3 resultados para major epitope on CII

em CaltechTHESIS


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Amorphous metals that form fully glassy parts over a few millimeters in thickness are still relatively new materials. Their glassy structure gives them particularly high strengths, high yield strains, high hardness values, high resilience, and low damping losses, but this can also result in an extremely low tolerance to the presence of flaws in the material. Since this glassy structure lacks the ordered crystal structure, it also lacks the crystalline defect (dislocations) that provides the micromechanism of toughening and flaw insensitivity in conventional metals. Without a sufficient and reliable toughness that results in a large tolerance of damage in the material, metallic glasses will struggle to be adopted commercially. Here, we identify the origin of toughness in metallic glass as the competition between the intrinsic toughening mechanism of shear banding ahead of a crack and crack propagation by the cavitation of the liquid inside the shear bands. We present a detailed study over the first three chapters mainly focusing on the process of shear banding; its crucial role in giving rise to one of the most damage-tolerant materials known, its extreme sensitivity to the configurational state of a glass with moderate toughness, and how the configurational state can be changed with the addition of minor elements. The last chapter is a novel investigation into the cavitation barrier in glass-forming liquids, the competing process to shear banding. The combination of our results represents an increased understanding of the major influences on the fracture toughness of metallic glasses and thus provides a path for the improvement and development of tougher metallic glasses.

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More than thirty years after the discovery that Human Immunodeficiency Virus (HIV) was the causative agent of Acquired Immunodeficiency Syndrome (AIDS), the disease remains pandemic as long as no effective universal vaccine is found. Over 34 million individuals in the world are infected with the virus, and the vast majority of them have no access to the antiretroviral therapies that have largely reduced HIV to a chronic disease in the developed world. The first chapter of this thesis introduces the history of the virus. The key to the infectious mechanism of the virus lies in its envelope glycoprotein (Env), a trimeric spike on the viral surface that utilizes host T cell receptors for entry. Though HIV-1 Env is immunogenic, most infected patients do not mount an effective neutralizing antibody response against it. Broadly-neutralizing anti-Env antibodies (bNAbs) present in the serum of a minority of infected individuals are usually sufficient to prevent the progression to full blown AIDS. Thus, the molecular details of these bNAbs as well as the antibody-antigen interface are of prime interest for structural studies, as insight gained would contribute to the design of a more effective immunogen and potential vaccine candidate. The second chapter of this thesis describes the low-resolution crystal structure of one such antibody, 2G12 dimer, which targets a high mannose epitope on the surface of Env. Patients infected with HIV-2, a related virus with ~35% sequence identity in the Env region, can generally mount a robust antibody response sufficient for viral control for reasons still unknown. The final two chapters of this thesis focus on the first reported structural studies of HIV-2 Env, the molecular details of which may inform HIV-1 therapy and immunogen design.

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This thesis is an investigation into the nature of data analysis and computer software systems which support this activity.

The first chapter develops the notion of data analysis as an experimental science which has two major components: data-gathering and theory-building. The basic role of language in determining the meaningfulness of theory is stressed, and the informativeness of a language and data base pair is studied. The static and dynamic aspects of data analysis are then considered from this conceptual vantage point. The second chapter surveys the available types of computer systems which may be useful for data analysis. Particular attention is paid to the questions raised in the first chapter about the language restrictions imposed by the computer system and its dynamic properties.

The third chapter discusses the REL data analysis system, which was designed to satisfy the needs of the data analyzer in an operational relational data system. The major limitation on the use of such systems is the amount of access to data stored on a relatively slow secondary memory. This problem of the paging of data is investigated and two classes of data structure representations are found, each of which has desirable paging characteristics for certain types of queries. One representation is used by most of the generalized data base management systems in existence today, but the other is clearly preferred in the data analysis environment, as conceptualized in Chapter I.

This data representation has strong implications for a fundamental process of data analysis -- the quantification of variables. Since quantification is one of the few means of summarizing and abstracting, data analysis systems are under strong pressure to facilitate the process. Two implementations of quantification are studied: one analagous to the form of the lower predicate calculus and another more closely attuned to the data representation. A comparison of these indicates that the use of the "label class" method results in orders of magnitude improvement over the lower predicate calculus technique.