Analysis of the feeding behaviour of the mosquito Culex pipiens L. (Diptera: Culicidae) in relation to West Nile virus

The goal ofthis literature review is to inform the reader on several aspects of West Nile Virus (WNV) transmission by its mosquito vector, Culex pipiens and to elucidate how Cx. pipiens and WNV are intertwined. The first few sections of the literature review describe the life cycle and blood feeding behaviours ofmosquitoes so that baseline data ofmosquito biology are established. In addition to explaining how and why a mosquito blood feeds, the section on "Blood Meal Analysis" describes the different methods for determining the vertebrate source of mosquito blood meals and a brief history of these testing methods. Since this thesis looks at the feeding behaviour of Cx. pipiens, it is important to know how to determine what they are feeding upon. Discussion on other mosquito-borne diseases related to WNV gives a broader perspective to the thesis, and examines other diseases that have occurred in Ontario in the past. This is followed by background information on WNV and theories on how this virus came to North America and how it relates to Cx. pipiens. The final sections discuss Cx. pipiens and give background information to how this species of mosquito exists and behaves within North America.

The Influence of Male Diet on Life History Traits of Female Mosquitoes

In the field, mosquitoes characteristically feed on sugars soon after emergence and intermittently during their adult lives. Sugar meals are commonly derived from plant nectar and homopteran honeydew, and without them, adults can only survive for a few days on larval reserves. In addition to sugar, females of most species rely on blood for the initiation and maintenance of egg development; thus their reproductive success depends to some extent on the availability of blood hosts. Males, on the other hand, feed exclusively on sugars. Consequently, their sexual maturation and reproductive success is largely dependent upon access to sugar sources. Plant nectar and homopteran honeydew are the two main sugar sources utilized by mosquitoes in the wild. Previous laboratory studies had shown that differences between nectar sources can affect the survivorship and biting frequency of disease vectoring mosquitoes. However, little is known on how sugar composition influence the reproductive processes in male mosquitoes. Male mosquitoes transfer accessory gland proteins and other hormones to their mates along with sperm during mating. In the female, these seminal fluid constituents exert their influence on reproductive genes that control ovulation and vitellogenesis. The present study tests the hypothesis that the mates of males consuming different sugar meals will exhibit varying levels of induction of vitellogenin (a gene which regulates the expression of egg yolk precursor proteins). Real-time quantitative RT-PCR was used to investigate how each sugar meal indirectly influences vitellogenin mRNA abundance in female Anopheles stephensi following mating. Results indicate that mates of nectar-fed males exhibit 2-fold greater change in vitellogenin expression than the mates of honeydew-fed males. However, this response did not occur in non-blood fed controls. These findings suggest that the stimulatory effect of mating on vitellogenesis in blood meal-reliant (i.e. anautogenous) mosquitoes may only be synergistic in nature. The present study also sought to compare the potential fitness costs of mating incurred by females that do not necessarily require a blood meal to initiate a reproductive cycle (i.e., exhibit autogeny). Females of the facultatively autogenous mosquito, Culex molestus were allowed to mate with males sustained on either nectar or honedyew. Mean lifetime fecundity and survivorship of females under the two different mating regimes were then recorded. Additionally, one-dimensional gel electrophoresis was used to verify the transfer of male accessory gland proteins to the sperm storage organs of females during mating.While there was no significant difference in survival between the test treatments, the mates of nectar-fed males produced 11% more eggs on average than mates of honeydew-fed males. However, additional data are needed to justify the extrapolation of these findings to natural settings. These findings prompt further investigation as the differences caused by diet variation in males may be reflected across other life history traits such as mating frequency and insemination capacity.

The role of molecular, clinical and socioeconomic factors in the long-term survival of axillary node negative breast cancer patients

The overall objective of this study was to investigate factors associated with long-term survival in axillary node negative (ANN) breast cancer patients. Clinical and biological factors included stage, histopathologic grade, p53 mutation, Her-2/neu amplification, estrogen receptor status (ER), progesterone receptor status (PR) and vascular invasion. Census derived socioeconomic (SES) indicators included median individual and household income, proportions of university educated individuals, housing type, "incidence" of low income and an indicator of living in an affluent neighbourhood. The effects of these measures on breast cancer-specific survival and competing cause survival were investigated. A cohort study examining survival among axillary node negative (ANN) breast cancer patients in the greater Toronto area commenced in 1 989. Patients were followed up until death, lost-to-follow up or study termination in 2004. Data were collected from several sources measuring patient demographics, clinical factors, treatment, recurrence of disease and survival. Census level SES data were collected using census geo-coding of patient addresses' at the time of diagnosis. Additional survival data were acquired from the Ontario Cancer Registry to enhance and extend the observation period of the study. Survival patterns were examined using KaplanMeier and life table procedures. Associations were examined using log-rank and Wilcoxon tests of univariate significance. Multivariate survival analyses were perfonned using Cox proportional hazards models. Analyses were stratified into less than and greater than 5 year survival periods to observe whether known markers of short-tenn survival were also associated with reductions in long-tenn survival among breast cancer patients. The 15 year survival probabilities in this cohort were: for breast cancerspecific survival 0.88, competing causes survival 0.89 and for overall survival 0.78. Estrogen receptor (ER) and progesterone receptor (PR) status (Hazard Ratio (HR) ERIPR- versus ER+/PR+, 8.15,95% CI, 4.74, 14.00), p53 mutation (HR, 3.88, 95% CI, 2.00, 7.53) and Her-2 amplification (HR, 2.66, 95% CI, 1.36, 5.19) were associated with significant reductions in short-tenn breast cancer-specific survival «5 years following diagnosis), however, not with long-term survival in univariate analyses. Stage, histopathologic grade and ERiPR status were the clinicallbiologieal factors that were associated with short-term breast cancer specific survival in multivariate results. Living in an affluent neighbourhood (top quintile of median household income compared to the rest of the population) was associated with the largest significant increase in long-tenn breast cancer-specific survival after adjustment for stage, histopathologic grade and treatment (HR, 0.36, 95% CI, 0.12, 0.89).

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.