Dynamical Instability of Holographic QCD at Finite Density

In this paper we study the dynamical instability of Sakai-Sugimoto's holographic QCD model at finite baryon density. In this model, the baryon density, represented by the smeared instanton on the worldvolume of the probe D8-\overline{D8} mesonic brane, sources the worldvolume electric field, and through the Chern-Simons term it will induces the instability to form a chiral helical wave. This is similar to Deryagin-Grigoriev-Rubakov instability to form the chiral density wave for large N_c QCD at finite density. Our results show that this kind of instability occurs for sufficiently high baryon number densities. The phase diagram of holographic QCD will thus be changed from the one which is based only on thermodynamics. This holographic approach provides an effective way to study the phases of QCD at finite density, where the conventional perturbative QCD and lattice simulation fail.Comment: 18 pages, 6 figures;v2. add thermodynamics discussion; v4. Treatment of the instanton energy changed and QGP analysis added. Some figures replaced and added, including the phase diagra

CpGPAP: CpG island predictor analysis platform

<p>Abstract</p> <p>Background</p> <p>Genomic islands play an important role in medical, methylation and biological studies. To explore the region, we propose a CpG islands prediction analysis platform for genome sequence exploration (CpGPAP).</p> <p>Results</p> <p>CpGPAP is a web-based application that provides a user-friendly interface for predicting CpG islands in genome sequences or in user input sequences. The prediction algorithms supported in CpGPAP include complementary particle swarm optimization (CPSO), a complementary genetic algorithm (CGA) and other methods (CpGPlot, CpGProD and CpGIS) found in the literature. The CpGPAP platform is easy to use and has three main features (1) selection of the prediction algorithm; (2) graphic visualization of results; and (3) application of related tools and dataset downloads. These features allow the user to easily view CpG island results and download the relevant island data. CpGPAP is freely available at <url>http://bio.kuas.edu.tw/CpGPAP/</url>.</p> <p>Conclusions</p> <p>The platform's supported algorithms (CPSO and CGA) provide a higher sensitivity and a higher correlation coefficient when compared to CpGPlot, CpGProD, CpGIS, and CpGcluster over an entire chromosome.</p

SNP-RFLPing 2: an updated and integrated PCR-RFLP tool for SNP genotyping

<p>Abstract</p> <p>Background</p> <p>PCR-restriction fragment length polymorphism (RFLP) assay is a cost-effective method for SNP genotyping and mutation detection, but the manual mining for restriction enzyme sites is challenging and cumbersome. Three years after we constructed SNP-RFLPing, a freely accessible database and analysis tool for restriction enzyme mining of SNPs, significant improvements over the 2006 version have been made and incorporated into the latest version, SNP-RFLPing 2.</p> <p>Results</p> <p>The primary aim of SNP-RFLPing 2 is to provide comprehensive PCR-RFLP information with multiple functionality about SNPs, such as SNP retrieval to multiple species, different polymorphism types (bi-allelic, tri-allelic, tetra-allelic or indels), gene-centric searching, HapMap tagSNPs, gene ontology-based searching, miRNAs, and SNP500Cancer. The RFLP restriction enzymes and the corresponding PCR primers for the natural and mutagenic types of each SNP are simultaneously analyzed. All the RFLP restriction enzyme prices are also provided to aid selection. Furthermore, the previously encountered updating problems for most SNP related databases are resolved by an on-line retrieval system.</p> <p>Conclusions</p> <p>The user interfaces for functional SNP analyses have been substantially improved and integrated. SNP-RFLPing 2 offers a new and user-friendly interface for RFLP genotyping that can be used in association studies and is freely available at <url>http://bio.kuas.edu.tw/snp-rflping2</url>.</p

Improved branch and bound algorithm for detecting SNP-SNP interactions in breast cancer

