Modeling Susceptibility versus Resistance in Allergic Airway Disease Reveals Regulation by Tec Kinase Itk

Murine models of allergic asthma have been used to understand the mechanisms of development and pathology in this disease. In addition, knockout mice have contributed significantly to our understanding of the roles of specific molecules and cytokines in these models. However, results can vary significantly depending on the mouse strain used in the model, and in particularly in understanding the effect of specific knockouts. For example, it can be equivocal as to whether specific gene knockouts affect the susceptibility of the mice to developing the disease, or lead to resistance. Here we used a house dust mite model of allergic airway inflammation to examine the response of two strains of mice (C57BL/6 and BALB/c) which differ in their responses in allergic airway inflammation. We demonstrate an algorithm that can facilitate the understanding of the behavior of these models with regards to susceptibility (to allergic airway inflammation) (Saai) or resistance (Raai) in this model. We verify that both C57BL/6 and BALB/c develop disease, but BALB/c mice have higher Saai for development. We then use this approach to show that the absence of the Tec family kinase Itk, which regulates the production of Th2 cytokines, leads to Raai in the C57BL/6 background, but decreases Saai on the BALB/c background. We suggest that the use of such approaches could clarify the behavior of various knockout mice in modeling allergic asthma

D3-instantons, Mock Theta Series and Twistors

The D-instanton corrected hypermultiplet moduli space of type II string theory compactified on a Calabi-Yau threefold is known in the type IIA picture to be determined in terms of the generalized Donaldson-Thomas invariants, through a twistorial construction. At the same time, in the mirror type IIB picture, and in the limit where only D3-D1-D(-1)-instanton corrections are retained, it should carry an isometric action of the S-duality group SL(2,Z). We prove that this is the case in the one-instanton approximation, by constructing a holomorphic action of SL(2,Z) on the linearized twistor space. Using the modular invariance of the D4-D2-D0 black hole partition function, we show that the standard Darboux coordinates in twistor space have modular anomalies controlled by period integrals of a Siegel-Narain theta series, which can be canceled by a contact transformation generated by a holomorphic mock theta series.Comment: 42 pages; discussion of isometries is amended; misprints correcte

Does vascular endothelial growth factor (VEGF) predict local relapse and survival in radiotherapy-treated node-negative breast cancer?

The aim of this study was to determine the association of vascular endothelial growth factor (VEGF) content in 302 consecutive node-negative breast cancer (NNBC) patients treated with only locoregional radiotherapy to relapse free- (RFS) and overall survival (OS). VEGF content in tumour cytosols was measured by an enzymatic immunoassay for the major isoform VEGF165. The median age was 56 years, the median follow-up time 56 months. A wide range (0.01–144.79 pg μg−1 DNA) of VEGF content was found (median 1.92). Significant associations were found between VEGF and oestrogen receptor (ER) content, progesterone receptor (PR) and tumour size (P = 0.005). Univariate analysis displayed significant reduced RFS and OS for patients with higher VEGF content (P = 0.0113 and P = 0.0075 respectively). A total of 43 recurrences have been found (ten local relapses within the breast, five in the axillary or supraclavicular lymph nodes and 28 distant metastasis). There was no significant correlation between the localization of the relapse and the VEGF content. Multivariate analysis suggested VEGF as the only predictor of OS (relative risk (RR) = 3.6, 95% confidence interval (CI) = 0.97–13.37), and in patients with T1 tumours (n = 236) the multivariate analysis clearly displayed VEGF as the only independent predictor of both RFS and OS (RR = 5.1, CI = 1.07–24.59). In the sub-group with ER-positive tumours (n = 229), multivariate analysis showed VEGF as the only significant predictor of RFS and OS (RR = 10.44, CI = 1.26–86.38). The results suggest VEGF165 as a predictor of RFS and OS in NNBC patients treated with locoregional radiotherapy, comprising especially patients with favourable prognosis of T1 tumours, or ER-positive tumours. The high VEGF expression might define a radioresistant phenotype, or indicate an early distant spread which might require adjuvant systemic treatment. © 1999 Cancer Research Campaig

