The goal of this inductive study was to identify factors that facilitate and inhibit binational collaboration in the recovery of endangered species in the northern Mexico borderlands, focusing on the Mexican wolf (Canis lupus baileyi). A conceptual model was developed using qualitative techniques, providing the basis for design of a mail survey. The target population included participants with experience in recovery efforts for over a dozen species at risk in the region. Long interviews were recorded with 44 participants from Mexico and the United States. Thematic hierarchical analysis was used to develop a conceptual model of how interviewees talked about factors influencing binational collaboration. Issues were classified in five thematic clusters: project, organization, people, resources, culture/history. The survey was used to conduct a needs assessment, measuring respondents' attitudes about the relative priority of issues identified in the conceptual model. High priority needs were identified from each thematic cluster: (a) equitable participation in project design and implementation, (b) continuity of personnel, (c) coordination of federal, state and local efforts, (d) increased funding, managed with accountability, and (e) exchange visits to facilitate understanding of diverse perspectives. Responses to almost half the survey items indicated accord among the sample of respondents, providing a basis for shared common ground. The nature of discord was within the range of "manageable", with no clear polarization of attitudes measured. This exploratory data analysis suggested that the structure of the conceptual model developed from the Mexican wolf case study was generally a valid basis for future deductive analysis and reflection by practitioners. For 82% of 22 statements of need, priorities of participants in the Mexican wolf recovery efforts did not differ significantly from other respondents. Nationality (of respondents) significantly affected priority rankings for only 18% of the need statements. Significant effects of five demographic variables indicated that interactive effects should be examined in future multivariate analyses to determine how respondents' attitudes on issues related to priority rankings. Recommendations were provided for a more efficient and effective approach to collaborative problem-solving, engaging reflective practitioners from the private and public sectors in principled negotiation processes to better understand diverse perspectives.

The use of the local likelihood method (Tibshirani and Hastie, 1987; Loader, 1996) in the presence of interval-censored or aggregated data leads to a natural consideration of an EM-type strategy, or rather a local EM algorithm. In the thesis, we consider local EM to analyze the point process data that are either interval-censored or aggregated into regional counts. We specifically formulate local EM algorithms for density, intensity and risk estimation and implement the algorithms using a piecewise constant function. We demonstrate that the use of the piecewise constant function at the E-step explicitly results in an iteration that involves an expectation, maximization and smoothing step, or an EMS algorithm considered in Silverman, Jones, Wilson and Nychka (1990). Consequently, we reveal a previously unknown connection between local EM and the EMS algorithm. From a theoretical perspective, local EM and the EMS algorithm complement each other. Although the statistical methodology literature often characterizes EMS methods as ad hoc, local likelihood suggests otherwise as the EMS algorithm arises naturally from a local likelihood consideration in the context of point processes. Moreover, the EMS algorithm not only serves as a convenient implementation of the local EM algorithm but also provides a set of theoretical tools to better understand the role of local EM. In particular, we present results that reinforce the suggestion that the pair of local EM and penalized likelihood are analogous to that of EM and likelihood. Applications include the analysis of bivariate interval-censored data as well as disease mapping for a rare disease, lupus, in the Greater Toronto Area.

The use of the local likelihood method (Tibshirani and Hastie, 1987; Loader, 1996) in the presence of interval-censored or aggregated data leads to a natural consideration of an EM-type strategy, or rather a local EM algorithm. In the thesis, we consider local EM to analyze the point process data that are either interval-censored or aggregated into regional counts. We specifically formulate local EM algorithms for density, intensity and risk estimation and implement the algorithms using a piecewise constant function. We demonstrate that the use of the piecewise constant function at the E-step explicitly results in an iteration that involves an expectation, maximization and smoothing step, or an EMS algorithm considered in Silverman, Jones, Wilson and Nychka (1990). Consequently, we reveal a previously unknown connection between local EM and the EMS algorithm. From a theoretical perspective, local EM and the EMS algorithm complement each other. Although the statistical methodology literature often characterizes EMS methods as ad hoc, local likelihood suggests otherwise as the EMS algorithm arises naturally from a local likelihood consideration in the context of point processes. Moreover, the EMS algorithm not only serves as a convenient implementation of the local EM algorithm but also provides a set of theoretical tools to better understand the role of local EM. In particular, we present results that reinforce the suggestion that the pair of local EM and penalized likelihood are analogous to that of EM and likelihood. Applications include the analysis of bivariate interval-censored data as well as disease mapping for a rare disease, lupus, in the Greater Toronto Area.

