Using Markov chain Monte Carlo methods for estimating parameters with gravitational radiation data

We present a Bayesian approach to the problem of determining parameters for coalescing binary systems observed with laser interferometric detectors. By applying a Markov Chain Monte Carlo (MCMC) algorithm, specifically the Gibbs sampler, we demonstrate the potential that MCMC techniques may hold for the computation of posterior distributions of parameters of the binary system that created the gravity radiation signal. We describe the use of the Gibbs sampler method, and present examples whereby signals are detected and analyzed from within noisy data.Comment: 21 pages, 10 figure

HLA-A, -B, -C, -DRB1, DRB3, DRB4, DRB5 and DQB1 polymorphism detected by PCR-SSP in a semi-urban HIV-positive Ugandan population.

PCR-SSP was used to HLA-type a cohort of Ugandan HIV-positive individuals. The results represent a more comprehensive description of HLA in an African population than previously described and are in concordance with data from a general Black population. Substantial differences exist between this population and Caucasoid populations in which immunological responses to HIV have been investigated; this emphasises that the main HLA-restrictive elements for HIV-specific cytotoxic T lymphocytes will most likely be different for each population

BCL-2 Expression is Prognostic for Improved Survival in Non-small Cell Lung Cancer

ObjectiveWe used a large patient population to identify immunohistochemical biomarkers to enable improved prognostication in patients with non-small cell lung carcinoma (NSCLC).MethodsA tissue microarray was constructed using duplicate 0.6 mm cores of formalin-fixed paraffin-embedded tissue blocks from 609 patients with NSCLC. Immunohistochemical was used to detect 11 biomarkers including epidermal growth factor receptor, Her2, Her3, p53, p63, bcl-1, bcl-2, Thyroid transcription factor, carcinoembryonic antigen, chromogranin, and synaptophysin. A clinical database was generated prospectively at the time of tissue collection. Survival outcomes were obtained from a Provincial Cancer Registry database. Univariate and multivariate analyses were performed to look for a relationship between biomarker expression, smoking history, and survival.ResultsSurvival data for 535 cases were available. As of June 2005, 429 patients (80%) had died; of these 286 (54%) died of lung cancer, 117 (22%) died of other known causes, and for 26 (5%) the cause of death was not available. Univariate analysis revealed that bcl-2 (p = 0.007) was the only biomarker prognostic for improved overall survival (OS). bcl-2 (p = 0.021) and p63 (p = 0.025) were both found to be prognostic for improved disease-specific survival (DSS). Multivariate analysis (using age and biomarker expression) revealed that bcl-2 expression is prognostic for improved OS (p = 0.005) and DSS (p = 0.021).ConclusionsOur results suggest that bcl-2 expression is prognostic for improved OS and DSS in NSCLC. Testing for bcl-2 expression in a prospective study will help to determine its clinical relevance in prognostication

Relic gravitational waves in the light of 7-year Wilkinson Microwave Anisotropy Probe data and improved prospects for the Planck mission

The new release of data from Wilkinson Microwave Anisotropy Probe improves the observational status of relic gravitational waves. The 7-year results enhance the indications of relic gravitational waves in the existing data and change to the better the prospects of confident detection of relic gravitational waves by the currently operating Planck satellite. We apply to WMAP7 data the same methods of analysis that we used earlier [W. Zhao, D. Baskaran, and L.P. Grishchuk, Phys. Rev. D 80, 083005 (2009)] with WMAP5 data. We also revised by the same methods our previous analysis of WMAP3 data. It follows from the examination of consecutive WMAP data releases that the maximum likelihood value of the quadrupole ratio $R$, which characterizes the amount of relic gravitational waves, increases up to $R=0.264$, and the interval separating this value from the point $R=0$ (the hypothesis of no gravitational waves) increases up to a $2\sigma$ level. The primordial spectra of density perturbations and gravitational waves remain blue in the relevant interval of wavelengths, but the spectral indices increase up to $n_s =1.111$ and $n_t=0.111$. Assuming that the maximum likelihood estimates of the perturbation parameters that we found from WMAP7 data are the true values of the parameters, we find that the signal-to-noise ratio $S/N$ for the detection of relic gravitational waves by the Planck experiment increases up to $S/N=4.04$, even under pessimistic assumptions with regard to residual foreground contamination and instrumental noises. We comment on theoretical frameworks that, in the case of success, will be accepted or decisively rejected by the Planck observations.Comment: 27 pages, 12 (colour) figures. Published in Phys. Rev. D. V.3: modifications made to reflect the published versio

HIV infected adults do not have an excess of colonising bacteria in their large airways

BACKGROUND: HIV infected adults have increased susceptibility to bacterial pneumonia but the underlying immune defect is poorly understood. We tested the hypothesis that HIV infection might be associated with increased bacterial colonisation of distal airways by nasal flora, which would then predispose patients to bacterial pneumonia. METHODS: Healthy volunteer adults with normal chest radiographs were recruited. Bronchoscopy was carried out and uncontaminated mucosal samples were collected from proximal and distal sites in the large airways using a protected specimen brush. Samples were cultured to detect typical respiratory tract colonising organisms, and the proportion of samples found to contain colonising bacteria compared between HIV infected and uninfected subjects using non-parametric tests. RESULTS: Forty-nine subjects were studied of whom 27 were HIV infected. Colonising bacteria were identified in the nasopharynx of all subjects including Streptococcus pneumoniae in 6/49 subjects (5 HIV uninfected). Colonising bacteria were found in the distal airway of 6 subjects (3/27 HIV infected vs 3/22 HIV uninfected ; χ(2 )= 0.07, p = 0.8). Streptococcus pneumoniae was identified in the trachea of all subjects with nasal colonisation but in the distal airway of only 1 subject. CONCLUSIONS: There was no evidence to support a hypothesis of increased airway bacterial colonisation in healthy HIV infected subjects

