is worthy of further promotion and application.
4. Application of the concept of evidence-based medicine in the training of professional postgraduate students in hematology
Lei GAO ; Xi ZHANG ; Peiyan KONG ; Shicang YU ; Yao LIU ; Cheng ZHANG ; Li GAO
Chinese Journal of Medical Education Research 2019;18(10):979-981
The clinical research model based on evidence