The purpose of this study was to characterize the association between anti-prothrombin antibodies and the lupus anticoagulant (LA) in order to elucidate the antigenic site of the LA. Plasma from 8 patients with the LA had evidence of anti-prothrombin antibodies on prothrombin crossed immunoelectrophoresis as characterized by material moving slower in the first dimension of electrophoresis than normal prothrombin, i.e., a trailing shoulder. Four of 5 LA patients with a prolonged prothrombin time demonstrated the most pronounced evidence of anti-prothrombin antibodies. All patients were shown to have an essentially normal level of prothrombin antigen. Using an enzyme-linked immunosorbent assay (ELISA), six of 8 LA patients tested positive for anticardiolipin antibodies (aCL) of the IgG isotype while 7 of 8 LA patients tested positive for antiphosphatidylserine antibodies (aPS) of the IgG isotype.An anti-human Factor II (prothrombin) ELISA was developed to confirm the presence of anti-Factor II (aFII) activity in LA patients. Seven of 8 LA patients were positive for aFII activity. A strong parallel existed between the presence of aPS activity, anti-human Factor II activity, and the LA, i.e., 7 of 8 LA plasmas were aPS (+)/aFII (+). An antibovine Factor II ELISA was developed to determine if the aFII activity associated with LA patients is speciesspecific. Three of 5 LA patients positive for anti-human Factor II activity were also shown to be positive for antibovine Factor II activity. Antibodies with specificity for human prothrombin were purified from LA plasmas using a prothrombin affinity column. Three of 8 LA patient eluates were shown to be positive for aPS (IgG) while none were positive for aCL (IgG or IgM) or human aFII activity. Affinity-purified eluates were assayed for LA activity using the dilute Russell viper venom time (dRVVT). None of the LA patient eluates were shown to prolong the dRVVT when present with normal plasma in concentrations up to 100 micrograms/mL. / Department of Chemistry

Access to abstract permanently restricted to Ball State community only. / Access to thesis permanently restricted to Ball State community only. / Department of Physiology and Health Science

Systemic Lupus Erythematosus (SLE), a prototypic multi-organ autoimmune disease, is associated with a dramatically increased risk of coronary artery disease (CAD) manifesting as angina, myocardial infarction and sudden cardiac death. Traditional cardiac risk factors such as hypertension and hypercholesterolemia, measured at baseline in accordance with the Framingham model, only partially account for the increased risk of CAD in SLE. In this thesis, I have shown that blood pressure (BP), lipids and novel risk factors such as the inflammatory marker high-sensitivity C-reactive protein (hsCRP), take a dynamic course in SLE, with more than half of the variance in serial measurements over time occurring within rather than between individuals. This variability is due to changes in disease activity, treatment, accrual of other cardiac risk factors, and complications such as infection. I have demonstrated that by capturing cumulative exposure over time, ‘summary measures’ such as arithmetic mean and time-adjusted mean (AM) are better able to quantify CAD risk in patients with SLE than single-point-in-time measurements of risk factors. By incorporating ‘summary measures’ such as mean and AM into time-dependent covariate survival analysis models, I was able to quantify the magnitude of increase in CAD risk associated with increments in systolic and diastolic BP, and to demonstrate and quantify the association between several lipids / lipoproteins and CAD risk in SLE. Using this methodology, I was also able to demonstrate that despite marked variability over time, ‘summary measures’ of hsCRP are independently predictive of CAD risk among patients with SLE, highlighting the pivotal role of inflammation in atherosclerosis. Furthermore, I was able to determine lipid and hsCRP ‘cut-points’ that will aid clinicians in identifying a subgroup of patients with SLE who are at significantly increased cardiac risk.

