BACKGROUND: Long-term exposure to fine particulate matter (PM2.5) has been identified as a potential risk factor for developing type 2 diabetes mellitus (T2DM). Given the rising prevalence of T2DM and unhealthy concentrations of PM2.5 in China, our attention is brought to examining the association in this region of the world. Furthermore, rural China, although largely ignored, also finds itself suffering from increased risks of T2DM and high levels of PM2.5. OBJECTIVE: The goal of this study is to characterize the relationship between long-term exposure to PM2.5 and the risk of T2DM in rural China. We do so by confirming that greater long-term exposure to PM2.5 is associated with a higher risk of T2DM incidence, assessing the potential multiplicative and additive interactions with important covariates, and identifying constituents of PM2.5 that may be responsible for the effect PM2.5 on the increased incidence of T2DM. CONCLUSIONS: Greater long-term exposure to PM2.5 is associated with increased risk of developing T2DM in rural Deqing County, Zhejiang, China. Smoking status modifies the relationship between PM2.5 and T2DM incidence on a multiplicative scale. There is no synergism between smoking and PM2.5 in association with T2DM incidence. There is no conclusive evidence on which constituents of PM2.5 play greater roles in the adverse effects of PM2.5 on T2DM incidence.

Aims: to test the hypothesis that peripheral blood neutrophils (PMN) exhibit delayed spontaneous apoptosis in individuals with type 2 Diabetes, and that the delay is further exacerbated in individuals who co-express chronic periodontitis. Materials and methods: 73 individuals were enrolled, including those with type 2 diabetes (T2DM) (n=16), chronic periodontitis (CP) (n=15), diabetics with chronic periodontitis (T2DM+CP) (n=21) and healthy volunteers (n=21). PMN apoptosis was determined by flow cytometry using TUNEL and Annexin V assays. Caspase 3, 8 and 9 activity was measured by colorimetric assay. PMN surface death receptor quantification was performed by flow cytometry staining with fluorescence conjugated anti-CD120a (TNFR1) and anti- CD95 (FasR) antibody. Inflammatory biomarker analyses of serum samples were performed using multiplexed sandwich immunoassays. Results: In healthy volunteers, individuals with T2DM, CP and T2DM+CP, spontaneous PMN apoptosis observed at 12 hours reached 85.3% ± 3.1, 67.3% ± 3.9, 62.9% ± 3.5 and 62.5% ± 5.4, respectively (p<0.05 ). Caspase-3 activity was significantly reduced in individuals with T2DM and T2DM+CP (p<0.05), when compared to healthy volunteers. Caspase-8 activity was also significantly decreased in CP and T2DM+CP (p<0.05), associated with reduced cell surface Fas receptor, TNF receptors and Fas ligand serum levels. Glucose alone was not observed to effect PMN apoptosis; concurrent incubation with the RAGE agonist S-100B induced a significant PMN apoptosis (p<0.05). Conclusion: These data support the premise that the inhibition of PMN apoptosis in individuals with T2DM occurs through an AGE/RAGE ligand/receptor mediated interaction.

No description available.

No description available.

Objectives: To describe the profile of Canadian adults with type 2 diabetes mellitus (T2DM), examine the prevalence of diabetes-related complications and investigate the factors associated with having common diabetes-related complications. Methods: Self-reported data from Statistics Canada’s 2011 Survey on Living with Chronic Diseases in Canada (SLCDC) – Diabetes component were available to describe the prevalence of T2DM, related complications and co-morbidities. Associations with diabetes-related complications were evaluated using logistic regression models. Survey weights and bootstrapping resampling method were applied to account for the complex survey design. Results: 2,341 T2DM respondents (weighted Canadian population estimate n=1,365,165) had a mean age of 62.9 years and diabetes duration of 10.6 years. The prevalence of diabetes-related complications and comorbidities were high: eye (34.0%), foot or leg (24.4%), cardiovascular (22.6%), renal (15.7%), neuropathy (10.8%), hypertension (68.4%) and high cholesterol (67.2%). Factors associated with diabetes-related complications were: Eye: > 65 years of age (odds ratio [OR] 3.7, 95% CI 2.4 – 5.5, p=<0.0001); household income < $29,999 (OR 1.9, 95% CI 1.1 – 3.2, p=0.01), diabetes duration > 10 years (OR 2.3, 95% CI 1.6 – 3.5, p<0.001), cardiovascular complications (OR 1.8, 95% CI 1.1 – 2.9, p=0.01). Renal: duration of diabetes 6 – 9 years (OR 3.0, 95% CI 1.4 – 6.3, p=0.02), duration of diabetes > 10 years (OR 2.1, 95% CI 1.1 – 3.9, p=0.04) Cardiovascular: male sex (OR 1.9, 95% CI 1.3 – 2.7, p=0.0006), eye complication (OR 1.9, 95% CI 1.2 – 3.0, p=0.007), foot or leg complication (OR 2.0, 95% CI 1.3 – 3.0, p=0.002). Foot or leg: cardiovascular complication (OR 2.0, 95% CI 1.4 – 3.1, p=0.0006). Neuropathy: household income $30,000 - $59,999 (OR 2.1, 95% CI 1.2 – 3.9, p=0.03); duration of diabetes >10 years (OR 1.9, 95% CI 1.1 – 3.8, p=0.01), foot or leg complication (OR 7.0, 95% CI 4.1 – 11.8, p<0.0001), eye complication (OR 2.0, 95% CI 1.1 – 3.7, p=0.006). Conclusions: The presence of diabetes-related complications among Canadians with T2DM is multifactorial. / Thesis / Master of Science (MSc)

