Bayesian model comparison with un-normalised likelihoods

Models for which the likelihood function can be evaluated only up to a parameter-dependent unknown normalizing constant, such as Markov random field models, are used widely in computer science, statistical physics, spatial statistics, and network analysis. However, Bayesian analysis of these models using standard Monte Carlo methods is not possible due to the intractability of their likelihood functions. Several methods that permit exact, or close to exact, simulation from the posterior distribution have recently been developed. However, estimating the evidence and Bayes’ factors for these models remains challenging in general. This paper describes new random weight importance sampling and sequential Monte Carlo methods for estimating BFs that use simulation to circumvent the evaluation of the intractable likelihood, and compares them to existing methods. In some cases we observe an advantage in the use of biased weight estimates. An initial investigation into the theoretical and empirical properties of this class of methods is presented. Some support for the use of biased estimates is presented, but we advocate caution in the use of such estimates

Dendritic cell subsets differentially regulate angiogenesis in human ovarian cancer

Angiogenesis is essential for both primary and metastatic tumor growth. Tumor blood vessel formation is complex and regulated by many factors. Ovarian carcinomas have a poor prognosis, often associated with multifocal intraperitoneal dissemination accompanied by intense neovascularization. To examine tumor angiogenesis in the tumor microenvironment, we studied malignant ascites of patients with untreated ovarian carcinoma. We observed high numbers of plasmacytoid dendritic cells (PDCs) and significant stromal-derived factor (CXCL-12/SDF)-1 in their malignant ascites, attracting PDCs into the tumor environment. We now show that tumor-associated PDCs induced angiogenesis in vivo through production of tumor necrosis factor alpha and interleukin 8. By contrast, myeloid dendritic cells (MDCs) were absent from malignant ascites. MDCs derived in vitro suppressed angiogenesis in vivo through production of interleukin 12. Thus, the tumor may attract PDCs to augment angiogenesis while excluding MDCs to prevent angiogenesis inhibition, demonstrating a novel mechanism for modulating tumor neovascularization. Because dendritic cells (DCs) have long been known to affect tumor immunity, our data also implicate DCs in regulation of tumor neoangiogenesis, suggesting a novel role of DCs in tumor pathology.status: publishe