Study of the influence of actin-binding proteins using linear analyses of cell deformability

The actin cytoskeleton plays a key role in the deformability of the cell and in mechanosensing. Here we analyze the contributions of three major actin cross-linking proteins, myosin II, a-actinin and filamin, to cell deformability, by using micropipette aspiration of Dictyostelium cells. We examine the applicability of three simple mechanical models: for small deformation, linear viscoelasticity and drop of liquid with a tense cortex; and for large deformation, a Newtonian viscous fluid. For these models, we have derived linearized equations and we provide a novel, straightforward methodology to analyze the experiments. This methodology allowed us to differentiate the effects of the cross-linking proteins in the different regimes of deformation. Our results confirm some previous observations and suggest important relations between the molecular characteristics of the actin-binding proteins and the cell behavior: the effect of myosin is explained in terms of the relation between the lifetime of the bond to actin and the resistive force; the presence of a-actinin obstructs the deformation of the cytoskeleton, presumably mainly due to the higher molecular stiffness and to the lower dissociation rate constants; and filamin contributes critically to the global connectivity of the network, possibly by rapidly turning over crosslinks during the remodeling of the cytoskeletal network, thanks to the higher rate constants, flexibility and larger size. The results suggest a sophisticated relationship between the expression levels of actinbinding proteins, deformability and mechanosensing.

Diseño y desarrollo de un modelo booleano probabilístico de regulación genética en el simulador de colonias bacterianas GRO

Resulta interesante comprender como microorganismos sencillos como la bacteria Escherichia coli poseen mecanismos no tan simples para responder al entorno en el que está gestionada por complicadas redes de regulación formadas por genes y proteínas, donde cada elemento de la red genética debe tomar parte en armonía, en el momento justo y la cantidad adecuada para dar lugar a la respuesta celular apropiada. La biología sintética es un nuevo área de la biología y la tecnología que fusiona la biolog ía molecular, la ingeniería genética y las herramientas computacionales, para crear sistemas biológicos con funcionalidades novedosas. Los sistemas creados sintéticamente son ya una realidad, y cada vez se acumulan más trabajos alrededor del mundo que muestran su factibilidad. En este campo no solo se hacen pequeñas modificaciones en la información genética, sino que también se diseñan, manipulan e introducen circuitos genéticos a los organismos. Actualmente, se hace un gran esfuerzo para construir circuitos genéticos formados por numerosos genes y caracterizar la interacción de los mismos con otras moléculas, su regulaci ón, expresión y funcionalidad en diferentes organismos. La mayoría de los proyectos de biología sintética que se han desarrollado hasta ahora, se basan en el conocimiento actual del funcionamiento de los organismos vivos. Sin embargo, la información es numerosa y creciente, por lo que se requiere de herramientas computacionales y matem áticas para integrar y hacer manejable esta gran cantidad de información. El simulador de colonias bacterianas GRO posee la capacidad de representar las dinámicas más simples del comportamiento celular, tales como crecimiento, división y comunicación intercelular mediante conjugación, pero carece de la capacidad de simular el comportamiento de la colonia en presencia de un circuito genético. Para ello, se ha creado un nuevo módulo de regulación genética que maneja las interaciones entre genes y proteínas de cada célula ejecutando respuestas celulares específicas. Dado que en la mayoría de los experimentos intervienen colonias del orden de 105 individuos, es necesario un módulo de regulación genética simplificado que permita representar de la forma más precisa posible este proceso en colonias de tales magnitudes. El módulo genético integrado en GRO se basa en una red booleana, en la que un gen puede transitar entre dos estados, on (expresado) o off (reprimido), y cuya transición viene dada por una serie de reglas lógicas.---ABSTRACT---It is interesting to understand how simple organisms such as Escherichia coli do not have simple mechanisms to respond to the environment in which they find themselves. This response is managed by complicated regulatory networks formed by genes and proteins, where each element of the genetic network should take part in harmony, at the right time and with the right amount to give rise to the appropriate cellular response. Synthetic biology is a new area of biology and technology that combines molecular biology, genetic engineering and computational tools to create biological systems with novel features. The synthetically created systems are already a reality, and increasingly accumulate work around the world showing their feasibility. In this field not only minor changes are made in the genetic information but also genetic circuits designed, manipulated and introduced into the organisms. Currently, it takes great effort to build genetic circuits formed by numerous genes and characterize their interaction with other molecules, their regulation, their expression and their function in different organisms. Most synthetic biology projects that have been developed so far are based on the current knowledge of the functioning of living organisms. However, there is a lot of information and it keeps accumulating, so it requires computational and mathematical tools to integrate and manage this wealth of information. The bacterial colonies simulator, GRO, has the ability to represent the simplest dynamics of cell behavior, such as growth, division and intercellular communication by conjugation, but lacks the ability to simulate the behavior of the colony in the presence of a genetic circuit. To this end, a new genetic regulation module that handles interactions between genes and proteins for each cell running specific cellular responses has been created. Since most experiments involve colonies of about 105 individuals, a simplified genetic module which represent cell dynamics as accurately and simply as possible is needed. The integrated genetic GRO module is based on a Boolean network, in which a gene can be in either of two states, on (expressed) or off (repressed), and whose transition is given by a set of logical rules.

