IDENTIFICATION OF DIFFERENTIAL GENES IN OVARIAN CANCER USING REPRESENTATIONAL DIFFERENCE ANALYSIS OF cDNA

Objoctive To identify differential genes between normal ovarian epithelium tissue and ovarian epithelial cancer using representational difference analysis of cDNA （cDNA-RDA）. Methods cDNA-RDA was performed to identify the differentially expressed sequences between cDNAs from cancer tissue and cDNAs from normal ovarian tissue in the same patient who was in the early stage of ovarian serous cystadenocarcinoma. These differentially expressed fragments were cloned and analyzed, then sequenced and compared with known genes. Results Three differentially cxpressed cDNA fragments were isolated using cDNA from normal ovarian tissue as tester and cDNA from cancer tissue as driver amplicon by cDNA-RDA. DP Ⅲ- 1 and DP Ⅲ-2 cDNA clone showed significant homology to the cDNA of alpha actin gene; DPⅢ-3 cDNA clone showed significant homology to the cDNA oftransgelin gene. Conclusion cDNA-RDA can bc used to sensitively identify the differentially expressed genes in ovarian serous cystadenocarcinoma. Ovarian serous cystadenocarcinoma involves alteration of multiple genes.

Metastatic suppressor genes inactivated by aberrant methylation in gastric cancer

AIM: To screen out the differentially methylated DNA sequences between gastric primary tumor and metastatic lymph nodes, test the methylation difference of gene PTPRG between primary gastric tumor and metastatic lymph nodes, and test the regulatory function of 5-aza- 2-deoxycytidine which is an agent with suppression on methylation and the level of methylation in gastric cancer cell line. METHODS: Methylated DNA sequences in genome were enriched with methylated CpG islands amplification (MCA) to undergo representational difference analysis (RDA), with MCA production of metastatic lymph nodes as tester and that of primary tumor as driver. The obtained differentially methylated fragments were cloned and sequenced to acquire the base sequence, which was analyzed with bioinformatics. With methylation-specific PCR (MSP) and RT-PCR, methylation difference of gene PTPRG was detected between primary tumor and metastatic lymph nodes in 36 cases of gastric cancer. Methylation of gene PTPRG and its regulated expression were observed in gastric cancer cell line before and after being treated with methylation-suppressive agent. RESULTS: Nineteen differentially methylated sequences were obtained and located at 5' end, exons, introns and 3' end, in which KL59 was observed to be located at 9p21 as the first exon of gene p16 and KL22 to be located at promoter region of PRPRG . KL22, as the probes, was hybridized with driver, tester and 3-round RDA products respectively with all positive signals except with the driver. Significant difference was observed in both methylation rate of gene PTPRG and PTPRG mRNA expression rate between primary tumor and metastatic lymph nodes. Demethylation of gene PTPRG, with recovered expression of PTPRG mRNA, was observed after gastric cancer cell line being treated with methylation-suppressive agent. CONCLUSION: Difference exists in DNA methylation between primary tumor and metastatic lymph nodes of gastric cancer, with MCA-RDA as one of the good analytical methods. Significant difference exists in methylation of gene PTPRG between primary tumor and metastatic lymph nodes of gastric cancer. Methylation level in gastric cancer cell line can be decreased by 5-aza-2'-deoxycytidine, which is the methylation- suppressive agent, with PTPRG expression being recovered.

Consensus intuitionistic fuzzy group decision-making method for aircraft cockpit display and control system evaluation

A novel group decision-making （GDM） method based on intuitionistic fuzzy sets （IFSs） is developed to evaluate the ergonomics of aircraft cockpit display and control system （ACDCS）. The GDM process with four steps is discussed. Firstly, approaches are proposed to transform four types of common judgement representations into a unified expression by the form of the IFS, and the features of unifications are analyzed. Then, the aggregation operator called the IFSs weighted averaging （IFSWA） operator is taken to synthesize decision-makers’ （DMs’） preferences by the form of the IFS. In this operator, the DM’s reliability weights factors are determined based on the distance measure between their preferences. Finally, an improved score function is used to rank alternatives and to get the best one. An illustrative example proves the proposed method is effective to valuate the ergonomics of the ACDCS.

