Trevor J. Sweeting

Disordered macrophage cytokine secretion underlies impaired acute inflammation and bacterial clearance in Crohn's disease

The cause of Crohns disease (CD) remains poorly understood. Counterintuitively, these patients possess an impaired acute inflammatory response, which could result in delayed clearance of bacteria penetrating the lining of the bowel and predispose to granuloma formation and chronicity. We tested this hypothesis in human subjects by monitoring responses to killed Escherichia coli injected subcutaneously into the forearm. Accumulation of 111In-labeled neutrophils at these sites and clearance of 32P-labeled bacteria from them were markedly impaired in CD. Locally increased blood flow and bacterial clearance were dependent on the numbers of bacteria injected. Secretion of proinflammatory cytokines by CD macrophages was grossly impaired in response to E. coli or specific Toll-like receptor agonists. Despite normal levels and stability of cytokine messenger RNA, intracellular levels of tumor necrosis factor (TNF) were abnormally low in CD macrophages. Coupled with reduced secretion, these findings indicate accelerated intracellular breakdown. Differential transcription profiles identified disease-specific genes, notably including those encoding proteins involved in vesicle trafficking. Intracellular destruction of TNF was decreased by inhibitors of lysosomal function. Together, our findings suggest that in CD macrophages, an abnormal proportion of cytokines are routed to lysosomes and degraded rather than being released through the normal secretory pathway.

Plasmacytoid Dendritic Cells Sequester High Prion Titres at Early Stages of Prion Infection

In most transmissible spongiform encephalopathies prions accumulate in the lymphoreticular system (LRS) long before they are detectable in the central nervous system. While a considerable body of evidence showed that B lymphocytes and follicular dendritic cells play a major role in prion colonization of lymphoid organs, the contribution of various other cell types, including antigen-presenting cells, to the accumulation and the spread of prions in the LRS are not well understood. A comprehensive study to compare prion titers of candidate cell types has not been performed to date, mainly due to limitations in the scope of animal bioassays where prohibitively large numbers of mice would be required to obtain sufficiently accurate data. By taking advantage of quantitative in vitro prion determination and magnetic-activated cell sorting, we studied the kinetics of prion accumulation in various splenic cell types at early stages of prion infection. Robust estimates for infectious titers were obtained by statistical modelling using a generalized linear model. Whilst prions were detectable in B and T lymphocytes and in antigen-presenting cells like dendritic cells and macrophages, highest infectious titers were determined in two cell types that have previously not been associated with prion pathogenesis, plasmacytoid dendritic (pDC) and natural killer (NK) cells. At 30 days after infection, NK cells were more than twice, and pDCs about seven-fold, as infectious as lymphocytes respectively. This result was unexpected since, in accordance to previous reports prion protein, an obligate requirement for prion replication, was undetectable in pDCs. This underscores the importance of prion sequestration and dissemination by antigen-presenting cells which are among the first cells of the immune system to encounter pathogens. We furthermore report the first evidence for a release of prions from lymphocytes and DCs of scrapie-infected mice ex vivo, a process that is associated with a release of exosome-like membrane vesicles.

Approximate Inference in Location—Scale Regression Models

Abstract It is shown that χ2 and multivariate t distributions provide good approximations to posterior distributions arising in location-scale regression models. In the case of a linear regression model, Bayesian inferences based on an improper prior have conditional frequency, as well as fiducial/structural interpretation; so the results are also applicable in a non-Bayesian context. Numerical support for the approximations is presented for the case of a Weibull regression model and a regression with t distributed errors.

Nonsubjective priors via predictive relative entropy regret

We explore the construction of nonsubjective prior distributions in Bayesian statistics via a posterior predictive relative entropy regret criterion. We carry out a minimax analysis based on a derived asymptotic predictive loss function and show that this approach to prior construction has a number of attractive features. The approach here differs from previous work that uses either prior or posterior relative entropy regret in that we consider predictive performance in relation to alternative nondegenerate prior distributions. The theory is illustrated with an analysis of some specific examples.

