Overexpression and altered glycosylation of MUC1 in malignant mesothelioma

Current interest in the MUC1/EMA mucin relates to its role in malignancy, and its potential as a therapeutic target. MUC1/EMA expression has been observed in the majority of epithelioid mesotheliomas. However, little is known of the characteristics of MUC1/EMA in mesothelioma. Herein, we studied the cell surface and soluble expression of the MUC1/EMA glycoprotein, and determined the mRNA and genomic expression profiles in mesothelioma. We found that the anti-MUC1 antibody, E29, was the most diagnostically useful of seven antibody clones examined with a sensitivity of 84% (16 out of 19 cases) and no false positive results. MUC1 mRNA expression was significantly higher in mesothelioma samples than in benign mesothelial cells. No amplification of the MUC1 gene was observed by FISH. Seven of 9 mesothelioma samples expressed MUC1-secreted mRNA isoform in addition to the archetypal MUC1/transmembrane form. CA15.3 (soluble MUC1) levels were significantly higher in the serum of mesothelioma patients than in healthy controls but were not significantly different to levels in patients with benign asbestos-related disease. CA15-3 in effusions could differentiate malignant from benign effusions but were not specific for mesothelioma. Thus, as in other cancers, alterations in MUC1 biology occur in mesothelioma and these results suggest that specific MUC1 characteristics may be useful for mesothelioma diagnosis and should also be investigated as a potential therapeutic target

The APOA5 Trp19 allele is associated with metabolic syndrome via its association with plasma triglycerides

<p>Abstract</p> <p>Background</p> <p>The goal of the present study was to assess the effect of genetic variability at the APOA5/A4/C3/A1 cluster locus on the risk of metabolic syndrome.</p> <p>Methods</p> <p>The <it>APOA5 </it>Ser19Trp, <it>APOA5 </it>-12,238T>C, <it>APOA4 </it>Thr347Ser, <it>APOC3 </it>-482C>T and <it>APOC3 </it>3238C>G (<it>Sst</it>I) polymorphisms were analyzed in a representative population sample of 3138 men and women from France, including 932 individuals with metabolic syndrome and 2206 without metabolic syndrome, as defined by the NCEP criteria.</p> <p>Results</p> <p>Compared with homozygotes for the common allele, the odds ratio (OR) [95% CI] for metabolic syndrome was 1.30 [1.03–1.66] (<it>p </it>= 0.03) for <it>APOA5 </it>Trp19 carriers, 0.81 [0.69–0.95] (<it>p </it>= 0.01) for <it>APOA5 </it>-12,238C carriers and 0.84 [0.70–0.99] (<it>p </it>= 0.04) for <it>APOA4 </it>Ser347 carriers. Adjustment for plasma triglycerides, (but not for waist girth, HDL, blood pressure or glycemia – the other components of metabolic syndrome) abolished these associations and suggests that triglyceride levels explain the association with metabolic syndrome. There was no association between the <it>APOC3 </it>-482C>T or <it>APOC3 </it>3238C>G polymorphisms and metabolic syndrome. The decreased risk of metabolic syndrome observed in <it>APOA5 </it>-12,238C and <it>APOA4 </it>Ser347 carriers merely reflected the fact that the <it>APOA5 </it>Trp19 allele was in negative linkage disequilibrium with the common alleles of <it>APOA5 </it>-12,238T>C and <it>APOA4 </it>Thr347Ser polymorphisms.</p> <p>Conclusion</p> <p>The <it>APOA5 </it>Trp19 allele increased susceptibility to metabolic syndrome via its impact on plasma triglyceride levels.</p

Measurement of the cross-section of high transverse momentum vector bosons reconstructed as single jets and studies of jet substructure in pp collisions at √s = 7 TeV with the ATLAS detector

This paper presents a measurement of the cross-section for high transverse momentum W and Z bosons produced in pp collisions and decaying to all-hadronic final states. The data used in the analysis were recorded by the ATLAS detector at the CERN Large Hadron Collider at a centre-of-mass energy of √s = 7 TeV;{\rm Te}{\rm V}$and correspond to an integrated luminosity of$4.6\;{\rm f}{{{\rm b}}^{-1}}$. The measurement is performed by reconstructing the boosted W or Z bosons in single jets. The reconstructed jet mass is used to identify the W and Z bosons, and a jet substructure method based on energy cluster information in the jet centre-of-mass frame is used to suppress the large multi-jet background. The cross-section for events with a hadronically decaying W or Z boson, with transverse momentum${{p}_{{\rm T}}}\gt 320\;{\rm Ge}{\rm V}$and pseudorapidity$|\eta |\lt 1.9$, is measured to be${{\sigma }_{W+Z}}=8.5\pm 1.7$ pb and is compared to next-to-leading-order calculations. The selected events are further used to study jet grooming techniques

Search for direct pair production of the top squark in all-hadronic final states in proton-proton collisions at s√=8 TeV with the ATLAS detector

The results of a search for direct pair production of the scalar partner to the top quark using an integrated luminosity of 20.1fb−1 of proton–proton collision data at √s = 8 TeV recorded with the ATLAS detector at the LHC are reported. The top squark is assumed to decay via t˜→tχ˜01 or t˜→ bχ˜±1 →bW(∗)χ˜01 , where χ˜01 (χ˜±1 ) denotes the lightest neutralino (chargino) in supersymmetric models. The search targets a fully-hadronic final state in events with four or more jets and large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits are reported in terms of the top squark and neutralino masses and as a function of the branching fraction of t˜ → tχ˜01 . For a branching fraction of 100%, top squark masses in the range 270–645 GeV are excluded for χ˜01 masses below 30 GeV. For a branching fraction of 50% to either t˜ → tχ˜01 or t˜ → bχ˜±1 , and assuming the χ˜±1 mass to be twice the χ˜01 mass, top squark masses in the range 250–550 GeV are excluded for χ˜01 masses below 60 GeV

