Reaction of N-Acetylcysteine with Cu2+: Appearance of Intermediates with High Free Radical Scavenging Activity: Implications for Anti-/Pro-Oxidant Properties of Thiols.

We studied the kinetics of the reaction of N-acetyl-l-cysteine (NAC or RSH) with cupric ions at an equimolar ratio of the reactants in aqueous acid solution (pH 1.4−2) using UV/Vis absorption and circular dichroism (CD) spectroscopies. Cu2+ showed a strong catalytic effect on the 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonate) radical (ABTSr) consumption and autoxidation of NAC. Difference spectra revealed the formation of intermediates with absorption maxima at 233 and 302 nm (ε302/Cu > 8 × 103 M−1 cm−1) and two positive Cotton effects centered at 284 and 302 nm. These intermediates accumulate during the first, O2-independent, phase of the NAC autoxidation. The autocatalytic production of another chiral intermediate, characterized by two positive Cotton effects at 280 and 333 nm and an intense negative one at 305 nm, was observed in the second reaction phase. The intermediates are rapidly oxidized by added ABTSr; otherwise, they are stable for hours in the reaction solution, undergoing a slow pH- and O2-dependent photosensitive decay. The kinetic and spectral data are consistent with proposed structures of the intermediates as disulfide-bridged dicopper(I) complexes of types cis-/trans-CuI2(RS)2(RSSR) and CuI2(RSSR)2. The electronic transitions observed in the UV/Vis and CD spectra are tentatively attributed to Cu(I) → disulfide charge transfer with an interaction of the transition dipole moments (exciton coupling). The catalytic activity of the intermediates as potential O2 activators via Cu(II) peroxo-complexes is discussed. A mechanism for autocatalytic oxidation of Cu(I)−thiolates promoted by a growing electronically coupled −[CuI2(RSSR)]n− polymer is suggested. The obtained results are in line with other reported observations regarding copper-catalyzed autoxidation of thiols and provide new insight into these complicated, not yet fully understood systems. The proposed hypotheses point to the importance of the Cu(I)−disulfide interaction, which may have a profound impact on biological systems.

Turbulent pattern in the 1,4-cyclohexanedione Belousov-Zhabotinsky reaction.

Chemical turbulence was observed experimentally in the 1,4-cyclohexanedione Belousov-Zhabotinsky (CHD-BZ) reaction in a double layer consisting of a catalyst-loaded gel and uncatalyzed liquid on a Petri dish. The chemical patterns in the CHD-BZ reaction occur spontaneously in various forms as follows: the initial, regular, transient, and turbulent patterns, subsequently. These four patterns are characterized by using the two-dimensional Fourier transform (2D-FT). Mechanism of the onset of the turbulence in the CHD-BZ reaction is proposed. Turbulence in the CHD-BZ reaction is reproducible under a well defined protocol and it exists for a period of time of about 50 minutes, which is sufficiently long to offer a good opportunity to study and control the turbulence in the future. Two models of the BZ reaction were used to simulate the spiral breakup. Both are capable of producing spiral turbulence from initially regular patterns in each layer and reflect certain features of dynamics observed in experiments.

Advanced Chemical Computing Using Discrete Turing Patterns in Arrays of Coupled Cells.

We examine dynamical switching among discrete Turing patterns that enable chemical computing performed by mass-coupled reaction cells arranged as arrays with various topological configurations: three coupled cells in a cyclic array, four coupled cells in a linear array, four coupled cells in a cyclic array, and four coupled cells in a branched array. Each cell is operating as a continuous stirred tank reactor, within which the glycolytic reaction takes place, represented by a skeleton inhibitor-activator model where ADP plays the role of activator and ATP is the inhibitor. The mass coupling between cells is assumed to be operating in three possible transport regimes: (i) equal transport coefficients of the inhibitor and activator (ii) slightly faster transport of the activator, and (iii) strongly faster transport of the inhibitor. Each cellular array is characterized by two pairs of tunable parameters, the rate coefficients of the autocatalytic and inhibitory steps, and the transport coefficients of the coupling. Using stability and bifurcation analysis we identified conditions for occurrence of discrete Turing patterns associated with non-uniform stationary states. We found stable symmetric and/or asymmetric discrete Turing patterns coexisting with stable uniform periodic oscillations. To switch from one of the coexisting stable regimes to another we use carefully targeted perturbations, which allows us to build systems of logic gates specific to each topological type of the array, which in turn enables to perform advanced modes of chemical computing. By combining chemical computing techniques in the arrays with glycolytic excitable channels, we propose a cellular assemblage design for advanced chemical computing.

Oscillations of pH in the urea-urease system in a membrane reactor.

