Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Red Blood Cell Fatty Acid Patterns and Acute Coronary Syndrome

BACKGROUND:Assessment of coronary heart disease (CHD) risk is typically based on a weighted combination of standard risk factors. We sought to determine the extent to which a lipidomic approach based on red blood cell fatty acid (RBC-FA) profiles could discriminate acute coronary syndrome (ACS) cases from controls, and to compare RBC-FA discrimination with that based on standard risk factors. METHODOLOGY/PRINCIPAL FINDINGS:RBC-FA profiles were measured in 668 ACS cases and 680 age-, race- and gender-matched controls. Multivariable logistic regression models based on FA profiles (FA) and standard risk factors (SRF) were developed on a random 2/3(rds) derivation set and validated on the remaining 1/3(rd). The area under receiver operating characteristic (ROC) curves (c-statistics), misclassification rates, and model calibrations were used to evaluate the individual and combined models. The FA discriminated cases from controls better than the SRF (c = 0.85 vs. 0.77, p = 0.003) and the FA profile added significantly to the standard model (c = 0.88 vs. 0.77, p<0.0001). Hosmer-Lemeshow calibration was poor for the FA model alone (p = 0.01), but acceptable for both the SRF (p = 0.30) and combined models (p = 0.22). Misclassification rates were 23%, 29% and 20% for FA, the SRF, and the combined models, respectively. CONCLUSIONS/SIGNIFICANCE:RBC-FA profiles contribute significantly to the discrimination of ACS cases, especially when combined with standard risk factors. The utility of FA patterns in risk prediction warrants further investigation

Variation in Herbivory-induced Volatiles Among Cucumber (Cucumis sativus L.) Varieties has Consequences for the Attraction of Carnivorous Natural Enemies

In response to herbivory by arthropods, plants emit herbivory-induced volatiles that attract carnivorous enemies of the inducing herbivores. Here, we compared the attractiveness of eight cucumber varieties (Cucumis sativus L.) to Phytoseiulus persimilis predatory mites after infestation of the plants with herbivorous spider mites (Tetranychus urticae) under greenhouse conditions. Attractiveness differed considerably, with the most attractive variety attracting twice as many predators as the least attractive variety. Chemical analysis of the volatiles released by the infested plants revealed significant differences among varieties, both in quantity and quality of the emitted blends. Comparison of the attractiveness of the varieties with the amounts of volatiles emitted indicated that the quality (composition) of the blend is more important for attraction than the amount of volatiles emitted. The amount of (E)-β-ocimene, (E,E)-TMTT, and two other, yet unidentified compounds correlated positively with the attraction of predatory mites. Quantities of four compounds negatively correlated with carnivore attraction, among them methyl salicylate, which is known to attract the predatory mite P. persimilis. The emission of methyl salicylate correlated with an unknown compound that had a negative correlation with carnivore attraction and hence could be masking the attractiveness of methyl salicylate. The results imply that the foraging success of natural enemies of pests can be enhanced by breeding for crop varieties that release specific volatiles

Adjuvant hyperthermic intraperitoneal chemotherapy (HIPEC) in patients with colon cancer at high risk of peritoneal carcinomatosis; the COLOPEC randomized multicentre trial

Background: The peritoneum is the second most common site of recurrence in colorectal cancer. Early detection of peritoneal carcinomatosis (PC) by imaging is difficult. Patients eventually presenting with clinically apparent PC have a poor prognosis. Median survival is only about five months if untreated and the benefit of palliative systemic chemotherapy is limited. Only a quarter of patients are eligible for curative treatment, consisting of cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CR/HIPEC). However, the effectiveness depends highly on the extent of disease and the treatment is associated with a considerable complication rate. These clinical problems underline the need for effective adjuvant therapy in high-risk patients to minimize the risk of outgrowth of peritoneal micro metastases. Adjuvant hyperthermic intraperitoneal chemotherapy (HIPEC) seems to be suitable for this purpose. Without the need for cytoreductive surgery, adjuvant HIPEC can be performed with a low complication rate and short hospital stay. Methods/Design: The aim of this study is to determine the effectiveness of adjuvant HIPEC in preventing the development of PC in patients with colon cancer at high risk of peritoneal recurrence. This study will be performed in the nine Dutch HIPEC centres, starting in April 2015. Eligible for inclusion are patients who underwent curative resection for T4 or intra-abdominally perforated cM0 stage colon cancer. After resection of the primary tumour, 176 patients will be randomized to adjuvant HIPEC followed by routine adjuvant systemic chemotherapy in the experimental arm, or to systemic chemotherapy only in the control arm. Adjuvant HIPEC will be performed simultaneously or shortly after the primary resection. Oxaliplatin will be used as chemotherapeutic agent, for 30 min at 42-43 degrees C. Just before HIPEC, 5-fluorouracil and leucovorin will be administered intravenously. Primary endpoint is peritoneal disease-free survival at 18 months. Diagnostic laparoscopy will be performed routinely after 18 months postoperatively in both arms of the study in patients without evidence of disease based on routine follow-up using CT imaging and CEA. Discussion: Adjuvant HIPEC is assumed to reduce the expected 25 % absolute risk of PC in patients with T4 or perforated colon cancer to a risk of 10 %. This reduction is likely to translate into a prolonged overall survival

