Complex tracer mobilities in polymer networks revealed by fluorescence correlation spectroscopy

Gels are elastic porous polymer networks that are accompanied by pronounced mechanical properties. Due to their biocompatibility, ‘responsive hydrogels’ (HG) have many biomedical applications ranging from biosensors and drug delivery to tissue engineering. They respond to external stimuli such as temperature and salt by changing their dimensions. Of paramount importance is the ability to engineer penetrability and diffusion of interacting molecules in the crowded HG environment, as this would enable one to optimize a specific functionality. Even though the conditions under which biomedical devices operate are rather complex, a bottom-up approach could reduce the complexity of mutually coupled parameters influencing tracer mobility. The present thesis focuses on the interaction-induced tracer diffusion in polymer solutions and their homologous gels, probed by means of Fluorescence Correlation Spectroscopy (FCS). This is a single-molecule-sensitive technique having the advantage of optimal performance under ultralow tracer concentrations, typically employed in biosensors. Two different types of hydrogels have been investigated, a conventional one with broad polydispersity in the distance between crosslink points and a so-called ‘ideal’, with uniform mesh size distribution. The former is based on a thermoresponsive polymer, exhibiting phase separation in water at temperatures close to the human body temperature. The latter represents an optimal platform to study tracer diffusion. Mobilities of different tracers have been investigated in each network, varying in size, geometry and in terms of tracer-polymer attractive strength, as perturbed by different stimuli. The thesis constitutes a systematic effort towards elucidating the role of the strength and nature of different tracer-polymer interactions, on tracer mobilities; it outlines that interactions can still be very important even in the simplified case of dilute polymer solutions; it also demonstrates that the presence of permanent crosslinks exerts distinct tracer slowdown, depending on the tracer type and the nature of the tracer-polymer interactions, expressed differently by each tracer with regard to the selected stimulus. In aqueous polymer solutions, the tracer slowdown is found to be system-dependent and no universal trend seems to hold, in contrast to predictions from scaling theory for non-interacting nanoparticle mobility and empirical relations concerning the mesh size in polymer solutions. Complex tracer dynamics in polymer networks may be distinctly expressed by FCS, depending on the specific synergy among-at least some of - the following parameters: nature of interactions, external stimuli employed, tracer size and type, crosslink density and swelling ratio.

Anomalous diffusion in non-Markovian walks having amnestically induced persistence

We report numerically and analytically estimated values for the Hurst exponent for a recently proposed non-Markovian walk characterized by amnestically induced persistence. These results are consistent with earlier studies showing that log-periodic oscillations arise only for large memory losses of the recent past. We also report numerical estimates of the Hurst exponent for non-Markovian walks with diluted memory. Finally, we study walks with a fractal memory of the past for a Thue-Morse and Fibonacci memory patterns. These results are interpreted and discussed in the context of the necessary and sufficient conditions for the central limit theorem to hold.

Free inertial processes driven by Gaussian noise: Probability distributions, anomalous diffusion and fractal behavior

We study the motion of an unbound particle under the influence of a random force modeled as Gaussian colored noise with an arbitrary correlation function. We derive exact equations for the joint and marginal probability density functions and find the associated solutions. We analyze in detail anomalous diffusion behaviors along with the fractal structure of the trajectories of the particle and explore possible connections between dynamical exponents of the variance and the fractal dimension of the trajectories.

Generalized Langevin equations: Anomalous diffusion and probability distributions

We study the motion of a particle governed by a generalized Langevin equation. We show that, when no fluctuation-dissipation relation holds, the long-time behavior of the particle may be from stationary to superdiffusive, along with subdiffusive and diffusive. When the random force is Gaussian, we derive the exact equations for the joint and marginal probability density functions for the position and velocity of the particle and find their solutions.

On anomalous diffusion and the fractional generalized Langevin equation for a harmonic oscillator

The fractional generalized Langevin equation (FGLE) is proposed to discuss the anomalous diffusive behavior of a harmonic oscillator driven by a two-parameter Mittag-Leffler noise. The solution of this FGLE is discussed by means of the Laplace transform methodology and the kernels are presented in terms of the three-parameter Mittag-Leffler functions. Recent results associated with a generalized Langevin equation are recovered.

Particular solution for anomalous diffusion equation with source term

In literature the phenomenon of diffusion has been widely studied, however for nonextensive systems which are governed by a nonlinear stochastic dynamic, there are a few soluble models. The purpose of this study is to present the solution of the nonlinear Fokker-Planck equation for a model of potential with barrier considering a term of absorption. Systems of this nature can be observed in various chemical or biological processes and their solution enriches the studies of existing nonextensive systems.

Anomalous diffusion of pions at RHIC

After pointing out the difference between normal and anomalous diffusion, we consider a hadron resonance cascade (HRC) model simulation for particle emission at RHIC and point out that rescattering in an expanding hadron resonance gas leads to a heavy tail in the source distribution. The results are compared to recent PHENIX measurements of the tail of the particle emitting source in Au+Au collisions at RHIC. In this context, we show how can one distinguish experimentally the anomalous diffusion of hadrons from a second order QCD phase transition.