Biological models of predator-prey interaction have been shown to have high sensitivity to the functional form of the predator response (see [3]). Chemo- stat models with competition have been shown to be robust under various forms of response function (see [15]). The fcus here is restricted to a simple chemostat model with predator-prey dynamics. Several functional responses of Holling Type II form are considered. The sensitivity of dynamics to our choice of functional form is demonstrated by way of bifurcation theory. These results should be a warning to modelers, since by data collection and curve- fitting alone it is impossible to determine the exact functional form of the predator response function. / Thesis / Master of Science (MSc)

Metformin is the most common type 2 diabetes therapy, and may also reduce colorectal cancer growth. Currently, two mechanisms driving reduced cancer growth are considered: 1) Regulation of glucose and insulin levels, which may support cancer growth, and 2) Direct entry into cancer cells to activate the AMP-activated kinase (AMPK) protein, and inhibit cell growth pathways. The gut microbiome is the community of commensal microorganisms in the gastrointestinal tract. It is also affected by metformin, and may elevate production of short-chain fatty acids (SCFAs). Therefore, this thesis aimed to clarify how metformin may inhibit colorectal cancer growth and if the microbiome is involved. The hyperglycemic-responsive, murine-derived MC38 colon cancer cell line was used to test these effects. This model was confirmed to experience growth stimulation caused by high-fat diet (HFD) feeding in mice. Daily i.p. injections of metformin (100mg/kg) had no measurable effect on glucose and insulin sensitivity, or MC38 tumor growth. Oral metformin (250mg/kg) improved glucose tolerance and inhibited MC38 tumor growth in HFD-fed mice. To see if the gut microbiome is required for this effect, the antibiotic ampicillin was used to limit the gut microbiome. The addition of ampicillin blunted metformin’s glucose sensitization and tumor inhibition effects. A fecal microbiome transfer model was then used to isolate the role of the microbiome. Conventional mice fed HFD and gavaged with feces from metformin-treated donors experienced no glucose or insulin tolerance improvements. However, tumor growth was decreased by 30%, and serum SCFAs concentrations were elevated. The SCFA butyrate inhibited in vitro MC38 colony growth, but did not activate AMPK. These data suggest that metformin alters the gut microbiome, and fecal transfer from metformin-treated animals can uncouple MC38 tumor growth inhibition from the glucose homeostasis effects of metformin. These novel findings support a new mechanism for metformin to prevent cancer growth and development. / Thesis / Doctor of Philosophy (PhD) / Metformin is the most commonly used type 2 diabetes therapy, and may also reduce colorectal cancer growth. Anti-cancer effects may be caused by: 1) decreased glucose and insulin levels, which support cancer growth; or 2) entry into cancer cells to directly decrease cell growth. The gut microbiome, microorganisms that live symbiotically in the gastrointestinal tract, is also affected by metformin. This thesis aimed to clarify how metformin can inhibit cancer, and if the microbiome is involved. Mice treated with metformin had improved glucose metabolism and decreased colorectal tumor growth; when an antibiotic was introduced, this effect was lost. A fecal microbiome transfer model was used to determine if the microbiome is driving this effect. Mice receiving feces from metformin treated mice also experienced tumor growth inhibition. This suggests that the gut microbiome is involved in the anti-cancer effects of metformin, and is a new potential mechanism of action.

