HERBVI - a program for simulation of baryon- and lepton- number violating processes

We describe a Monte Carlo event generator for the simulation of baryon- and lepton-number violating processes at supercolliders. The package, {\HERBVI}, is designed as a hard-process generator interfacing to the general hadronic event simulation program {\HW}. In view of the very high multiplicity of gauge bosons expected in such processes, particular attention is paid to the efficient generation of multiparticle phase space. The program also takes account of the expected colour structure of baryon-number violating vertices, which has important implications for the hadronization of the final state.Comment: 19 pages, standard LaTeX, no figure

Multiplierz: An Extensible API Based Desktop Environment for Proteomics Data Analysis

BACKGROUND. Efficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources. Moreover, proteomics technologies and experimental methods are not yet standardized; hence a high degree of flexibility is necessary for efficient support of high- and low-throughput data analytic tasks. Development of a desktop environment that is sufficiently robust for deployment in data analytic pipelines, and simultaneously supports customization for programmers and non-programmers alike, has proven to be a significant challenge. RESULTS. We describe multiplierz, a flexible and open-source desktop environment for comprehensive proteomics data analysis. We use this framework to expose a prototype version of our recently proposed common API (mzAPI) designed for direct access to proprietary mass spectrometry files. In addition to routine data analytic tasks, multiplierz supports generation of information rich, portable spreadsheet-based reports. Moreover, multiplierz is designed around a "zero infrastructure" philosophy, meaning that it can be deployed by end users with little or no system administration support. Finally, access to multiplierz functionality is provided via high-level Python scripts, resulting in a fully extensible data analytic environment for rapid development of custom algorithms and deployment of high-throughput data pipelines. CONCLUSION. Collectively, mzAPI and multiplierz facilitate a wide range of data analysis tasks, spanning technology development to biological annotation, for mass spectrometry-based proteomics research.Dana-Farber Cancer Institute; National Human Genome Research Institute (P50HG004233); National Science Foundation Integrative Graduate Education and Research Traineeship grant (DGE-0654108

The Brighton declaration: the value of non-communicable disease modelling in population health sciences.

The Brighton declaration arose out of a one day workshop held in Brighton in September 2013 as part of the Society for Social Medicine annual conference. The workshop convened UK based non-communicable disease modellers to discuss the challenges and opportunities for non-communicable disease modelling in the UK. The declaration describes the value and importance of non-communicable disease modelling, both for research and for informing health policy. The declaration also describes challenges and issues for non-communicable disease modelling. The declaration has been endorsed by many non-communicable disease modellers in the UK.The following academics collaborated with the authors to finalise this article are and acknowledged as co-signatories on its content. The authors are extremely grateful for their input. University of Cambridge: Ali Abbas, Marko Tanio; University of Edinburgh: Dr Susannah McLean; UK Health Forum: Martin Brown, Tim Marsh, Marco Mesa-Frias, Lise Retat; Imperial College London: Anthony Laverty; The London School of Hygiene and Tropical Medicine: Zaid Chalabi; University College London: Luz Sanchez Romero; University of Oxford: Anja Mizdrak, Mike Rayner, Marco Springmann; University of Sheffield: Alan Brennan, James Chilcott, John Holmes, Petra Meier, John Mooney; University of Southampton: Grant Aitken. ADMB and OTM are funded by the Wellcome Trust. PS is funded by the British Heart Foundation. JW is funded by an MRC Population Health Scientist Fellowship.This is the final published version. The article was originally published in the European Journal of Epidemiology (2014) 29, 867–870, DOI 10.1007/s10654-014-9978-0

multiplierz: An Extensible API Based Desktop Environment for Proteomics Data Analysis

Background: Efficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources. Moreover, proteomics technologies and experimental methods are not yet standardized; hence a high degree of flexibility is necessary for efficient support of high- and low-throughput data analytic tasks. Development of a desktop environment that is sufficiently robust for deployment in data analytic pipelines, and simultaneously supports customization for programmers and non-programmers alike, has proven to be a significant challenge. Results: We describe multiplierz, a flexible and open-source desktop environment for comprehensive proteomics data analysis. We use this framework to expose a prototype version of our recently proposed common API (mzAPI) designed for direct access to proprietary mass spectrometry files. In addition to routine data analytic tasks, multiplierz supports generation of information rich, portable spreadsheet-based reports. Moreover, multiplierz is designed around a "zero infrastructure" philosophy, meaning that it can be deployed by end users with little or no system administration support. Finally, access to multiplierz functionality is provided via high-level Python scripts, resulting in a fully extensible data analytic environment for rapid development of custom algorithms and deployment of high-throughput data pipelines. Conclusion: Collectively, mzAPI and multiplierz facilitate a wide range of data analysis tasks, spanning technology development to biological annotation, for mass spectrometry-based proteomics research

Accelerated DNA methylation age plays a role in the impact of cardiovascular risk factors on the human heart