Weakly anomalous diffusion with non-Gaussian propagators

A poorly understood phenomenon seen in complex systems is diffusion characterized by Hurst exponent H approximate to 1/2 but with non-Gaussian statistics. Motivated by such empirical findings, we report an exact analytical solution for a non-Markovian random walk model that gives rise to weakly anomalous diffusion with H = 1/2 but with a non-Gaussian propagator.

Constraining anomalous Higgs boson interactions

The recently announced Higgs boson discovery marks the dawn of the direct probing of the electroweak symmetry breaking sector. Sorting out the dynamics responsible for electroweak symmetry breaking now requires probing the Higgs boson interactions and searching for additional states connected to this sector. In this work, we analyze the constraints on Higgs boson couplings to the standard model gauge bosons using the available data from Tevatron and LHC. We work in a model-independent framework expressing the departure of the Higgs boson couplings to gauge bosons by dimension-six operators. This allows for independent modifications of its couplings to gluons, photons, and weak gauge bosons while still preserving the Standard Model (SM) gauge invariance. Our results indicate that best overall agreement with data is obtained if the cross section of Higgs boson production via gluon fusion is suppressed with respect to its SM value and the Higgs boson branching ratio into two photons is enhanced, while keeping the production and decays associated to couplings to weak gauge bosons close to their SM prediction.

Anomalous diffusion evidenced by particle tracking at high frame rates.

Diffusion is a common phenomenon in nature and generally is associated with a system trying to reach a local or a global equilibrium state, as a result of highly irregular individual particle motion. Therefore it is of fundamental importance in physics, chemistry and biology. Particle tracking in complex fluids can reveal important characteristics of its properties. In living cells, we coat the microbead with a peptide (RGD) that binds to integrin receptors at the plasma membrane, which connects to the CSK. This procedure is based on the hypothesis that the microsphere can move only if the structure where it is attached move as well. Then, the observed trajectory of microbeads is a probe of the cytoskeleton (CSK), which is governed by several factors, including thermal diffusion, pressure gradients, and molecular motors. The possibility of separating the trajectories into passive and active diffusion may give information about the viscoelasticity of the cell structure and molecular motors activity. And also we could analyze the motion via generalized Stokes-Einstein relation, avoiding the use of any active techniques. Usually a 12 to 16 Frames Per Second (FPS) system is used to track the microbeads in cell for about 5 minutes. Several factors make this FPS limitation: camera computer communication, light, computer speed for online analysis among others. Here we used a high quality camera and our own software, developed in C++ and Linux, to reach high FPS. Measurements were conducted with samples for 10£ and 20£ objectives. We performed sequentially images with different intervals, all with 2 ¹s exposure. The sequences of intervals are in milliseconds: 4 5 ms (maximum speed) 14, 25, 50 and 100 FPS. Our preliminary results highlight the difference between passive and active diffusion, since the passive diffusion is represented by a Gaussian in the distribution of displacements of the center of mass of individual beads between consecutive frames. However, the active process, or anomalous diffusion, shows as long tails in the distribution of displacements.

Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

A MICROFLUIDIC METHOD TO MEASURE DIFFUSION IN HYDROGELS

A novel microfluidic method is proposed for studying diffusion of small molecules in a hydrogel. Microfluidic devices were prepared with semi-permeable microchannels defined by crosslinked poly(ethylene glycol) (PEG). Uptake of dye molecules from aqueous solutions flowing through the microchannels was observedoptically and diffusion of the dye into the hydrogel was quantified. To complement the diffusion measurements from the microfluidic studies, nuclear magnetic resonance(NMR) characterization of the diffusion of dye in the PEG hydrogels was performed. The diffusion of small molecules in a hydrogel is relevant to applications such asdrug delivery and modeling transport for tissue-engineering applications. The diffusion of small molecules in a hydrogel is dependent on the extent of crosslinking within the gel, gel structure, and interactions between the diffusive species and the hydrogel network. These effects were studied in a model environment (semi-infinite slab) at the hydrogelfluid boundary in a microfluidic device. The microfluidic devices containing PEG microchannels were fabricated using photolithography. The unsteady diffusion of small molecules (dyes) within the microfluidic device was monitored and recorded using a digital microscope. The information was analyzed with techniques drawn from digital microscopy and image analysis to obtain concentration profiles with time. Using a diffusion model to fit this concentration vs. position data, a diffusion coefficient was obtained. This diffusion coefficient was compared to those from complementary NMR analysis. A pulsed field gradient (PFG) method was used to investigate and quantify small molecule diffusion in gradient (PFG) method was used to investigate and quantify small molecule diffusion in hydrogels. There is good agreement between the diffusion coefficients obtained from the microfluidic methods and those found from the NMR studies. The microfluidic approachused in this research enables the study of diffusion at length scales that approach those of vasculature, facilitating models for studying drug elution from hydrogels in blood-contacting applications.

