• Genomics & Informatics
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• v.21 no.1
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• pp.8.1-8.19
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• 2023

Cancer of the stomach is the second most frequent cancer-related death worldwide. The survival rate of patients with gastric cancer (GC) remains fragile. There is a requirement to discover biomarkers for prognosis approaches. Helicobacter pylori in the stomach is closely associated with the progression of GC. We identified the genes associated with poor/favorable prognosis in H. pylori-induced GC. Multivariate statistical analysis was applied on the Gene Expression Omnibus (GEO) dataset GSE54397 to identify differentially expressed miRNAs (DEMs) in gastric tissues with H. pylori-induced cancer compared with the H. pylori-positive with non-cancerous tissue. A protein interaction map (PIM) was built and subjected to DEMs targets. The enriched pathways and biological processes within the PIM were identified based on substantial clusters. Thereafter, the most critical genes in the PIM were illustrated, and their prognostic impact in GC was investigated. Considering p-value less than 0.01 and |Log2 fold change| as >1, five microRNAs demonstrated significant changes among the two groups. Gene functional analysis revealed that the ubiquitination system, neddylation pathway, and ciliary process are primarily involved in H. pylori-induced GC. Survival analysis illustrated that the overexpression of DOCK4, GNAS, CTGF, TGF-b1, ESR1, SELE, TIMP3, SMARCE1, and TXNIP was associated with poor prognosis, while increased MRPS5 expression was related to a favorable prognosis in GC patients. DOCK4, GNAS, CTGF, TGF-b1, ESR1, SELE, TIMP3, SMARCE1, TXNIP, and MRPS5 may be considered prognostic biomarkers for H. pylori-induced GC. However, experimental validation is necessary in the future.

• Reproductive and Developmental Biology
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• v.30 no.3
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• pp.169-174
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• 2006

To search of a new porcine pheromonal odorants, the comparative molecular similarity indices analysis(CoMSIA) between porcine odorant binding protein(pOBP) as receptor and ligands of green odorants 2-(Cyclohexyloxy)tetrahydrofurane derivatives as substrate molecule were conducted and disscused quantitatively. In the optimized CoMSIA model(I-AI) with chirality($I:\;C_{1'}(R),\;C_2(S)$) in substrate molecules and atom based fit alignment(AE) of the odorants the statistical PLS results showed the best predictability of the binding affinities based on the LOO cross-validated value ${r^2}_{cv.}\;(q^2=0.856)$ and non cross-validated conventional coefficient(${r^2}_{ncv.}=0.964)$). The structural distinctions of the highest active molecules were able to understand from the interaction between pOBP and green odorants in the contour maps with CoMSIA model.