Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Optimization of KOH etching process to obtain textured substrates suitable for heterojunction solar cells fabricated by HWCVD

In this work, we have studied the texturization process of (100) c-Si wafers using a low concentration potassium hydroxide solution in order to obtain good quality textured wafers. The optimization of the etching conditions have led to random but uniform pyramidal structures with good optical properties. Then, symmetric heterojunctions were deposited by Hot-Wire CVD onto these substrates and the Quasi-Steady-State PhotoConductance technique was used to measure passivation quality. Little degradation in the effective lifetime and implicit open circuit voltage of these devices (< 20 mV) was observed in all cases. It is especially remarkable that for big uniform pyramids, the open-circuit voltage is comparable to the values obtained on flat substrates.

Design and optimization of selfnanoemulsifying drug delivery systems for enhanced dissolution of gemfibrozil

Self-nanoemulsifying drug delivery systems of gemfibrozil were developed under Quality by Design approach for improvement of dissolution and oral absorption. Preliminary screening was performed to select proper components combination. BoxBehnken experimental design was employed as statistical tool to optimize the formulation variables, X1 (Cremophor® EL), X2 (Capmul® MCM-C8), and X3 (lemon essential oil). Systems were assessed for visual characteristics (emulsification efficacy), turbidity, droplet size, polydispersity index and drug release. Different pH media were also assayed for optimization. Following optimization, the values of formulation components (X1, X2, and X3) were 32.43%, 29.73% and 21.62%, respectively (16.22% of gemfibrozil). Transmission electron microscopy demonstrated spherical droplet morphology. SNEEDS release study was compared to commercial tablets. Optimized SNEDDS formulation of gemfibrozil showed a significant increase in dissolution rate compared to conventional tablets. Both formulations followed Weibull mathematical model release with a significant difference in td parameter in favor of the SNEDDS. Equally amodelistic parameters were calculated being the dissolution efficiency significantly higher for SNEDDS, confirming that the developed SNEDDS formulation was superior to commercial formulation with respect to in vitro dissolution profile. This paper provides an overview of the SNEDDS of the gemfibrozil as a promising alternative to improve oral absorption.

Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer.

Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.

The Optimization of Flotation Process Parameters in the Deinking Plant

Tämän diplomityön tavoitteena oli sekundäärisen esiflotaation optimointi Stora Enso Sachsen GmbH:n tehtaalla. Optimoinnin muuttujana käytettiin vaahdon määrää ja optimointiparametreinä ISO-vaaleutta, saantoja sekä tuhkapitoisuutta. Lisäksi tutkittiin flotaatiosakeuden vaikutusta myös muihin tehtaan flotaatioprosesseihin. Kirjallisuusosassa tarkasteltiin flotaatiotapahtumaa, poistettavien partikkeleiden ja ilmakuplien kontaktia, vaahdon muodostumista sekä tärkeimpiä käytössä olevia siistausflotaattoreiden laiteratkaisuja. Kokeellisessa osassa tutkittiin flotaatiosakeuden pienetämisen vaikutuksia tehtaan flotaatioprosesseihin tuhkapitoisuuden, ISO-vaaleuden, valon sironta- ja valon absorpiokerrointen kannalta. Sekundäärisen esiflotaation optimonti suoritettiin muuttamalla vaahdon määrää kolmella erilaisella injektorin koolla, (8 mm, 10 mm ja 13 mm), joista keskimmäinen kasvattaa 30 % massan tilavuusvirtaa ilmapitoisuuden muodossa. Optimonnin tarkoituksena oli kasvattaa hyväksytyn massajakeen ISO-vaaleutta, sekä kasvattaa kuitu- ja kokonaissaantoa sekundäärisessä esiflotaatiossa. Flotaatiosakeuden pienentämisellä oli edullisia vaikutuksia ISO-vaaleuteen ja valon sirontakertoimeen kussakin flotaatiossa. Tuhkapitoisuus pieneni sekundäärisissä flotaatioissa enemmän sakeuden ollessa pienempi, kun taas primäärisissä flotaatiossa vaikutus oli päinvastainen. Valon absorptiokerroin parani jälkiflotaatioissa alhaisemmalla sakeudella, kun taas esiflotaatioissa vaikutus oli päinvastainen. Sekundäärisen esiflotaation optimoinnin tuloksena oli lähes 5 % parempi ISO-vaaleus hyväksytyssä massajakeessa. Kokonaissaanto parani optimoinnin myötä 5 % ja kuitusaanto 2 %. Saantojen nousu tuottaa vuosittaisia säästöjä siistauslaitoksen tuotantokapasiteetin noustessa 0,5 %. Tämän lisäksi sekundäärisessä esiflotaatiossa rejektoituvan massavirran pienentyminen tuottaa lisäsäästöjä tehtaan voimalaitoksella.

Some optimization and decision problems in proportional reinsurance

Reinsurance is one of the tools that an insurer can use to mitigate the underwriting risk and then to control its solvency. In this paper, we focus on the proportional reinsurance arrangements and we examine several optimization and decision problems of the insurer with respect to the reinsurance strategy. To this end, we use as decision tools not only the probability of ruin but also the random variable deficit at ruin if ruin occurs. The discounted penalty function (Gerber & Shiu, 1998) is employed to calculate as particular cases the probability of ruin and the moments and the distribution function of the deficit at ruin if ruin occurs.

