BACKGROUND: HEPSIN (HPN) gene is one of the most consistently overexpressed genes in patients with prostate cancer; furthermore, there is some evidence supporting an association between HPN gene variants and the risk of developing prostate cancer. In this study, sequence variants in the HPN gene were investigated to determine whether they were associated with prostate cancer risk in a Korean study cohort. METHODS: We evaluated the association of 17 single-nucleotide polymorphisms (SNPs) in the HPN gene with prostate cancer risk and clinical characteristics (Gleason score and tumor stage) in Korean men (240 case subjects and 223 control subjects) using unconditional logistic regression. RESULTS: The statistical analysis suggested that three SNPs (rs45512696, rs2305745, rs2305747) were significantly associated with the risk of prostate cancer (odds ratio (OR) ¼ 2.22, P ¼ 0.04; OR ¼ 0.73, P ¼ 0.03; OR ¼ 0.76, P ¼ 0.05, respectively). CONCLUSIONS:The results of this study suggest that, in Korean men, some polymorphisms in the HPN gene might be associated with the risk of developing prostate cancer.

Lactococcus garvieae is recognized as an emerging pathogen in fish. Several PCR-based methods have been developed for the detection and identification of L. garvieae; however, the sensitivity of these methods is still in question regarding the discrimination of this organism from other closely related species. Two primers, ITSLg30F and ITSLg319R, were designed from the sequence in the 16S-23S internal transcribed spacer (ITS) region and used for the specific detection of L. garvieae. L. garvieae strains including fish isolates were positive by this method. In contrast, previously developed PCR methods showed false-positive results with non-L. garvieae species. Our results indicate that a PCR method using the newly designed ITS primer set provides a sensitive and efficient tool for the detection of L. garvieae in fish and aquaculture environments.

Hfq is the bacterial orthologue of the eukaryotic (L)Sm family of proteins found across all domains of life and potentially an ancient protein, but it has not been found in all phyletic lines. A careful search successfully identified a distant hfq orthologue in the cyanobacteria leaving the actinobacteria as the major phylum with no known hfq orthologue. A search for hfq in actinobacteria, using domain enhanced searching (DELTA-BLAST) with cyanobacterial hfq, identified a conserved actinobacterial specific protein as remotely homologous. Structural homology modelling using profile matching to fold libraries and ab initio 3D structure determination supports this prediction and suggests module shuffling in the evolution of the actinobacterial hfq. Our results provide the basis to explore this prediction, and exploit it, across diverse taxa with potentially important post-transcriptional regulatory effects in virulence, antibiotic production and interactions in human microbiomes. However, the role of hfq in gram positive bacteria has remained elusive and experimental verification will be challenging.

Background Tumor necrosis factor (TNF) antagonists are recommended for patients with ulcerative colitis (UC) for the effectiveness in inducing and maintaining clinical remission. We investigated the altered fecal metabolites and lipids by anti-TNF treatment and prediction model of remission in patients with UC. Methods A prospective, observational multicenter study was conducted at 17 academic hospitals in Korea. Fecal samples were collected from adult patients with moderately to severely active UC (n=116) before and after 8 and 56 weeks of adalimumab treatment and from healthy controls (HC, n=37). Clinical remission was assessed using Mayo score. Metabolome and lipidome analyses were performed using gas chromatography-, and nano electro spray ionization-mass spectrometry, respectively. Prediction models of remission were developed using baseline fecal samples by Fourier transform-infrared (FT-IR) spectroscopy combined with machine learning algorithms. Results Fecal metabolites and lipids in UC were different from HC at baseline and were changed similarly to HC during treatment. Fecal metabolites and lipids in remitters (RM) after treatment were more grouped and clustered with those of HC compared with non-remitters (NRM). In RM, 2-aminobutyric acid, galactose and dodecanoate levels which were previously decreased at baseline compared to HC increased to the levels of HC, whereas benzoate, stigmasterol, 3-hydroxybutyrate, diacylglycerol and triacylglycerol levels which were previously increased at baseline compared to HC decreased to the levels of HC after 56 weeks of treatment. The best model predicting short-term remission was developed by applying logistic regression (LR) and radial basis functions (rbf) support vector machine (SVM) with an accuracy of 0.99 (95% confidence interval [CI], 0.98–1.01). For long-term remission, the best prediction model was developed by rbf-SVM revealing 0.99 [CI 0.98–1.01]. LR and K-nearest neighbors also showed excellent performance for prediction of long-term remission (accuracy of 0.96 [CI 0.90–1.02] and 0.96 [CI 0.92–1.00], respectively. Conclusion Fecal characteristics in UC were changed after anti-TNF treatment and became similar to those of HC. Potential therapeutic target compounds were suggested to develop novel therapeutic strategies for UC. Novel remission prediction models by FT-IR spectroscopy were also established.