The association of depression and perceived stress with beta cell function between African and Haitian Americans with and without type 2 diabetes

Background: Diabetes and diabetes-related complications are major causes of morbidity and mortality in the United States. Depressive symptoms and perceived stress have been identified as possible risk factors for beta cell dysfunction and diabetes. The purpose of this study was to assess associations between depression symptoms and perceived stress with beta cell function between African and Haitian Americans with and without type 2 diabetes. Participants and Methods: Informed consent and data were available for 462 participants (231 African Americans and 231 Haitian Americans) for this cross-sectional study. A demographic questionnaire developed by the Primary Investigator was used to collect information regarding age, gender, smoking, and ethnicity. Diabetes status was determined by self-report and confirmed by fasting blood glucose. Anthropometrics (weight, and height and waist circumference) and vital signs (blood pressure) were taken. Blood samples were drawn after 8 10 hours over-night fasting to measure lipid panel, fasting plasma glucose and serum insulin concentrations. The homeostatic model assessment, version 2 (HOMA2) computer model was used to calculate beta cell function. Depression was assessed using the Beck Depression Inventory-II (BDI-II) and stress levels were assessed using the Perceived Stress Scale (PSS). Results: Moderate to severe depressive symptoms were more likely for persons with diabetes (p = 0.030). There were no differences in perceived stress between ethnicity and diabetes status (p = 0.283). General linear models for participants with and without type 2 diabetes using beta cell function as the dependent variable showed no association with depressive symptoms and perceived stress; however, Haitian Americans had significantly lower beta cell function than African Americans both with and without diabetes and adjusting for age, gender, waist circumference and smoking. Further research is needed to compare these risk factors in other race/ethnic groups.

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.

Signal processing and information fusing algorithms for the synthesis of an alternative electromyogram/eye gaze tracking computer cursor control system

This research pursued the conceptualization and real-time verification of a system that allows a computer user to control the cursor of a computer interface without using his/her hands. The target user groups for this system are individuals who are unable to use their hands due to spinal dysfunction or other afflictions, and individuals who must use their hands for higher priority tasks while still requiring interaction with a computer. ^ The system receives two forms of input from the user: Electromyogram (EMG) signals from muscles in the face and point-of-gaze coordinates produced by an Eye Gaze Tracking (EGT) system. In order to produce reliable cursor control from the two forms of user input, the development of this EMG/EGT system addressed three key requirements: an algorithm was created to accurately translate EMG signals due to facial movements into cursor actions, a separate algorithm was created that recognized an eye gaze fixation and provided an estimate of the associated eye gaze position, and an information fusion protocol was devised to efficiently integrate the outputs of these algorithms. ^ Experiments were conducted to compare the performance of EMG/EGT cursor control to EGT-only control and mouse control. These experiments took the form of two different types of point-and-click trials. The data produced by these experiments were evaluated using statistical analysis, Fitts' Law analysis and target re-entry (TRE) analysis. ^ The experimental results revealed that though EMG/EGT control was slower than EGT-only and mouse control, it provided effective hands-free control of the cursor without a spatial accuracy limitation, and it also facilitated a reliable click operation. This combination of qualities is not possessed by either EGT-only or mouse control, making EMG/EGT cursor control a unique and practical alternative for a user's cursor control needs. ^

Quality of life and application of the transtheoretical model to diabetes self -management behaviors in older adults with type 2 diabetes

One in five adults 65 years and older has diabetes. Coping with diabetes is a lifelong task, and much of the responsibility for managing the disease falls upon the individual. Reports of non-adherence to recommended treatments are high. Understanding the additive impact of diabetes on quality of life issues is important. The purpose of this study was to investigate the quality of life and diabetes self-management behaviors in ethnically diverse older adults with type 2 diabetes. The SF-12v2 was used to measure physical and mental health quality of life. Scores were compared to general, age sub-groups, and diabetes-specific norms. The Transtheoretical Model (TTM) was applied to assess perceived versus actual behavior for three diabetes self-management tasks: dietary management, medication management, and blood glucose self-monitoring. Dietary intake and hemoglobin A1c values were measured as outcome variables. Utilizing a cross-sectional research design, participants were recruited from Elderly Nutrition Program congregate meal sites (n = 148, mean age 75). ^ Results showed that mean scores of the SF-12v2 were significantly lower in the study sample than the general norms for physical health (p < .001), mental health (p < .01), age sub-group norms (p < .05), and diabetes-specific norms for physical health (p < .001). A multiple regression analysis found that adherence to an exercise plan was significantly associated with better physical health (p < .001). Transtheoretical Model multiple regression analyses explained 68% of the variance for % Kcal from fat, 41% for fiber, 70% for % Kcal from carbohydrate, and 7% for hemoglobin A 1c values. Significant associations were found between TTM stage of change and dietary fiber intake (p < .01). Other significant associations related to diet included gender (p < .01), ethnicity (p < .05), employment (p < .05), type of insurance (p < .05), adherence to an exercise plan (p < .05), number of doctor visits/year ( p < .01), and physical health (p < .05). Significant associations were found between hemoglobin A1c values and age ( p < .05), being non-Hispanic Black (p < .01), income (p < .01), and eye problems (p < .05). ^ The study highlights the importance of the beneficial effects of exercise on quality of life issues. Furthermore, application of the Transtheoretical Model in conjunction with an assessment of dietary intake may be valuable in helping individuals make lifestyle changes. ^

A Case-Only Genome-wide Association Study of Gender- and Age-specific Risk Markers for Childhood Leukemia

Males and age group 1 to 5 years show a much higher risk for childhood acute lymphoblastic leukemia (ALL). We performed a case-only genome-wide association study (GWAS), using the Illumina Infinium HumanCoreExome Chip, to unmask gender- and age-specific risk variants in 240 non-Hispanic white children with ALL recruited at Texas Children’s Cancer Center, Houston, Texas. Besides statistically most significant results, we also considered results that yielded the highest effect sizes. Existing experimental data and bioinformatic predictions were used to complement results, and to examine the biological significance of statistical results. Our study identified novel risk variants for childhood ALL. The SNP, rs4813720 (RASSF2), showed the statistically most significant gender-specific associations (P < 2 x 10-6). Likewise, rs10505918 (SOX5) yielded the lowest P value (P < 1 x 10-5) for age-specific associations, and also showed the statistically most significant association with age-at-onset (P < 1 x 10-4). Two SNPs, rs12722042 and 12722039, from the HLA-DQA1 region yielded the highest effect sizes (odds ratio (OR) = 15.7; P = 0.002) for gender-specific results, and the SNP, rs17109582 (OR = 12.5; P = 0.006), showed the highest effect size for age-specific results. Sex chromosome variants did not appear to be involved in gender-specific associations. The HLA-DQA1 SNPs belong to DQA1*01:07and confirmed previously reported male-specific association with DQA1*01:07. Twenty one of the SNPs identified as risk markers for gender- or age-specific associations were located in the transcription factor binding sites and 56 SNPs were non-synonymous variants, likely to alter protein function. Although bioinformatic analysis did not implicate a particular mechanism for gender- and age-specific associations, RASSF2 has an estrogen receptor-alpha binding site in its promoter. The unknown mechanisms may be due to lack of interest in gender- and age-specificity in associations. These results provide a foundation for further studies to examine the gender- and age-differential in childhood ALL risk. Following replication and mechanistic studies, risk factors for one gender or age group may have a potential to be used as biomarkers for targeted intervention for prevention and maybe also for treatment.