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- Creators: Harrington Bioengineering Program
- Creators: Moran, Stacey
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Polymer drug delivery system offers a key to a glaring issue in modern administration routes of drugs and biologics. Poly(lactic-co-glycolic acid) (PLGA) can be used to encapsulate drugs and biologics and deliver them into the patient, which allows high local concentration (compared to current treatment methods), protection of the cargo from the bodily environment, and reduction in systemic side effects. This experiment used a single emulsion technique to encapsulate L-tyrosine in PLGA microparticles and UV spectrophotometry to analyze the drug release over a period of one week. The release assay found that for the tested samples, the released amount is distinct initially, but is about the same after 4 days, and they generally follow the same normalized percent released pattern. The experiment could continue with testing more samples, test the same samples for a longer duration, and look into higher w/w concentrations such as 20% or 50%.
The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and time effectiveness. Theoretical data for the time to 60% drug release and the slope and intercept of the log-log plot were collected and subjected to statistical analysis in JMP. Since the scope of this project focuses on microparticle surface degradation drug release with no drug diffusion, the characteristic variables relating to the slope (n = diffusional release exponent) and the intercept (k = kinetic constant) do not directly apply to the distribution model within the scope of the research. However, these variables are useful for analysis when the Mathcad template is applied to other types of drug release models.
A friend of mine once told me that coding is like doing magic, and frankly, I am inclined to agree. With a keyboard, a development environment, and a little bit of language skill, you can build an entire world. Despite being heavily rooted in logic, math, and science, there is a certain mystery to it, a sense of illusion and wizardry. The sense of pride and power that comes from successfully finishing an app, program, or website is like no other. I recently watched the film Ex Machina (Alex Garland, 2014) for the first time, and I was struck by one of the lines. In thinking about the success of his creation and what that means for the world, he says, “I’m not a man, I’m God.” And although I wouldn’t say that is exactly how I feel when I turn in a coding assignment, I understand the sentiment. This thesis is going to be a bit different than the one I thought I was going to write. When I started this, I thought it would be about an amazing coding project I had completed. I would write about all the beautiful code and the nitty gritty of the technical aspects. But, the project that I intended to create is not the project I ended up with, and I couldn’t be happier. I finished with something a lot more meaningful, a lot more interdisciplinary, and a lot more me. In this essay and the accompanying coding project, I aim to take you on the journey of building my own piece of digital culture, an app titled “Exposed.” I begin by discussing how the motivation to create Exposed came from the desire to stop using an app made by an internet celebrity and how the values of Gen Z and their relationship with technology influenced and guided the creation of the app. Then I examine the relationship between code and the coder, and how external factors such as being a woman in technology impacts project development. Then I explain the results of the coding process and outline how Exposed turned out. Finally, I consider the meaning of digital culture and how it functions in the creation of Exposed. Along the way this project became extremely personal. I found that the deeper I dove into making the code work, the more I learned about myself and my relationship to technology. If I promise to be honest with you, will you promise to listen to what I have to say?
protocols, including within sleep-focused studies. This study seeks to address accuracy of
accelerometer data in detection of the beginnings and ends of sleep bouts in young adults with
polysomnography (PSG) corroboration. An existing algorithm used to differentiate valid/invalid wear
time and detect bouts of sleep has been modified with the goal of maximizing accuracy of sleep bout
detection. Methods: Three key decisions and thresholds of the algorithm have been modified with three
experimental values each being tested. The main experimental variable Sleepwindow controls the
amount of time before and after a determined bout of sleep that is searched for additional sedentary
time to incorporate and consider part of the same sleep bout. Results were compared to PSG and sleep
diary data for absolute agreement of sleep bout start time (START), end time (END) and time in bed
(TIB). Adjustments were made for outliers as well as sleep latency, snooze time, and the sum of both.
Results: Only adjustments made to a sleep window variable yielded altered results. Between a 5-, 15-,
and 30-minute window, a 15-minute window incurred the least error and most agreement to
comparisons for START, while a 5-minute window was best for END and TIB. Discussion: Contrary
to expectation, corrections for snooze, latency, and both did not substantially improve agreement to
PSG. Algorithm-derived estimates of START and END always fell after sleep diary and PSG both,
suggesting either participants’ sedentary behavior beginning and ends were at a delay from sleep and
wake times, or the algorithm estimates consistently later times than appropriate. The inclusion of a
sleep window variable yields substantial variety in results. A 15-minute window appears best at
determining START while a 5-minute window appears best for END and TIB. Further investigation on
the optimal window length per demographic and condition is required.