Some new formulae for posterior expectations and Bartlett corrections

Some new accurate approximations for posterior expectations and Bartlett corrections are derived. These approximations are modifications of formulae based on signed root log-likelihood ratios obtained in Sweeting (1996) and are designed to address two problems that arise in the practical application of these formulae in the multiparameter case. The first problem is a computational one associated with inversion of signed root log-likelihood ratios. The second concerns the form of the posterior expectation formula, which is not in a particularly convenient form for the computation of predictive densities. The theory is illustrated by two examples.

On estimator efficiency in stochastic processes

It is shown, under mild regularity conditions on the random information matrix, that the maximum likelihood estimator is efficient in the sense of having asymptotically maximum probability of concentration about the true parameter value. In the case of a single parameter, the conditions are improvements of those used by Heyde (1978). The proof is based on the idea of maximum probability estimators introduced by Weiss and Wolfowitz (1967).

Selecting a subset of queries for acquisition of further relevance judgements

Assessing the relative performance of search systems requires the use of a test collection with a pre-defined set of queries and corresponding relevance assessments. The state-of-the-art process of constructing test collections involves using a large number of queries and selecting a set of documents, submitted by a group of participating systems, to be judged per query. However, the initial set of judgments may be insufficient to reliably evaluate the performance of future as yet unseen systems. In this paper, we propose a method that expands the set of relevance judgments as new systems are being evaluated. We assume that there is a limited budget to build additional relevance judgements. From the documents retrieved by the new systems we create a pool of unjudged documents. Rather than uniformly distributing the budget across all queries, we first select a subset of queries that are effective in evaluating systems and then uniformly allocate the budget only across these queries. Experimental results on TREC 2004 Robust track test collection demonstrate the superiority of this budget allocation strategy.

Prioritizing relevance judgments to improve the construction of IR test collections

We consider the problem of optimally allocating a fixed budget to construct a test collection with associated relevance judgements, such that it can (i) accurately evaluate the relative performance of the participating systems, and (ii) generalize to new, previously unseen systems. We propose a two stage approach. For a given set of queries, we adopt the traditional pooling method and use a portion of the budget to evaluate a set of documents retrieved by the participating systems. Next, we analyze the relevance judgments to prioritize the queries and remaining pooled documents for further relevance assessments. The query prioritization is formulated as a convex optimization problem, thereby permitting efficient solution and providing a flexible framework to incorporate various constraints. Query-document pairs with the highest priority scores are evaluated using the remaining budget. We evaluate our resource optimization approach on the TREC 2004 Robust track collection. We demonstrate that our optimization techniques are cost efficient and yield a significant improvement in the reusability of the test collections.

On the construction of Bayes–confidence regions

We obtain approximate Bayes-confidence intervals for a scalar parameter based on directed likelihood. The posterior probabilities of these intervals agree with their unconditional coverage probabilities to fourth order, and with their conditional coverage probabilities to third order. These intervals are constructed for arbitrary smooth prior distributions. A key feature of the construction is that log-likelihood derivatives beyond second order are not required, unlike the asymptotic expansions of Severini.

Application of a predictive distribution formula to Bayesian computation for incomplete data models

We consider exact and approximate Bayesian computation in the presence of latent variables or missing data. Specifically we explore the application of a posterior predictive distribution formula derived in Sweeting And Kharroubi (2003), which is a particular form of Laplace approximation, both as an importance function and a proposal distribution. We show that this formula provides a stable importance function for use within poor man’s data augmentation schemes and that it can also be used as a proposal distribution within a Metropolis-Hastings algorithm for models that are not analytically tractable. We illustrate both uses in the case of a censored regression model and a normal hierarchical model, with both normal and Student t distributed random effects. Although the predictive distribution formula is motivated by regular asymptotic theory, it is not necessary that the likelihood has a closed form or that it possesses a local maximum.