Matching Items (5)
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- All Subjects: viruses
- Creators: Mubayi, Anuj
Description
This study evaluates medical pluralism among 1.5 generation Indian American immigrants. 1.5 generation Indian Americans (N=16) were surveyed regarding their engagement in complementary and alternative medical systems (CAM), how immigration affected that, and reasons for and for not continuing the use of CAM. Results indicated most 1.5 Indian immigrants currently engage in CAM, given that their parents also engage in CAM. The top reasons respondents indicated continued engagement in CAM was that it has no side effects and is preventative. Reasons for not practicing CAM included feeling out of place, not living with parents or not believing in CAM. After immigration, most participants decreased or stopped their engagement in CAM. More women than men continued to practice CAM after immigration. From the results, it was concluded that CAM is still important to 1.5 generation Indian immigrants.
ContributorsMurugesh, Subhiksha (Author) / Stotts, Rhian (Thesis director) / Mubayi, Anuj (Committee member) / School of Human Evolution & Social Change (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Combination therapy has shown to improve success for cancer treatment. Oncolytic virotherapy is cancer treatment that uses engineered viruses to specifically infect and kill cancer cells, without harming healthy cells. Immunotherapy boosts the body's natural defenses towards cancer. The combination of oncolytic virotherapy and immunotherapy is explored through deterministic systems of nonlinear differential equations, constructed to match experimental data for murine melanoma. Mathematical analysis was done in order to gain insight on the relationship between cancer, viruses and immune response. One extension of the model focuses on clinical needs, with the underlying goal to seek optimal treatment regimens; for both frequency and dose quantity. The models in this work were first used to estimate parameters from preclinical experimental data, to identify biologically realistic parameter values. Insight gained from the mathematical analysis in the first model, allowed for numerical analysis to explore optimal treatment regimens of combination oncolytic virotherapy and dendritic vaccinations. Permutations accounting for treatment scheduled were done to find regimens that reduce tumor size. Observations from the produced data lead to in silico exploration of immune-viral interactions. Results suggest under optimal settings, combination treatment works better than monotherapy of either type. The most optimal result suggests treatment over a longer period of time, with fractioned doses, while reducing the total dendritic vaccination quantity, and maintaining the maximum virotherapy used in the experimental work.
ContributorsSummer, Ilyssa Aimee (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Nagy, John (Thesis advisor) / Mubayi, Anuj (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2016
Description
Due to the COVID-19 pandemic, declared in March of 2020, there have been many lifestyle changes which have likely influenced tobacco smoking behavior. Such lifestyle changes include lockdowns, stay at home orders, reduction in social cues related to smoking, increased stress, and boredom among other things. This study utilized a cross-sectional survey which looked into these behaviors, primarily perceived risk to COVID-19, and determined if there is an association between perceived risk and education level/race. Education level is a proxy for income and material resources, therefore making it more likely that people with lower levels of education have fewer resources and higher perceived risk to negative effects of COVID-19. Additionally, people of color are often marginalized in the medical community along with being the target of heavy advertising by tobacco companies which have likely impacted risk to COVID-19 as well.
ContributorsLodha, Pratishtha (Author) / Leischow, J. Scott (Thesis director) / Pearson, Jennifer (Committee member) / School of Life Sciences (Contributor) / School of Human Evolution & Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Ecological modeling can be used to analyze health risk behaviors and their relationship to ecological factors, which is useful in determining how social environmental factors influence an individual’s decisions. Environmental interactions shape the way that humans behave throughout the day, either through observation, action, or consequences. Specifically, health risk behaviors can be analyzed in relation to ecological factors. Alcohol drinking among college students has been a long concern and there are many risks associated with these behaviors in this population. Consistent engagement in health risk behaviors as a college student, such as drinking and smoking, can pose a much larger issues later in life and can lead to many different health problems. A research study was conducted in the form of a 27 question survey to determine and evaluate the impact of ecological factors on drinking and smoking behaviors among Arizona State University students. Ecological factors such as demographics, living conditions, contexts of social interactions, and places where students spend most of their time were used to evaluate the relationship between drinking and smoking behaviors and the ecological factors, both on- and off- campus.
ContributorsAndrade, Amber Marie (Co-author) / Naik, Sparshee (Co-author) / Werbick, Meghan (Co-author) / Mubayi, Anuj (Thesis director) / Gaughan, Monica (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Honeybees are important pollinators worldwide and pollinate about one-third of the food we consume. Recently though, honeybee colonies have been under increasing stress due to changing environments, pesticides, mites, and viruses, which has increased the incidence of
colony collapse. This paper aims to understand how these different factors contribute to the decline of honeybee populations by using two separate approaches: data analysis and mathematical modeling. The data analysis examines the relative impacts of mites, pollen, mites, and viruses on honeybee populations and colony collapse. From the data, low initial bee populations lead to collapse in September while mites and viruses can lead to collapse in December. Feeding bee colonies also has a mixed effect, where it increases both bee and mite populations. For the model, we focus on the population dynamics of the honeybee-mite interaction. Using a system of delay differential equations with five population components, we find that bee colonies can collapse from mites, coexist with mites, and survive without them. As long as bees produce more pupa than the death rate of pupa and mites produce enough phoretic mites compared to their death rates, bees and mites can coexist. Thus, it is possible for honeybee colonies to withstand mites, but if the parasitism is too large, the colony will collapse. Provided
this equilibrium exists, the addition of mites leads to the colony moving to the interior equilibrium. Additionally, population oscillations are persistent if they occur and are connected to the interior equilibrium. Certain parameter values destabilize bee populations, leading to large
oscillations and even collapse. From these parameters, we can develop approaches that can help us prevent honeybee colony collapse before it occurs.
colony collapse. This paper aims to understand how these different factors contribute to the decline of honeybee populations by using two separate approaches: data analysis and mathematical modeling. The data analysis examines the relative impacts of mites, pollen, mites, and viruses on honeybee populations and colony collapse. From the data, low initial bee populations lead to collapse in September while mites and viruses can lead to collapse in December. Feeding bee colonies also has a mixed effect, where it increases both bee and mite populations. For the model, we focus on the population dynamics of the honeybee-mite interaction. Using a system of delay differential equations with five population components, we find that bee colonies can collapse from mites, coexist with mites, and survive without them. As long as bees produce more pupa than the death rate of pupa and mites produce enough phoretic mites compared to their death rates, bees and mites can coexist. Thus, it is possible for honeybee colonies to withstand mites, but if the parasitism is too large, the colony will collapse. Provided
this equilibrium exists, the addition of mites leads to the colony moving to the interior equilibrium. Additionally, population oscillations are persistent if they occur and are connected to the interior equilibrium. Certain parameter values destabilize bee populations, leading to large
oscillations and even collapse. From these parameters, we can develop approaches that can help us prevent honeybee colony collapse before it occurs.
ContributorsSweeney, Brian Felix (Author) / Kang, Yun (Thesis director) / Mubayi, Anuj (Committee member) / College of Integrative Sciences and Arts (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05