红外热成像技术在建筑物检测中的应用研究

红外成像技术采用非接触式检测方法,对建筑物进行实时、快速大面积扫描检测,在建筑工程中得到越来越广泛的应用。基于红外热成像法的建筑物检测技术正处在定性化分析转向定量化分析、智能化处理和多信息融合检测的过渡期,在此从检测方法组合化、检测技术定量化和检测过程智能化等三个方面探讨红外成像技术在建筑物检测中新的技术特征和实现方法。

Correlation of p53 over-expression and alteration in p53 gene detected by polymerase chain reaction-single strand conformation polymorphism in adenocarcinoma of gastric cancer patients from India

AIM： To study the alterations in p53 gene among Indian gastric cancer patients and to correlate them with the various clinicopathological parameters. METHODS： A total of 103 gastric cancer patients were included in this study. The p53 alterations were studied by both immunohistochemical method as well as polymerase chain reaction （PCR）-single strand conformation polymorphism （SSCP） analysis. We only studied four （exon 5, 6, 7, and 8） of the 11 ,p53 exons. The alterations in p53 were also correlated with respect to various clinicopathological parameters. RESULTS： Among 103 cases, p53 over-expression and alteration were detected in 37 （35.92%） and 19 （18.44%） cases, respectively. Most of the ,p53 alterations were found at exon 5 （31.54%）, followed by exon 6 （26.31%）, exon 7 （21.04%） and exon 8 （21.04%）. A significant correlation of p53 overexpression was found with p53 alteration （P = 0.000）. Concordance between ,p53 alteration （as detected by SSCP） and over-expression [as detected by immunohistochemistry （IHC）] was found in 75% cases. We found that IHC-positive/SSCP-negative cases accounted for 21% of cases and IHC-negative/SSCP- positive cases accounted for remaining 4% cases. CONCLUSION： Our results show that p53 gene mutations are significantly correlated with p53 protein over-expression, with 75% concordance in over-expression and alteration in the p53 gene, but 25% disconcordance also cautions against the assumption that p53 over-expression is always associated with a gene mutation. There may be other mechanisms responsible for stabilization and accumulation of p53 protein with no evidence of gene mutation that reflect an accumulation of a non-mutated protein, or a false negative SSCP result.

Clinical significance of human kallikrein 12 gene expression in gastric cancer

AIM:To investigate whether the expression of kallikrein 12(KLK12) is related to the development of gastric cancer(GC) and to determine the role of KLK12 in gastric cancer cells growth,invasion and migration.METHODS:Between September 2007 and March 2008,133 patients with histologically confirmed GC were recruited for the study.Expression of KLK12 was detected in samples from GC patients by quantitative real-time reverse transcription polymerase chain reaction and immunohistochemistry.The relationship between KLK12 protein expression and clinicopathological features of GC was analyzed.The difference in 5-year survival rates between the high KLK12 protein expression group and the low KLK12 expression group was compared.Additionally,the expression of KLK12 was examined in various human GC cell lines,including MKN-28,SGC-7901 and MKN-45.Small interfering RNA(siRNA) was used to inhibit KLK12 expression in MKN-45 cells.Cell clones stably transfected with KLK12 siRNA were tested for KLK12 expression by quantitative real-time reverse transcription-polymerase chain reaction and Western blotting.Furthermore,a series of functional assays were performed in this study to assess the biological features of transfected cells.Cell proliferation was assessed using the methylthiazolyltetrazoliumassay.Finally,cell migration and invasion were assessed using transwell chamber assays.RESULTS:Of the 133 GC patients included in the study,126(94.7%) showed a higher expression level of KLK12 mRNA when compared to noncancerous tissue specimens.Expression of KLK12 mRNA was significantly higher in GC tissues than in normal tissue(P < 0.001).KLK12 protein expression was detected in 96 of 133(72.2%) GC samples with moderate or strong staining primarily in the cytoplasm.In contrast,negative immunostaining for KLK12 protein was observed in the corresponding normal gastric mucosal tissue.Overexpression of KLK12 protein was significantly associated with lymph node metastasis(P = 0.001),histological type(P < 0.001) and tumor-node-metastasis stage(P = 0.005),while no significant correlation was observed between expression of KLK12 protein and sex,age,depth of invasion,tumor size or lymphatic invasion.Furthermore,patients with high KLK12 expression had a significantly poorer 5-year survival rate than those with low KLK12 expression(P = 0.002).Expression of KLK12 mRNA was significantly higher in MKN-45 GC cells compared to normal mucosal cells or two other GC cell lines(P < 0.01).Expression of KLK12 in MKN-45 cells was downregulated after transfection with siRNA.Knockdown of KLK12 markedly decreased the proliferation of MKN-45 cells when compared with parent or mock-transfected cells(P = 0.001),especially from the 3rd to the 5th day of the assay.In migration assays,fewer KLK12 siRNA cells migrated through the chambers(22.00 ± 1.81) when compared to the parent(46.47 ± 2.42) or mock-transfected cells(45.40 ± 1.99);these differences were statistically significant(P < 0.001).However,in the invasion assay,the number of KLK12 siRNA cells that invaded the chambers was 18.40 ± 1.12,closely similar to both the parent(18.67 ± 0.98) and mock-transfected cells(18.53 ± 0.92).There was no significantly difference between the three groups in the invasion assay(P = 0.054).CONCLUSION:The KLK12 gene is markedly overexpressed in GC tissue,and its expression status may be a powerful prognostic indicator for patients with GC.KLK12 might serve as a novel diagnosis and prognosis biomarker in GC.

Hybrid Optimization of Support Vector Machine for Intrusion Detection

Support vector machine (SVM) technique has recently become a research focus in intrusion detection field for its better generalization performance when given less priori knowledge than other soft-computing techniques. But the randomicity of parameter selection in its implement often prevents it achieving expected performance. By utilizing genetic algorithm (GA) to optimize the parameters in data preprocessing and the training model of SVM simultaneously, a hybrid optimization algorithm is proposed in the paper to address this problem. The experimental results demonstrate that it’s an effective method and can improve the performance of SVM-based intrusion detection system further.