Browsing by Author "Ashkar, Rana"

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    Aspects of population dynamics
    Swailem, Mohamed (Virginia Tech, 2024-05-24)
    Natural ecologies are prone to stochastic effects and changing environments that shape their dynamical behavior. Ecological systems can be modeled through relatively simple population dynamics models. There is a plethora of models describing deterministic models of ecological systems evolving in a constant environment. However, stochasticity can lead to extinction or fixation events, noise-stabilized patterns, and nontrivial correlations. Likewise, changing environments can greatly affect the behavior and ultimate fate of ecological systems. In fact, the dynamics of evolution are mostly driven by randomness and changing environments. Therefore, it is of utmost importance to develop population dynamics models that are able to capture the effects of noise and environmental drive. In this thesis, we use both theoretical tools and simulations to investigate population dynamics in the following contexts: We study the stochastic spatial Lotka-Volterra (LV) model for predator-prey interaction subject to a periodically varying carrying capacity. The LV model with on-site lattice occupation restrictions that represent finite food resources for the prey exhibits a continuous active-to-absorbing phase transition. The active phase is sustained by spatio-temporal patterns in the form of pursuit and evasion waves. Monte Carlo simulations on a two-dimensional lattice are utilized to investigate the effect of seasonal variations of the environment on species coexistence. The results of our simulations are also compared to a mean-field analysis. We find that the parameter region of predator and prey coexistence is enlarged relative to the stationary situation when the carrying capacity varies periodically. The stationary regime of our periodically varying LV system shows qualitative agreement between the stochastic model and the mean-field approximation. However, under periodic carrying capacity switching environments, the mean-field rate equations predict period-doubling scenarios that are washed out by internal reaction noise in the stochastic lattice model. Utilizing visual representations of the lattice simulations and dynamical correlation functions, we study how the pursuit and evasion waves are affected by ensuing resonance effects. Correlation function measurements indicate a time delay in the response of the system to sudden changes in the environment. Resonance features are observed in our simulations that cause prolonged persistent spatial correlations. Different effective static environments are explored in the extreme limits of fast- and slow periodic switching. The analysis of the mean-field equations in the fast-switching regime enables a semi-quantitative description of the stationary state. The mean-field analysis of the Lotka-Volterra predator-prey model with seasonally varying carrying capacity is extended to the resonant regime. This is done by introducing a homotopy mapping from this model to another model that allows for the application of Floquet theory. The stability of the coexistence fixed point is studied and the period doubling is related to a bifurcation point in the homotopy mapping. However, we find that the predator-prey ecology's coexistence is stable for most of its parameter region. We apply a perturbative Doi–Peliti field-theoretical analysis to the stochastic spatially extended symmetric Rock-Paper-Scissors (RPS) and May–Leonard (ML) models, in which three species compete cyclically. Compared to the two-species Lotka–Volterra predator-prey (LV) model, according to numerical simulations, these cyclical models appear to be less affected by intrinsic stochastic fluctuations. Indeed, we demonstrate that the qualitative features of the ML model are insensitive to intrinsic reaction noise. In contrast, and although not yet observed in numerical simulations, we find that the RPS model acquires significant fluctuation-induced renormalizations in the perturbative regime, similar to the LV model. We also study the formation of spatio-temporal structures in the framework of stability analysis and provide a clearcut explanation for the absence of spatial patterns in the RPS system, whereas the spontaneous emergence of spatio-temporal structures features prominently in the LV and the ML models. Stochastic reaction-diffusion models are employed to represent many complex physical, biological, societal, and ecological systems. The macroscopic reaction rates describing the large-scale, long-time kinetics in such systems are effective, scale-dependent renormalized parameters that need to be either measured experimentally or computed by means of a microscopic model. In a Monte Carlo simulation of