Typical Parkinson’s disease (PD) is thought to be caused by a combination of genetic and environmental factors. α-Synuclein (SNCA) is central to PD pathogenesis; however, functions of SNCA outside the brain remain largely unknown. We, and others, have found that wild-type Snca expression confers anti-microbial effects in mice by reducing the severity of viral infections. Our aim is to further characterize a role of SNCA in systemic and brain health of the host during infection. We hypothesize that SNCA plays a role in innate defenses and that SNCA gene dosage will modulate outcomes of infection in the brain following pathogen exposure. Intranasal delivery of reovirus in mouse pups causes systemic illness, leading to encephalitis. In this study, intracranial inoculations of reovirus are used to differentiate the relative contribution of Snca-mediated protection in the brain versus the periphery. Two outcomes are monitored: survival and viral titres in select organs. When comparing wild-type Snca, heterozygous, and knock-out mice, I found that Snca expression did not confer any protection with respect to survival or regarding viral brain titres. These results are paralleled by cellular overexpression models. Unexpectedly, the anti-viral property of Snca, which was previously observed systemically with three distinct dsRNA viruses, did not extend to a paradigm where neural cells were directly exposed to reovirus. These results suggest a complex, anti-viral role for Snca in host defenses that may be mediated, in part, outside the central nervous system. Future studies will address whether this occurs in peripheral neurons or cells of hematopoietic lineages.

Interrupting the Sepsis Process with an Evidence-Based Education Intervention by Martha Olson MSN, Walden University, 2013 MS, Southwest Minnesota State University, 2003 BSN, The University of Iowa, 1998 Project Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Nursing Practice Walden University May 2015 Abstract Sepsis is a concern, especially for the vulnerable populations. The early signs of sepsis are vague and often difficult to detect, but when detected early, are treatable with antibiotics and fluid resuscitation. When a nurse is unaware of the early signs, treatment is delayed and multiorgan failure may progress quickly. To teach nurses about changes in patient condition and thus increase their confidence in identifying sepsis, an educational intervention, guided by adult learning theory and social learning theory, was created using a PowerPoint presentation, simulation, and debriefing. The purpose of this project was to educate nurses working in a critical access hospital on the early signs of sepsis, laboratory values, and the 2012 Surviving Sepsis Campaign Guidelines. The education was implemented and evaluated using a pre-post survey which demonstrated an increased confidence level in early sign and symptom recognition, identification of laboratory values, and implementation of the guidelines for treating sepsis. Descriptive statistics revealed that the confidence level improved following the education session in all 3 areas. Interrupting sepsis based on evidence-based practice improves the outcomes for the patient with sepsis. It also improves nurses' confidence in identifying sepsis in the early stages via clinical changes and laboratory values.

No description available.

Problem: Primary HSV-2 infection during pregnancy is associated with adverse pregnancy outcomes. However the mechanisms underlying these outcomes remain largely unknown. In this study we developed and characterized a mouse model of primary HSV-2 infection during early pregnancy and examined its effects on pregnancy and fetal outcomes. Methods of Study: C57BL/6 female mice positive for vaginal plugs were infected intravaginally (IVAG) with 10^3/10^4/10^5 PFU/mouse of HSV-2 (333) or saline (control) on gestational day (GD) 5. For comparison, female mice in diestrus stage were infected with HSV-2 at the same doses. Survival, pathology scores and vaginal viral shedding were measured post-infection. Systemic viral dissemination was examined by real-time PCR. Vaginal tissue, implantation sites, placenta and fetuses were examined by histology. Maternal serum (GD 13) and amniotic fluid (GD 8) was collected for multiplex cytokine analysis. Results: The minimum viral inoculation dose for infection in pregnant mice was 10^3 PFU of HSV-2, compared to 100-fold higher dose required to infect diestrus mice (10^5 PFU). There was a dose-dependent increase in implantation failure and number of resorptions with increasing dose of viral inoculum in pregnant mice at GD 8. In the 10^3 PFU group, although vaginal viral shedding was observed in all mice, 75% survived the infection, while all the mice in 10^4 and 10^5 PFU groups succumbed to infection by GD 13-15. There was evidence of abnormal placental morphology and necrotic fetal tissues in HSV-2 infected, pregnant mice compared to controls. Presence of HSV-2 DNA was measured in the vaginal tract, uterus (mated non-pregnant mice), and implantations of infected mated mice. HSV-2 DNA was also present in the spleen of the GD 13 time point group. Conclusions: These results indicate a 100-fold increase in susceptibility to HSV-2 infection during early pregnancy. At higher inoculation doses, IVAG HSV-2 infection spread systemically resulting in poor pregnancy outcomes and maternal mortality, especially in later gestation. At lower inoculation dose, the infection was localized in the reproductive tract and implantation sites, resulting in increased inflammation and adverse outcomes. This model will help to understand pathological mechanisms underlying adverse outcomes following primary HSV-2 infection in pregnancy. / Thesis / Master of Science (MSc)