Herein, we present direct experimental evidence of pH oscillatory dynamics in the urea-urease enzymatic reaction conducted in a continuous reactor-membrane-reservoir system. Our results are consistent with earlier model predictions requiring differential transport of H+ and substrate. We report oscillations with periods in hundreds of seconds and the amplitude of ∼0.1 pH units.

Constrained stoichiometric network analysis.

Stoichiometric network analysis (SNA) is a method for studying the stability of steady states of stoichiometric systems by decomposing the corresponding network into elementary subnetworks (also known as extreme currents) and identifying those that may cause loss of a network's stability via interplay of positive and negative feedback. Experimentally studied complex (bio)chemical reactions often display dynamical instabilities leading to oscillations or bistable switches. When modelling such systems, a frequently met case is that an assumed detailed mechanism in terms of power law kinetics is available, but some of the rate coefficients are unknown and obtaining them by traditional kinetic methods based on a least-square fit is cumbersome or unfeasible. We propose a method combining the SNA and experimental data at the point of instability, which provides an estimate of the unknown rate coefficients along with unknown steady state concentrations. The core of the method rests in using constrained linear optimization to find a combination of the elementary subnetworks such that the dominant instability-causing subnetwork is just counter-balanced by stabilizing effects of all other subnetworks to obtain the instability threshold, and at the same time, the experimentally available data (inflow constraints, measured steady state concentrations of some species, frequency of emerging oscillations, etc.) are exactly matched. We illustrate this approach by examining two classical chemical oscillators: the Brusselator chosen as the simplest model for illustration of our methods and the Belousov-Zhabotinsky reaction and its mechanism represented by the Oregonator model as a more advanced example.

Identifying the Oscillatory Mechanism of the Glucose Oxidase-Catalase Coupled Enzyme System.

We provide experimental evidence of periodic and aperiodic oscillations in an enzymatic system of glucose oxidase-catalase in a continuous-flow stirred reactor coupled by a membrane with a continuous-flow reservoir supplied with hydrogen peroxide. To describe such dynamics, we formulate a detailed mechanism based on partial results in the literature. Finally, we introduce a novel method for estimation of unknown kinetic parameters. The method is based on matching experimental data at an oscillatory instability with stoichiometric constraints of the mechanism formulated by applying the stability theory of reaction networks. This approach has been used to estimate rate coefficients in the catalase part of the mechanism. Remarkably, model simulations show good agreement with the observed oscillatory dynamics, including apparently chaotic intermittent behavior. Our method can be applied to any reaction system with an experimentally observable dynamical instability.

Minimal oscillating subnetwork in the Huang-Ferrell model of the MAPK cascade.

Prompted by the recent growing evidence of oscillatory behavior involving MAPK cascades we present a systematic approach of analyzing models and elucidating the nature of biochemical oscillations based on reaction network theory. In particular, we formulate a minimal biochemically consistent mass action subnetwork of the Huang-Ferrell model of the MAPK signalling that provides an oscillatory response when a parameter controlling the activation of the top-tier kinase is varied. Such dynamics are either intertwined with or separated from the earlier found bistable/hysteretic behavior in this model. Using the theory of stability of stoichiometric networks, we reduce the original MAPK model, convert kinetic to convex parameters and examine those properties of the minimal subnetwork that underlie the oscillatory dynamics. We also use the methods of classification of chemical oscillatory networks to explain the rhythmic behavior in physicochemical terms, i.e., we identify of the role of individual biochemical species in positive and negative feedback loops and describe their coordinated action leading to oscillations. Our approach provides an insight into dynamics without the necessity of knowing rate coefficients and thus is useful prior the statistical evaluation of parameters.

Use of Phase Transition Curves for Testing Models of the pH-Oscillatory Hydrogen Peroxide-Thiosulfate-Sulfite Reaction.

The reaction system hydrogen peroxide-thiosulfate-sulfite in diluted sulfuric acid (HPTS) displays strongly nonlinear dynamics when operated in a continuous-flow stirred tank reactor. Due to a crucial role of hydrogen ion during the reaction, this system is a prime example of an inorganic pH-oscillator. Under specific external conditions the system exhibits multiple steady states, periodic oscillations and chaotic behavior. We focus on evaluating alternative kinetic models by exploring phase resetting of the periodic oscillatory regime caused by a single-pulse perturbation with various reacting species. Phase transition curve (PTC), the plot of phase after the resetting against the phase of perturbation, is a convenient characteristic of the oscillatory dynamics adopted as a major tool in this work. Experimental results for hydrogen ions, hydroxide ions, thiosulfate ions, sulfite ions, and hydrogen sulfite ions used as perturbants are systematically compared with calculations under corresponding conditions using two available reaction mechanisms. In addition, we use the stoichiometric network analysis to identify possible core oscillatory subnetworks in the models and choose the one that corresponds best to the measured PTCs.