Type 2 Diabetes Mellitus (T2DM), a metabolic disorder denoted by elevated blood glucose levels and insufficient insulin action, is growing in prevalence worldwide . Barriers to improving disease outcome resolve primarily around identifying and intervening during the preliminary stages of insulin resistance, a state clinically referred to as pre-diabetes. Emerging evidence suggests that mitochondrial dysfunction may underlie , and potentially precede, progressive insulin resistance, suggesting that biomarkers indicative of mitochondrial dysfunction could predict disease risk and status. In this study, we examined epigenetic modifications, in the form of DNA methylation, in the promoter region of peroxisome proliferator activated receptor gamma coactivator 1 alpha (PGC-1α), a known regulator of mitochondrial biogenesis. Following the initiation of a high fat diet, we observed significant genotypic (DNA methylation) and phenotypic (mitochondrial copy number) alterations in C57/BL6 rodent models. These changes preceded overt disease onset, as classified by clinically utilized indices, which included the homeostatic model assessment for insulin resistance (HOMA-IR), the homeostatic model assessment for β-cell dysfunction (HOMA- β), and the quantitative insulin-sensitivity check index (QUICKI). Our data indicate that methylation analysis may serve as an effective clinical parameter to use in conjunction with physiological criterion for the diagnosis of pre-diabetes and the assessment of T2DM disease risk, and adds to the growing body of work seeking to elucidate the role. / Doctor of Philosophy / High blood glucose, referred to as type 2 diabetes (T2DM), increases the risk for heart and kidney disease, blindness, stroke, and death. Efforts to prevent T2DM have centered primarily around behavioral interventions, which include increased physical activity and decreased caloric intake. Importantly, the interventions are most effective when implemented early on in disease progression. In this study, we sought to examine the effects of a high fat diet on the epigenetic profile of PGC-1α, a gene responsible for maintaining mitochondrial biogenesis. The mitochondria, the powerhouse of the cell, is responsible for maintaining the energy systems in the body. Therefore, we examined how increasing in caloric intake resulted in changes in the epigenetic profile of the PGC-1α promoter, and how these changes impacted mitochondrial number. Further, we sought to examine how hypermethylation of PGC-1α led to changes in gene and protein expression in the mitochondria. Results from our study indicate that DNA methylation changes preceded disease onset, as characterized by the homeostatic model assessment for insulin resistance (HOMA-IR), the homeostatic model assessment for β-cell dysfunction (HOMA- β), and the quantitative insulin-sensitivity check index (QUICKI). Our data indicate that methylation analysis may serve as diagnostic and risk assessment tool for pre-diabetes and T2DM in conjunction with physiological measures.

Yes / Individuals with type 2 diabetes play a pivotal role in their health. Enhancing the self-management of diabetes can improve blood glucose control, and quality of life, and reduce diabetes-related complications. We have identified factors influencing the self-management of type 2 diabetes to inform strategies that may be applied in the long-term management of blood glucose control. Methods: We conducted a systematic literature review of recent studies published between January 2010 to December 2020 to identify the available evidence on effective self-management strategies for type 2 diabetes. The databases used for the searchers were Scopus, PubMed, Science Direct, CINAHL, and Google Scholar. We assessed English language publications only. The screening of titles was duplicated by two researchers. We then conducted a thematic analysis of the key findings from eligible publications to identify reoccurring messages that may augment or abate self-management strategies. Results: We identified 49 relevant publications involving 90,857 participants. Four key themes were identified from these publications: Individual drive, social capital, Knowledge base, and Insufficient health care. High motivation and self-efficacy enabled greater self-management. The importance of family, friends, and the health care professional was salient, as were the negative effects of stigma and labelling. Enablers to good self-management were the level of support provided and its affordability. Finally, the accessibility and adequacy of the health care services emerged as fundamental to permit diabetes self-management. Conclusions: Self-management of type 2 diabetes is an essential strategy given its global presence and impact, and the current resource constraints in health care. Individuals with type 2 diabetes should be empowered and supported to self-manage. This includes awareness raising on their role in self-health, engaging broader support networks, and the pivotal role of health care professionals to inform and support. Further research is needed into the capacity assessment of healthcare systems in diabetes medicine, targeted low-cost resources for self-management, and the financial requirements that enable self-management advice to be enacted. / While this research did not receive any specific project funding, KRB is funded by a University of Otago Pacific Ph.D. Scholarship. ANR is funded as a Research Fellow by the National Heart Foundation.

This research realises a type-2 fuzzy probabilistic system for proactive monitoring of uncertain data-intensive seasonal time series in both theoretical and practical implications. In this thesis, a new form of representation, J˜-plane, is proposed for concave and unnormalized type-2 fuzzy events as well as convex and normalized ones, which facilitates bridging the gaps between higher order fuzzy probability realizations and real world problems. Since J˜-plane representation, the investigation of type-2 fuzzy probability theory and the proposal of a type-2 fuzzy probabilistic system become possible. Based on J˜-plane representation, a new fuzzy systemmodel - a type-2 fuzzy probabilistic system is proposed incorporating probabilistic inference with type-2 fuzzy sets. A special case study, a type-2 fuzzy SARIMA system is proposed and experimented in forecasting singleton and uncertain non-singleton bench mark data - Mackey-Glass time series. The results show that the type-2 fuzzy SARIMA system has achieved significant improvements beyond its predecessors - the classical statistical model - SARIMA, type-1 and general type-2 fuzzy logic systems, no matter whether in the singleton or the non-singleton experiments, whereas a SARIMA model cannot forecast non-singleton data at all. The type-2 fuzzy SARIMA system is applied in a real world scenario - WSS CAPS proactive monitoring, and compared with the results of the statistical model SARIMA, type-1 and general type-2 fuzzy logic systems to show that, the type-2 fuzzy SARIMA system can monitor practical uncertain data-intensive seasonal time series proactively and accurately, whereas its predecessors - the statistical model SARIMA, type-1 and general type-2 fuzzy logic systems - cannot deal with this at all. As a series of concepts, algorithms, experiments, practical implements and comparisons prove that, a type-2 fuzzy probabilistic system is viable in practice which realises that type-2 fuzzy systems evolve from rule-based fuzzy systems to the systems incorporating probabilistic inference with type-2 fuzzy sets.