Search for pair-produced long-lived neutral particles decaying to jets in the ATLAS hadronic calorimeter in ppcollisions at √s=8TeV

The ATLAS detector at the Large Hadron Collider at CERN is used to search for the decay of a scalar boson to a pair of long-lived particles, neutral under the Standard Model gauge group, in 20.3fb−1of data collected in proton–proton collisions at √s=8TeV. This search is sensitive to long-lived particles that decay to Standard Model particles producing jets at the outer edge of the ATLAS electromagnetic calorimeter or inside the hadronic calorimeter. No significant excess of events is observed. Limits are reported on the product of the scalar boson production cross section times branching ratio into long-lived neutral particles as a function of the proper lifetime of the particles. Limits are reported for boson masses from 100 GeVto 900 GeV, and a long-lived neutral particle mass from 10 GeVto 150 GeV

Exploring Cell Tropism as a Possible Contributor to Influenza Infection Severity

Several mechanisms have been proposed to account for the marked increase in severity of human infections with avian compared to human influenza strains, including increased cytokine expression, poor immune response, and differences in target cell receptor affinity. Here, the potential effect of target cell tropism on disease severity is studied using a mathematical model for in-host influenza viral infection in a cell population consisting of two different cell types. The two cell types differ only in their susceptibility to infection and rate of virus production. We show the existence of a parameter regime which is characterized by high viral loads sustained long after the onset of infection. This finding suggests that differences in cell tropism between influenza strains could be sufficient to cause significant differences in viral titer profiles, similar to those observed in infections with certain strains of influenza A virus. The two target cell mathematical model offers good agreement with experimental data from severe influenza infections, as does the usual, single target cell model albeit with biologically unrealistic parameters. Both models predict that while neuraminidase inhibitors and adamantanes are only effective when administered early to treat an uncomplicated seasonal infection, they can be effective against more severe influenza infections even when administered late

Computational Models of HIV-1 Resistance to Gene Therapy Elucidate Therapy Design Principles

Gene therapy is an emerging alternative to conventional anti-HIV-1 drugs, and can potentially control the virus while alleviating major limitations of current approaches. Yet, HIV-1's ability to rapidly acquire mutations and escape therapy presents a critical challenge to any novel treatment paradigm. Viral escape is thus a key consideration in the design of any gene-based technique. We develop a computational model of HIV's evolutionary dynamics in vivo in the presence of a genetic therapy to explore the impact of therapy parameters and strategies on the development of resistance. Our model is generic and captures the properties of a broad class of gene-based agents that inhibit early stages of the viral life cycle. We highlight the differences in viral resistance dynamics between gene and standard antiretroviral therapies, and identify key factors that impact long-term viral suppression. In particular, we underscore the importance of mutationally-induced viral fitness losses in cells that are not genetically modified, as these can severely constrain the replication of resistant virus. We also propose and investigate a novel treatment strategy that leverages upon gene therapy's unique capacity to deliver different genes to distinct cell populations, and we find that such a strategy can dramatically improve efficacy when used judiciously within a certain parametric regime. Finally, we revisit a previously-suggested idea of improving clinical outcomes by boosting the proliferation of the genetically-modified cells, but we find that such an approach has mixed effects on resistance dynamics. Our results provide insights into the short- and long-term effects of gene therapy and the role of its key properties in the evolution of resistance, which can serve as guidelines for the choice and optimization of effective therapeutic agents

Effect of Acinetobacter sp on Metalaxyl Degradation and Metabolite Profile of Potato Seedlings (Solanum tuberosum L.) Alpha Variety

One of the most serious diseases in potato cultivars is caused by the pathogen Phytophthora infestans, which affects leaves, stems and tubers. Metalaxyl is a fungicide that protects potato plants from Phytophthora infestans. In Mexico, farmers apply metalaxyl 35 times during the cycle of potato production and the last application is typically 15 days before harvest. There are no records related to the presence of metalaxyl in potato tubers in Mexico. In the present study, we evaluated the effect of Acinetobacter sp on metalaxyl degradation in potato seedlings. The effect of bacteria and metalaxyl on the growth of potato seedlings was also evaluated. A metabolite profile analysis was conducted to determine potential molecular biomarkers produced by potato seedlings in the presence of Acinetobacter sp and metalaxyl. Metalaxyl did not affect the growth of potato seedlings. However, Acinetobacter sp strongly affected the growth of inoculated seedlings, as confirmed by plant length and plant fresh weights which were lower in inoculated potato seedlings (40% and 27%, respectively) compared to the controls. Acinetobacter sp also affected root formation. Inoculated potato seedlings showed a decrease in root formation compared to the controls. LC-MS/MS analysis of metalaxyl residues in potato seedlings suggests that Acinetobacter sp did not degrade metalaxyl. GC–TOF–MS platform was used in metabolic profiling studies. Statistical data analysis and metabolic pathway analysis allowed suggesting the alteration of metabolic pathways by both Acinetobacter sp infection and metalaxyl treatment. Several hundred metabolites were detected, 137 metabolites were identified and 15 metabolic markers were suggested based on statistical change significance found with PLS-DA analysis. These results are important for better understanding the interactions of putative endophytic bacteria and pesticides on plants and their possible effects on plant metabolism

Optimization in computational systems biology

Optimization aims to make a system or design as effective or functional as possible. Mathematical optimization methods are widely used in engineering, economics and science. This commentary is focused on applications of mathematical optimization in computational systems biology. Examples are given where optimization methods are used for topics ranging from model building and optimal experimental design to metabolic engineering and synthetic biology. Finally, several perspectives for future research are outlined