Lattice Percolation Approach to Numerical Modeling of Tissue Aging

We describe a percolation-type approach to modeling of the processes of aging and certain other properties of tissues analyzed as systems consisting of interacting cells. Tissues are considered as structures made of regular healthy, senescent, dead (apoptotic) cells, and studied dynamically, with the ongoing processes including regular cell division to fill vacant sites left by dead cells, healthy cells becoming senescent or dying, and other processes. Statistical-mechanics description can provide patterns of time dependence and snapshots of morphological system properties. An illustrative application of the developed theoretical modeling approach is reported, confirming recent experimental findings that inhibition of senescence can lead to extended lifespan.

Mechanisms of Interparticle Bridging in Sintering of Dispersed Nanoparticles

We model within the kinetic Monte Carlo method the initiation of neck formation and then later evolution of the resulting bridging regions for configurations involving small particles initially positioned fitted between large particles for situations typical for sintering of FCC nanocrystals, e.g., noble-metal nanoparticles. Neck initiation mechanisms by layering or clustering are identified. The stability of the resulting bridging configurations depends on several parameters, notably, on the relative small to large particle size ratio, and we explain recent experimental findings on improved sintering achieved for certain bimodal size distributions.

Nonequilibrium Kinetic Modeling of Sintering of a Layer of Dispersed Nanocrystals

We report a kinetic Monte Carlo modeling study of nanocrystal layer sintering. Features that are of interest for the dynamics of the layer as a whole, especially the morphology of the evolving structure, are considered. It is found that the kinetics of sintering is not entirely a local process, with the layer morphology affected by the kinetics in a larger than few-particle neighborhood. Consideration of a single layer of particles makes the numerics manageable and allows visualization of the results, as well as numerical simulations of several realizations for statistical averaging of properties of interest. We identify optimal regimes for sintering, considering several particle size distributions and temperature control protocols.

Modeling of Growth Morphology of Core-Shell Nanoparticles

We model shell formation of core-shell noble metal nanoparticles. A recently developed kinetic Monte Carlo approach is utilized to reproduce growth morphologies realized in recent experiments on core-shell nanoparticle synthesis, which reported smooth epitaxially grown shells. Specifically, we identify growth regimes that yield such smooth shells, but also those that lead to the formation of shells made of small clusters. The developed modeling approach allows us to qualitatively study the effects of temperature and supply the shell-metal atoms on the resulting shell morphology, when grown on a pre-synthesized nanocrystal core.

Networked Enzymatic Logic Gates with Filtering: New Theoretical Modeling Expressions and Their Experimental Application

We report the first study of a network of connected enzyme-catalyzed reactions, with added chemical and enzymatic processes that incorporate the recently developed biochemical filtering steps into the functioning of this biocatalytic cascade. New theoretical expressions are derived to allow simple, few-parameter modeling of network components concatenated in such cascades, both with and without filtering. The derived expressions are tested against experimental data obtained for the realized networks responses, measured optically, to variations of its input chemicals concentrations with and without filtering processes. We also describe how the present modeling approach captures and explains several observations and features identified in earlier studies of enzymatic processes when they were considered as potential network components for multi-step information/signal processing systems.

Nonequilibrium Kinetic Study of Sintering of Dispersed Nanoparticles

Kinetic Monte Carlo approach is developed to study aspects of sintering of dispersed nanoparticles of bimodal size distributions. We explore mechanisms of neck development when sintering is initiated at elevated temperatures for nanosize crystalline surfaces of particles of different sizes. Specifically, the role of smaller particles fitting between larger particles, on the sintering of the latter is considered. Formation of stable necks bridging particles at the nanoscale was found to be governed by layering or clustering mechanisms at the facing surfaces, with clustering leading to a much faster formation of the bridging structure. Temperature, particle sizes and local arrangement, as well as other geometrical factors were found to have a profound effect on sintering mediated by a smaller particle placed in a void between larger particles.

Enzymatic AND Logic Gate with Sigmoid Response Induced by Photochemically Controlled Oxidation of the Output

We report a study of a system which involves an enzymatic cascade realizing an AND logic gate, with an added photochemical processing of the output allowing to make the gates response sigmoid in both inputs. New functional forms are developed for quantifying the kinetics of such systems, specifically designed to model their response in terms of signal and information processing. These theoretical expressions are tested for the studied system, which also allows us to consider aspects of biochemical information processing such as noise transmission properties and control of timing of the chemical and physical steps.

Modularity of Biochemical Filtering for Inducing Sigmoid Response in Both Inputs in an Enzymatic AND Gate

We report the first systematic study of designed two-input biochemical systems as information processing gates with favorable noise-transmission properties accomplished by modifying the gates response from convex shape to sigmoid in both inputs. This is realized by an added chemical filter process which recycles some of the output back into one of the inputs. We study a system involving the biocatalytic function of the enzyme horseradish peroxidase, functioning as an AND gate. We consider modularity properties, such as the use of three different input chromogens that, when oxidized yield signal-detection outputs for various ranges of the primary input, hydrogen peroxide. We also examine possible uses of different filter-effect chemicals (reducing agents) to induce the sigmoid-response. A modeling approach is developed and applied to our data, allowing us to describe the enzymatic kinetics in the framework of a formulation suitable for evaluating the noise-handling properties of the studied systems as logic gates for information processing steps.

Two-Input Enzymatic Logic Gates Made Sigmoid by Modifications of the Biocatalytic Reaction Cascades

Computing based on biochemical processes is a newest rapidly developing field of unconventional information and signal processing. In this paper we present results of our research in the field of biochemical computing and summarize the obtained numerical and experimental data for implementations of the standard two-input OR and AND gates with double-sigmoid shape of the output signal. This form of response was obtained as a function of the two inputs in each of the realized biochemical systems. The enzymatic gate processes in the first system were activated with two chemical inputs and resulted in optically detected chromogen oxidation, which happens when either one or both of the inputs are present. In this case, the biochemical system is functioning as the OR gate. We demonstrate that the addition of a filtering biocatalytic process leads to a considerable reduction of the noise transmission factor and the resulting gate response has sigmoid shape in both inputs. The second system was developed for functioning as an AND gate, where the output signal was activated only by a simultaneous action of two enzymatic biomarkers. This response can be used as an indicator of liver damage, but only if both of these of the inputs are present at their elevated, pathophysiological values of concentrations. A kinetic numerical model was developed and used to estimate the range of parameters for which the experimentally realized logic gate is close to optimal. We also analyzed the system to evaluate its noise-handling properties.

Extended Linear Response for Bioanalytical Applications Using Multiple Enzymes

We develop a framework for optimizing a novel approach to extending the linear range of bioanalytical systems and biosensors by utilizing two enzymes with different kinetic responses to the input chemical as their substrate. Data for the flow-injection amperometric system devised for detection of lysine based on the function of L-Lysine-alpha-Oxidase and Lysine-2-monooxygenase are analyzed. Lysine is a homotropic substrate for the latter enzyme. We elucidate the mechanism for extending the linear response range and develop optimization techniques for future applications of such systems.