ANALYSIS OF Lyl1 EXPRESSION AS A FREQUENT PARTNER OF LMO2 IN T-CELL LEUKEMOGENESIS IN HUMAN

Objective： To identify aberrant gene expression in primary human T-cell acute lymphoblastic leukemia （T-ALL） and to evaluate the differently expressed level of Lyll and LMO2 genes in human LMO2 positive/TALl negative T-ALL tumors. Methods： Three methods, representational difference analysis （RDA） of cDNA, cDNA microarrays and RT-PCR were used to detect if Lyll and LMO2 genes were differently expressed in human LMO2 positive/tall negative T-ALL tumors. Results： The results of cDNA RDA and cDNA array shown that Lyll and LMO2 genes are differently expressed in human T-cell tumors. The result of RT-PCR also shown Lyll and LMO2 are high expressed in human T-cell tumors and very low level or no expressed in normal group. Conclusion： We have found that cDNA RDA and cDNA microarray can be successfully used to identify aberrant gene expression in T-ALL cells. In the study described in this manuscript we found that Lyll and LMO2 are aberrantly expressed in human T-ALL LMO2 positive/TALl negative T-ALL tumors.

cDNA representational difference analysis of differentially expressed cDNA sequences in human nasopharyngeal carcinoma

Objective To search differentially expressed sequences correlated with pathogenesis of human nasopharyngeal carcinoma (NPC), including the candidates of tumor suppressor genes Methods Representational difference analysis (RDA) was performed to isolate differentially expressed sequences between cDNA from normal human primary cultures of nasopharyngeal epithelial cells and cDNA from NPC cell line HNE1 The source of differentially expressed products were proved by Southern blot, Northern blot and in situ hybridization The fragments were cloned with pGEM T easy kit and sequenced by the chain termination reaction Results Four differentially expressed cDNA fragments were isolated in the fourth subtractive hybridization using cDNA from normal human nasopharyngeal epithelial cells as tester amplicon and cDNA from NPC cell line HNE1 as driver amplicon by cDNA RDA These differential cDNA fragments revealed that they really came from the tester amplicon and were not expressed or down regulated in the NPC HNE1 cells Some of the genes were expressed only in human nasopharyngeal epithelial cells but deleted or down regulated in the biopsies of NPC Of these obtained clones, some were the sequences of the human known genes including house keeping genes, the others represented novel gene sequences Conclusion The differentially expressed products including the candidates of tumor suppressor genes may be associated with the initiation of the NPC

SemID: Blind Image Inpainting with Semantic Inconsistency Detection

Most existing image inpainting methods aim to fill in the missing content in the inside-hole region of the target image. However, the areas to be restored in realistically degraded images are unspecified. Previous studies have failed to recover the degradations due to the absence of the explicit mask indication. Meanwhile, inconsistent patterns are blended complexly with the image content. Therefore, estimating whether certain pixels are out of distribution and considering whether the object is consistent with the context is necessary. Motivated by these observations, a two-stage blind image inpainting network, which utilizes global semantic features of the image to locate semantically inconsistent regions and then generates reasonable content in the areas, is proposed. Specifically, the representation differences between inconsistent and available content are first amplified, iteratively predicting the region to be restored from coarse to fine. A confidence-driven inpainting network based on prediction masks is then used to estimate the information regarding missing regions. Furthermore, a multiscale contextual aggregation module is introduced for spatial feature transfer to refine the generated contents. Extensive experiments over multiple datasets demonstrate that the proposed method can generate visually plausible and structurally complete results that are particularly effective in recovering diverse degraded images.