One-Loop Calculation of the Oblique S Parameter in Higgsless Electroweak Models

We present a one-loop calculation of the oblique S parameter within Higgsless models of electroweak symmetry breaking and analyze the phenomenological implications of the available electroweak precision data. We use the most general effective Lagrangian with at most two derivatives, implementing the chiral symmetry breaking SU(2)_L x SU(2)_R -> SU(2)_{L+R} with Goldstones, gauge bosons and one multiplet of vector and axial-vector massive resonance states. Using the dispersive representation of Peskin and Takeuchi and imposing the short-distance constraints dictated by the operator product expansion, we obtain S at the NLO in terms of a few resonance parameters. In asymptotically-free gauge theories, the final result only depends on the vector-resonance mass and requires M_V > 1.8 TeV (3.8 TeV) to satisfy the experimental limits at the 3 \sigma (1\sigma) level; the axial state is always heavier, we obtain M_A > 2.5 TeV (6.6 TeV) at 3\sigma (1\sigma). In strongly-coupled models, such as walking or conformal technicolour, where the second Weinberg sum rule does not apply, the vector and axial couplings are not determined by the short-distance constraints; but one can still derive a lower bound on S, provided the hierarchy M_V < M_A remains valid. Even in this less constrained situation, we find that in order to satisfy the experimental limits at 3\sigma one needs M_{V,A} > 1.8 TeV.Comment: 34 pages, 9 figures. Version published in JHEP. Some references and sentences have been added to facilitate the discussio

The Role of Quantitative Pharmacology in an Academic Translational Research Environment

Translational research is generally described as the application of basic science discoveries to the treatment or prevention of disease or injury. Its value is usually determined based on the likelihood that exploratory or developmental research can yield effective therapies. While the pharmaceutical industry has evolved into a highly specialized sector engaged in translational research, the academic medical research community has similarly embraced this paradigm largely through the motivation of the National Institute of Health (NIH) via its Roadmap initiative. The Clinical and Translational Science Award (CTSA) has created opportunities for institutions which can provide the multidisciplinary environment required to engage such research. A key component of the CTSA and an element of both the NIH Roadmap and the FDA Critical Path is the bridging of bench and bedside science via quantitative pharmacologic relationships. The infrastructure of the University of Pennsylvania/Children’s Hospital of Philadelphia CTSA is highlighted relative to both research and educational objectives reliant upon quantitative pharmacology. A case study, NIH-sponsored research program exploring NK1r antagonism for the treatment NeuroAIDS is used to illustrate the application of quantitative pharmacology in a translational research paradigm

Aurora kinase A drives the evolution of resistance to third-generation EGFR inhibitors in lung cancer.

Although targeted therapies often elicit profound initial patient responses, these effects are transient due to residual disease leading to acquired resistance. How tumors transition between drug responsiveness, tolerance and resistance, especially in the absence of preexisting subclones, remains unclear. In epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma cells, we demonstrate that residual disease and acquired resistance in response to EGFR inhibitors requires Aurora kinase A (AURKA) activity. Nongenetic resistance through the activation of AURKA by its coactivator TPX2 emerges in response to chronic EGFR inhibition where it mitigates drug-induced apoptosis. Aurora kinase inhibitors suppress this adaptive survival program, increasing the magnitude and duration of EGFR inhibitor response in preclinical models. Treatment-induced activation of AURKA is associated with resistance to EGFR inhibitors in vitro, in vivo and in most individuals with EGFR-mutant lung adenocarcinoma. These findings delineate a molecular path whereby drug resistance emerges from drug-tolerant cells and unveils a synthetic lethal strategy for enhancing responses to EGFR inhibitors by suppressing AURKA-driven residual disease and acquired resistance

Couplings of light I=0 scalar mesons to simple operators in the complex plane

The flavour and glue structure of the light scalar mesons in QCD are probed by studying the couplings of the I=0 mesons $\sigma(600)$ and $f_0(980)$ to the operators $\bar{q}q$, $\alpha_s G^2$ and to two photons. The Roy dispersive representation for the $\pi\pi$ amplitude $t_0^0(s)$ is used to determine the pole positions as well as the residues in the complex plane. On the real axis, $t_0^0$ is constrained to solve the Roy equation together with elastic unitarity up to the K\Kbar threshold leading to an improved description of the $f_0(980)$. The problem of using a two-particle threshold as a matching point is discussed. A simple relation is established between the coupling of a scalar meson to an operator $j_S$ and the value of the related pion form-factor computed at the resonance pole. Pion scalar form-factors as well as two-photon partial-wave amplitudes are expressed as coupled-channel Omn\`es dispersive representations. Subtraction constants are constrained by chiral symmetry and experimental data. Comparison of our results for the $\bar{q}q$ couplings with earlier determinations of the analogous couplings of the lightest I=1 and $I=1/2$ scalar mesons are compatible with an assignment of the $\sigma$, $\kappa$, $a_0(980)$, $f_0(980)$ into a nonet. Concerning the gluonic operator $\alpha_s G^2$ we find a significant coupling to both the $\sigma$ and the $f_0(980)$.Comment: 31 pages, 5 figure

