Søren Tolver Jensen

Sensing of RNA Viruses: a Review of Innate Immune Receptors Involved in Recognizing RNA Virus Invasion

ABSTRACT Our knowledge regarding the contribution of the innate immune system in recognizing and subsequently initiating a host response to an invasion of RNA virus has been rapidly growing over the last decade. Descriptions of the receptors involved and the molecular mechanisms they employ to sense viral pathogen-associated molecular patterns have emerged in great detail. This review presents an overview of our current knowledge regarding the receptors used to detect RNA virus invasion, the molecular structures these receptors sense, and the involved downstream signaling pathways.

Adenovirus-Based Vaccine against Listeria monocytogenes: Extending the Concept of Invariant Chain Linkage

The use of replication-deficient adenoviruses as vehicles for transfer of foreign genes offers many advantages in a vaccine setting, eliciting strong cellular immune responses involving both CD8+ and CD4+ T cells. Further improving the immunogenicity, tethering of the inserted target Ag to MHC class II–associated invariant chain (Ii) greatly enhances both the presentation of most target Ags, as well as overall protection against viral infection, such as lymphocytic choriomeningitis virus (LCMV). The present study extends this vaccination concept to include protection against intracellular bacteria, using Listeria monocytogenes as a model organism. Protection in C57BL/6 mice against recombinant L. monocytogenes expressing an immunodominant epitope of the LCMV glycoprotein (GP33) was greatly accelerated, augmented, and prolonged following vaccination with an adenoviral vaccine encoding GP linked to Ii compared with vaccination with the unlinked vaccine. Studies using knockout mice demonstrated that CD8+ T cells were largely responsible for this protection, which is mediated through perforin-dependent lysis of infected cells and IFN-γ production. Taking the concept a step further, vaccination of C57BL/6 (L. monocytogenes–resistant) and BALB/c (L. monocytogenes–susceptible) mice with adenoviral vectors encoding natural L. monocytogenes-derived soluble Ags (listeriolysin O and p60) revealed that tethering of these Ags to Ii markedly improved the vaccine-induced CD8+ T cell response to two of three epitopes studied. More importantly, Ii linkage accelerated and augmented vaccine-induced protection in both mouse strains and prolonged protection, in particular that induced by the weak Ag, p60, in L. monocytogenes–susceptible BALB/c mice.

Estimation and Asymptotic Inference in the AR-ARCH Model

This article studies asymptotic properties of the quasi-maximum likelihood estimator (QMLE) for the parameters in the autoregressive (AR) model with autoregressive conditional heteroskedastic (ARCH) errors. A modified QMLE (MQMLE) is also studied. This estimator is based on truncation of individual terms of the likelihood function and is related to the recent so-called self-weighted QMLE in Ling (2007b). We show that the MQMLE is asymptotically normal irrespectively of the existence of finite moments, as geometric ergodicity alone suffice. Moreover, our included simulations show that the MQMLE is remarkably well-behaved in small samples. On the other hand, the ordinary QMLE, as is well-known, requires finite fourth order moments for asymptotic normality. But based on our considerations and simulations, we conjecture that in fact only geometric ergodicity and finite second order moments are needed for the QMLE to be asymptotically normal. Finally, geometric ergodicity for AR-ARCH processes is shown to hold under mild and classic conditions on the AR and ARCH processes.

On convergence of multivariate Laplace transforms

It is well-known that convergence of Laplace transforms in a neighbourhood of the origin is a sufficient criteria for weak convergence. It is worthwhile to note that the interior of the set of convergence points is convex. This provides a link to exponential family theory. As an example an autoregressive model is studied.

Estimation of proportional covariances

In the model for proportional covariance matrices of p-dimensional normally distributed random variables, the existence and uniqueness of the maximum likelihood estimator is establishing using convexity results.