There is an urgent need for the development of an effective therapeutic vaccine against cancer caused by human papilloma virus (HPV). We focused on HPV-induced malignancies because of their high worldwide prevalence (e.g., cervical carcinoma and head & neck cancer). A successful therapeutic vaccine could prevent the 250 000 deaths/year worldwide and the 2.25 billion dollars that are expended in related care in the US. We used an HPV-induced mouse cancer model to test vaccines composed of a CD8 T cell peptide epitope administered with potent adjuvants designed to generate vast numbers of high avidity cytotoxic T lymphocytes specific for the HPV16-E7 antigen. One vaccination strategy (TriVax) consists of intravenous administration of synthetic peptide HPV16-E749-57 administered together with a Poly-IC (a TLR3 agonist) and anti-CD40 monoclonal antibody(αCD40 mAb) while the second more simple strategy (BiVax) comprises solely of peptide plus Poly-IC. We used an E7 peptide as antigen in the vaccination strategies because expression of the viral E6 and E7 proteins is required to maintain oncogenic phenotype and because normal cells do not express E6/E7, therefore a therapeutic vaccine targeting these proteins has several advantages: a) a strong immune response can be induced since immune tolerance to these foreign antigens does not exist and b) the strong immune response should not inflict damage to normal cells. TriVax and BiVax generate a high number of antigen specific CD8 T cells capable clear subcutaneous tumors and prevent recurrences, both vaccines are efficient through the i.v. and i.m. route. TriVax (prime-boost) clears tumor in 100% of mice while BiVax clears tumor in 50% of mice, this differential effect is due to the number of antigen specific CD8 T cells and increasing the number of booster shot makes BiVax as immunogenic and efficient in clearing tumors. In the absence of type-I IFN signaling (in IFNαΒR KO mice), TriVax is less effective in generating sufficient numbers of CD8 T cells that could be necessary for total disease eradication. We observed a significant anti-tumor effect of TriVax in the absence of interferon gamma, however the cytokine may play some role in the overall effectiveness of TriVax to completely reject the tumors. Immune responses produced by BiVax are highly dependent on the simultaneous administration of peptide and Poly-IC, on the peptide composition, vaccine formulation and route of administration. The magnitude of the response is dependent on the expression of the Poly-IC receptors TLR3 and melanoma differentiation-associated protein 5 (MDA5). Interestingly, the magnitude and duration of the CD8 T cell responses generated by peptide and Poly-IC mixtures does not rely on the presence of CD4 T cells, scavenger receptor-A (SR-A) or type-I IFN signals and was minimally affected by the absence of CD40 signaling. The present findings could facilitate the development of simple and effective subunit vaccines for diseases where CD8 T cells may hold a therapeutic benefit.

