Charles Taylor, D.Phil - US grants

This project is being funded through the Learning and Intelligent Systems (LIS) Initiative. The focus is on learning as it occurs in complex environments, where the data have rich and potentially confusing structures. Nine investigators in five different disciplines - biology, chemistry, linguistics, psychology, and high school teaching of mathematics and science - will mount a collaborative, multi-level experimental and theoretical analysis of the mind's learning structures. The work integrates research on formal analyses of learnability, the evolution of complex natural and artificial adapative systems, the genetics of memory, the mind's ability to keep track of language learning data, perceptual learning of complex displays like equations and molecular models, and the creation of integrative math and science modules for use with interactive learning technologies. The unifying theme running through all of the projects, and across every level of analysis, is the interaction between the structure of the brain's learning mechanisms, and the structure of the data that support learning. Two related leitmotives cut across the planned work. First, the project itself is conceived of as a complex, interdisciplinary learning environment for people ranging from high school students and science teachers in the Los Angeles community, to senior faculty at UCLA. Second, the research efforts interact with and inform advancements in the rapidly evolving technologies for learning, instruction, genetic screening, and the development of artificial systems.

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The goal of this project is to quantify the acute and chronic effects of exercise on hemodynamic conditions[unreadable] in the infrarenal aorta of human subjects with small AAA (AAA diameter equal to or > 3, equal to or < 5 cm). The subjects will be a subset of the patients in the standard therapy arm and exercise intervention arm described in Specific Aim 2 of Project IV: Evaluation of Exercise Therapy for Small AAA. We will test the hypotheses that: (i) Shape matters: Differences in shear and dynamic tensile forces acting on the vessel wall, resulting from differences in[unreadable] aneurysm shape, are predictive of AAA growth rate, (ii) Size matters: As AAA enlarge, adverse hemodynamic[unreadable] conditions (including regions of low mean wall shear stress and high particle residence time) are exacerbated[unreadable] under resting conditions, (iii) Structure and motion matter: Differences in wall thickness, tissue composition,[unreadable] cyclic wall motion, and fluid-solid interactions affect AAA enlargement, (iv) Exercise matters: Increased[unreadable] infrarenal blood flow resulting from acute lower limb exercise, eliminates regions of adverse hemodynamic[unreadable] conditions, dramatically increasing wall shear stress and reducing particle residence time in all subjects[unreadable] regardless of AAA shape or size, (v) Persistence matters: Regular exercise slows AAA progression affecting[unreadable] size and shape, and results in more favorable hemodynamics and vessel wall motion. We will test these[unreadable] hypotheses by quantifying hemodynamics and wall tensile stresses under resting and exercise conditions in[unreadable] the abdominal aorta of patients with small AAA randomized to chronic exercise therapy or standard therapy.[unreadable] Our specific aims are: (1) Quantify time-varying abdominal aortic anatomy in AAA patients, (2) Quantify[unreadable] abdominal aortic blood flow at rest and during dynamic exercise using a custom MR-compatible bike in a 0.5T[unreadable] open MRI, and (3) Develop and validate computational methods to model blood flow, pressure, and wall[unreadable] motion in "patient-specific" computational models of the abdominal aorta of patients with small AAA[unreadable] randomized to chronic exercise therapy or standard therapy.

