Specifying and Validating Probabilistic Inputs for Prescriptive Models of Decision Making over Time

Optimization models for making decisions over time in uncertain environments rely on probabilistic inputs, such as scenario trees for stochastic mathematical programs. The quality of model outputs, i.e., the solutions obtained, depends on the quality of these inputs. However, solution quality is rarely assessed in a rigorous way. The connection between validation of model inputs and quality of the resulting solution is not immediate. This chapter discusses some efforts to formulate realistic probabilistic inputs and subsequently validate them in terms of the quality of solutions they produce. These include formulating probabilistic models based on statistical descriptions understandable to decision makers; conducting statistical tests to assess the validity of stochastic process models and their discretization; and conducting re-enactments to assess the quality of the formulation in terms of solution performance against observational data. Studies of long-term capacity expansion in service industries, including electric power, and short-term scheduling of thermal electricity generating units provide motivation and illustrations. The chapter concludes with directions for future research

Platelet-Activating Factor Receptor Plays a Role in Lung Injury and Death Caused by Influenza A in Mice

Influenza A virus causes annual epidemics which affect millions of people worldwide. A recent Influenza pandemic brought new awareness over the health impact of the disease. It is thought that a severe inflammatory response against the virus contributes to disease severity and death. Therefore, modulating the effects of inflammatory mediators may represent a new therapy against Influenza infection. Platelet activating factor (PAF) receptor (PAFR) deficient mice were used to evaluate the role of the gene in a model of experimental infection with Influenza A/WSN/33 H1N1 or a reassortant Influenza A H3N1 subtype. The following parameters were evaluated: lethality, cell recruitment to the airways, lung pathology, viral titers and cytokine levels in lungs. The PAFR antagonist PCA4248 was also used after the onset of flu symptoms. Absence or antagonism of PAFR caused significant protection against flu-associated lethality and lung injury. Protection was correlated with decreased neutrophil recruitment, lung edema, vascular permeability and injury. There was no increase of viral load and greater recruitment of NK1.1+ cells. Antibody responses were similar in WT and PAFR-deficient mice and animals were protected from re-infection. Influenza infection induces the enzyme that synthesizes PAF, lyso-PAF acetyltransferase, an effect linked to activation of TLR7/8. Therefore, it is suggested that PAFR is a disease-associated gene and plays an important role in driving neutrophil influx and lung damage after infection of mice with two subtypes of Influenza A. Further studies should investigate whether targeting PAFR may be useful to reduce lung pathology associated with Influenza A virus infection in humans

Notch signaling in response to excitotoxicity induces neurodegeneration via erroneous cell cycle reentry

Neurological disorders such as Alzheimer’s disease, stroke and epilepsy are currently marred by the lack of effective treatments to prevent neuronal death. Erroneous cell cycle reentry (CCR) is hypothesized to have a causative role in neurodegeneration. We show that forcing S-phase reentry in cultured hippocampal neurons is sufficient to induce neurodegeneration. We found that kainic-acid treatment in vivo induces erroneous CCR and neuronal death through a Notch-dependent mechanism. Ablating Notch signaling in neurons provides neuroprotection against kainic acid-induced neuronal death. We further show that kainic-acid treatment activates Notch signaling, which increases the bioavailability of CyclinD1 through Akt/GSK3β pathway, leading to aberrant CCR via activation of CyclinD1-Rb-E2F1 axis. In addition, pharmacological blockade of this pathway at critical steps is sufficient to confer resistance to kainic acid-induced neurotoxicity in mice. Taken together, our results demonstrate that excitotoxicity leads to neuronal death in a Notch-dependent manner through erroneous CCR

Feedback Set Problems

. This paper is a short survey of feedback set problems. It will be published in Encyclopedia of Optimization, Kluwer Academic Publishers, 2000. 1. INTRODUCTION In recent years feedback set problems have been the subject of growing interest. They have found applications in many fields, including deadlock prevention [89], program verification [78], and Bayesian inference [2]. Therefore, it is natural that in the past few years there have been intensive efforts on exact and approximation algorithms for these kinds of problems. Exact algorithms have been proposed for solving the problems restricted to special classes of graphs as well as several approximation algorithms with provable bounds for the cases that are not known to be polynomially solvable. The most general feedback set problem consists in finding a minimum-weight (or minimum cardinality) set of vertices (arcs) that meets all cycles in a collection C of cycles in a graph (G,w), where w is a nonnegative function defined on th..