Solving a Slick Problem; Morally Preferable; Objectors by Conscience

News release announces a UD biologist\u27s solutions for cleaning up the massive oil spill in the Persian golf, a senior research scientist\u27s comments on the use of smart weapons in the Persian Gulf, and counseling concerning the selective service law and legal option for members of the UD community will be offered

Co-Inventor of Jet Engine to Donate Draper Prize Medal to UD

News release announces that Hans von Ohain will present the Charles Stark Draper medal to the University of Dayton

Report from the HarmoSter study: inter-laboratory comparison of LC-MS/MS measurements of corticosterone, 11-deoxycortisol and cortisone.

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) panels that include glucocorticoid-related steroids are increasingly used to characterize and diagnose adrenal cortical diseases. Limited information is currently available about reproducibility of these measurements among laboratories. The aim of the study was to compare LC-MS/MS measurements of corticosterone, 11-deoxycortisol and cortisone at eight European centers and assess the performance after unification of calibration. Seventy-eight patient samples and commercial calibrators were measured twice by laboratory-specific procedures. Results were obtained according to in-house and external calibration. We evaluated intra-laboratory and inter-laboratory imprecision, regression and agreement against performance specifications derived from 11-deoxycortisol biological variation. Intra-laboratory CVs ranged between 3.3 and 7.7%, 3.3 and 11.8% and 2.7 and 12.8% for corticosterone, 11-deoxycortisol and cortisone, with 1, 4 and 3 laboratories often exceeding the maximum allowable imprecision (MAI), respectively. Median inter-laboratory CVs were 10.0, 10.7 and 6.2%, with 38.5, 50.7 and 2.6% cases exceeding the MAI for corticosterone, 11-deoxycortisol and cortisone, respectively. Median laboratory bias vs. all laboratory-medians ranged from -5.6 to 12.3% for corticosterone, -14.6 to 12.4% for 11-deoxycortisol and -4.0 to 6.5% for cortisone, with few cases exceeding the total allowable error. Modest deviations were found in regression equations among most laboratories. External calibration did not improve 11-deoxycortisol and worsened corticosterone and cortisone inter-laboratory comparability. Method imprecision was variable. Inter-laboratory performance was reasonably good. However, cases with imprecision and total error above the acceptable limits were apparent for corticosterone and 11-deoxycortisol. Variability did not depend on calibration but apparently on imprecision, accuracy and specificity of individual methods. Tools for improving selectivity and accuracy are required to improve harmonization

Lumpability Abstractions of Rule-based Systems

The induction of a signaling pathway is characterized by transient complex formation and mutual posttranslational modification of proteins. To faithfully capture this combinatorial process in a mathematical model is an important challenge in systems biology. Exploiting the limited context on which most binding and modification events are conditioned, attempts have been made to reduce the combinatorial complexity by quotienting the reachable set of molecular species, into species aggregates while preserving the deterministic semantics of the thermodynamic limit. Recently we proposed a quotienting that also preserves the stochastic semantics and that is complete in the sense that the semantics of individual species can be recovered from the aggregate semantics. In this paper we prove that this quotienting yields a sufficient condition for weak lumpability and that it gives rise to a backward Markov bisimulation between the original and aggregated transition system. We illustrate the framework on a case study of the EGF/insulin receptor crosstalk.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

Effect of Network Architecture on Synchronization and Entrainment Properties of the Circadian Oscillations in the Suprachiasmatic Nucleus

In mammals, the suprachiasmatic nucleus (SCN) of the hypothalamus constitutes the central circadian pacemaker. The SCN receives light signals from the retina and controls peripheral circadian clocks (located in the cortex, the pineal gland, the liver, the kidney, the heart, etc.). This hierarchical organization of the circadian system ensures the proper timing of physiological processes. In each SCN neuron, interconnected transcriptional and translational feedback loops enable the circadian expression of the clock genes. Although all the neurons have the same genotype, the oscillations of individual cells are highly heterogeneous in dispersed cell culture: many cells present damped oscillations and the period of the oscillations varies from cell to cell. In addition, the neurotransmitters that ensure the intercellular coupling, and thereby the synchronization of the cellular rhythms, differ between the two main regions of the SCN. In this work, a mathematical model that accounts for this heterogeneous organization of the SCN is presented and used to study the implication of the SCN network topology on synchronization and entrainment properties. The results show that oscillations with larger amplitude can be obtained with scale-free networks, in contrast to random and local connections. Networks with the small-world property such as the scale-free networks used in this work can adapt faster to a delay or advance in the light/dark cycle (jet lag). Interestingly a certain level of cellular heterogeneity is not detrimental to synchronization performances, but on the contrary helps resynchronization after jet lag. When coupling two networks with different topologies that mimic the two regions of the SCN, efficient filtering of pulse-like perturbations in the entrainment pattern is observed. These results suggest that the complex and heterogeneous architecture of the SCN decreases the sensitivity of the network to short entrainment perturbations while, at the same time, improving its adaptation abilities to long term changes

‘Glocal’ Robustness Analysis and Model Discrimination for Circadian Oscillators

To characterize the behavior and robustness of cellular circuits with many unknown parameters is a major challenge for systems biology. Its difficulty rises exponentially with the number of circuit components. We here propose a novel analysis method to meet this challenge. Our method identifies the region of a high-dimensional parameter space where a circuit displays an experimentally observed behavior. It does so via a Monte Carlo approach guided by principal component analysis, in order to allow efficient sampling of this space. This ‘global’ analysis is then supplemented by a ‘local’ analysis, in which circuit robustness is determined for each of the thousands of parameter sets sampled in the global analysis. We apply this method to two prominent, recent models of the cyanobacterial circadian oscillator, an autocatalytic model, and a model centered on consecutive phosphorylation at two sites of the KaiC protein, a key circadian regulator. For these models, we find that the two-sites architecture is much more robust than the autocatalytic one, both globally and locally, based on five different quantifiers of robustness, including robustness to parameter perturbations and to molecular noise. Our ‘glocal’ combination of global and local analyses can also identify key causes of high or low robustness. In doing so, our approach helps to unravel the architectural origin of robust circuit behavior. Complementarily, identifying fragile aspects of system behavior can aid in designing perturbation experiments that may discriminate between competing mechanisms and different parameter sets