Triple-junction solar cell performance under Fresnel-based concentrators taking into account chromatic aberration and off-axis operation

Concentration photovoltaic (CPV) systems might produce quite uneven irradiance distributions (both on their level and on their spectral distribution) on the solar cell. This effect can be even more evident when the CPV system is slightly off-axis, since they are often designed to assure good uniformity only at normal incidence. The non-uniformities both in absolute irradiance and spectral content produced by the CPV systems, can originate electrical losses in multi-junction solar cells (MJSC). This works is focused on the integration of ray-tracing methods for simulating the irradiance and spectrum maps produced by different optic systems throughout the solar cell surface, with a 3D fully distributed circuit model which simulates the electrical behavior of a state-of-the-art triple-junction solar cell under the different light distributions obtained with ray-tracing. In this study four different CPV system (SILO, XTP, RTP, and FK) comprising Fresnel lenses concentrating sunlight onto the same solar cell are modeled when working on-axis and 0.6 degrees off-axis. In this study the impact of non-uniformities on a CPV system behavior is revealed. The FK outperforms other Fresnel-based CPV systems in both on-axis and off-axis conditions.

Asymptotic stability of a mathematical model of cell population

We consider a simplified system of a growing colony of cells described as a free boundary problem. The system consists of two hyperbolic equations of first order coupled to an ODE to describe the behavior of the boundary. The system for cell populations includes non-local terms of integral type in the coefficients. By introducing a comparison with solutions of an ODE's system, we show that there exists a unique homogeneous steady state which is globally asymptotically stable for a range of parameters under the assumption of radially symmetric initial data.

Building intuition of iron evolution during solar cell processing through analysis of different process models

An important aspect of Process Simulators for photovoltaics is prediction of defect evolution during device fabrication. Over the last twenty years, these tools have accelerated process optimization, and several Process Simulators for iron, a ubiquitous and deleterious impurity in silicon, have been developed. The diversity of these tools can make it difficult to build intuition about the physics governing iron behavior during processing. Thus, in one unified software environment and using self-consistent terminology, we combine and describe three of these Simulators. We vary structural defect distribution and iron precipitation equations to create eight distinct Models, which we then use to simulate different stages of processing. We find that the structural defect distribution influences the final interstitial iron concentration ([Fe-i]) more strongly than the iron precipitation equations. We identify two regimes of iron behavior: (1) diffusivity-limited, in which iron evolution is kinetically limited and bulk [Fe-i] predictions can vary by an order of magnitude or more, and (2) solubility-limited, in which iron evolution is near thermodynamic equilibrium and the Models yield similar results. This rigorous analysis provides new intuition that can inform Process Simulation, material, and process development, and it enables scientists and engineers to choose an appropriate level of Model complexity based on wafer type and quality, processing conditions, and available computation time.