Systemic Lupus Erythematosus (SLE), a prototypic multi-organ autoimmune disease, is associated with a dramatically increased risk of coronary artery disease (CAD) manifesting as angina, myocardial infarction and sudden cardiac death. Traditional cardiac risk factors such as hypertension and hypercholesterolemia, measured at baseline in accordance with the Framingham model, only partially account for the increased risk of CAD in SLE. In this thesis, I have shown that blood pressure (BP), lipids and novel risk factors such as the inflammatory marker high-sensitivity C-reactive protein (hsCRP), take a dynamic course in SLE, with more than half of the variance in serial measurements over time occurring within rather than between individuals. This variability is due to changes in disease activity, treatment, accrual of other cardiac risk factors, and complications such as infection. I have demonstrated that by capturing cumulative exposure over time, ‘summary measures’ such as arithmetic mean and time-adjusted mean (AM) are better able to quantify CAD risk in patients with SLE than single-point-in-time measurements of risk factors. By incorporating ‘summary measures’ such as mean and AM into time-dependent covariate survival analysis models, I was able to quantify the magnitude of increase in CAD risk associated with increments in systolic and diastolic BP, and to demonstrate and quantify the association between several lipids / lipoproteins and CAD risk in SLE. Using this methodology, I was also able to demonstrate that despite marked variability over time, ‘summary measures’ of hsCRP are independently predictive of CAD risk among patients with SLE, highlighting the pivotal role of inflammation in atherosclerosis. Furthermore, I was able to determine lipid and hsCRP ‘cut-points’ that will aid clinicians in identifying a subgroup of patients with SLE who are at significantly increased cardiac risk.

Systemic lupus erythematosus (SLE) is a relatively rare autoimmune disease with no known aetiology or cure. In addition to numerous physical symptoms, those living with SLE have also been shown to experience significant emotional and psychosocial difficulties. There has been little psychological research into SLE despite the rapidly increasing interest in health psychology and quality of life issues over the last two decades. One such issue that has commanded particular attention is that of cognitive bias in individuals with chronic pain and/or chronic illness. Cognitive bias toward illness-related information is theorised to indicate the presence of an illness self-schema, and is a valuable tool of investigation as it permits access to a level of cognitive structure that is inaccessible via self-report instruments. The primary focus of the present study is to investigate recall bias for pain- and illness-related words in SLE patients. This bias is explored relative to the recall of neutral words and depression-related words, and also relative to the responses of rheumatoid arthritis (RA) patients and healthy controls. Two hypotheses are proposed: firstly, that bias is related to disease activity; and secondly, that bias is related to the combination of illness and depression. The findings provide support for the second hypothesis, with the additional caveat that the nature of the pain/illness stimuli used is important in determining the presence of cognitive bias. No recall bias for illness-related words as a whole was found in any of the groups, nor was there evidence of a recall bias in the SLE and RA patients when they were divided according to depression status. However, when the illness words were examined separately according to �sensory pain� and �disability-related� words, a clear bias for disability words was found in the depressed patient group. It is concluded that there is a relationship between depression in chronically ill individuals, and the way in which such individuals process disability-related words. In accordance with the schema-enmeshment model (Pincus & Morley, 2001), it is suggested that both a pain-schema and an illness-schema exist, and it is when these two schemas become enmeshed with the self-schema that depression occurs in chronic pain/chronically ill patients. The cognitive bias assessment paradigm adopted in this study-one that is typically used in similar investigations-is lengthy, requires sophisticated equipment and can be difficult to interpret on an individual level. The present study investigates the relationship between cognitive biases in SLE patients and a recently-developed task, PRISM, which appears to symbolise the enmeshment of illness-, pain- and self-schemas. Analyses confirmed that recall of negative illness words was the only independent predictor of PRISM scores. This suggests that PRISM, a quick and easy task to administer, may have considerable usefulness as a clinical tool to assess information relevant to the enmeshment of illness- and self-schema. A greater understanding of schema and the processing styles of chronically ill patients will allow for more effective psychological treatment such that quality of life can be improved.

Thesis (Ph. D.)--University of Toronto, 2004. / Adviser: Tom Humphries.

Thesis (M.Res.(Med.))--University of Hong Kong, 2007.