Autism is a heterogeneous neurodevelopmental disorder that is characterized by impaired social interaction and communication as well as restricted and repetitive behaviors and focused interests. In addition to the cardinal behavioral characteristics observed for diagnosis, autistic individuals exhibit a number of comorbid conditions as well as a variety of aberrant immunological features. Recent studies report that plasma from autistic children contained elevated levels of secreted amyloid precursor protein alpha (sAPP-á), the á-secretase cleavage product of the amyloid precursor protein (APP) which is ubiquitously expressed in the brain, spleen, thymus and other organs. Interestingly, the sAPP-á fragment functions as a neurotrophic and neuroprotective factor in the central nervous system (CNS) and is also implicated in T-lymphocyte activation in the periphery. These functions of sAPP-á, alongside the observation of the fragment at elevated levels in autism patients, led us to hypothesize that sAPP-á over-expression is associated with autism and may be involved in its pathophysiology by impacting the brain or the immune system, leading to autistic-like behavior. In order to determine how the sAPP-á fragment may affect autism pathophysiology, we generated transgenic mice that overexpress human sAPP-á and used molecular biology, immunohistochemistry and behavioral techniques to study them. Additionally, we examined sAPP-á levels in plasma from a unique cohort of autism patients, and levels of both sAPP-á and the á-C-terminal fragment (á-CTF) in post mortem brains from an unrelated cohort of autistic patients. Resulting data from studies on autistic patient tissue samples confirmed the increase in plasma sAPP-á seen in autism patients in an earlier study and identified elevations in the sAPP-á and á-CTF fragments of post mortem insular cortex brain homogenates from autistic children. Data from molecular biology studies on the human sAPP-á transgenic (TgsAPP-á) mice demonstrate that these mice mimic the human autistic condition, expressing elevated levels of hsAPP-á in both the brain and plasma. They also show increased synaptophysin expression, suggesting increased synaptic density, in the brain. Behavior tests showed that while they do not display anxiety, lack of motor coordination/balance or impaired cognition, TgsAPP-á mice are hypoactive and the males exhibit decreased preference for social interaction. Molecular biology, immunohistochemistry and flow cytometry experiments focusing on immune function in TgsAPP-á mice unearthed aberrant development and function of T-cells. Compared to those from wild-type littermates, splenocytes from TgsAPP-á mice consisted of decreased B-cell and increased T-cell populations and secreted increased interferon-ã (IFN-ã), interleukin-2 (IL-2) and IL-4 after T-cell mitogen challenge. We discovered alterations in T-cell and thymocyte populations within TgsAPP-á mouse thymi, which may be explained by data portraying reduced apoptosis and decreased pro-apoptotic signaling. Finally, the splenocytes from TgsAPP-á mice immunized with myelin oligodendrocyte protein displayed impaired recall memory function which may be influenced by reduced phosphorylation of æ-chain-associated protein kinase 70 (ZAP-70), an apparent trait in TgsAPP-á mice irrespective of immunization. Altogether, the data leads us to conclude that overexpression of the sAPP-á fragment is indeed associated with autism, and sAPP-á overexpression leads to hypoactivity and impaired social behavior as well as aberrant T-lymphocyte development and function. For autism, the data implies that sAPP-á overexpression may contribute to autism pathophysiology through its effects on the immune system, leading to the characteristic behaviors. The data also provides evidence for a likely association between sAPP-á over-expression and aberrant T-cell populations and function in autism patients. Studies of sAPP-á interaction with the immune system and in the brain at the molecular level are needed to further clarify the purpose of sAPP-á overexpression in autism patients.

Bacteria evolve during the colonization of human hosts, yet little is known about the selective pressures and evolutionary forces that shape this evolution. Illumination of these processes may inspire new therapeutic directions for combating bacterial infections and promoting healthy bacteria-host interactions. The advent of high-throughput sequencing has enabled the identification of mutations that occur within the human host, and various tools from computational and evolutionary biology can aid in creating biological understanding from these mutations. Chapter 1 describes recent progress in understanding within-patient bacterial adaption, focusing on insights made from genomic studies.

Chlamydia trachomatis (CT) is a pestilent infection affecting upwards of 90 million people worldwide. An efficacious vaccine is needed to control the morbidities and rising healthcare cost associated with genital CT infection. We have established that protection against chlamydia infection parallels with a high frequency of T helper Type 1 cells and the associated antibodies. The current study focuses on the induction of innate immune responses involved during Chlamydia infection by a Vibrio cholera ghost-based (VCG) vaccine vector. THP-1 cells were used for dose and kinetic experiments. HeLa cells were used for infectivity assays. Based on preliminary studies, we hypothesized that the induction of immune responses by a VCG-based vaccine involves multiple innate immune signaling. Multiplex assay was used to measure T helper Type I and Type II cytokine secretion by THP-1 monocytes (Mn) or macrophages (Mϕ). Immunostimulatory cytokine secretion was significant when both cell morphologies were pulsed with VCG or VCG/murine splenocytes. We concluded that this secretion was significant enough to compliment that which would be secreted when THP-1 cells are pulsed with Chlamydia elementary bodies alone, enhancing the innate immune response during infection. Cellular supernatants (conditioned media) containing Th1-type and Th2-type cytokines were used to culture Chlamydia-infected HeLa cell monolayers. Infected HeLa monolayers cultured in the conditioned media were significantly less infected (968 IFUs) versus HeLa monolayers cultured in Earle’s minimum essential media (16,486 IFUs; p<0.001). We concluded that factors contained in conditioned media prevent and/or significantly reduce infection by Chlamydia and the development of inclusion forming units.

