Manipulating Stress Receptor Signaling to Enhance Immunosuppression and Prolong Survival of Vascularized Composite Tissue

Vascularized composite tissue allotransplantation (VCA) can replace severely damaged body parts but the unavoidable toxicity of high doses of immunosuppressive drugs, such as tacrolimus, required results in significant morbidity. Here we tested whether we could suppress immune activity in a mouse model of VCA by mimicking the natural immune suppression generated by nervous system-induced signaling of adrenergic receptors (AR) by using a safe and well-studied β-AR agonist (terbutaline). Using wild-type and β2-AR-knockout (KO) mice, we found that increased β2-AR signaling results in delayed rejection in VCA recipients, even with subtherapeutic doses of tacrolimus, and this was associated with changes in immune contexture, expression of pro-inflammatory cytokines and chemokines, and function of endothelial adhesion molecules. We propose that β-AR agonists can be used safely to mimic the natural suppression of immune responses generated by adrenergic stress signaling and thereby reduce the dose needed of other more toxic immunosuppressive drugs.

A Discrete Bouncy Particle Sampler

Most Markov chain Monte Carlo methods operate in discrete time and are reversible with respect to the target probability. Nevertheless, it is now understood that the use of nonreversible Markov chains can be beneficial in many contexts. In particular, the recently-proposed bouncy particle sampler leverages a continuous-time and nonreversible Markov process and empirically shows state-of-the-art performances when used to explore certain probability densities; however, its implementation typically requires the computation of local upper bounds on the gradient of the log target density. We present the discrete bouncy particle sampler, a general algorithm based upon a guided random walk, a partial refreshment of direction, and a delayed-rejection step. We show that the bouncy particle sampler can be understood as a scaling limit of a special case of our algorithm. In contrast to the bouncy particle sampler, implementing the discrete bouncy particle sampler only requires point-wise evaluation of the target density and its gradient. We propose extensions of the basic algorithm for situations when the exact gradient of the target density is not available. In a Gaussian setting, we establish a scaling limit for the radial process as dimension increases to infinity. We leverage this result to obtain the theoretical efficiency of the discrete bouncy particle sampler as a function of the partial-refreshment parameter, which leads to a simple and robust tuning criterion. A further analysis in a more general setting suggests that this tuning criterion applies more generally. Theoretical and empirical efficiency curves are then compared for different targets and algorithm variations.

Immunology and Pathology in Ocular Drug Development

Clear vision is dependent on features that protect the anatomical integrity of the eye (cornea and sclera) and those that contribute to internal ocular homeostasis by conferring hemangiogenic (avascular tissues and antiangiogenic factors), lymphangiogenic (lack of draining lymphatics), and immunologic (tight junctions that form blood–ocular barriers, immunosuppressive cells, and modulators) privileges. The later examples are necessary components that enable the eye to maintain an immunosuppressive environment that responds to foreign invaders in a deviated manner, minimizing destructive inflammation that would impair vision. These conditions allowed for the observations made by Medawar, in 1948, of delayed rejection of allogenic tissue grafts in the anterior chamber of mouse eye and permit the sequestration of foreign invaders (eg, Toxoplasma gondii) within the retina of healthy individuals. Yet successful development of intraocular drugs (biologics and delivery devices) has been stymied by adverse ocular pathology, much of which is driven by immune pathways. The eye can be intolerant of foreign protein irrespective of delivery route, and endogenous ocular cells have remarkable plasticity when recruited to preserve visual function. This article provides a review of current understanding of ocular immunology and the potential role of immune mechanisms in pathology observed with intraocular drug delivery.

Impact of Damping Models in Damage Identification

Several damage identification approaches are based on computational models, and their diagnostics depend on the set of modelling hypotheses adopted when building the model itself. Among these hypotheses, the choice of appropriate damping models seems to be one of the key issues. The goal of this paper is to analyze the impact of a set of damping models on the damage identification diagnostics. The damage identification is built on a Bayesian framework, and the measured data are the modal data associated with the first modes of the structure. The exploration of the posterior density of unknown model parameters is performed by means of the Markov chain Monte Carlo method (MCMC) with Delayed Rejection Adaptive Metropolis (DRAM) algorithm. The analyses are based on experimental dynamic response obtained from an aluminum beam instrumented with a set of accelerometers. The presence of damage/anomaly within the system is physically simulated by placing lumped masses over the beam, considering three different masses and two different placing positions. For the set of cases analyzed, it is shown that the proposed approach was able to identify both the position and magnitude of the lumped masses and that the damping models may not provide an increase of knowledge of some unknown parameters when damping rates are lower than 1%.