Development and evolution of caste dimorphism in honeybees - a modeling approach

The difference in phenotypes of queens and workers is a hallmark of the highly eusocial insects. The caste dimorphism is often described as a switch-controlled polyphenism, in which environmental conditions decide an individual's caste. Using theoretical modeling and empirical data from honeybees, we show that there is no discrete larval developmental switch. Instead, a combination of larval developmental plasticity and nurse worker feeding behavior make up a colony-level social and physiological system that regulates development and produces the caste dimorphism. Discrete queen and worker phenotypes are the result of discrete feeding regimes imposed by nurses, whereas a range of experimental feeding regimes produces a continuous range of phenotypes. Worker ovariole numbers are reduced through feeding-regime-mediated reduction in juvenile hormone titers, involving reduced sugar in the larval food. Based on the mechanisms identified in our analysis, we propose a scenario of the evolutionary history of honeybee development and feeding regimes.

ESTIMATING REACTION CONSTANTS BY AB INITIO MOLECULAR MODELING: A STUDY ON THE OXIDATION OF PHENOL TO CATECHOL AND HYDROQUINONE IN ADVANCED OXIDATION PROCESSES

Molecular modeling is growing as a research tool in Chemical Engineering studies, as can be seen by a simple research on the latest publications in the field. Molecular investigations retrieve information on properties often accessible only by expensive and time-consuming experimental techniques, such as those involved in the study of radical-based chain reactions. In this work, different quantum chemical techniques were used to study phenol oxidation by hydroxyl radicals in Advanced Oxidation Processes used for wastewater treatment. The results obtained by applying a DFT-based model showed good agreement with experimental values available, as well as qualitative insights into the mechanism of the overall reaction chain. Solvation models were also tried, but were found to be limited for this reaction system within the considered theoretical level without further parameterization.

Modeling the Emergence of Circadian Rhythms in a Clock Neuron Network

Circadian rhythms in pacemaker cells persist for weeks in constant darkness, while in other types of cells the molecular oscillations that underlie circadian rhythms damp rapidly under the same conditions. Although much progress has been made in understanding the biochemical and cellular basis of circadian rhythms, the mechanisms leading to damped or self-sustained oscillations remain largely unknown. There exist many mathematical models that reproduce the circadian rhythms in the case of a single cell of the Drosophila fly. However, not much is known about the mechanisms leading to coherent circadian oscillation in clock neuron networks. In this work we have implemented a model for a network of interacting clock neurons to describe the emergence (or damping) of circadian rhythms in Drosophila fly, in the absence of zeitgebers. Our model consists of an array of pacemakers that interact through the modulation of some parameters by a network feedback. The individual pacemakers are described by a well-known biochemical model for circadian oscillation, to which we have added degradation of PER protein by light and multiplicative noise. The network feedback is the PER protein level averaged over the whole network. In particular, we have investigated the effect of modulation of the parameters associated with (i) the control of net entrance of PER into the nucleus and (ii) the non-photic degradation of PER. Our results indicate that the modulation of PER entrance into the nucleus allows the synchronization of clock neurons, leading to coherent circadian oscillations under constant dark condition. On the other hand, the modulation of non-photic degradation cannot reset the phases of individual clocks subjected to intrinsic biochemical noise.

Modeling the gluon propagator in Landau gauge: Lattice estimates of pole masses and dimension-two condensates

We present an analytic description of numerical results for the Landau-gauge SU(2) gluon propagator D(p(2)), obtained from lattice simulations (in the scaling region) for the largest lattice sizes to date, in d = 2, 3 and 4 space-time dimensions. Fits to the gluon data in 3d and in 4d show very good agreement with the tree-level prediction of the refined Gribov-Zwanziger (RGZ) framework, supporting a massive behavior for D(p(2)) in the infrared limit. In particular, we investigate the propagator's pole structure and provide estimates of the dynamical mass scales that can be associated with dimension-two condensates in the theory. In the 2d case, fitting the data requires a noninteger power of the momentum p in the numerator of the expression for D(p(2)). In this case, an infinite-volume-limit extrapolation gives D(0) = 0. Our analysis suggests that this result is related to a particular symmetry in the complex-pole structure of the propagator and not to purely imaginary poles, as would be expected in the original Gribov-Zwanziger scenario.

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.

Modeling and simulation of severe slugging with mass transfer effects

A mathematical model and numerical simulations are presented to investigate the dynamics of gas, oil and water flow in a pipeline-riser system. The pipeline is modeled as a lumped parameter system and considers two switchable states: one in which the gas is able to penetrate into the riser and another in which there is a liquid accumulation front, preventing the gas from penetrating the riser. The riser model considers a distributed parameter system, in which movable nodes are used to evaluate local conditions along the subsystem. Mass transfer effects are modeled by using a black oil approximation. The model predicts the liquid penetration length in the pipeline and the liquid level in the riser, so it is possible to determine which type of severe slugging occurs in the system. The method of characteristics is used to simplify the differentiation of the resulting hyperbolic system of equations. The equations are discretized and integrated using an implicit method with a predictor-corrector scheme for the treatment of the nonlinearities. Simulations corresponding to severe slugging conditions are presented and compared to results obtained with OLGA computer code, showing a very good agreement. A description of the types of severe slugging for the three-phase flow of gas, oil and water in a pipeline-riser system with mass transfer effects are presented, as well as a stability map. (C) 2011 Elsevier Ltd. All rights reserved.

Estimating reaction constants by ab initio molecular modeling: a study on the oxidation of phenol to catechol and hydroquinone in advanced oxidation processes

Molecular modeling is growing as a research tool in Chemical Engineering studies, as can be seen by a simple research on the latest publications in the field. Molecular investigations retrieve information on properties often accessible only by expensive and time-consuming experimental techniques, such as those involved in the study of radical-based chain reactions. In this work, different quantum chemical techniques were used to study phenol oxidation by hydroxyl radicals in Advanced Oxidation Processes used for wastewater treatment. The results obtained by applying a DFT-based model showed good agreement with experimental values available, as well as qualitative insights into the mechanism of the overall reaction chain. Solvation models were also tried, but were found to be limited for this reaction system within the considered theoretical level without further parameterization.