Thiabendazole, the most commonly used drug to treat strongyloidiasis, has many side effects and high relapse rates. Ivermectin is an effective antiparasitic drug that could be used in the treatment of this disease. Sixteen patients with proven strongyloidiasis were randomized to receive either 1 dose of ivermectin 200 mg/kg; ivermectin 200 mg/kg/day for 2 days; or thiabendazole 25 mg/kg twice a day for 3 days. Nine patients (total) received ivermectin and 7 received thiabendazole. Two relapses occurred in the thiabendazole group. All side effects were seen only in this group. Ivermectin may be a better tolerated, more effective treatment for strongyloidiasis.

Biofilm formation within burn wounds pose numerous health-related problems as they prolong recovery, inhibit antimicrobial treatments, and serve as a reservoir to spread new infections. In the United States alone there are half a million burn wounds each year. These burn wounds result in tens of thousands of patients to be admitted to hospitals and thousands of deaths. Burn wound infections alone account for over half of these deaths. Currently, standard models of burn wound biofilms, both in-vivo and in-vitro, have their benefits and limitations. These models include skin explants, animal models, and complex growth media. For the examination of microbial biofilms and rapid screening of potential antimicrobial topical treatments, a physiologically relevant media that more closely mimics what would be found in the host’s tissue would be advantageous. This pilot study was conducted to examine different formulations of a synthetic tissue-like media, the biofilm growth of common burn wound infectious microbes, and served as a high-throughput means of testing current and potentially new antimicrobials. Our laboratory has begun characterizing a new antimicrobial gel and its ability to eradicate microorganisms that commonly infect burn wounds, specifically focusing on the common wound microbe Staphylococcus aureus. Utilizing a constitutively expressed green fluorescent protein, both the growth on the textured media, as well as, biofilm inhibition by the antimicrobial gel showed significant reduction in S. aureus. On a molecular level, we examined biofilm gene expression, via reverse transcription polymerase chain reaction, of adhesion, quorum sensing, and drug resistance markers in our new model in conjunction with our antimicrobial gel. Our new synthetic wound-like media supported the growth of S. aureus and was successful in its ability to quickly screen different formulations of topical antimicrobial treatments. The antimicrobial gel produced significant reduction of S. aureus burden. The results of this study indicate that our formulated synthetic burn wound media model supports microbial growth, is efficient in the ability to rapidly screen antimicrobials, and could lead to a better understanding of the etiology of burn wound infections.

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No description available.

Obesity is a major predictor for type 2 diabetes. The etiology and comorbidities of these two diseases are associated. Diabetics are twice as likely to contract any type of infection and at greater risk of worse clinical outcomes to infection. However, the individual effects of diet, glycemia and obesity on risk and severity of enteric infection has not been elucidated. Here we show that high blood glucose (i.e. hyperglycemia), independent of obesity, is sufficient to promote mortality during infection with Citrobacter rodentium, a diarrhea-causing pathogen in mice. Mortality was caused by dehydration as a result of excessive Wnt/β-catenin signalling. Our findings highlight the importance of glucose lowering and fluid therapy as opposed to immunological dysfunction, gut barrier defects or bacteraemia as modifiers of outcomes from enteric infection during diabetes. Future work should develop a more comprehensive understanding of the molecular changes that connect hyperglycemia, Wnt/β-catenin pathway and fluid balance during infection. We used the most common model to cause diet-induced obesity in mice to study another enteric pathogen. We showed that long- and short-term high-fat diet (HFD) feeding promoted the colonization and expansion of adherent-invasive Escherichia coli. Higher pathogen burdens in the intestinal tissues and feces were detected in diet-induced obese mice, which coincided with increased distal gut pathology. Initiating the diet one day prior or after infection was sufficient to promote the expansion of adherent-invasive E. coli in the absence of robust weight gain implicating components of diet as a major determinant of pathogen burden. We isolated the dietary factor and found that low fibre content of the high-fat diet was partially responsible for the increased intestinal pathogen burden. Future work should determine how lower fibre alters host and bacterial metabolism in order to promote overgrowth of adherent-invasive E. coli in the gut. / Thesis / Doctor of Philosophy (PhD) / Obesity and diabetes are major public health issues that are connected in many ways, including how diet changes glucose metabolism. Diabetics have a higher risk of contracting infections and also have worse outcomes from infections. It was unknown what factors of obesity or diabetes influence how the immune system combats bacterial infections. The gut is an important site as it is where diet, the immune system, and metabolism all directly interact. We discovered that high blood sugar was associated with death related to dehydration in diabetic, but not necessarily obese mice infected with a diarrhea causing bacteria. Diet-induced obesity in mice infected with bacteria associated with Crohn's disease, showed an overgrowth of bacteria and worse intestinal damage. We isolated the key dietary factor responsible, which was low fibre rather than high fat or sugar. Even one day of lower dietary fibre promoted overgrowth of infectious bacteria in the gut.