Circulating Angiopoietins-1 and -2, Angiopoietin Receptor Tie-2 and Vascular Endothelial Growth Factor-A as Biomarkers of Acute Myocardial Infarction: a Prospective Nested Case-Control Study

<p>Abstract</p> <p>Background</p> <p>Angiogenesis is up-regulated in myocardial ischemia. However, limited data exist assessing the value of circulating angiogenic biomarkers in predicting future incidence of acute myocardial infarction (AMI). Our aim was to examine the association between circulating levels of markers of angiogenesis with risk of incident acute myocardial infarction (AMI) in men and women.</p> <p>Methods</p> <p>We performed a case-control study (nested within a large cohort of persons receiving care within Kaiser Permanente of Northern California) including 695 AMI cases and 690 controls individually matched on age, gender and race/ethnicity.</p> <p>Results</p> <p>Median [inter-quartile range] serum concentrations of vascular endothelial growth factor-A (VEGF-A; 260 [252] vs. 235 [224] pg/mL; p = 0.01) and angiopoietin-2 (Ang-2; 1.18 [0.66] vs. 1.05 [0.58] ng/mL; p < 0.0001) were significantly higher in AMI cases than in controls. By contrast, endothelium-specific receptor tyrosine kinase (Tie-2; 14.2 [3.7] vs. 14.0 [3.1] ng/mL; p = 0.07) and angiopoietin-1 levels (Ang-1; 33.1 [13.6] vs. 32.5 [12.7] ng/mL; p = 0.52) did not differ significantly by case-control status. After adjustment for educational attainment, hypertension, diabetes, smoking, alcohol consumption, body mass index, LDL-C, HDL-C, triglycerides and C-reactive protein, each increment of 1 unit of Ang-2 as a Z score was associated with 1.17-fold (95 percent confidence interval, 1.02 to 1.35) increased odds of AMI, and the upper quartile of Ang-2, relative to the lowest quartile, was associated with 1.63-fold (95 percent confidence interval, 1.09 to 2.45) increased odds of AMI.</p> <p>Conclusions</p> <p>Our data support a role of Ang-2 as a biomarker of incident AMI independent of traditional risk factors.</p

Search for the neutral Higgs bosons of the minimal supersymmetric standard model in pp collisions at root s=7 TeV with the ATLAS detector

A search for neutral Higgs bosons of the Minimal Supersymmetric Standard Model (MSSM) is reported. The analysis is based on a sample of proton-proton collisions at a centre-of-mass energy of 7TeV recorded with the ATLAS detector at the Large Hadron Collider. The data were recorded in 2011 and correspond to an integrated luminosity of 4.7 fb-1 to 4.8 fb-1. Higgs boson decays into oppositely-charged muon or τ lepton pairs are considered for final states requiring either the presence or absence of b-jets. No statistically significant excess over the expected background is observed and exclusion limits at the 95% confidence level are derived. The exclusion limits are for the production cross-section of a generic neutral Higgs boson, φ, as a function of the Higgs boson mass and for h/A/H production in the MSSM as a function of the parameters mA and tan β in the mhmax scenario for mA in the range of 90GeV to 500 GeV. Copyright CERN

Prediction of Glioblastoma Multiform Response to Bevacizumab Treatment Using Multi-Parametric MRI

Glioblastoma multiform (GBM) is a highly malignant brain tumor. Bevacizumab is a recent therapy for stopping tumor growth and even shrinking tumor through inhibition of vascular development (angiogenesis). This paper presents a non-invasive approach based on image analysis of multi-parametric magnetic resonance images (MRI) to predict response of GBM to this treatment. The resulting prediction system has potential to be used by physicians to optimize treatment plans of the GBM patients. The proposed method applies signal decomposition and histogram analysis methods to extract statistical features from Gd-enhanced regions of tumor that quantify its microstructural characteristics. MRI studies of 12 patients at multiple time points before and up to four months after treatment are used in this work. Changes in the Gd-enhancement as well as necrosis and edema after treatment are used to evaluate the response. Leave-one-out cross validation method is applied to evaluate prediction quality of the models. Predictive models developed in this work have large regression coefficients (maximum R2 = 0.95) indicating their capability to predict response to therapy