BACKGROUND: DNA methylation (DNAm) age acceleration (AgeAccel) and cardiac age by 12-lead advanced electrocardiography (A-ECG) are promising biomarkers of biological and cardiac aging, respectively. We aimed to explore the relationships between DNAm age and A-ECG heart age and to understand the extent to which DNAm AgeAccel relates to cardiovascular (CV) risk factors in a British birth cohort from 1946. RESULTS: We studied four DNAm ages (AgeHannum, AgeHorvath, PhenoAge, and GrimAge) and their corresponding AgeAccel. Outcomes were the results from two publicly available ECG-based cardiac age scores: the Bayesian A-ECG-based heart age score of Lindow et al. 2022 and the deep neural network (DNN) ECG-based heart age score of Ribeiro et al. 2020. DNAm AgeAccel was also studied relative to results from two logistic regression-based A-ECG disease scores, one for left ventricular (LV) systolic dysfunction (LVSD), and one for LV electrical remodeling (LVER). Generalized linear models were used to explore the extent to which any associations between biological cardiometabolic risk factors (body mass index, hypertension, diabetes, high cholesterol, previous cardiovascular disease [CVD], and any CV risk factor) and the ECG-based outcomes are mediated by DNAm AgeAccel. We derived the total effects, average causal mediation effects (ACMEs), average direct effects (ADEs), and the proportion mediated [PM] with their 95% confidence intervals [CIs]. 498 participants (all 60-64 years) were included, with the youngest ECG heart age being 27 and the oldest 90. When exploring the associations between cardiometabolic risk factors and Bayesian A-ECG cardiac age, AgeAccelPheno appears to be a partial mediator, as ACME was 0.23 years [0.01, 0.52] p = 0.028 (i.e., PM≈18%) for diabetes, 0.34 [0.03, 0.74] p = 0.024 (i.e., PM≈15%) for high cholesterol, and 0.34 [0.03, 0.74] p = 0.024 (PM≈15%) for any CV risk factor. Similarly, AgeAccelGrim mediates ≈30% of the relationship between diabetes or high cholesterol and the DNN ECG-based heart age. When exploring the link between cardiometabolic risk factors and the A-ECG-based LVSD and LVER scores, it appears that AgeAccelPheno or AgeAccelGrim mediate 10-40% of these associations. CONCLUSION: By the age of 60, participants with accelerated DNA methylation appear to have older, weaker, and more electrically impaired hearts. We show that the harmful effects of CV risk factors on cardiac age and health, appear to be partially mediated by DNAm AgeAccelPheno and AgeAccelGrim. This highlights the need to further investigate the potential cardioprotective effects of selective DNA methyltransferases modulators

Precision measurements of the top quark mass from the Tevatron in the pre-LHC era

The top quark is the heaviest of the six quarks of the Standard Model. Precise knowledge of its mass is important for imposing constraints on a number of physics processes, including interactions of the as yet unobserved Higgs boson. The Higgs boson is the only missing particle of the Standard Model, central to the electroweak symmetry breaking mechanism and generation of particle masses. In this Review, experimental measurements of the top quark mass accomplished at the Tevatron, a proton-antiproton collider located at the Fermi National Accelerator Laboratory, are described. Topologies of top quark events and methods used to separate signal events from background sources are discussed. Data analysis techniques used to extract information about the top mass value are reviewed. The combination of several most precise measurements performed with the two Tevatron particle detectors, CDF and \D0, yields a value of \Mt = 173.2 \pm 0.9 GeV/$c^2$.Comment: This version contains the most up-to-date top quark mass averag

Synthetic Lethal Targeting of ARID1A-Mutant Ovarian Clear Cell Tumors with Dasatinib

New targeted approaches to ovarian clear cell carcinomas (OCCC) are needed, given the limited treatment options in this disease and the poor response to standard chemotherapy. Using a series of high-throughput cell-based drug screens in OCCC tumor cell models, we have identified a synthetic lethal (SL) interaction between the kinase inhibitor dasatinib and a key driver in OCCC, ARID1A mutation. Imposing ARID1A deficiency upon a variety of human or mouse cells induced dasatinib sensitivity, both in vitro and in vivo, suggesting that this is a robust synthetic lethal interaction. The sensitivity of ARID1A-deficient cells to dasatinib was associated with G1 -S cell-cycle arrest and was dependent upon both p21 and Rb. Using focused siRNA screens and kinase profiling, we showed that ARID1A-mutant OCCC tumor cells are addicted to the dasatinib target YES1. This suggests that dasatinib merits investigation for the treatment of patients with ARID1Amutant OCCC. Mol Cancer Ther; 15(7); 1472-84. Ó2016 AACR.</p

Differences in Presentation and Outcomes between Children with Familial Dilated Cardiomyopathy and Children with Idiopathic Dilated Cardiomyopathy: A Report from the Pediatric Cardiomyopathy Registry Study Group

Research comparing the survival of children with familial dilated cardiomyopathy (FDCM) to that of children with idiopathic dilated cardiomyopathy (IDCM) has produced conflicting results

Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer.

Dysregulation of the PI3K-AKT-mTOR signaling network is a prominent feature of breast cancers. However, clinical responses to drugs targeting this pathway have been modest, possibly because of dynamic changes in cellular signaling that drive resistance and limit drug efficacy. Using a quantitative chemoproteomics approach, we mapped kinome dynamics in response to inhibitors of this pathway and identified signaling changes that correlate with drug sensitivity. Maintenance of AURKA after drug treatment was associated with resistance in breast cancer models. Incomplete inhibition of AURKA was a common source of therapy failure, and combinations of PI3K, AKT or mTOR inhibitors with the AURKA inhibitor MLN8237 were highly synergistic and durably suppressed mTOR signaling, resulting in apoptosis and tumor regression in vivo. This signaling map identifies survival factors whose presence limits the efficacy of targeted therapies and reveals new drug combinations that may unlock the full potential of PI3K-AKT-mTOR pathway inhibitors in breast cancer

QCD

We discuss issues of QCD at the LHC including parton distributions, Monte Carlo event generators, the available next-to-leading order calculations, resummation, photon production, small x physics, double parton scattering, and backgrounds to Higgs production.Comment: 115 pages, Latex, 47 figures, to appear in the Report of the ``1999 CERN Workshop on SM Physics (and more) at the LHC'', S. Catani, M. Dittmar, D. Soper, W.J. Stirling, S. Tapprogge (convenors