The Feynman-Wilson gas and the Lund model

We derive a partition function for the Lund fragmentation model and compare it with that of a classical gas. For a fixed rapidity ``volume'' this partition function corresponds to a multiplicity distribution which is very close to a binomial distribution. We compare our results with the multiplicity distributions obtained from the JETSET Monte Carlo for several scenarios. Firstly, for the fragmentation vertices of the Lund string. Secondly, for the final state particles both with and without decays.Comment: Latex, 21+1 pages, 11 figure

Is there screwiness at the end of the QCD cascades?

We discuss what happens at the end of the QCD cascades. We show that, with just a few reasonable assumptions, the emission of soft gluons is constrained to produce an ordered field in the form of a helix. We describe how to modify the Lund fragmentation scheme in order to fragment such a field. Our modified fragmentation scheme yields results which are consistent with current experimental measurements, but predicts at least one signature which should be observable.Comment: 21+1 page

Metabolomics of Ulva lactuca Linnaeus (Chlorophyta) exposed to oil fuels: Fourier transform infrared spectroscopy and multivariate analysis as tools for metabolic fingerprint

Fossil fuels, e.g. gasoline and diesel oil, account for substantial share of the pollution that affects marine ecosystems. Environmental metabolomics is an emerging field that may help unravel the effect of these xenobiotics on seaweeds and provide methodologies for biomonitoring coastal ecosystems. In the present study, FTIR and multivariate analysis were used to discriminate metabolic profiles of Ulva lactuca after in vitro exposure to diesel oil and gasoline, in combinations of concentrations (0.001%, 0.01%, 0.1%, and 1.0% - v/v) and times of exposure (30 min, 1 h, 12 h, and 24 h). PCA and HCA performed on entire mid-infrared spectral window were able to discriminate diesel oil-exposed thalli from the gasoline-exposed ones. HCA performed on spectral window related to the protein absorbance (17001500 cm 1) enabled the best discrimination between gasoline-exposed samples regarding the time of exposure, and between diesel oil-exposed samples according to the concentration. The results indicate that the combination of FTIR with multivariate analysis is a simple and efficient methodology for metabolic profiling with potential use for biomonitoring strategies.To Coordination for the Improvement of Higher Education Personnel (CAPES) for financial support. The research fellowships granted to Marcelo Maraschin (Proc. 307099/2015-6) and Fernanda Ramlov (Proc. 473408/2013-9) by National Council of Technological and Scientific Development (CNPq) are also acknowledged. This work was partially funded by CNPq and FCT agreement through the PropMine (Proc. 490383/2013-0) and PVE (Proc. 407323/2013-9, Dr. Miguel Rocha) grants

pcaGoPromoter - An R Package for Biological and Regulatory Interpretation of Principal Components in Genome-Wide Gene Expression Data

Analyzing data obtained from genome-wide gene expression experiments is challenging due to the quantity of variables, the need for multivariate analyses, and the demands of managing large amounts of data. Here we present the R package pcaGoPromoter, which facilitates the interpretation of genome-wide expression data and overcomes the aforementioned problems. In the first step, principal component analysis (PCA) is applied to survey any differences between experiments and possible groupings. The next step is the interpretation of the principal components with respect to both biological function and regulation by predicted transcription factor binding sites. The robustness of the results is evaluated using cross-validation, and illustrative plots of PCA scores and gene ontology terms are available. pcaGoPromoter works with any platform that uses gene symbols or Entrez IDs as probe identifiers. In addition, support for several popular Affymetrix GeneChip platforms is provided. To illustrate the features of the pcaGoPromoter package a serum stimulation experiment was performed and the genome-wide gene expression in the resulting samples was profiled using the Affymetrix Human Genome U133 Plus 2.0 chip. Array data were analyzed using pcaGoPromoter package tools, resulting in a clear separation of the experiments into three groups: controls, serum only and serum with inhibitor. Functional annotation of the axes in the PCA score plot showed the expected serum-promoted biological processes, e.g., cell cycle progression and the predicted involvement of expected transcription factors, including E2F. In addition, unexpected results, e.g., cholesterol synthesis in serum-depleted cells and NF-κB activation in inhibitor treated cells, were noted. In summary, the pcaGoPromoter R package provides a collection of tools for analyzing gene expression data. These tools give an overview of the input data via PCA, functional interpretation by gene ontology terms (biological processes), and an indication of the involvement of possible transcription factors

Prioritizing single-nucleotide variations that potentially regulate alternative splicing