Escherichia coli O157 infection on Scottish cattle farms: dynamics and control

In this study, we parametrize a stochastic individual-based model of the transmission dynamics of Escherichia coli O157 infection among Scottish cattle farms and use the model to predict the impacts of both targeted and non-targeted interventions. We first generate distributions of model parameter estimates using Markov chain Monte Carlo methods. Despite considerable uncertainty in parameter values, each set of parameter values within the 95th percentile range implies a fairly similar impact of interventions. Interventions that reduce the transmission coefficient and/or increase the recovery rate of infected farms (e.g. via vaccination and biosecurity) are much more effective in reducing the level of infection than reducing cattle movement rates, which improves effectiveness only when the overall control effort is small. Targeted interventions based on farm-level risk factors are more efficient than non-targeted interventions. Herd size is a major determinant of risk of infection, and our simulations confirmed that targeting interventions at farms with the largest herds is almost as effective as targeting based on overall risk. However, because of the striking characteristic that the infection force depends weakly on the number of infected farms, no interventions that are less than 100 per cent effective can eradicate E. coli O157 infection from Scottish cattle farms, implying that eliminating the disease is impractical

On analog quantum algorithms for the mixing of Markov chains

The problem of sampling from the stationary distribution of a Markov chain finds widespread applications in a variety of fields. The time required for a Markov chain to converge to its stationary distribution is known as the classical mixing time. In this article, we deal with analog quantum algorithms for mixing. First, we provide an analog quantum algorithm that given a Markov chain, allows us to sample from its stationary distribution in a time that scales as the sum of the square root of the classical mixing time and the square root of the classical hitting time. Our algorithm makes use of the framework of interpolated quantum walks and relies on Hamiltonian evolution in conjunction with von Neumann measurements. There also exists a different notion for quantum mixing: the problem of sampling from the limiting distribution of quantum walks, defined in a time-averaged sense. In this scenario, the quantum mixing time is defined as the time required to sample from a distribution that is close to this limiting distribution. Recently we provided an upper bound on the quantum mixing time for Erd\"os-Renyi random graphs [Phys. Rev. Lett. 124, 050501 (2020)]. Here, we also extend and expand upon our findings therein. Namely, we provide an intuitive understanding of the state-of-the-art random matrix theory tools used to derive our results. In particular, for our analysis we require information about macroscopic, mesoscopic and microscopic statistics of eigenvalues of random matrices which we highlight here. Furthermore, we provide numerical simulations that corroborate our analytical findings and extend this notion of mixing from simple graphs to any ergodic, reversible, Markov chain.Comment: The section concerning time-averaged mixing (Sec VIII) has been updated: Now contains numerical plots and an intuitive discussion on the random matrix theory results used to derive the results of arXiv:2001.0630

The Oncogenic Roles of DICER1 RNase IIIb Domain Mutations in Ovarian Sertoli-Leydig Cell Tumors

AbstractDICER1, an endoribonuclease required for microRNA (miRNA) biogenesis, is essential for embryogenesis and the development of many organs including ovaries. We have recently identified somatic hotspot mutations in RNase IIIb domain of DICER1 in half of ovarian Sertoli-Leydig cell tumors, a rare class of sex-cord stromal cell tumors in young women. These hotspot mutations lost IIIb cleavage activity of DICER1 in vitro and failed to produce 5p-derived miRNAs in mouse Dicer1-null ES cells. However, the oncogenic potential of these hotspot DICER1 mutations has not been studied. Here, we further revealed that the global expression of 5p-derived miRNAs was dramatically reduced in ovarian Sertoli-Leydig cell tumors carrying DICER1 hotspot mutations compared with those without DICER1 hotspot mutation. The miRNA production defect was associated with the deregulation of genes controlling cell proliferation and the cell fate. Using an immortalized human granulosa cell line, SVOG3e, we determined that the D1709N-DICER1 hotspot mutation failed to produce 5p-derived miRNAs, deregulated the expression of several genes that control gonadal differentiation and cell proliferation, and promoted cell growth. Re-expression of let-7 significantly inhibited the growth of D1709N-DICER1 SVOG3e cells, accompanied by the suppression of key regulators of cell cycle control and ovarian gonad differentiation. Taken together, our data revealed that DICER1 hotspot mutations cause systemic loss of 5p-miRNAs that can both drive pseudodifferentiation of testicular elements and cause oncogenic transformation in the ovary

Coherent Bayesian inference on compact binary inspirals using a network of interferometric gravitational wave detectors

Presented in this paper is a Markov chain Monte Carlo (MCMC) routine for conducting coherent parameter estimation for interferometric gravitational wave observations of an inspiral of binary compact objects using data from multiple detectors. The MCMC technique uses data from several interferometers and infers all nine of the parameters (ignoring spin) associated with the binary system, including the distance to the source, the masses, and the location on the sky. The Metropolis-algorithm utilises advanced MCMC techniques, such as importance resampling and parallel tempering. The data is compared with time-domain inspiral templates that are 2.5 post-Newtonian (PN) in phase and 2.0 PN in amplitude. Our routine could be implemented as part of an inspiral detection pipeline for a world wide network of detectors. Examples are given for simulated signals and data as seen by the LIGO and Virgo detectors operating at their design sensitivity.Comment: 10 pages, 4 figure