423 research outputs found

    Adverse prognostic and predictive significance of low DNA-dependent protein kinase catalytic subunit (DNA-PKcs) expression in early-stage breast cancers

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    Background: DNA-dependent protein kinase catalytic subunit (DNA-PKcs), a serine threonine kinase belonging to the PIKK family (phosphoinositide 3-kinase-like-family of protein kinase), is a critical component of the non-homologous end joining (NHEJ) pathway required for the repair of DNA double strand breaks. DNA-PKcs may be involved in breast cancer pathogenesis. Methods: We evaluated clinicopathological significance of DNA-PKcs protein expression in 1161 tumours and DNA-PKcs mRNA expression in 1950 tumours. We correlated DNA-PKcs to other markers of aggressive phenotypes, DNA repair, apoptosis and cell cycle regulation. Results: Low DNA-PKcs protein expression was associated with higher tumour grade, higher mitotic index, tumour de-differentiation and tumour type (ps<0.05). Absence of BRCA1, low XRCC1/SMUG1/APE1/Polβ were also more likely in low DNA-PKcs expressing tumours (ps<0.05). Low DNA-PKcs protein expression was significantly associated with worse breast cancer specific survival (BCCS) in univariate and multivariate analysis (ps<0.01). At the mRNA level, low DNA-PKcs was associated with PAM50.Her2 and PAM50.LumA molecular phenotypes (ps<0.01) and poor BCSS. In patients with ER positive tumours who received endocrine therapy, low DNA-PKcs (protein and mRNA) was associated with poor survival. In ER negative patients, low DNA-PKcs mRNA remains significantly associated with adverse outcome. Conclusions: Our study suggests that low DNA-PKcs expression may have prognostic and predictive significance in breast cancers

    Constraining the Sommerfeld enhancement with Cherenkov telescope observations of dwarf galaxies

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    The presence of dark matter in the halo of our galaxy could be revealed through indirect detection of annihilation products. Dark matter annihilation is one of the possible interpretations of the recent measured excesses in positron and electron fluxes, once boost factors of the order of 10^3 or more are taken into account. Such boost factors are actually achievable through the velocity-dependent Sommerfeld enhancement of the annihilation cross-section. Here we study the expected gamma-ray flux from two local dwarf galaxies for which air Cerenkov measurements are available, namely Draco and Sagittarius. We use velocity dispersion measurements to model the dark matter halos of the dwarfs, and the results of numerical simulations to model the presence of an associated population of subhalos. We incorporate the Sommerfeld enhancement of the annihilation cross-section. We compare our predictions with observations of Draco and Sagittarius performed by MAGIC and HESS, respectively. We also compare our results with the sensitivities of Fermi and of the future Cherenkov Telescope Array. We find that the boost factor due to the Sommerfeld enhancement is already constrained by the MAGIC and HESS data, with enhancements greater than 5 x 10^4 being excluded. While Fermi will not be able to detect gamma-rays from the dwarf galaxies s even with the most optimistic Sommerfeld effect, we show that the Cherenkov Telescope Array will be able to test enhancements greater than 1.5 x 10^3.Comment: 7 pages, 7 figure

    Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

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    One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution

    A hospital-site controlled intervention using audit and feedback to implement guidelines concerning inappropriate treatment of catheter-associated asymptomatic bacteriuria

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    <p>Abstract</p> <p>Background</p> <p>Catheter-associated urinary tract infection (CAUTI) is one of the most common hospital-acquired infections. However, many cases treated as hospital-acquired CAUTI are actually asymptomatic bacteriuria (ABU). Evidence-based guidelines recommend that providers neither screen for nor treat ABU in most catheterized patients, but there is a significant gap between these guidelines and clinical practice. Our objectives are (1) to evaluate the effectiveness of an audit and feedback intervention for increasing guideline-concordant care concerning catheter-associated ABU and (2) to measure improvements in healthcare providers' knowledge of and attitudes toward the practice guidelines associated with the intervention.</p> <p>Methods/Design</p> <p>The study uses a controlled pre/post design to test an intervention using audit and feedback of healthcare providers to improve their compliance with ABU guidelines. The intervention and the control sites are two VA hospitals. For objective 1 we will review medical records to measure the clinical outcomes of inappropriate screening for and treatment of catheter-associated ABU. For objective 2 we will survey providers' knowledge and attitudes. Three phases of our protocol are proposed: the first 12-month phase will involve observation of the baseline incidence of inappropriate screening for and treatment of ABU at both sites. This surveillance for clinical outcomes will continue at both sites throughout the study. Phase 2 consists of 12 months of individualized audit and feedback at the intervention site and guidelines distribution at both sites. The third phase, also over 12 months, will provide unit-level feedback at the intervention site to assess sustainability. Healthcare providers at the intervention site during phase 2 and at both sites during phase 3 will complete pre/post surveys of awareness and familiarity (knowledge), as well as of acceptance and outcome expectancy (attitudes) regarding the relevant practice guidelines.</p> <p>Discussion</p> <p>Our proposal to bring clinical practice in line with published guidelines has significant potential to decrease overdiagnosis of CAUTI and associated inappropriate antibiotic use. Our study will also provide information about how to maximize effectiveness of audit and feedback to achieve guideline adherence in the inpatient setting.</p> <p>Trial Registration</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT01052545">NCT01052545</a></p

    Efficient Identification of Critical Residues Based Only on Protein Structure by Network Analysis

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    Despite the increasing number of published protein structures, and the fact that each protein's function relies on its three-dimensional structure, there is limited access to automatic programs used for the identification of critical residues from the protein structure, compared with those based on protein sequence. Here we present a new algorithm based on network analysis applied exclusively on protein structures to identify critical residues. Our results show that this method identifies critical residues for protein function with high reliability and improves automatic sequence-based approaches and previous network-based approaches. The reliability of the method depends on the conformational diversity screened for the protein of interest. We have designed a web site to give access to this software at http://bis.ifc.unam.mx/jamming/. In summary, a new method is presented that relates critical residues for protein function with the most traversed residues in networks derived from protein structures. A unique feature of the method is the inclusion of the conformational diversity of proteins in the prediction, thus reproducing a basic feature of the structure/function relationship of proteins

    Prostate Cancer Postoperative Nomogram Scores and Obesity

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    Nomograms are tools used in clinical practice to predict cancer outcomes and to help make decisions regarding management of disease. Since its conception, utility of the prostate cancer nomogram has more than tripled. Limited information is available on the relation between the nomograms' predicted probabilities and obesity. The purpose of this study was to examine whether the predictions from a validated postoperative prostate cancer nomogram were associated with obesity.We carried out a cross-sectional analysis of 1220 patients who underwent radical prostatectomy (RP) in southern California from 2000 to 2008. Progression-free probabilities (PFPs) were ascertained from the 10-year Kattan postoperative nomogram. Multivariable logistic regression models estimated odds ratios (ORs) and 95% confidence intervals (CIs).In the present study, aggressive prostate cancer (Gleason ≥7), but not advanced stage, was associated with obesity (p = 0.01). After adjusting for age, black race, family history of prostate cancer and current smoking, an inverse association was observed for 10-year progression-free predictions (OR = 0.50; 95% CI = 0.28–0.90) and positive associations were observed for preoperative PSA levels (OR = 1.23; 95% CI = 1.01–1.50) and Gleason >7 (OR = 1.45; 95% CI = 1.11–1.90).Obese RP patients were more likely to have lower PFP values than non-obese patients, suggesting a higher risk of experiencing prostate cancer progression. Identifying men with potentially higher risks due to obesity may improve disease prognosis and treatment decision-making
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