The logic of receptor-ligand interactions in the Notch signaling pathway

The Notch signaling pathway enables neighboring cells to coordinate developmental fates in diverse processes such as angiogenesis, neuronal differentiation, and immune system development. Although key components and interactions in the Notch pathway are known, it remains unclear how they work together to determine a cell's signaling state, defined as its quantitative ability to send and receive signals using particular Notch receptors and ligands. Recent work suggests that several aspects of the system can lead to complex signaling behaviors: First, receptors and ligands interact in two distinct ways, inhibiting each other in the same cell (in cis) while productively interacting between cells (in trans) to signal. The ability of a cell to send or receive signals depends strongly on both types of interactions. Second, mammals have multiple types of receptors and ligands, which interact with different strengths, and are frequently co-expressed in natural systems. Third, the three mammalian Fringe proteins can modify receptor-ligand interaction strengths in distinct and ligand-specific ways. Consequently, cells can exhibit non-intuitive signaling states even with relatively few components.

In order to understand what signaling states occur in natural processes, and what types of signaling behaviors they enable, this thesis puts forward a quantitative and predictive model of how the Notch signaling state is determined by the expression levels of receptors, ligands, and Fringe proteins. To specify the parameters of the model, we constructed a set of cell lines that allow control of ligand and Fringe expression level, and readout of the resulting Notch activity. We subjected these cell lines to an assay to quantitatively assess the levels of Notch ligands and receptors on the surface of individual cells. We further analyzed the dependence of these interactions on the level and type of Fringe expression. We developed a mathematical modeling framework that uses these data to predict the signaling states of individual cells from component expression levels. These methods allow us to reconstitute and analyze a diverse set of Notch signaling configurations from the bottom up, and provide a comprehensive view of the signaling repertoire of this major signaling pathway.

Velocity resolved - scalar modeled simulations of high Schmidt number turbulent transport

The objective of this thesis is to develop a framework to conduct velocity resolved - scalar modeled (VR-SM) simulations, which will enable accurate simulations at higher Reynolds and Schmidt (Sc) numbers than are currently feasible. The framework established will serve as a first step to enable future simulation studies for practical applications. To achieve this goal, in-depth analyses of the physical, numerical, and modeling aspects related to Sc>>1 are presented, specifically when modeling in the viscous-convective subrange. Transport characteristics are scrutinized by examining scalar-velocity Fourier mode interactions in Direct Numerical Simulation (DNS) datasets and suggest that scalar modes in the viscous-convective subrange do not directly affect large-scale transport for high Sc. Further observations confirm that discretization errors inherent in numerical schemes can be sufficiently large to wipe out any meaningful contribution from subfilter models. This provides strong incentive to develop more effective numerical schemes to support high Sc simulations. To lower numerical dissipation while maintaining physically and mathematically appropriate scalar bounds during the convection step, a novel method of enforcing bounds is formulated, specifically for use with cubic Hermite polynomials. Boundedness of the scalar being transported is effected by applying derivative limiting techniques, and physically plausible single sub-cell extrema are allowed to exist to help minimize numerical dissipation. The proposed bounding algorithm results in significant performance gain in DNS of turbulent mixing layers and of homogeneous isotropic turbulence. Next, the combined physical/mathematical behavior of the subfilter scalar-flux vector is analyzed in homogeneous isotropic turbulence, by examining vector orientation in the strain-rate eigenframe. The results indicate no discernible dependence on the modeled scalar field, and lead to the identification of the tensor-diffusivity model as a good representation of the subfilter flux. Velocity resolved - scalar modeled simulations of homogeneous isotropic turbulence are conducted to confirm the behavior theorized in these a priori analyses, and suggest that the tensor-diffusivity model is ideal for use in the viscous-convective subrange. Simulations of a turbulent mixing layer are also discussed, with the partial objective of analyzing Schmidt number dependence of a variety of scalar statistics. Large-scale statistics are confirmed to be relatively independent of the Schmidt number for Sc>>1, which is explained by the dominance of subfilter dissipation over resolved molecular dissipation in the simulations. Overall, the VR-SM framework presented is quite effective in predicting large-scale transport characteristics of high Schmidt number scalars, however, it is determined that prediction of subfilter quantities would entail additional modeling intended specifically for this purpose. The VR-SM simulations presented in this thesis provide us with the opportunity to overlap with experimental studies, while at the same time creating an assortment of baseline datasets for future validation of LES models, thereby satisfying the objectives outlined for this work.

Neural and computational representations of decision variables

These studies explore how, where, and when representations of variables critical to decision-making are represented in the brain. In order to produce a decision, humans must first determine the relevant stimuli, actions, and possible outcomes before applying an algorithm that will select an action from those available. When choosing amongst alternative stimuli, the framework of value-based decision-making proposes that values are assigned to the stimuli and that these values are then compared in an abstract “value space” in order to produce a decision. Despite much progress, in particular regarding the pinpointing of ventromedial prefrontal cortex (vmPFC) as a region that encodes the value, many basic questions remain. In Chapter 2, I show that distributed BOLD signaling in vmPFC represents the value of stimuli under consideration in a manner that is independent of the type of stimulus it is. Thus the open question of whether value is represented in abstraction, a key tenet of value-based decision-making, is confirmed. However, I also show that stimulus-dependent value representations are also present in the brain during decision-making and suggest a potential neural pathway for stimulus-to-value transformations that integrates these two results.