Excision Repair Cross-Complementation Group 1 (ERCC1) Status and Lung Cancer Outcomes: A Meta-Analysis of Published Studies and Recommendations

Despite discrepant results on clinical utility, several trials are already prospectively randomizing non-small cell lung cancer (NSCLC) patients by ERCC1 status. We aimed to characterize the prognostic and predictive effect of ERCC1 by systematic review and meta-analysis.Eligible studies assessed survival and/or chemotherapy response in NSCLC or SCLC by ERCC1 status. Effect measures of interest were hazard ratio (HR) for survival or relative risk (RR) for chemotherapy response. Random-effects meta-analyses were used to account for between-study heterogeneity, with unadjusted/adjusted effect estimates considered separately.23 eligible studies provided survival results in 2,726 patients. Substantial heterogeneity was observed in all meta-analyses (I(2) always >30%), partly due to variability in thresholds defining 'low' and 'high' ERCC1. Meta-analysis of unadjusted estimates showed high ERCC1 was associated with significantly worse overall survival in platinum-treated NSCLC (average unadjusted HR = 1.61, 95%CI:1.23-2.1, p = 0.014), but not in NSCLC untreated with chemotherapy (average unadjusted HR = 0.82, 95%CI:0.51-1.31). Meta-analysis of adjusted estimates was limited by variable choice of adjustment factors and potential publication bias (Egger's p<0.0001). There was evidence that high ERCC1 was associated with reduced response to platinum (average RR = 0.80; 95%CI:0.64-0.99). SCLC data were inadequate to draw firm conclusions.Current evidence suggests high ERCC1 may adversely influence survival and response in platinum-treated NSCLC patients, but not in non-platinum treated, although definitive evidence of a predictive influence is lacking. International consensus is urgently required to provide consistent, validated ERCC1 assessment methodology. ERCC1 assessment for treatment selection should currently be restricted to, and evaluated within, clinical trials

Generation of a non-small cell lung cancer transcriptome microarray

<p>Abstract</p> <p>Background</p> <p>Non-small cell lung cancer (NSCLC) is the leading cause of cancer mortality worldwide. At present no reliable biomarkers are available to guide the management of this condition. Microarray technology may allow appropriate biomarkers to be identified but present platforms are lacking disease focus and are thus likely to miss potentially vital information contained in patient tissue samples.</p> <p>Methods</p> <p>A combination of large-scale in-house sequencing, gene expression profiling and public sequence and gene expression data mining were used to characterise the transcriptome of NSCLC and the data used to generate a disease-focused microarray – the Lung Cancer DSA research tool.</p> <p>Results</p> <p>Built on the Affymetrix GeneChip platform, the Lung Cancer DSA research tool allows for interrogation of ~60,000 transcripts relevant to Lung Cancer, tens of thousands of which are unavailable on leading commercial microarrays.</p> <p>Conclusion</p> <p>We have developed the first high-density disease specific transcriptome microarray. We present the array design process and the results of experiments carried out to demonstrate the array's utility. This approach serves as a template for the development of other disease transcriptome microarrays, including non-neoplastic diseases.</p

Structural Maintenance of Chromosomes (SMC) Proteins Promote Homolog-Independent Recombination Repair in Meiosis Crucial for Germ Cell Genomic Stability

In meiosis, programmed DNA breaks repaired by homologous recombination (HR) can be processed into inter-homolog crossovers that promote the accurate segregation of chromosomes. In general, more programmed DNA double-strand breaks (DSBs) are formed than the number of inter-homolog crossovers, and the excess DSBs must be repaired to maintain genomic stability. Sister-chromatid (inter-sister) recombination is postulated to be important for the completion of meiotic DSB repair. However, this hypothesis is difficult to test because of limited experimental means to disrupt inter-sister and not inter-homolog HR in meiosis. We find that the conserved Structural Maintenance of Chromosomes (SMC) 5 and 6 proteins in Caenorhabditis elegans are required for the successful completion of meiotic homologous recombination repair, yet they appeared to be dispensable for accurate chromosome segregation in meiosis. Mutations in the smc-5 and smc-6 genes induced chromosome fragments and dismorphology. Chromosome fragments associated with HR defects have only been reported in mutants, which have disrupted inter-homolog crossover. Surprisingly, the smc-5 and smc-6 mutations did not disrupt the formation of chiasmata, the cytologically visible linkages between homologous chromosomes formed from meiotic inter-homolog crossovers. The mutant fragmentation defect appeared to be preferentially enhanced by the disruptions of inter-homolog recombination but not by the disruptions of inter-sister recombination. Based on these findings, we propose that the C. elegans SMC-5/6 proteins are required in meiosis for the processing of homolog-independent, presumably sister-chromatid-mediated, recombination repair. Together, these results demonstrate that the successful completion of homolog-independent recombination is crucial for germ cell genomic stability

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives