Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks

Motivation: Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs). Results: In this work, we present an optimal control-based methodology for designing optimal stimulus experiments aimed at robust model discrimination. For estimating the time-varying model response PDF, which results from the nonlinear propagation of the parameter PDF under the ODE dynamics, we suggest using the sigma-point approach. Using the model overlap (expected likelihood) as a robust discrimination criterion to measure dissimilarities between expected model response PDFs, we benchmark the proposed nonlinear design approach against linearization with respect to prediction accuracy and design quality for two nonlinear biological reaction networks. As shown, the sigma-point outperforms the linearization approach in the case of widely distributed parameter sets and/or existing multiple steady states. Since the sigma-point approach scales linearly with the number of model parameter, it can be applied to large systems for robust experimental planning. Availability: An implementation of the method in MATLAB/AMPL is available at http://www.uni-magdeburg.de/ivt/svt/person/rf/roed.html. Contact: [email protected] Supplementary information: Supplementary data are are available at Bioinformatics online

Hybrid data-driven and mechanistic modeling approaches for multiscale material and process design

The world’s increasing population requires the process industry to produce food, fuels, chemicals, and consumer products in a more efficient and sustainable way. Functional process materials lie at the heart of this challenge. Traditionally, new advanced materials are found empirically or through trial-and-error approaches. As theoretical methods and associated tools are being continuously improved and computer power has reached a high level, it is now efficient and popular to use computational methods to guide material selection and design. Due to the strong interaction between material selection and the operation of the process in which the material is used, it is essential to perform material and process design simultaneously. Despite this significant connection, the solution of the integrated material and process design problem is not easy because multiple models at different scales are usually required. Hybrid modeling provides a promising option to tackle such complex design problems. In hybrid modeling, the material properties, which are computationally expensive to obtain, are described by data-driven models, while the well-known process-related principles are represented by mechanistic models. This article highlights the significance of hybrid modeling in multiscale material and process design. The generic design methodology is first introduced. Six important application areas are then selected: four from the chemical engineering field and two from the energy systems engineering domain. For each selected area, state-of-the-art work using hybrid modeling for multiscale material and process design is discussed. Concluding remarks are provided at the end, and current limitations and future opportunities are pointed out

Eccentric lamellar keratolimbal grafts harvested with a manually guided microkeratome

Background: To perform lamellar keratolimbal allograft transplantation in a one- step procedure with a single graft, we investigated the feasibility of harvesting eccentric lamellar keratolimbal grafts from conventionally processed corneoscleral buttons using a manually guided microkeratome in conjunction with an artificial anterior chamber system. Methods: We used the Moria LSK- One microkeratome and the automated lamellar therapeutic keratoplasty ( ALTK) system ( Antony, France). Ten human donor eyes were used to obtain single- piece lamellar keratolimbal grafts. Specimens were processed for light and electron microscopy. Results: Eccentric keratolimbal grafts could be obtained from all human donor buttons. Grafts include a crescent- shaped limbal and a large corneal portion. No visible damage to the limbal region was discernible. Conclusion: Our data show that the LSK- One microkeratome in conjunction with the ALTK system allows harvesting eccentric keratolimbal grafts from donor corneoscleral buttons. Copyright (c) 2007 S. Karger AG, Basel

Electrochemical evaluation of the de-/re-activation of oxygen evolving Ir oxide

Understanding the influence of dynamic and stationary polarization on the deactivation of state-of-the-art IrOx catalysts is imperative for the design and operation of robust and efficient proton exchange membrane water electrolyzers. In this work, the deactivation and activity regeneration of a commercial IrOx catalyst investigated under potentiodynamic and potentiostatic conditions in acidic media by means of rotating disk electrode and electrogravimetry. Systematic electrochemical protocols were designed to decouple reversible from irreversible activity losses. Cyclic voltammetry provided a metric of the active surface area and traced the charge growth under different oxygen evolution reaction conditions. A direct logt dependent charge growth is observed, accompanied by the same fractional kinetic activity decay under potentiodynamic conditions. The loss is essentially recoverable after electrochemical reductive treatment, however at the expense of mild material dissolution. In contrast, extended potentiostatic operation induced irreversible intrinsic degradation after a critical time (0.5-1 h), accompanied by stability enhancement. This irreversible deactivation attributed to a gradual transformation of the hydrated IrOx to a dehydrated condensed oxide. Our results suggest that Ir dissolution during the regenerative treatment is not prohibitive, as long as the low potential modulations are not frequent