Diffusion on a solid surface: anomalous is normal

We present a numerical study of classical particles diffusing on a solid surface. The particles motion is modeled by an underdamped Langevin equation with ordinary thermal noise. The particle-surface interaction is described by a periodic or a random two-dimensional potential. The model leads to a rich variety of different transport regimes, some of which correspond to anomalous diffusion such as has recently been observed in experiments and Monte Carlo simulations. We show that this anomalous behavior is controlled by the friction coefficient and stress that it emerges naturally in a system described by ordinary canonical Maxwell-Boltzmann statistics.

Étude des propriétés de transport dans les hydrogels de curdlan

Les hydrogels de polysaccharide sont des biomatériaux utilisés comme matrices à libération contrôlée de médicaments et comme structures modèles pour l’étude de nombreux systèmes biologiques dont les biofilms bactériens et les mucus. Dans tous les cas, le transport de médicaments ou de nutriments à l’intérieur d’une matrice d’hydrogel joue un rôle de premier plan. Ainsi, l’étude des propriétés de transport dans les hydrogels s’avère un enjeu très important au niveau de plusieurs applications. Dans cet ouvrage, le curdlan, un polysaccharide neutre d’origine bactérienne et formé d’unités répétitives β-D-(1→3) glucose, est utilisé comme hydrogel modèle. Le curdlan a la propriété de former des thermogels de différentes conformations selon la température à laquelle une suspension aqueuse est incubée. La caractérisation in situ de la formation des hydrogels de curdlan thermoréversibles et thermo-irréversibles a tout d’abord été réalisée par spectroscopie infrarouge à transformée de Fourier (FT-IR) en mode réflexion totale atténuée à température variable. Les résultats ont permis d’optimiser les conditions de gélation, menant ainsi à la formation reproductible des hydrogels. Les caractérisations structurales des hydrogels hydratés, réalisées par imagerie FT-IR, par microscopie électronique à balayage en mode environnemental (eSEM) et par microscopie à force atomique (AFM), ont permis de visualiser les différentes morphologies susceptibles d’influencer la diffusion d’analytes dans les gels. Nos résultats montrent que les deux types d’hydrogels de curdlan ont des architectures distinctes à l’échelle microscopique. La combinaison de la spectroscopie de résonance magnétique nucléaire (RMN) à gradients pulsés et de l’imagerie RMN a permis d’étudier l’autodiffusion et la diffusion mutuelle sur un même système dans des conditions expérimentales similaires. Nous avons observé que la diffusion des molécules dans les gels est ralentie par rapport à celle mesurée en solution aqueuse. Les mesures d’autodiffusion, effectuées sur une série d’analytes de diverses tailles dans les deux types d’hydrogels de curdlan, montrent que le coefficient d’autodiffusion relatif décroit en fonction de la taille de l’analyte. De plus, nos résultats suggèrent que l’équivalence entre les coefficients d’autodiffusion et de diffusion mutuelle dans les hydrogels de curdlan thermo-irréversibles est principalement due au fait que l’environnement sondé par les analytes durant une expérience d’autodiffusion est représentatif de celui exploré durant une expérience de diffusion mutuelle. Dans de telles conditions, nos résultats montrent que la RMN à gradients pulsés peut s’avérer une approche très avantageuse afin de caractériser des systèmes à libération contrôlée de médicaments. D’autres expériences de diffusion mutuelle, menées sur une macromolécule de dextran, montrent un coefficient de diffusion mutuelle inférieur au coefficient d’autodiffusion sur un même gel de curdlan. L’écart mesuré entre les deux modes de transport est attribué au volume différent de l’environnement sondé durant les deux mesures. Les coefficients d’autodiffusion et de diffusion mutuelle similaires, mesurés dans les deux types de gels de curdlan pour les différents analytes étudiés, suggèrent une influence limitée de l’architecture microscopique de ces gels sur leurs propriétés de transport. Il est conclu que les interactions affectant la diffusion des analytes étudiés dans les hydrogels de curdlan se situent à l’échelle moléculaire.

Identifying optimal lipid raft characteristics required to promote nanoscale protein-protein interactions on the plasma membrane

The dynamic lateral segregation of signaling proteins into microdomains is proposed to facilitate signal transduction, but the constraints on microdomain size, mobility, and diffusion that might realize this function are undefined. Here we interrogate a stochastic spatial model of the plasma membrane to determine how microdomains affect protein dynamics. Taking lipid rafts as representative microdomains, we show that reduced protein mobility in rafts segregates dynamically partitioning proteins, but the equilibrium concentration is largely independent of raft size and mobility. Rafts weakly impede small-scale protein diffusion but more strongly impede long-range protein mobility. The long-range mobility of raft-partitioning and raft-excluded proteins, however, is reduced to a similar extent. Dynamic partitioning into rafts increases specific interprotein collision rates, but to maximize this critical, biologically relevant function, rafts must be small (diameter, 6 to 14 nm) and mobile. Intermolecular collisions can also be favored by the selective capture and exclusion of proteins by rafts, although this mechanism is generally less efficient than simple dynamic partitioning. Generalizing these results, we conclude that microdomains can readily operate as protein concentrators or isolators but there appear to be significant constraints on size and mobility if microdomains are also required to function as reaction chambers that facilitate nanoscale protein-protein interactions. These results may have significant implications for the many signaling cascades that are scaffolded or assembled in plasma membrane microdomains.