Oscillations and patterns in a model of simultaneous CO and C2H2 oxidation and NO(x) reduction in a cross-flow reactor.

A model describing simultaneous catalytic oxidation of CO and C2H2 and reduction of NOx in a cross-flow tubular reactor is explored with the aim of relating spatiotemporal patterns to specific pathways in the mechanism. For that purpose, a detailed mechanism proposed for three-way catalytic converters is split into two subsystems, (i) simultaneous oxidation of CO and C2H2, and (ii) oxidation of CO combined with NOx reduction. The ability of these two subsystems to display mechanism-specific dynamical effects is studied initially by neglecting transport phenomena and applying stoichiometric network and bifurcation analyses. We obtain inlet temperature - inlet oxygen concentration bifurcation diagrams, where each region possessing specific dynamics - oscillatory, bistable and excitable - is associated with a dominant reaction pathway. Next, the spatiotemporal behaviour due to reaction kinetics combined with transport processes is studied. The observed spatiotemporal patterns include phase waves, travelling fronts, pulse waves and spatiotemporal chaos. Although these types of pattern occur generally when the kinetic scheme possesses autocatalysis, we find that some of their properties depend on the underlying dominant reaction pathway. The relation of patterns to specific reaction pathways is discussed.

Control of Turing patterns and their usage as sensors, memory arrays, and logic gates.

We study a model system of three diffusively coupled reaction cells arranged in a linear array that display Turing patterns with special focus on the case of equal coupling strength for all components. As a suitable model reaction we consider a two-variable core model of glycolysis. Using numerical continuation and bifurcation techniques we analyze the dependence of the system's steady states on varying rate coefficient of the recycling step while the coupling coefficients of the inhibitor and activator are fixed and set at the ratios 100:1, 1:1, and 4:5. We show that stable Turing patterns occur at all three ratios but, as expected, spontaneous transition from the spatially uniform steady state to the spatially nonuniform Turing patterns occurs only in the first case. The other two cases possess multiple Turing patterns, which are stabilized by secondary bifurcations and coexist with stable uniform periodic oscillations. For the 1:1 ratio we examine modular spatiotemporal perturbations, which allow for controllable switching between the uniform oscillations and various Turing patterns. Such modular perturbations are then used to construct chemical computing devices utilizing the multiple Turing patterns. By classifying various responses we propose: (a) a single-input resettable sensor capable of reading certain value of concentration, (b) two-input and three-input memory arrays capable of storing logic information, (c) three-input, three-output logic gates performing combinations of logical functions OR, XOR, AND, and NAND.

Classification of the pH-oscillatory hydrogen peroxide-thiosulfate-sulfite reaction.

The reaction of hydrogen peroxide with thiosulfate and sulfite in acidic solution is characterized by marked temporal pH variations suggesting autocatalytic nature of hydrogen ions. When carried out in a continuous-flow stirred tank reactor this reaction provides nonlinear dynamical regimes including periodic oscillations, chaotic behavior, and multiple steady states coexisting over a range of operating conditions. The aim of the presented experimental study is a classification of the role of species and the underlying mechanism in the periodic oscillatory mode by applying single pulse additions of chosen reaction species. The external perturbations at various phases of the periodically oscillating system may cause phase advance or phase delay of the oscillations. The resulting phase transition curves are obtained for hydrogen ions, hydroxide ions, thiosulfate ions, sulfite ions, and hydrogen sulfite ions. These curves are compared with the phase transition curves calculated using the prototype mechanisms representing categories of chemical oscillators established in previous work. We found our system to be compatible with the mechanism of the category 1CX.

Electrodiffusion kinetics of ionic transport in a simple membrane channel.

We employ numerical techniques for solving time-dependent full Poisson-Nernst-Planck (PNP) equations in 2D to analyze transient behavior of a simple ion channel subject to a sudden electric potential jump across the membrane (voltage clamp). Calculated spatiotemporal profiles of the ionic concentrations and electric potential show that two principal exponential processes can be distinguished in the electrodiffusion kinetics, in agreement with original Planck's predictions. The initial fast process corresponds to the dielectric relaxation, while the steady state is approached in a second slower exponential process attributed to the nonlinear ionic redistribution. Effects of the model parameters such as the channel length, height of the potential step, boundary concentrations, permittivity of the channel interior, and ionic mobilities on electrodiffusion kinetics are studied. Numerical solutions are used to determine spatiotemporal profiles of the electric field, ionic fluxes, and both the conductive and displacement currents. We demonstrate that the displacement current is a significant transient component of the total electric current through the channel. The presented results provide additional information about the classical voltage-clamp problem and offer further physical insights into the mechanism of electrodiffusion. The used numerical approach can be readily extended to multi-ionic models with a more structured domain geometry in 2D or 3D, and it is directly applicable to other systems, such as synthetic nanopores, nanofluidic channels, and nanopipettes.

