Deletion and Down-Regulation of HRH4 Gene in Gastric Carcinomas: A Potential Correlation with Tumor Progression

Background: Histamine is an established growth factor for gastrointestinal malignancies. The effect of histamine is largely determined locally by the histamine receptor expression pattern. Histamine receptor H4 (HRH4), the newest member of the histamine receptor family, is positively expressed on the epithelium of the gastrointestinal tract, and its function remains to be elucidated. Previously, we reported the decreased expression of HRH4 in colorectal cancers and revealed its correlation with tumor proliferation. In the current study, we aimed to investigate the abnormalities of HRH4 gene in gastric carcinomas (GCs). Methodology/Principal Findings: We analyzed H4R expression in collected GC samples by quantitative PCR, Western blot analysis, and immunostaining. Our results showed that the protein and mRNA levels of HRH4 were reduced in some GC samples, especially in advanced GC samples. Copy number decrease of HRH4 gene was observed (17.6%, 23 out of 131), which was closely correlated with the attenuated expression of H4R. In vitro studies, using gastric cancer cell lines, showed that the alteration of HRH4 expression on gastric cancer cells influences tumor growth upon exposure to histamine. Conclusions/Significance: We show for the first time that deletion of HRH4 gene is present in GC cases and is closely correlated with attenuated gene expression. Down-regulation of HRH4 in gastric carcinomas plays a role in histaminemediate

Logging to Facilitate Combinatorial System Testing

Testing a web application is typically very complicated. Imposing simple coverage criteria such as function or line coverage is often not sufficient to uncover bugs due to incorrect components integration. Combinatorial testing can enforce a stronger criterion, while still allowing the prioritization of test cases in order to keep the overall effort feasible. Combinatorial testing requires the whole testing domain to be classified and formalized, e.g., in terms of classification trees. At the system testing level, these trees can be quite large. This short paper presents our preliminary work to automatically construct classification trees from loggings of the system, and to subsequently calculate the coverage of our test runs against various combinatorial criteria. We use the tool CTE which allows such criteria to be custom specified. Furthermore, it comes with a graphical interface to simplify the specification of new test sequences