Cooling system optimization in medium-speed engines

Tässä työssä optimoidaan keskinopean Wärtsilä 32 -dieselmoottorin jäähdytysjärjestelmää ja tutkitaan taajuusmuuttajien käyttömahdollisuutta kiertopumppujen yhteydessä niin, että järjestelmässä saataisiin kiertämään vain kulloinkin tarvittava määrä vettä. Tutkimuksen mallinnus on toteutettu laatimalla aiemmin käytössä olleista yksinkertaisista simulointimalleista yksi malli, johon on sisällytetty sekä virtauksen että lämmönsiirron laskenta, jotka on aiemmin mallinnettu erillisillä ohjelmilla. Diplomityö on osa projektia, joka on tehty Sähkötekniikan osaston tutkijan Mikko Pääkkösen kanssa yhteistyössä. Tämän diplomityö keskittyy lähinnä virtausteknisiin ja lämmönsiirtoon liittyviin asioihin, kun taas sähkötekniikan osuus on esitetty Mikko Pääkkösen raportissa. Tulosten perustella voidaan sanoa, että taajuusmuuttajakäyttö kannattaa kiertopumppujen yhteydessä. Käyttämällä pumppujen virtaussäätöä voidaan jäähdytysjärjestelmästä jättää monia komponentteja, kuten termostaattiventtiilejä pois. Mallinnetut yksinkertaiset piiriratkaisut näyttävät toimivan ainakin yleisellä tasolla. Tutkimusta pumppujen säädöstä ja tässä projektissa luoduista jäähdytysjärjestelmäkonfiguraatioista kannattaa jatkaa.

Optimization of Radiation Dose and Image Quality in Musculoskeletal CT: Emphasis on Iterative Reconstruction Techniques (Part 1).

Computed tomography (CT) is a modality of choice for the study of the musculoskeletal system for various indications including the study of bone, calcifications, internal derangements of joints (with CT arthrography), as well as periprosthetic complications. However, CT remains intrinsically limited by the fact that it exposes patients to ionizing radiation. Scanning protocols need to be optimized to achieve diagnostic image quality at the lowest radiation dose possible. In this optimization process, the radiologist needs to be familiar with the parameters used to quantify radiation dose and image quality. CT imaging of the musculoskeletal system has certain specificities including the focus on high-contrast objects (i.e., in CT of bone or CT arthrography). These characteristics need to be taken into account when defining a strategy to optimize dose and when choosing the best combination of scanning parameters. In the first part of this review, we present the parameters used for the evaluation and quantification of radiation dose and image quality. In the second part, we discuss different strategies to optimize radiation dose and image quality at CT, with a focus on the musculoskeletal system and the use of novel iterative reconstruction techniques.

Optimization of Radiation Dose and Image Quality in Musculoskeletal CT: Emphasis on Iterative Reconstruction Techniques (Part 2).

Computed tomography (CT) is a modality of choice for the study of the musculoskeletal system for various indications including the study of bone, calcifications, internal derangements of joints (with CT arthrography), as well as periprosthetic complications. However, CT remains intrinsically limited by the fact that it exposes patients to ionizing radiation. Scanning protocols need to be optimized to achieve diagnostic image quality at the lowest radiation dose possible. In this optimization process, the radiologist needs to be familiar with the parameters used to quantify radiation dose and image quality. CT imaging of the musculoskeletal system has certain specificities including the focus on high-contrast objects (i.e., in CT of bone or CT arthrography). These characteristics need to be taken into account when defining a strategy to optimize dose and when choosing the best combination of scanning parameters. In the first part of this review, we present the parameters used for the evaluation and quantification of radiation dose and image quality. In the second part, we discuss different strategies to optimize radiation dose and image quality of CT, with a focus on the musculoskeletal system and the use of novel iterative reconstruction techniques.

Question Waves: A multicast query routing algorithm for social search

This paper describes Question Waves, an algorithm that can be applied to social search protocols, such as Asknext or Sixearch. In this model, the queries are propagated through the social network, with faster propagation through more trustable acquaintances. Question Waves uses local information to make decisions and obtain an answer ranking. With Question Waves, the answers that arrive first are the most likely to be relevant, and we computed the correlation of answer relevance with the order of arrival to demonstrate this result. We obtained correlations equivalent to the heuristics that use global knowledge, such as profile similarity among users or the expertise value of an agent. Because Question Waves is compatible with the social search protocol Asknext, it is possible to stop a search when enough relevant answers have been found; additionally, stopping the search early only introduces a minimal risk of not obtaining the best possible answer. Furthermore, Question Waves does not require a re-ranking algorithm because the results arrive sorted

Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

Mapping the microstructure properties of the local tissues in the brain is crucial to understand any pathological condition from a biological perspective. Most of the existing techniques to estimate the microstructure of the white matter assume a single axon orientation whereas numerous regions of the brain actually present a fiber-crossing configuration. The purpose of the present study is to extend a recent convex optimization framework to recover microstructure parameters in regions with multiple fibers.