stochastic reactiondiffusion systems, microscopic probabilities for specific events to happen serve as the input control parameters. To match the results of any computer simulation to observations or experiments carried out on the macroscale, a mapping is required between the microscopic probabilities that define the Monte Carlo algorithm and the macroscopic reaction rates that are experimentally measured. Finding the functional dependence of emergent macroscopic rates on the microscopic probabilities (subject to specific rules of interaction) is a very difficult problem, and there is currently no systematic, accurate analytical way to achieve this goal. Therefore, we introduce a straightforward numerical method of using lattice Monte Carlo simulations to evaluate the macroscopic reaction rates by directly obtaining the count statistics of how many events occur per simulation time step. Our technique is first tested on well-understood fundamental examples, namely restricted birth processes, diffusion-limited two-particle coagulation, and two-species pair annihilation kinetics. Next we utilize the thus gained experience to investigate how the microscopic algorithmic probabilities become coarse-grained into effective macroscopic rates in more complex model systems such as the Lotka–Volterra model for predator-prey competition and coexistence, as well as the rock-paper-scissors or cyclic Lotka–Volterra model as well as its May–Leonard variant that capture population dynamics with cyclic dominance motifs. Thereby we achieve a more thorough and deeper understanding of coarse-graining in spatially extended stochastic reactiondiffusion systems and the nontrivial relationships between the associated microscopic and macroscopic model parameters, with a focus on ecological systems. The proposed technique should generally provide a useful means to better fit Monte Carlo simulation results to experimental or observational data.
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    Biomembrane Structure and Material Properties Studied With Neutron Scattering
    Kinnun, Jacob J.; Scott, Haden L.; Ashkar, Rana; Katsaras, John (Frontiers, 2021-04-27)
    Cell membranes and their associated structures are dynamical supramolecular structures where different physiological processes take place. Detailed knowledge of their static and dynamic structures is therefore needed, to better understand membrane biology. The structure–function relationship is a basic tenet in biology and has been pursued using a range of different experimental approaches. In this review, we will discuss one approach, namely the use of neutron scattering techniques as applied, primarily, to model membrane systems composed of lipid bilayers. An advantage of neutron scattering, compared to other scattering techniques, is the differential sensitivity of neutrons to isotopes of hydrogen and, as a result, the relative ease of altering sample contrast by substituting protium for deuterium. This property makes neutrons an ideal probe for the study of hydrogen-rich materials, such as biomembranes. In this review article, we describe isotopic labeling studies of model and viable membranes, and discuss novel applications of neutron contrast variation in order to gain unique insights into the structure, dynamics, and molecular interactions of biological membranes. We specifically focus on how small-angle neutron scattering data is modeled using different contrast data and molecular dynamics simulations. We also briefly discuss neutron reflectometry and present a few recent advances that have taken place in neutron spin echo spectroscopy studies and the unique membrane mechanical data that can be derived from them, primarily due to new models used to fit the data.
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    Cinematic reflectometry using QIKR, the quite intense kinetics reflectometer
    Ankner, J. F.; Ashkar, Rana; Browning, J. F.; Charlton, T. R.; Doucet, M.; Halbert, C. E.; Islam, F.; Karim, A.; Kharlampieva, E.; Kilbey II, S. M.; Lin, J. Y. Y.; Phan, M. D.; Smith, G. S.; Sukhishvili, S. A.; Thermer, R.; Veith, G. M.; Watkins, E. B.; Wilson, D. (Aip Publishing, 2023-01)