BACKGROUND: Single nucleotide polymorphisms (SNPs) in genes derived from distinct pathways are associated with a breast cancer risk. Identifying possible SNP-SNP interactions in genome-wide case–control studies is an important task when investigating genetic factors that influence common complex traits; the effects of SNP-SNP interaction need to be characterized. Furthermore, observations of the complex interplay (interactions) between SNPs for high-dimensional combinations are still computationally and methodologically challenging. An improved branch and bound algorithm with feature selection (IBBFS) is introduced to identify SNP combinations with a maximal difference of allele frequencies between the case and control groups in breast cancer, i.e., the high/low risk combinations of SNPs. RESULTS: A total of 220 real case and 334 real control breast cancer data are used to test IBBFS and identify significant SNP combinations. We used the odds ratio (OR) as a quantitative measure to estimate the associated cancer risk of multiple SNP combinations to identify the complex biological relationships underlying the progression of breast cancer, i.e., the most likely SNP combinations. Experimental results show the estimated odds ratio of the best SNP combination with genotypes is significantly smaller than 1 (between 0.165 and 0.657) for specific SNP combinations of the tested SNPs in the low risk groups. In the high risk groups, predicted SNP combinations with genotypes are significantly greater than 1 (between 2.384 and 6.167) for specific SNP combinations of the tested SNPs. CONCLUSIONS: This study proposes an effective high-speed method to analyze SNP-SNP interactions in breast cancer association studies. A number of important SNPs are found to be significant for the high/low risk group. They can thus be considered a potential predictor for breast cancer association

Backtesting VaR in consideration of the higher moments of the distribution for minimum-variance hedging portfolios

a b s t r a c t a r t i c l e i n f o The higher moments of a distribution often lead to estimated value-at-risk (VaR) biases. This study&apos;s objective is to examine the backtesting of VaR models that consider the higher moments of the distribution for minimumvariance hedging portfolios (MVHPs) of the stock indices and futures in the Greater China Region for both short and long hedgers. The results reveal that the best backtesting VaR for the MVHP considered both the higher moments of the MVHP distribution and the asymmetry in volatility, cross-market asymmetry in volatility, and level effects in the covariance matrix of assets in the MVHP. These empirical results provide references for investors in risk management

SNP-RFLPing: restriction enzyme mining for SNPs in genomes

BACKGROUND: The restriction fragment length polymorphism (RFLP) is a common laboratory method for the genotyping of single nucleotide polymorphisms (SNPs). Here, we describe a web-based software, named SNP-RFLPing, which provides the restriction enzyme for RFLP assays on a batch of SNPs and genes from the human, rat, and mouse genomes. RESULTS: Three user-friendly inputs are included: 1) NCBI dbSNP "rs" or "ss" IDs; 2) NCBI Entrez gene ID and HUGO gene name; 3) any formats of SNP-in-sequence, are allowed to perform the SNP-RFLPing assay. These inputs are auto-programmed to SNP-containing sequences and their complementary sequences for the selection of restriction enzymes. All SNPs with available RFLP restriction enzymes of each input genes are provided even if many SNPs exist. The SNP-RFLPing analysis provides the SNP contig position, heterozygosity, function, protein residue, and amino acid position for cSNPs, as well as commercial and non-commercial restriction enzymes. CONCLUSION: This web-based software solves the input format problems in similar softwares and greatly simplifies the procedure for providing the RFLP enzyme. Mixed free forms of input data are friendly to users who perform the SNP-RFLPing assay. SNP-RFLPing offers a time-saving application for association studies in personalized medicine and is freely available at

Prevalence and molecular characterization of plasmidmediated beta-lactamase genes among nosocomial Staphylococcus aureus isolated in Taiwan

Purpose: To analyze the drug susceptibility phenotypes and the patterns of plasmid-mediated β- lactamase genes among nosocomial Staphylococcus aureus drug resistance isolates in Taiwan.Methods: The antibiotic susceptibilities of 617 clinical Staphylococcus aureus isolates collected from 2005 - 2009 from Chiayi Christian Hospital (Chiayi, Taiwan) were examined in vitro against 8 antimicrobial agents using agar diffusion method. Among the clinical isolates, 114 strains of methicillinsensitive Staphylococcus aureus and 45 strains of methicillin-resistant Staphylococcus aureus (MRSA) isolates were selected for plasmid profile analysis. The patterns of β-lactamase genes presented in plasmids were investigated by polymerase chain reaction analysis.Results: Most test strains were resistant to multiple antibiotics, particularly for the traditional agents such as ampicillin, penicillin, cephalexin and kanamycin. Plasmid profile analysis revealed that up to 36 % of the clinical strains harbored plasmids and were able to develop multi-drug resistant. Among them, most of the isolates harbored at least one plasmid (range 1 – 7) with a size range of 2.3 to 23 Kb. Among the several types of β-lactamases, blaTEM was the most prevalent.Conclusion: The results obtained from this study can serve as a valuable reference for the future control for clinical antibiotic resistant strains and more thorough discussions on resistance mechanisms.Keywords: Staphylococcus aureus, Antibiotic susceptibility, Nosocomial pathogens, Plasmid profile, β- lactamase