Search

This article presents a study on the operational stability of laboratory oxidation ditches, designated for synthetic and real wastewater and operable at low concentrations of dissolved oxygen. The project encompassed the stability monitoring of activated sludge depending on sedimentation characteristics and hydrobiological indicator microorganisms, determining (1) the size of sludge floccules and (2) the main functional groups of microorganisms identified in the course of the PCR analysis and reaction rates, plotted using the Michaelis–Menten enzymatic kinetics for the mixed culture biomass. The most stable system involves a bioreactor featuring dissolved oxygen gradients that range from 1.9 to 0.15 mg/L s, a specific organic load of 0.21 gBOD/g/d and a hydraulic retention time of 12 h. A built-in settling tank allows the consideration of the potential generation of large floccules of activated sludge in oxidation ditches (at least 300 μm) that increase the efficiency of simultaneous nitrification and denitrification. Thus, the obtained reaction rates can be used in calculations and simulations of the operation of oxidation ditches at low concentrations of dissolved oxygen.

Les microARN sont de petits ARN non codants d'environ 22 nucléotides impliqués dans la régulation de l'expression des gènes. Ils ciblent les régions complémentaires des molécules d'ARN messagers que ces gènes codent et ajustent leurs niveaux de traduction en protéines en fonction des besoins de la cellule. En s'attachant à leurs cibles par complémentarité partielle de leurs séquences, ces deux groupes de molécules d'ARN compétitionnent activement pour former des interactions régulatrices. Par conséquent, prédire quantitativement les concentrations d'équilibres des duplexes formés est une tâche qui doit prendre un compte plusieurs facteurs dont l'affinité pour l'hybridation, la capacité à catalyser la cible, la coopérativité et l'accessibilité de l'ARN cible. Dans le modèle que nous proposons, miRBooking 2.0, chaque interaction possible entre un microARN et un site sur un ARN cible pour former un duplexe est caractérisée par une réaction enzymatique. Une réaction de ce type opère en deux phases : une formation réversible d'un complexe enzyme-substrat, le duplexe microARN-ARN, suivie d'une conversion irréversible du substrat en produit, un ARN cible dégradé, et de la restitution l'enzyme qui pourra participer à une nouvelle réaction. Nous montrons que l'état stationnaire de ce système, qui peut comporter jusqu'à 10 millions d'équations en pratique, est unique et son jacobien possède un très petit nombre de valeurs non-nulles, permettant sa résolution efficace à l'aide d'un solveur linéaire épars. Cette solution nous permet de caractériser précisément ce mécanisme de régulation et d'étudier le rôle des microARN dans un contexte cellulaire donné. Les prédictions obtenues sur un modèle de cellule HeLa corrèlent significativement avec un ensemble de données obtenu expérimentalement et permettent d'expliquer remarquablement les effets de seuil d'expression des gènes. En utilisant ces prédictions comme condition initiale et une méthode d'intégration numérique, nous simulons en temps réel la réponse du système aux changements de conditions expérimentales. Nous appliquons ce modèle pour cibler des éléments impliqués dans la transition épithélio-mésenchymateuse (EMT), un mécanisme biologique permettant aux cellules d'acquérir une mobilité essentielle pour proliférer. En identifiant des éléments transcrits différentiellement entre les conditions épithéliale et mésenchymateuse, nous concevons des microARN synthétiques spécifiques pour interférer avec cette transition. Pour ce faire, nous proposons une méthode basée sur une recherche gloutonne parallèle pour rechercher efficacement l'espace de la séquence du microARN et présentons des résultats préliminaires sur des marqueurs connus de l'EMT., MicroRNAs are small non-coding RNAs of approximately 22 nucleotide long involved in the regulation of gene expression. They target complementary regions to the RNA transcripts molecules that these genes encode and adjust the concentration according to the needs of the cell. As microRNAs and their RNA targets binds each other with imperfect complementarity, these two groups actively compete to form regulatory interactions. Consequently, attempting to quantitatively predict their equilibrium concentrations is a task that must take several factors into account, including the affinity for hybridization, the ability to catalyze the target, cooperation, and RNA accessibility. In the model we propose, miRBooking 2.0, each possible interaction between a microRNA and a binding site on a target RNA is characterized by an enzymatic reaction. A reaction of this type operates in two phases: a reversible formation of an enzyme-substrate complex, the microRNA-RNA duplex, and an irreversible conversion of the substrate in an RNA degradation product that restores the enzyme which can subsequently participate to other reactions. We show that the stationary state of this system, which can include up to 10 million equations in practice, has a very shallow Jacobian, allowing its efficient resolution using a sparse linear solver. This solution allows us to characterize precisely the mechanism of regulation and to study the role of microRNAs in a given cellular context. Predictions obtained on a HeLa S3 cell model correlate significantly with a set of experimental data obtained experimentally and can remarkably explain the expression threshold effects of genes. Using this solution as an initial condition and an explicit method of numerical integration, we simulate in real time the response of the system to changes of experimental conditions. We apply this model to target elements involved in the Epithelio-Mesenchymal Transition (EMT), an important mechanism of tumours proliferation. By identifying differentially expressed elements between the two conditions, we design synthetic microRNAs to interfere with the transition. To do so, we propose a method based on a parallel greedy best-first search to efficiently crawl the sequence space of the microRNA and present preliminary results on known EMT markers.

The enzymatic biofuel cells (EBFCs) are considered as an attractive candidate for powering future implantable medical devices. In this study, a computational model of EBFCs based on three-dimensional (3-D) interdigitated microelectrode arrays was conducted. The main focus of this research is to investigate the effect of different designs and spatial distributions of the microelectrode arrays on mass transport of fuels, enzymatic reaction rate, open circuit output potential and current density. To optimize the performance of the EBFCs, numerical simulations have been performed for cylindrical electrodes with various electrode heights and well widths. Optimized cell performance was obtained when the well width is half of the height of the 3-D electrode. In addition, semi-elliptical shaped electrode is preferred based on the results from current density and resistive heating simulation.

A novel least squares optimization of parameters in Michaelis-Menten enzyme kinetics has been developed. The method is based on elimination of linear parameter from so called normal equations which transforms a non-linear, two-parameter optimization problem into one of finding a root of non-linear equation. The algorithm is simple and has guaranteed convergence with initial guess of zero for KM. Data set from literature is used to illustrate feasibility of the method and accuracy of the solution in comparison with linearization methods and general optimization technique., Razvijena je nova optimizacijska metoda za određivanje parametara u Michaelis-Mentenovoj kinetici enzimskih reakcija. Metoda se temelji na eliminiranju linearnoga parametra iz normalnih jednad`bi, što transformira nelinearni optimizacijski problem u problem nalaženja korijena nelinearne jednadžbe. Algoritam je učinkovit i ima zajamčenu konvergenciju s početnom vrijednošću nula za parameter KM. Skup podataka iz literature obrađen je za ilustraciju upotrebljivost i točnosti rješenja predložene metode u usporedbi s metodama linearizacije i općom metodom nelinearne optimizacije.