Gene Coexpression Network Analysis as a Source of Functional Annotation for Rice Genes

With the existence of large publicly available plant gene expression data sets, many groups have undertaken data analyses to construct gene coexpression networks and functionally annotate genes. Often, a large compendium of unrelated or condition-independent expression data is used to construct gene networks. Condition-dependent expression experiments consisting of well-defined conditions/treatments have also been used to create coexpression networks to help examine particular biological processes. Gene networks derived from either condition-dependent or condition-independent data can be difficult to interpret if a large number of genes and connections are present. However, algorithms exist to identify modules of highly connected and biologically relevant genes within coexpression networks. In this study, we have used publicly available rice (Oryza sativa) gene expression data to create gene coexpression networks using both condition-dependent and condition-independent data and have identified gene modules within these networks using the Weighted Gene Coexpression Network Analysis method. We compared the number of genes assigned to modules and the biological interpretability of gene coexpression modules to assess the utility of condition-dependent and condition-independent gene coexpression networks. For the purpose of providing functional annotation to rice genes, we found that gene modules identified by coexpression analysis of condition-dependent gene expression experiments to be more useful than gene modules identified by analysis of a condition-independent data set. We have incorporated our results into the MSU Rice Genome Annotation Project database as additional expression-based annotation for 13,537 genes, 2,980 of which lack a functional annotation description. These results provide two new types of functional annotation for our database. Genes in modules are now associated with groups of genes that constitute a collective functional annotation of those modules. Additionally, the expression patterns of genes across the treatments/conditions of an expression experiment comprise a second form of useful annotation

Model SNP development for complex genomes based on hexaploid oat using high-throughput 454 sequencing technology

<p>Abstract</p> <p>Background</p> <p>Genetic markers are pivotal to modern genomics research; however, discovery and genotyping of molecular markers in oat has been hindered by the size and complexity of the genome, and by a scarcity of sequence data. The purpose of this study was to generate oat expressed sequence tag (EST) information, develop a bioinformatics pipeline for SNP discovery, and establish a method for rapid, cost-effective, and straightforward genotyping of SNP markers in complex polyploid genomes such as oat.</p> <p>Results</p> <p>Based on cDNA libraries of four cultivated oat genotypes, approximately 127,000 contigs were assembled from approximately one million Roche 454 sequence reads. Contigs were filtered through a novel bioinformatics pipeline to eliminate ambiguous polymorphism caused by subgenome homology, and 96 <it>in silico </it>SNPs were selected from 9,448 candidate loci for validation using high-resolution melting (HRM) analysis. Of these, 52 (54%) were polymorphic between parents of the Ogle1040 × TAM O-301 (OT) mapping population, with 48 segregating as single Mendelian loci, and 44 being placed on the existing OT linkage map. Ogle and TAM amplicons from 12 primers were sequenced for SNP validation, revealing complex polymorphism in seven amplicons but general sequence conservation within SNP loci. Whole-amplicon interrogation with HRM revealed insertions, deletions, and heterozygotes in secondary oat germplasm pools, generating multiple alleles at some primer targets. To validate marker utility, 36 SNP assays were used to evaluate the genetic diversity of 34 diverse oat genotypes. Dendrogram clusters corresponded generally to known genome composition and genetic ancestry.</p> <p>Conclusions</p> <p>The high-throughput SNP discovery pipeline presented here is a rapid and effective method for identification of polymorphic SNP alleles in the oat genome. The current-generation HRM system is a simple and highly-informative platform for SNP genotyping. These techniques provide a model for SNP discovery and genotyping in other species with complex and poorly-characterized genomes.</p

Selection of Bone Metastasis Seeds by Mesenchymal Signals in the Primary Tumor Stroma

How organ-specific metastatic traits arise in primary tumors remains unknown. Here, we show a role of the breast tumor stroma in selecting cancer cells that are primed for metastasis in bone. Cancer-associated fibroblasts (CAFs) in triple-negative (TN) breast tumors skew heterogeneous cancer cell populations toward a predominance of clones that thrive on the CAF-derived factors CXCL12 and IGF1. Limiting concentrations of these factors select for cancer cells with high Src activity, a known clinical predictor of bone relapse and an enhancer of PI3K-Akt pathway activation by CXCL12 and IGF1. Carcinoma clones selected in this manner are primed for metastasis in the CXCL12-rich microenvironment of the bone marrow. The evidence suggests that stromal signals resembling those of a distant organ select for cancer cells that are primed for metastasis in that organ, thus illuminating the evolution of metastatic traits in a primary tumor and its distant metastases