DESCRIPTION (provided by applicant): Cardiovascular disease remains the leading cause of death and disability in the USA and stiffening of central arteries is now an unquestioned independent risk factor for many such diseases, including heart attack, stroke, and end-stage renal disease. The six primary determinants of the structural stiffness of arteries are elastic fiber integrity, collagen organization, smooth muscle tone, wall thickness, axial pre-stretch, and perivascular support, each of which has a molecular and cellular basis and affects system-level hemodynamics. Easily measured clinical metrics, such as pulse wave velocity, can and must play an increasingly greater role in cardiovascular risk assessment, but we must understand much better the mechanical and biological basis for changes in such metrics. For example, the relation between pulse wave velocity and arterial stiffness is often justified based on the Moens-Korteweg equation, which ignores almost all of the key determinants of wall stiffness. Our approach is unique because we will be the first to combine genetically modified mouse models and pharmacological interventions to delineate directly the effects on the material stiffness of the wall due to the integrity of elastic fibers, organization of collagen fibers, and contractility of smooth muscle. Moreover, this information will be incorporated within a novel computational tool that will allow effects of axial prestretch, perivascular support, and most importantly spatially and temporally progressive changes in large artery wall composition on hemodynamic metrics to be rigorously assessed for the first time. In particular, we suggest that large artery stiffening likely progresses from proximal to distal large arteries and identification of the early onset of such changes (e.g., prior to marked changes in pulse wave velocity) may allow earlier diagnosis and thus more effective intervention, prior to the propagation of detrimental effects of large artery stiffening to distal muscular arteries and eventually the microvessels, changes to which may be more difficult to reverse pharmacologically. Hence, we seek to deepen our fundamental understanding of the basis of arterial stiffening and to enable better clinical assessments and treatment planning based on readily available data. Specifically, we hypothesize that central arteries stiffen due, in large part, to a cyclic-strain induced damage to or degradation of elastic fibers that likely progresses over time from proximal to distal arteries because of initial spatial distributions of elastin and associated wall strains. To test this hypothesis, we will quantify and compare for the first time progressive changes in wall mechanics, composition, and hemodynamics in 3 basic mouse models (wild-type, fibrillin-1 deficient, and fibulin-5 null), each subjected to 3 pharmacological inter- ventions (L-NAME, doxycycline, and BAPN). That is, we will use genetically modified mouse models of graded decreases in elastic fiber integrity, not initially diminished elastin, for this will allow progressive changes to be quantified independent of possible compensatory adaptations that occur during development in elastin deficient mice. We expect loss of nitric oxide (L-NAME group) to highlight a role of smooth muscle tone and exacerbate the progression of wall stiffening, diminished proteinase activity (doxycycline) to separate roles of mechanical damage and chemical degradation of elastin while attenuating wall stiffening, and inhibiting collagen cross-linking (BAPN) to separate the coupled effects of elastin on the stiffness of extant collagen from the role of new collagen deposition. The experimental data will be used to construct, verify, and validate a novel fluid-solid-interaction model that can reveal precisely the effects of individual determinants of wall stiffening on system-level hemodynamics. Once accomplished for the mouse, parametric studies will be performed on 3 prototypical models of hemodynamics in humans (young, middle-aged, and old) to reveal, for the first time, the effects of progressive wall stiffening on clinical metrics of hemodynamics such as pulse wave velocity, pulse pressure, and pulse pressure waveform. We submit that modeling studies alone can delineate effects of spatially and temporally progressive increases in arterial stiffening on system-level hemodynamics, with the potential to identify improved indicators of early stiffening that may allow an earlier clinical intervention that can prevent the longer-term irreversible changes to the microstructure that otherwise inevitably occur. PUBLIC HEALTH RELEVANCE: Cardiovascular disease remains the leading cause of death and disability in the USA and stiffening of central arteries is now an unquestioned independent risk factor for many such diseases, including heart attack, stroke, and end-stage renal disease. The six primary contributors to arterial stiffness are elastic fiber integrity, collagen organization, smooth muscle contractility, wall thickness, axial prestretch, and perivascular support, each of which has a molecular and cellular basis. We will be the first to combine genetically modified mouse models, pharmacological interventions, and sophisticated computational biomechanical models to delineate effects of these six contributors on arterial stiffness and hemodynamics. Our novel data will provide unique insights into mechanisms of arterial stiffening and our new fluid-solid-interaction model will increase our ability to interpret current clinical indicators of cardiovascular risk and identify new metrics that yield more information.