    The Quite Intense Kinetics Reflectometer (QIKR) will be a general-purpose, horizontal-sample-surface neutron reflectometer. Reflectometers measure the proportion of an incident probe beam reflected from a surface as a function of wavevector (momentum) transfer to infer the distribution and composition of matter near an interface. The unique scattering properties of neutrons make this technique especially useful in the study of soft matter, biomaterials, and materials used in energy storage. Exploiting the increased brilliance of the Spallation Neutron Source Second Target Station, QIKR will collect specular and off-specular reflectivity data faster than the best existing such machines. It will often be possible to collect complete specular reflectivity curves using a single instrument setting, enabling "cinematic " operation, wherein the user turns on the instrument and "films " the sample. Samples in time-dependent environments (e.g., temperature, electrochemical, or undergoing chemical alteration) will be observed in real time, in favorable cases with frame rates as fast as 1 Hz. Cinematic data acquisition promises to make time-dependent measurements routine, with time resolution specified during post-experiment data analysis. This capability will be deployed to observe such processes as in situ polymer diffusion, battery electrode charge-discharge cycles, hysteresis loops, and membrane protein insertion into lipid layers. (c) 2023 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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    The effects of molecular and nanoscopic additives on phospholipid membranes
    Kumarage, Teshani; Morris, Nicholas B.; Ashkar, Rana (Frontiers, 2023-11-20)
    Lipid bilayers—the main matrix of cell membranes—are a paradigm of soft molecular assemblies whose properties have been evolutionarily optimized to satisfy the functional requirements of cells. For instance, lipid bilayers must be rigid enough to serve as the protective barrier between cells and their environment, yet fluid enough to enable the diffusion of proteins and molecular clusters necessary for biological functions. Inspired by their biological multifunctionality, lipid membranes have also been used as a central design element in many practical applications including artificial cells, drug nanocarriers, and biosensors. Whether biological or synthetic, lipid membranes often involve molecular or nanoscopic additives that modulate the membrane properties through various mechanisms. Hence, how lipid membranes respond to additives has justifiably drawn much attention in recent years. This review summarizes findings and observations on different classes of additives and their effects on structural, thermodynamic, elastic, and dynamical membrane properties that are central to biological function or synthetic membrane performance. The review primarily focuses on phospholipids as a major component of cell membranes and a widely used lipid type in synthetic membrane designs.
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    Exploring Multiple Hydrogen Bonding and Ionic Bonding in the Design of Supramolecular Polymers
    Chen, Xi (Virginia Tech, 2020-06-03)
    Supramolecular polymers represent a family of polymeric materials that are held together with dynamic, noncovalent interactions. In contrast to conventional functional polymers that usually have high melt-viscosity due to their covalent nature and chain entanglement, supramolecular polymers combine excellent physical properties with low melt-viscosity, allowing for less energy-intensive processability and recyclability. Dynamic bonding with multiple binding sites, such as multiple hydrogen bonding or multiple ionic bonding, exhibits much stronger binding strength compared to the counterparts containing only a single binding site, thereby allowing for enhanced mechanical integrity to the polymers and facilitate self-assembly. This dissertation focuses on the design of novel supramolecular polymers building from the doubly-charged or quadruple hydrogen bonding (QHB) scaffolds utilizing chain-growth polymerization or step-growth polymerization, as well as elucidate the structure-property-morphology relationships of the polymers. A 2-step nucleophilic substitution reaction afforded a series of 1,4-diazabicyclo[2.2.2]octane (DABCO)-based styrenic monomers with two pairs of charged groups. An optimized 2-step reversible-addition-fragmentation chain-transfer (RAFT) polymerization synthesized ABA triblock thermoplastic elastomers (TPEs) with a low Tg poly (n-butyl acrylate) central block and a high Tg external charged blocks. Strong ionic interactions between doubly-charged units drove molecular self-assembly to form densely packed, hierarchical microstructures, which contributed to a robust, crosslinked physical network that allows the polymer to retain thermomechanical integrity until degradation. High-resolution single-crystal X-ray diffraction (SCXRD) coupled with powder X-ray diffraction (PXRD) further disclosed a detailed 3-D structural information of molecular arrangement and ion distribution within the charged phase through comparing DABCO-salt monomer single-crystal structure and the corresponding homopolymer XRD pattern. It was found that the physical properties of the DABCO-salt copolymers not only relied on their charge content and architectures but also dependent on their electrostatically-bonded counterions. The size and structure of the