More broadly speaking, there is both neural and behavioral evidence that two distinct control systems are at work during action selection. These two systems compose the “goal-directed system”, which selects actions based on an internal model of the environment, and the “habitual” system, which generates responses based on antecedent stimuli only. Computational characterizations of these two systems imply that they have different informational requirements in terms of input stimuli, actions, and possible outcomes. Associative learning theory predicts that the habitual system should utilize stimulus and action information only, while goal-directed behavior requires that outcomes as well as stimuli and actions be processed. In Chapter 3, I test whether areas of the brain hypothesized to be involved in habitual versus goal-directed control represent the corresponding theorized variables.

The question of whether one or both of these neural systems drives Pavlovian conditioning is less well-studied. Chapter 4 describes an experiment in which subjects were scanned while engaged in a Pavlovian task with a simple non-trivial structure. After comparing a variety of model-based and model-free learning algorithms (thought to underpin goal-directed and habitual decision-making, respectively), it was found that subjects’ reaction times were better explained by a model-based system. In addition, neural signaling of precision, a variable based on a representation of a world model, was found in the amygdala. These data indicate that the influence of model-based representations of the environment can extend even to the most basic learning processes.

Knowledge of the state of hidden variables in an environment is required for optimal inference regarding the abstract decision structure of a given environment and therefore can be crucial to decision-making in a wide range of situations. Inferring the state of an abstract variable requires the generation and manipulation of an internal representation of beliefs over the values of the hidden variable. In Chapter 5, I describe behavioral and neural results regarding the learning strategies employed by human subjects in a hierarchical state-estimation task. In particular, a comprehensive model fit and comparison process pointed to the use of "belief thresholding". This implies that subjects tended to eliminate low-probability hypotheses regarding the state of the environment from their internal model and ceased to update the corresponding variables. Thus, in concert with incremental Bayesian learning, humans explicitly manipulate their internal model of the generative process during hierarchical inference consistent with a serial hypothesis testing strategy.

I. A seismotectonic study of the Middle America Subduction Zone. II. Lithosphere and upper mantle structure of the Canadian Shield and Eastern North America

This thesis consists of two separate parts. Part I (Chapter 1) is concerned with seismotectonics of the Middle America subduction zone. In this chapter, stress distribution and Benioff zone geometry are investigated along almost 2000 km of this subduction zone, from the Rivera Fracture Zone in the north to Guatemala in the south. Particular emphasis is placed on the effects on stress distribution of two aseismic ridges, the Tehuantepec Ridge and the Orozco Fracture Zone, which subduct at seismic gaps. Stress distribution is determined by studying seismicity distribution, and by analysis of 190 focal mechanisms, both new and previously published, which are collected here. In addition, two recent large earthquakes that have occurred near the Tehuantepec Ridge and the Orozco Fracture Zone are discussed in more detail. A consistent stress release pattern is found along most of the Middle America subduction zone: thrust events at shallow depths, followed down-dip by an area of low seismic activity, followed by a zone of normal events at over 175 km from the trench and 60 km depth. The zone of low activity is interpreted as showing decoupling of the plates, and the zone of normal activity as showing the breakup of the descending plate. The portion of subducted lithosphere containing the Orozco Fracture Zone does not differ significantly, in Benioff zone geometry or in stress distribution, from adjoining segments. The Playa Azul earthquake of October 25, 1981, M_s=7.3, occurred in this area. Body and surface wave analysis of this event shows a simple source with a shallow thrust mechanism and gives M_o=1.3x10²⁷ dyne-cm. A stress drop of about 45 bars is calculated; this is slightly higher than that of other thrust events in this subduction zone. In the Tehuantepec Ridge area, only minor differences in stress distribution are seen relative to adjoining segments. For both ridges, the only major difference from adjoining areas is the infrequency or lack of occurrence of large interplate thrust events.

Part II involves upper mantle P wave structure studies, for the Canadian shield and eastern North America. In Chapter 2, the P wave structure of the Canadian shield is determined through forward waveform modeling of the phases P_nl, P, and PP. Effects of lateral heterogeneity are kept to a minimum by using earthquakes just outside the shield as sources, with propagation paths largely within the shield. Previous mantle structure studies have used recordings of P waves in the upper mantle triplication range of 15-30°; however, the lack of large earthquakes in the shield region makes compilation of a complete P wave dataset difficult. By using the phase PP, which undergoes triplications at 30-60°, much more information becomes available. The WKBJ technique is used to calculate synthetic seismograms for PP, and these records are modeled almost as well as the P. A new velocity model, designated S25, is proposed for the Canadian shield. This model contains a thick, high-Q, high-velocity lid to 165 km and a deep low-velocity zone. These features combine to produce seismograms that are markedly different from those generated by other shield structure models. The upper mantle discontinuities in S25 are placed at 405 and 660 km, with a simple linear gradient in velocity between them. Details of the shape of the discontinuities are not well constrained. Below 405 km, this model is not very different from many proposed P wave models for both shield and tectonic regions.

Chapter 3 looks in more detail at recordings of P_nl in eastern North America. First, seismograms from four eastern North American earthquakes are analyzed, and seismic moments for the events are calculated. These earthquakes are important in that they are among the largest to have occurred in eastern North America in the last thirty years, yet in some cases were not large enough to produce many good long-period teleseismic records. A simple layer-over-a-halfspace model is used for the initial modeling, and is found to provide an excellent fit for many features of the observed waveforms. The effects on P_nl of varying lid structure are then investigated. A thick lid with a positive gradient in velocity, such as that proposed for the Canadian shield in Chapter 2, will have a pronounced effect on the waveforms, beginning at distances of 800 or 900 km. P_nl records from the same eastern North American events are recalculated for several lid structure models, to survey what kinds of variations might be seen. For several records it is possible to see likely effects of lid structure in the data. However, the dataset is too sparse to make any general observations about variations in lid structure. This type of modeling is expected to be important in the future, as the analysis is extended to more recent eastern North American events, and as broadband instruments make more high-quality regional recordings available.