Alors que la pandémie de COVID-19 affecte le monde depuis presque deux ans, il va sans dire qu'une meilleure compréhension des processus de contagion, de leur évolution et des effets des mesures de contrôle est essentielle pour réduire leur impact sur la société. Le cadre théorique pour la modélisation des processus de contagion est très général et permet, bien entendu, de décrire la propagation des maladies infectieuses causées par des agents pathogènes (virus, bactéries, parasites, etc.), mais aussi la propagation des rumeurs et de la désinformation. Peu importe la nature du processus, la transmission s'effectue de proche en proche grâce aux interactions entre les individus. Par conséquent, la structure sociale complexe des populations, qui n'est ni parfaitement ordonnée, ni complètement aléatoire, joue un rôle de premier plan. Dans cette thèse, nous étudions les processus de contagion sur réseaux, où les individus et les interactions entre ces individus sont représentés par des nœuds et des liens respectivement. Nous utilisons une approche théorique principalement basée sur la physique statistique et la dynamique non linéaire. Nous nous concentrons plus spécifiquement sur les réseaux d'ordre supérieur, lesquels mettent les interactions de groupe à l'avant-plan. Notre analyse va donc au-delà des interactions dyadiques. Bien plus qu'une reformulation mathématique de la structure, cette perspective est primordiale pour obtenir une compréhension plus complète de la phénoménologie des processus de contagion. Nous démontrons l'importance des interactions de groupe à l'aide de trois résultats principaux. D'abord, nous caractérisons un phénomène de localisation mésoscopique : pour certaines structures hétérogènes, la propagation persiste uniquement dans les groupes de grande taille. Ce phénomène a notamment une incidence sur l'effet des mesures de contrôle visant à prohiber les regroupements au-delà d'une certaine taille, à l'instar de ce qui fut instauré pour endiguer la pandémie de COVID-19. Ensuite, nous étudions un modèle où les individus doivent accumuler une dose infectieuse minimale pour devenir infectés. Nous montrons qu'une structure d'ordre supérieur et des temps d'exposition hétérogènes induisent une probabilité d'infection non linéaire universelle. L'épidémie résultante peut alors croître de manière super-exponentielle en fonction du temps. Finalement, nous poussons plus en profondeur l'analyse des processus de contagion non linéaire. Dans ce contexte, nous montrons que les groupes peuvent avoir plus d'importance que les individus ultra-connectés pour qu'une épidémie ou un phénomène social envahissent le plus rapidement possible une population. / After almost two years into the COVID-19 pandemic, it is clear that a better understanding of contagion processes, their evolution, and the impact of control measures is essential to reduce their burden on society. The theoretical framework for the modeling of contagion is quite general. It can describe the spread of pathogens causing diseases (viruses, bacteria, parasites, etc.), but also the spread of rumors and disinformation. Irrespective of the nature of the underlying process, the contagion evolves through local interactions between the individuals. Consequently, the complex social structure of populations, which is neither perfectly ordered nor completely random, plays a fundamental role in shaping spreading. In this thesis, we study contagion processes on networks where individuals and the interaction between them are represented by nodes and edges respectively. We use a theoretical approach based on statistical physics and nonlinear dynamics. We focus on higher-order networks, putting group interactions beyond pairwise interactions at the forefront. More than a mere mathematical generalization, we find this perspective is paramount to obtain a complete picture of the phenomenology of contagion dynamics. We demonstrate the importance of group interactions through three principal results. First, we characterize a mesoscopic localization phenomenon where the contagion thrives only in large groups for certain types of heterogeneous structure. This phenomenon significantly affects the results of interventions like the cancelation of events larger than a critical size, similar to the measures being used to limit the spreading of COVID-19. Second, we study a model where individuals must accumulate a minimal infective dose to become infected. We show that a higher-order structure and heterogeneous exposure induce a universal nonlinear infection probability. The epidemic size can then grow super-exponentially with time. Finally, with a more in-depth analysis of nonlinear contagions, we show that groups can be more influential than hubs (super-connected individuals) to maximize the early spread of an epidemic.