BACKGROUND: According to the Centers for Disease Control and Prevention and the National Immunization Program, there is an increase in the re-emergence of past diseases. Even with mandatory vaccination practices in the United States, there are still a number of cases of vaccine-preventable diseases (VPDs) reported yearly. It is speculated that the re-emergence of VPDs is in part due to the increase in international travel as well as the influx of immigrants. One particular group of interest includes the Hispanic migrants coming from Central and South America where some of these diseases are endemic. OBJECTIVE: The purpose of this paper is to determine the extent of VPD cases in the border state of Arizona that may be attributed to Hispanic migrant influx using data from the MMWR: Summary of Notifiable Diseases reports for the United States and the ADHS data from all Arizona counties. RESULTS: Since 1995, rates of hepatitis B and pertussis have been increasing in Arizona and have become higher for non-Hispanics than Hispanics. In 2005, hepatitis B rates were 1.53* for the United States and 7.31* for Arizona; pertussis rates were 8.72* for the United States and 21.60* for Arizona. CONCLUSION: The results of this study's analysis show the need to improve immunization efforts within the non-Hispanic populations in all Arizona counties. (*Per 100,000 population)

Public health professionals strive to understand how viruses are distributed in the environment, the factors that facilitate viral transmission, and the diversity of viral agents capable of infecting humans to characterize disease burdens and design effective disease intervention strategies. The public health discipline of conservation medicine supports this endeavor by encouraging researchers to identify previously unknown etiologic agents in wildlife and analyze the ecologic of basis of disease. Within this framework, this research reports the first examination of the prevalence in Southeast Asia of the orthoreovirus Nelson Bay virus in humans and in the Pteropus bat reservoir of the virus. Contact with Pteropus species bats places humans at risk for Nipah virus transmission, an important emerging infectious disease. This research furthermore explores the environmental determinants of Nelson Bay and Nipah viral prevalence in Pteropus bats and reports the characterization of two novel orthoreoviruses isolated from bat tissues collected in Bangladesh.

Individual-level models are a class of complex statistical models, often fitted within a Bayesian Markov chain Monte Carlo framework, that have been effectively used to model the spread of infectious diseases. The ability of these models to incorporate individual-level covariate information allows them to be highly flexible, and to account for such characteristics as population heterogeneity. However, these models can be subject to inherent uncertainties often found in infectious disease data. As well, their complex nature can lead to a significant computational expense when fitting these models to epidemic data, particularly for large populations. An individual-level model that incorporates a latent grouping structure into the modeling procedure, based on some heterogeneous population characteristics, is investigated. The dependence of this latent conditional individual-level model on a discrete latent grouping variable alleviates the need for explicit, although possibly unreliable, covariate information. A simulation study is used to assess the posterior predictive ability of this model, in comparison to individual-level models that utilize the full covariate information, or that assume population homogeneity. These models are also applied to data from the 2001 UK foot-and-mouth disease epidemic. When attempting to compare complex models fitted within the Bayesian framework, the identification of appropriate model selection tools would be beneficial. The use of deviance information criterion (DIC) as model comparison tool, particularly for the latent conditional individual-level models, is investigated. A simulation study is used to compare five variants of the DIC, and the ability of each DIC variant to select the true model is determined. Finally, an investigation into methods to reduce the computational burden associated with individual-level models is carried out, based on an individual-level model that also incorporates population heterogeneity through a discrete grouping variable. A simulation study is used to determine the effect of reducing the overall population size by aggregating the data into spatial clusters. Reparameterized individual-level models, accounting for the aggregation effect, are fitted to the aggregated data. The effect of data aggregation on the ability of two reparameterized individual-level models to identify a covariate effect, as well as on the computational expense of the model fitting procedure, is explored.