counterion determined the strength of dipole-dipole interaction, which significantly impact on thermal property, (thermo)mechanical performance, water affinity, and microstructure. A cytosine-functionalized monomer, cytosine acrylate (CyA), allowed the synthesis of acrylic ABA triblock TPEs with pendant nucleobase moieties in the external blocks and a low Tg central polymer matrix through RAFT polymerization. Post-functionalization of cytosine (Cyt) bidentate hydrogen bonding sites with alkyl isocyanate, allowed the formation of ureido-cytosine (UCyt) groups in the external block that were readily dimerized through QHB interactions. The UCyt units in the external block enhanced mechanical strength and induced stronger phase-separation of the block copolymers compared to the corresponding Cyt-containing TPE analogs. Facile conventional free-radical polymerization using CyA and subsequent post-functionalization enabled accessibility to random copolymers containing pendant UCyt QHB moieties in the soft polymer matrix. The synergy of the flexible polymer matrix and the dynamic character of QHB groups contributed to the ultra-high elasticity of the polymer and rapid self-healing properties. QHB interactions enabled efficient mechanical recovery upon deformation by facilitating elastic chain retraction to regenerate the original physical network. Finally, one-pot step-growth polymerization through chain extending a novel bis-Cyt monomer and a commercially available polyether diamine using a di-isocyanate extender afforded segmented polyurea series for extrusion additive manufacturing. The molecular design of the polyureas featured soft segments containing flexible polyether chain and a relatively weak urea hydrogen bonding sites in the soft segment and rigid UCyt hydrogen bonding groups in the hard segment. The reversible characteristics of QHB enabled low viscosity at the processing temperature while providing mechanical integrity after processing and reinforced bonding between the interlayers, which contributed to the remarkable strength, elasticity, toughness, and interlayer adhesion of the printed parts.
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    Phosphatidylinositol 3-phosphate binding properties and autoinhibition mechanism of Phafin2
    Tang, Tuoxian (Virginia Tech, 2021-05-26)
    Phafin2 is a member of the Phafin protein family. Phafins are modular with an N-terminal PH (Pleckstrin Homology) domain followed by a central FYVE (Fab1, YOTB, Vac1, and EEA1) domain. Both the Phafin2 PH and FYVE domains bind phosphatidylinositol 3-phosphate [PtdIns(3)P], a phosphoinositide mainly found in endosomal and lysosomal membranes. Phafin2 acts as a PtdIns(3)P effector for endosomal cargo trafficking, macropinocytosis, apoptosis, and autophagy. The PtdIns(3)P binding activity is critical to the localization of Phafin2 on a specific membrane and, subsequently, helps the recruitment of other binding partners to the same membrane surface. However, there are no studies on the structural basis of PtdIns(3)P binding, the PtdIns(3)P-binding properties of each domain, and the apparent redundancy of two PtdIns(3)P binding domains in Phafin proteins. In the present dissertation, different biochemical and biophysical techniques were utilized to investigate the structural features of Phafin2 and its lipid interactions. This dissertation shows that Phafin2 is a moderately elongated monomer with a predicted α/β structure and ~40% random coil content. Phafin2 binds lipid bilayer-embedded PtdIns(3)P with high affinity; its PH and FYVE domains display distinct PtdIns(3)P-binding properties. Unlike the PH domain, the Phafin2 FYVE domain binds both membrane-embedded PtdIns(3)P and water-soluble dibutanoyl PtdIns(3)P with similar affinity. An intramolecular autoinhibition mechanism is found in Phafin2, in which a conserved C-terminal aspartic acid-rich (polyD) motif inhibits the binding of Phafin2 PH domain to PtdIns(3)P. The polyD motif specifically interacts with the Phafin2 PH domain. Using negative-stain Transmission Electron Microscopy, Phafin2 was found to cause membrane tubulation in a PtdIns(3)P-dependent manner. In conclusion, this study provides the structural and functional basis of Phafin2 lipid interactions and evidence of an intramolecular autoinhibition mechanism for PtdIns(3)P binding to the Phafin2 PH domain, which is mediated by the C-terminal polyD. The distinct PtdIns(3)P binding properties of the Phafin2 PH and FYVE domains may indicate that these two domains have different functions. Considering that the Phafin2 PH domain's PtdIns(3)P binding is intramolecularly regulated, cells may employ a unique mechanism to release the Phafin2 PH domain from the conserved C-terminal motif and control the functions of Phafin2 in PtdIns(3)P- and PH domain-dependent signaling pathways.
