MMP 9 Gene Promoter Polymorphism in Gastric Cancer

Matrix metalloproteinase-9 (gelatinase B) plays a key role in cancer invasion and metastasis by degrading the extracellular matrix and basement membrane barriers. A cytosine (C) > thymidine (T) single nucleotide polymorphism (SNP) at position −1562 in the MMP-9 promoter is reported to influence the expression of the gene. Genotyping of MMP-9 −1562 C→T promoter polymorphism in 140 gastric cancer patients and 132 healthy control subjects was carried out in order to evaluate its association with progression and development of gastric cancer. The SNP was genotyped by tetra-primer amplification refractory mutation system-polymerase chain reaction followed by agarose gel electrophoresis. Statistical methods were adopted to test for the significance of the results. Risk factor profile of the patients revealed age above 50 years, smoking, alcoholism as the factors associated with the disease. The distribution of genotype frequencies in gastric cancer patients were 28.7 % of CC, 45.5 % of CT and 25.7 % of TT, whereas in control subjects 31.8 % of CC, 53.03 % of CT and 15.15 % of TT, respectively. The allelic frequencies were 51.51 % of C and 48.48 % of T in patient group and 58.33 % of C and 41.66 % of T in controls respectively. The present study shows the possible association of epidemiological risk factors with gastric cancer. There is an increased frequency of T allele in the disease compared to control subjects. However, there is no association of the MMP-9 −1562 C→T promoter polymorphism in the development of gastric cancer.     

A genetically modified fuzzy linear discriminant analysis for face recognition

This paper addresses the face recognition problem through a modification of the Fuzzy Fisherface classification method. In conventional methods, the relationship of each face to a class is assumed to be crisp. The Fuzzy Fisherface method introduces a gradual level of assignment of each face pattern to a class, using a membership grading based upon the K-Nearest Neighbor (KNN) algorithm. This method was further modified by incorporating the membership grade of each face pattern into the calculation of the between-class and within-class scatter matrices, termed as Complete Fuzzy LDA (CFLDA). The present work aims at improving the assignment of class membership by improving the parameters of the membership functions. A genetic algorithm is employed to optimize these parameters by searching the parameter space. Furthermore, the genetic algorithm is used to find the optimal number of nearest neighbors to be considered during the training phase. The experiments were performed on the Olivetti Research Laboratory (ORL) face image database and the results show consistent improvement in the recognition rate when compared to the results from other techniques applied on the same database and reported in literature.     

Characteristics of research and development performing firms in Canadian manufacturing

The purpose of this paper is to examine some of the salient characteristics of R&D performing firms in Canadian manufacturing. The paper begins by presenting a brief overview of recent trends in R&D in the Canadian economy. The next section analyzes the main characteristics of those firms which undertake research and development activities in Canadian manufacturing industries. Various aspects are examined in this section including the R&D expenditure patterns of industries in the research-intensive and non-research-intensive sectors, R&D by size of firm and by size of program, levels of R&D intensity in terms of small, medium and large R&D performing firms. The importance of foreign ownership and its implication for the level of R&D activity is also considered. The paper concludes by summarizing the highlights of R&D performing firms and draws some implications for the structure of Canadian manufacturing based on the findings.     

Evaluation of serum adenosine deaminase and 5′-nucleotidase activities as probable markers in ovarian cancer

Adenosine deaminase (ADA) and 5′-nucleotidase (5′-NT) activities were measured in sera of patients with ovarian cancer and patients with benign ovarian tumour. The results were compared with that of a control group consisting of healthy women. ADA levels were significantly increased (P<0.001) in the ovarian cancer group (n=50) but not in the benign group (n=28) when compared to the controls (n=20). The results indicate that ADA and 5′-NT levels may help to differentiate malignant conditions from benign tumours of the ovary in addition to the existing tests such as serum CA-125 levels and histopathological study.     

HIV/AIDS research in India: A bibliometric study

This article looks at the growth over time of Indian AIDS research output based on bibliographic data from PubMed and Web of Science. Authorship distribution was examined using Lotka's law. Bradford's law of scattering was used to identify core journals. The study identifies active institutions and statewide distributions of Indian AIDS research output. The yearly analysis of data shows that there is a rapid growth of literature from 1992 onwards. Still, in an international sense, relative productivity of India is low and requires more focused research and development.