Recent evidence suggests that many complex diseases are caused by genetic variations that play regulatory roles in controlling gene expression. Most genetic studies focus on nonsynonymous variations that can alter the amino acid composition of a protein and are therefore believed to have the highest impact on phenotype. Synonymous variations, however, can also play important roles in disease pathogenesis by regulating pre-mRNA processing and translational control. In this study, we systematically survey the effects of single-nucleotide variations (SNVs) on binding affinity of RNA-binding proteins (RBPs). Among the 10,113 synonymous SNVs identified in 697 individuals in the 1,000 Genomes Project and distributed by Genetic Analysis Workshop 17 (GAW17), we identified 182 variations located in alternatively spliced exons that can significantly change the binding affinity of nine RBPs whose binding preferences on 7-mer RNA sequences were previously reported. We found that the minor allele frequencies of these variations are similar to those of nonsynonymous SNVs, suggesting that they are in fact functional. We propose a workflow to identify phenotype-associated regulatory SNVs that might affect alternative splicing from exome-sequencing-derived genetic variations. Based on the affecting SNVs on the quantitative traits simulated in GAW17, we further identified two and four functional SNVs that are predicted to be involved in alternative splicing regulation in traits Q1 and Q2, respectively

Comparative Lipidomics of Azole Sensitive and Resistant Clinical Isolates of Candida albicans Reveals Unexpected Diversity in Molecular Lipid Imprints

Although transcriptome and proteome approaches have been applied to determine the regulatory circuitry behind multidrug resistance (MDR) in Candida, its lipidome remains poorly characterized. Lipids do acclimatize to the development of MDR in Candida, but exactly how the acclimatization is achieved is poorly understood. In the present study, we have used a high-throughput mass spectrometry-based shotgun approach and analyzed the lipidome of genetically matched clinical azole-sensitive (AS) and -resistant (AR) isolates of C. albicans. By comparing the lipid profiling of matched isolates, we have identified major classes of lipids and determined more than 200 individual molecular lipid species among these major classes. The lipidome analysis has been statistically validated by principal component analysis. Although each AR isolate was similar with regard to displaying a high MIC to drugs, they had a distinct lipid imprint. There were some significant commonalities in the lipid profiles of these pairs, including molecular lipid species ranging from monounsaturated to polyunsaturated fatty acid-containing phosphoglycerides. Consistent fluctuation in phosphatidyl serine, mannosylinositolphosphorylceramides, and sterol esters levels indicated their compensatory role in maintaining lipid homeostasis among most AR isolates. Notably, overexpression of either CaCdr1p or CaMdr1p efflux pump proteins led to a different lipidomic response among AR isolates. This study clearly establishes the versatility of lipid metabolism in handling azole stress among various matched AR isolates. This comprehensive lipidomic approach will serve as a resource for assessing strategies aimed at disrupting the functions of Candida lipids, particularly the functional interactions between lipids and MDR determinants

Landscape of somatic allelic imbalances and copy number alterations in HER2-amplified breast cancer

Introduction: Human epidermal growth factor receptor 2 (HER2)-amplified breast cancer represents a clinically well-defined subgroup due to availability of targeted treatment. However, HER2-amplified tumors have been shown to be heterogeneous at the genomic level by genome-wide microarray analyses, pointing towards a need of further investigations for identification of recurrent copy number alterations and delineation of patterns of allelic imbalance. Methods: High-density whole genome array-based comparative genomic hybridization (aCGH) and single nucleotide polymorphism (SNP) array data from 260 HER2-amplified breast tumors or cell lines, and 346 HER2-negative breast cancers with molecular subtype information were assembled from different repositories. Copy number alteration (CNA), loss-of-heterozygosity (LOH), copy number neutral allelic imbalance (CNN-AI), subclonal CNA and patterns of tumor DNA ploidy were analyzed using bioinformatical methods such as genomic identification of significant targets in cancer (GISTIC) and genome alteration print (GAP). The patterns of tumor ploidy were confirmed in 338 unrelated breast cancers analyzed by DNA flow cytometry with concurrent BAC aCGH and gene expression data. Results: A core set of 36 genomic regions commonly affected by copy number gain or loss was identified by integrating results with a previous study, together comprising > 400 HER2-amplified tumors. While CNN-AI frequency appeared evenly distributed over chromosomes in HER2-amplified tumors, not targeting specific regions and often < 20% in frequency, the occurrence of LOH was strongly associated with regions of copy number loss. HER2-amplified and HER2-negative tumors stratified by molecular subtypes displayed different patterns of LOH and CNN-AI, with basal-like tumors showing highest frequencies followed by HER2-amplified and luminal B cases. Tumor aneuploidy was strongly associated with increasing levels of LOH, CNN-AI, CNAs and occurrence of subclonal copy number events, irrespective of subtype. Finally, SNP data from individual tumors indicated that genomic amplification in general appears as monoallelic, that is, it preferentially targets one parental chromosome in HER2-amplified tumors. Conclusions: We have delineated the genomic landscape of CNAs, amplifications, LOH, and CNN-AI in HER2-amplified breast cancer, but also demonstrated a strong association between different types of genomic aberrations and tumor aneuploidy irrespective of molecular subtype