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    Relaxation and Spontaneous Ordering in Systems with Competition
    Esmaeili, Shadisadat (Virginia Tech, 2019-06-21)
    Spontaneous order happens in non-equilibrium systems composed of interacting elements. This phenomenon manifests in both the formation of space-time patterns in reaction-diffusion systems and collective rhythmic behaviors in coupled oscillators. In this thesis, we present the results of two studies: 1) The response of a multi-species predator-prey system to perturbation. 2) The features of a rich attractor space in a system of repulsively coupled Kuramoto oscillators. In the first part, we address this question: how does a complex coarsening system with non-trivial in-domain dynamics respond to perturbations? We choose a cyclic predator-prey model with six species each attacking three others. As a result of this interaction network, two competing domains form, while inside each domain three species play a rock-paper-scissors game which results in the formation of spirals inside the domains. We perturb the system by changing the interaction scheme which leads to a change of alliances and therefore a different spatial pattern. As expected, perturbing a complex space-time pattern results in a complex response. In the second part, we explore the attractor space of a system of repulsively coupled oscillators with non-homogeneous natural frequencies on a hexagonal lattice. Due to the negative coupling and the particular choice of geometry, some of the links between oscillators become frustrated. Coupled oscillators with frustration show similar features as frustrated magnetic systems. We use the parameters of the system like the coupling constant and the width of the frequency distribution to understand the system's attractor space. Further, we study the effects of external noise on the system. We also identify the breaking of time-translation invariance in the absence of external noise, in our system.
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    Sensor-Enabled Accelerated Engineering of Soft Materials
    Liu, Yang (Virginia Tech, 2024-05-24)
    Many grand societal challenges are rooted in the need for new materials, such as those related to energy, health, and the environment. However, the traditional way of discovering new materials is basically trial and error. This time-consuming and expensive method can't meet the quickly growing requirements for material discovery. To meet this challenge, the government of the United States started the Materials Genome Initiative (MGI) in 2011. MGI aims at accelerating the pace and reducing the cost of discovering new materials. The success of MGI needs materials innovation infrastructure including data tools, computation tools, and experiment tools. The last decade has witnessed significant progress for MGI, especially with respect to hard materials. However, relatively less attention has been paid to soft materials. One important reason is the lack of experimental tools, especially characterization tools for high-throughput experimentation. This dissertation aims to enrich the toolbox by trying new sensor tools for high-throughput characterization of hydrogels. Piezoelectric-excited millimeter-sized cantilever (PEMC) sensors were used in this dissertation to characterize hydrogels. Their capability to investigate hydrogels was first demonstrated by monitoring the synthesis and stimuli-response of composite hydrogels. The PEMC sensors enabled in-situ study of how the manufacturing process, i.e. bulk vs. layer-by-layer, affects the structure and properties of hydrogels. Afterwards, the PEMC sensors were integrated with robots to develop a method of high-throughput experimentation. Various hydrogels were formulated in a well-plate format and characterized by the sensor tools in an automated manner. High-throughput characterization, especially multi-property characterization enabled optimizing the formulation to achieve tradeoff between different properties. Finally, the sensor-based high-throughput experimentation was combined with active learning for accelerated material discovery. A collaborative learning was used to guide the high-throughput formulation and characterization of hydrogels, which demonstrated rapid discovery of mechanically optimized composite glycogels. Through this dissertation, we hope to provide a new tool for high-throughput characterization of soft materials to accelerate the discovery and optimization of materials.
