Convergence of Probability Measures. By P. Billingsley. Chichester, Sussex, Wiley, 1968. xii, 253 p. 9 1/4“. 117s.

Convergence of Probability Measures

Macrophages are strategically located throughout the body tissues, where they ingest and process foreign materials, dead cells and debris and recruit additional macrophages in response to inflammatory signals They are highly heterogeneous cells that can rapidly change their function in response to local microenvironmental signals In this Review, we discuss the four stages of orderly inflammation mediated by macrophages: recruitment to tissues; differentiation and activation in situ; conversion to suppressive cells; and restoration of tissue homeostasis We also discuss the protective and pathogenic functions of the various macrophage subsets in antimicrobial defence, antitumour immune responses, metabolism and obesity, allergy and asthma, tumorigenesis, autoimmunity, atherosclerosis, fibrosis and wound healing Finally, we briefly discuss the characterization of macrophage heterogeneity in humans

/pdf/protective-and-pathogenic-functions-of-macrophage-subsets-5d5nlezyqd.pdf

Protective and pathogenic functions of macrophage subsets

Macrophages, the most plastic cells of the haematopoietic system, are found in all tissues and show great functional diversity. They have roles in development, homeostasis, tissue repair and immunity. Although tissue macrophages are anatomically distinct from one another, and have different transcriptional profiles and functional capabilities, they are all required for the maintenance of homeostasis. However, these reparative and homeostatic functions can be subverted by chronic insults, resulting in a causal association of macrophages with disease states. In this Review, we discuss how macrophages regulate normal physiology and development, and provide several examples of their pathophysiological roles in disease. We define the 'hallmarks' of macrophages according to the states that they adopt during the performance of their various roles, taking into account new insights into the diversity of their lineages, identities and regulation. It is essential to understand this diversity because macrophages have emerged as important therapeutic targets in many human diseases.

/pdf/macrophage-biology-in-development-homeostasis-and-disease-2nq2u94n8n.pdf

Macrophage biology in development, homeostasis and disease

Many econometric testing problems involve nuisance parameters which are not identified under the null hypotheses. This paper studies the asymptotic distribution theory for such tests. The asymptotic distributions of standard test statistics are described as functionals of chi-square processes. In general, the distributions depend upon a large number of unknown parameters. We show that a transformation based upon a conditional probability measure yields an asymptotic distribution free of nuisance parameters, and we show that this transformation can be easily approximated via simulation. The theory is applied to threshold models, with special attention given to the so-called self-exciting threshold autoregressive model. Monte Carlo methods are used to assess the finite sample distributions. The tests are applied to U.S. GNP growth rates, and we find that Potter's (1995) threshold effect in this series can be possibly explained by sampling variation.

/pdf/inference-when-a-nuisance-parameter-is-not-identified-under-1kbhk92q65.pdf

Inference when a nuisance parameter is not identified under the null hypothesis

to the DLM: The First-Order Polynomial Model.- to the DLM: The Dynamic Regression Model.- The Dynamic Linear Model.- Univariate Time Series DLM Theory.- Model Specification and Design.- Polynomial Trend Models.- Seasonal Models.- Regression, Autoregression, and Related Models.- Illustrations and Extensions of Standard DLMs.- Intervention and Monitoring.- Multi-Process Models.- Non-Linear Dynamic Models: Analytic and Numerical Approximations.- Exponential Family Dynamic Models.- Simulation-Based Methods in Dynamic Models.- Multivariate Modelling and Forecasting.- Distribution Theory and Linear Algebra.

Bayesian Forecasting and Dynamic Models

The cause of Crohn's 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.

/pdf/disordered-macrophage-cytokine-secretion-underlies-impaired-3io2ry9bzf.pdf

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

Statistical Analysis of Reliability Data.

A very general result concerning the weak consistency and uniform asymptotic normality of the maximum likelihood estimator is presented. The result proves to be of particular value in establishing uniform asymptotic normality of randomly normalized maximum likelihood estimators of parameters in stochastic processes. The only conditions imposed are certain regularity conditions on the (random) information function, easily verified in practice. Application of the result is briefly considered.

/pdf/uniform-asymptotic-normality-of-the-maximum-likelihood-12ep7kqwju.pdf

Uniform Asymptotic Normality of the Maximum Likelihood Estimator

A probability matching prior is a prior distribution under which the posterior probabilities of certain regions coincide with their coverage probabilities, either exactly or approximately. Use of such a prior will ensure exact or approximate frequentist validity of Bayesian credible regions. Probability matching priors have been of interest for many years but there has been a resurgence of interest over the last twenty years. In this article we survey the main developments in probability matching priors, which have been derived for various types of parametric and predictive region.

Trevor J. Sweeting

Papers

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

Statistical Analysis of Reliability Data.

Uniform Asymptotic Normality of the Maximum Likelihood Estimator

Probability matching priors

Statistical Analysis of Reliability Data.