Oscillatory flow accelerates autocrine signaling due to nonlinear effect of convection on receptor-related actions.

We study effects of oscillatory convective flow in extracellular space on the velocity of chemical signal propagation having a form of a front wave above a cellular layer. We found that the time-averaged propagation velocity under oscillatory flow for a particular Péclet number amplitude is slower than the velocity under steady laminar flow regime for the same value of the Péclet number, but significantly faster than under no-flow conditions. We derive asymptotic values of the propagation velocity and asymptotic characteristics of the corresponding concentration fronts in high- and low-frequency regimes and show that the reason for the observed velocity increase under the oscillatory flow stems from a nonlinear dependence of the propagation velocity on the Péclet number, particularly from the convex character of the dependence. Our findings suggest that the specific responses of cellular cultures to different flow conditions in the extracellular space (for example, expression of atherosclerosis protective genes under steady laminar flow but not under oscillatory flow) is a consequence of a nonlinear coupling between the extracellular transport and complex intracellular reaction cascades forming a positive feedback loop of the autocrine signaling. This mechanism can operate independently of, or in conjunction with, a direct stress-sensing due to mechanotransduction.

Effects of convective transport on chemical signal propagation in epithelia.

We study effects of convective transport on a chemical front wave representing a signal propagation at a simple (single layer) epithelium by means of mathematical modeling. Plug flow and laminar flow regimes were considered. We observed a nonmonotonous dependence of the propagation velocity on the ligand receptor binding constant under influence of the convective transport. If the signal propagates downstream, the region of high velocities becomes much broader and spreads over several orders of magnitude of the binding constant. When the convective transport is oriented against the propagating signal, either velocity of the traveling front wave is slowed down or the traveling front wave can stop or reverse the direction of propagation. More importantly, chemical signal in epithelial systems influenced by the convective transport can propagate almost independently of the ligand-receptor binding constant in a broad range of this parameter. Furthermore, we found that the effects of the convective transport becomes more significant in systems where either the characteristic dimension of the extracellular space is larger/comparable with the spatial extent of the ligand diffusion trafficking or the ligand-receptor binding/ligand diffusion rate ratio is high.

Dynamical regimes of a pH-oscillator operated in two mass-coupled flow-through reactors.

We present results of experiments focused on emergent and cooperative dynamics in a system of two coupled flow-through stirred reaction cells with diffusion-like mass exchange and a strongly nonlinear chemical reaction between hydrogen peroxide and thiosulphate catalysed by cupric ions in diluted solution of sulphuric acid. Due to complex mechanism, in which a crucial role is played by hydrogen and/or hydroxide ions, dynamics in a single cell entail multiple stationary states, excitability and oscillations conveniently indicated by measuring pH. When coupled, the system shows a plethora of dynamical regimes depending on the coupling strength and flow rate. Under certain conditions both cells display dynamics close to that in the absence of coupling, but majority of the regimes are emergent and cannot be deduced from dynamics of decoupled reactors. The most prominent is a stationary state maintaining highly acidic values of pH in one of the reactors and weakly acidic in the other. When each cell is set to display excitability and the coupled system is externally perturbed, the cells may cooperate and transmit excitations elicited by pulsed perturbations in one cell to the other. Periodic pulses induce firing patterns marked by a various degree of propagated excitations and by being periodic or irregular.

Stoichiometric network analysis of the photochemical processes in the mesopause region.

The mechanism of photochemistry in the mesopause region entails a chemical oscillator forced by solar short-wave radiation. A model with periodic forcing between day and night conditions produces nonlinear dynamics including period-doubling bifurcations and chaos. The photochemical mechanism represents a network involving positive and negative feedbacks that can be examined by methods of stoichiometric network analysis. We use these methods to decompose the network into irreducible subnetworks and then apply linear stability analysis to find all possible sources of oscillatory instabilities in the mesopause chemistry. These oscillators are classified according to topological features in their reaction networks and phase shifts of oscillating species. We subsequently compare phase shifts indicated by the network analysis with those from direct simulations to identify a specific subnetwork in the mechanism underlying the complex oscillatory dynamics observed in earlier simulations.