Emerging multidrug-resistant tuberculosis (MDR/XDR-TB) has become a major public health problem, placing millions at risk. Further, nosocomial transmission of MDR/XDR-TB places both patients and healthcare workers at an even higher risk. Effective tuberculosis (TB) infection prevention and control (IPC) policies in high-risk settings must use evidence-based science and should be customized to the setting. However, the growing incidence of MDR/XDR-TB in some global settings raises questions about whether adequate healthcare-related TB IPC policies are in place and whether they are implemented effectively. The purpose of this systematic literature review was to catalogue healthcare-related TB IPC policy research conducted in high-prevalence settings and draw a picture of existing evidence-based TB IPC policies and their implementation, with a focus on preventing and controlling nosocomial transmission of MDR/XDR-TB. Two databases (PubMed and Embase) were searched from 1990 – 2013 and outputs were categorized by region/country, income, MDR/XDR-TB incidence, level of IC intervention, and time period. None of the 20 captured research studies were conducted in TB high-prevalence, low-income settings. Most (12/20) were implemented within the Pan American Health Organization region, followed by the African (4/20) and European (4, 20%) regions. Most studies reviewed (70%) were undertaken because of an outbreak and most (70%) were published between 1990 – 2000. This systematic literature review showed a gap in research on TB IPC policies addressing nosocomial transmission of MDR/XDR-TB in high-prevalence, low-income settings. TB IPC policy development and implementation should be routinely undertaken as a part of effective and efficient public health practice. Development of TB IPC global best practices should be guaranteed and a concerted effort to promote, distribute, train, and implement these TB IPC best practices in low-resource countries would help mitigate the growing incidence of MDR/XDR-TB worldwide.

Malaria poses a serious threat to much of the developing world and an enormous effort is under way to design vaccines and other novel interventions. Nevertheless, we understand very little about the ecology and evolution of malaria parasites. For instance, while scientists have had considerable success identifying factors involved in regulating parasite growth within hosts, it is extremely hard to disentangle the relative influences of host immunity and other within-host factors on infection dynamics. Many mathematical models have been directed at understanding the dynamics of malaria infections, and these have provided valuable insights. However, these models have also been criticized, most notably for lacking any statistical analysis of the goodness of fit of model predictions to data. Here, we develop a new modeling approach that improves on previous work, and apply it to a novel data set from a simplified rodent malaria system. We find that resource availability and competition are important drivers of dynamics, and we identify a number of parasite traits that may underlie differences in virulence between parasite strains. These include the number of progeny parasites produced per infected cell (burst size) and the invasion rates of target cells. We test these predictions with further experiments and find broad support for the role of burst sizes in determining virulence, but the role of invasion rates is less certain. We also find evidence of potential plasticity in these parasite traits in response to within-host environmental factors. These within-host interactions between parasites and hosts have effects that will scale up to between-host processes; we discuss the growing body of theory that seeks to combine these levels (‘embedded models’). Using between-host and embedded models, we test the plausibility of various hypotheses to explain why there are so few transmissible malaria parasite forms, yet vast numbers of host-damaging asexual forms are produced. We show that a specific form of density-dependent transmission-blocking immunity and the occurrence of multiple infections can each generate selection for this pattern. Overall, this thesis contributes to a better under- standing of malaria parasites, while providing a framework for addressing unanswered questions in disease biology, and offering interesting paths for future empirical work. / Thesis (Ph.D, Biology) -- Queen's University, 2009-08-20 06:41:14.198

Pathogen evolution poses a significant challenge to public health, as efforts to control the spread of infectious diseases struggle to keep up with a shifting target. To better understand this adaptive process, we turn to mathematical modelling. Specifically, we use multi-type branching processes to describe a pathogen's stochastic spread among members of a host population or growth within a single host. In each case, there is potential for new pathogen strains with different characteristics to arise through mutation. We first develop a specific model to study the emergence of a newly introduced infectious disease, where the pathogen must adapt to its new host or face extinction in this population. In an extension of previous models, we separate the processes of host-to-host contacts and disease transmission, in order to consider each of their contributions in isolation. We also allow for an arbitrary distribution of host contacts and arbitrary mutational pathways/rates among strains. This framework enables us to assess the impact of these various factors on the chance that the process develops into a large-scale epidemic. We obtain some intriguing results when interpreted in a biological context. Secondly, motivated by a desire to investigate the time course of pathogen evolutionary processes more closely, we derive some novel theoretical results for multi-type branching processes. Specifically, we obtain equations for: (1) the distribution of waiting time for a particular type to arise; and (2) the distribution of population numbers over time, conditioned on a particular type not having yet appeared. A few numerical examples scratch the surface of potential applications for these results, which we hope to develop further. / Thesis (Master, Mathematics & Statistics) -- Queen's University, 2010-07-28 11:43:22.984