A dynamic Bayesian nonlinear mixed-effects model of HIV response incorporating medication adherence, drug resistance and covariates

HIV dynamic studies have contributed significantly to the understanding of HIV pathogenesis and antiviral treatment strategies for AIDS patients. Establishing the relationship of virologic responses with clinical factors and covariates during long-term antiretroviral (ARV) therapy is important to the development of effective treatments. Medication adherence is an important predictor of the effectiveness of ARV treatment, but an appropriate determinant of adherence rate based on medication event monitoring system (MEMS) data is critical to predict virologic outcomes. The primary objective of this paper is to investigate the effects of a number of summary determinants of MEMS adherence rates on virologic response measured repeatedly over time in HIV-infected patients. We developed a mechanism-based differential equation model with consideration of drug adherence, interacted by virus susceptibility to drug and baseline characteristics, to characterize the long-term virologic responses after initiation of therapy. This model fully integrates viral load, MEMS adherence, drug resistance and baseline covariates into the data analysis. In this study we employed the proposed model and associated Bayesian nonlinear mixed-effects modeling approach to assess how to efficiently use the MEMS adherence data for prediction of virologic response, and to evaluate the predicting power of each summary metric of the MEMS adherence rates.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS376 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Arachidonic Acid as a Possible Negative Feedback Inhibitor of Nicotinic Acetylcholine Receptors on Neurons

Neuronal acetylcholine receptors, being highly permeable to calcium, are likely to regulate calcium-dependent events in neurons. Arachidonic acid is a membrane-permeant second messenger that can be released from membrane phospholipids by phospholipases in a calcium-dependent manner. We show here that activation of neuronal acetylcholine receptors triggers release of 3H-arachidonic acid in a calcium-dependent manner from neurons preloaded with the fatty acid. Moreover, low concentrations of arachidonic acid reversibly inhibit the receptors and act most efficiently on receptors likely to have the highest permeability to calcium, namely receptors containing α7 subunits. Low concentrations of arachidonic acid also reversibly inhibit α7- containing receptors expressed in Xenopus oocytes following injection of α7 cRNA. The oocyte results indicate following injection of α7 cRNA. The oocyte results indicate that the inhibition is a feature of the receptors rather than a consequence of neuron-specific machinery. The inhibition is not mediated by specific metabolites of arachidonic acid because the effects can be mimicked by other fatty acids; their effectiveness correlates with their content of double bonds. In contrast to arachidonic effects on calcium currents, inhibition of neuronal nicotinic receptors by the fatty acid cannot be prevented by blocking production of free radicals or by inhibiting protein kinase C. An alternative mechanism is that arachidonic acid binds directly to the receptors or perturbs the local environment in such a manner as to constrain receptor function

Physical transformations between quantum states

Given two sets of quantum states {A_1, ..., A_k} and {B_1, ..., B_k}, represented as sets of density matrices, necessary and sufficient conditions are obtained for the existence of a physical transformation T, represented as a trace-preserving completely positive map, such that T(A_i) = B_i for i = 1, ..., k. General completely positive maps without the trace-preserving requirement, and unital completely positive maps transforming the states are also considered

Strategic Design of a Robust Supply Chain

The strategic design of a robust supply chain has as goal the configuration of the supply chain structure so that the performance of the supply chain remains of a consistently high quality for all possible future scenarios. We model this goal with an objective function that trades off the central tendency of the supply chain profit with the dispersion of the profit as measured by the standard deviation for any value of the weights assigned to the two components. However, the standard deviation, used as the dispersion penalty for profit maximization, has a square root expression which makes standard maximization algorithms non applicable. The focus in this article is on the development of the strategic and tactical models. The application of the methodology to an industrial case will be reported. The optimization algorithm and detailed numerical experiments will be described in future research