Front waves and complex spatiotemporal patterns in a reaction-diffusion-convection system with thermokinetic autocatalysis.

We analyze dynamics of stationary nonuniform patterns, traveling waves, and spatiotemporal chaos in a simple model of a tubular cross-flow reactor. The reactant is supplied continuously via convective flow and/or by diffusion through permeable walls of the reactor. First order exothermic reaction kinetics is assumed and the system is described by mass and energy balances forming coupled reaction-diffusion-convection equations. Dynamical regimes of the reaction-diffusion subsystem range from pulses and fronts to periodic waves and complex chaotic behavior. Two distinct types of chaotic patterns are identified and characterized by Lyapunov dimension. Next we examine the effects of convection on various types of the reaction-diffusion regimes. Remarkable zigzag fronts and steady state patterns are found despite the absence of differential flow. We employ continuation techniques to elucidate the existence and form of these patterns.

Mixed-mode oscillations in a homogeneous pH-oscillatory chemical reaction system.

We examine experimentally a chemical system in a flow-through stirred reactor, which is known to provide large-amplitude oscillations of the pH value. By systematic variation of the flow rate, we find that the system displays hysteresis between a steady state and oscillations, and more interestingly, a transition to chaos involving mixed-mode oscillations. The basic pattern of the measured pH in the mixed-mode regime includes a large-scale peak followed by a series of oscillations on a much smaller scale, which are usually highly irregular and of variable duration. The bifurcation diagram shows that chaos sets in via a period-doubling route observed on the large-amplitude scale, but simultaneously small-amplitude oscillations are involved. Beyond the apparent accumulation of period doubling bifurcations, a mixed-mode regime with irregular oscillations on both scales is observed, occasionally interrupted by windows of periodicity. As the flow rate is further increased, chaos turns into quasiperiodicity and later to a simple small-amplitude periodic regime. Dynamics of selected typical regimes were examined with the tools of nonlinear time-series analysis, which include phase space reconstruction of an attractor and calculation of the maximal Lyapunov exponent. The analysis points to deterministic chaos, which appears via a period doubling route from below and via a route involving quasiperiodicity from above, when the flow rate is varied.

Response dynamics to pulsed perturbations of the hydrogen peroxide-thiosulfate-Cu2+ reaction.

The hydrogen peroxide-thiosulfate-Cu2+ reaction operated in a continuous flow stirred tank reactor is a pH-oscillator known to provide three different steady states, hysteresis, and oscillations. In addition to the various dynamical regimes established earlier, a question arises whether the reaction can be also excitable, whereby the system strongly responds to a small but supercritical external addition of certain chemical species. We carried out experiments aimed at finding excitability and studying response dynamics to single and repeated pulsed perturbations of varying amplitude and period. We found that the reaction displays a remarkable excitatory dynamics when forced. The available mechanism of the reaction involves several adjustable parameters, which need to be tuned so that the model corresponds to experimentally observed bifurcation diagrams. Our experimental findings are compared with numerical calculations, suggesting that the model is far from complete.

Oscillations, period doublings, and chaos in CO oxidation and catalytic mufflers.

Early experimental observations of chaotic behavior arising via the period-doubling route for the CO catalytic oxidation both on Pt(110) and Ptgamma-Al(2)O(3) porous catalyst were reported more than 15 years ago. Recently, a detailed kinetic reaction scheme including over 20 reaction steps was proposed for the catalytic CO oxidation, NO(x) reduction, and hydrocarbon oxidation taking place in a three-way catalyst (TWC) converter, the most common reactor for detoxification of automobile exhaust gases. This reactor is typically operated with periodic variation of inlet oxygen concentration. For an unforced lumped model, we report results of the stoichiometric network analysis of a CO reaction subnetwork determining feedback loops, which cause the oscillations within certain regions of parameters in bifurcation diagrams constructed by numerical continuation techniques. For a forced system, numerical simulations of the CO oxidation reveal the existence of a period-doubling route to chaos. The dependence of the rotation number on the amplitude and period of forcing shows a typical bifurcation structure of Arnold tongues ordered according to Farey sequences, and positive Lyapunov exponents for sufficiently large forcing amplitudes indicate the presence of chaotic dynamics. Multiple periodic and aperiodic time courses of outlet concentrations were also found in simulations using the lumped model with the full TWC kinetics. Numerical solutions of the distributed model in two geometric coordinates with the CO oxidation subnetwork consisting of several tens of nonlinear partial differential equations show oscillations of the outlet reactor concentrations and, in the presence of forcing, multiple periodic and aperiodic oscillations. Spatiotemporal concentration patterns illustrate the complexity of processes within the reactor.