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    Theoretical Modeling of Polymeric and Biological Nanostructured Materials
    Rahmaninejad, Hadi (Virginia Tech, 2023-02-23)
    Polymer coatings on periodic nanostructures have facilitated advanced applications in various fields. The performance of these structures is intimately linked to their nanoscale characteristics. Smart polymer coatings responsive to environmental stimuli such as temperature, pH level, and ionic strength have found important uses in these applications. Therefore, to optimize their performance and improve their design, precise characterization techniques are essential for understanding the nanoscale properties of polymer coating, especially in response to stimuli and interactions with the surrounding medium. Due to their layered compositions, applying non-destructive measurement methods by X-ray/neutron scattering is optimal. These approaches offer unique insights into the structure, dynamics, and kinetics of polymeric coatings and interfaces. The caveat is that scattering methods require non-trivial data modeling, particularly in the case of periodic structures, which result in strong correlations between scattered beams. The dynamical theory (DT) model offers an exact model for interpreting off-specular signals from periodically structured surfaces and has been validated on substrates measured by neutron scattering. In this dissertation, we improved the model using a computational optimization approach that simultaneously fits specular and off-specular scattering signals and efficiently retrieves the three-dimensional sample profile with high precision. In addition, we extended this to the case of X-ray scattering. We applied this approach to characterize polymer brushes for nanofluidic applications and protein binding to modulated lipid membranes. This approach opens new possibilities in developing soft matter nanostructured substrates with desired properties for various applications.
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    Topographically and Mechanically Tunable PNIPAM Scaffolds
    Chen, Chi (Virginia Tech, 2022-08-16)
    Poly(N-isopropyl-acrylamide) (PNIPAM) is a thermoresponsive polymer with a wide range of biological applications, including drug delivery, biosensing, and tissue engineering. The tunability of the structural and mechanical properties of PNIPAM makes it particularly at- tractive in emulating cell environments and dynamic cytoskeletal deformations. This thesis discusses PNIPAM's properties and applications in different forms i.e., solution, brushes, hydrogels, and surface patterned hydrogels, with specific focus on lithographically patterned substrates coated with PNIPAM films. The scaffolds are investigated for structural and me- chanical responses to thermally driven changes in the PNIPAM hydration states using atomic force microscopy (AFM). AFM measurements on our lithographically patterned substrates show that the substrate pattern and coating method enable the fabrication of scaffolds with different topographic and mechanical properties across a wide thermal range. Importantly, these scaffolds exhibit variations in both lateral topography and Young's modulus, rendering them well suited for investigations of differential mechanical stresses experienced by cells and cell membranes.
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    Uncovering Structure-Property Relations in Biomimetic Lipid Membranes with Molecular Additives
    Lihiniya Kumarage, Teshani Omanthika (Virginia Tech, 2024-08-15)
    The lipid bilayer, the fundamental structure of cell membranes, exemplifies a highly adaptable molecular assembly with characteristics that have been fine-tuned through evolution to meet the diverse functional needs of cells. These bilayers must strike a delicate balance: they need to be sufficiently rigid to act as protective barriers, yet fluid enough to facilitate the diffusion of proteins and molecular clusters crucial for various biological processes. Owing to their multifunctional nature, lipid membranes are not only vital in biological contexts but also in numerous practical applications, such as artificial cells, drug-delivery nanocarriers, and biosensors. Both biological and synthetic lipid membranes frequently incorporate molecular or nanoscale additives that modify their properties through a range of mechanisms. Gaining a comprehensive understanding of how lipid membranes interact with these additives is an area of active research, particularly with the advent of advanced high-resolution characterization techniques that reveal both the static and dynamic behaviors of these systems. This dissertation investigates the impact of small molecular additives – specifically natural and synthetic sterols – on the structure, elasticity, and organization of biomimetic lipid membranes. Utilizing advanced scattering techniques and other methods, the research elucidates the intricate interplay between the membrane composition, structure, and elasticity. Key findings demonstrate that, unlike previous observations, cholesterol significantly affects the bending rigidity of lipid membranes regardless of chain unsaturation, when measured on mesoscopic length and time scales. Interestingly, the replacement of cholesterol with engineered molecules, comprised of a sterol unit that is chemically conjugated to one or both of the lipid chains, results in further enhancement in the membrane bending rigidity and mechanical stability, making them a promising additive for advanced liposomal drug delivery systems. Further studies on phase-separating membranes illustrate the effective use of sterol-modified lipids in regulating the formation and size of distinct lipid domains implicated in protein recruitment and biological function. This work advances the current understanding of membrane biophysics and paves the way for novel therapeutic strategies and biomaterial designs.