Matching Items (11)
Filtering by

Clear all filters

136509-Thumbnail Image.png
Description
The primary objective of this research project is to develop dual layered polymeric microparticles with a tunable delayed release profile. Poly(L-lactic acid) (PLA) and poly(lactic-co-glycolic acid) (PLGA) phase separate in a double emulsion process due to differences in hydrophobicity, which allows for the synthesis of double-walled microparticles with a PLA

The primary objective of this research project is to develop dual layered polymeric microparticles with a tunable delayed release profile. Poly(L-lactic acid) (PLA) and poly(lactic-co-glycolic acid) (PLGA) phase separate in a double emulsion process due to differences in hydrophobicity, which allows for the synthesis of double-walled microparticles with a PLA shell surrounding the PLGA core. The microparticles were loaded with bovine serum albumin (BSA) and different volumes of ethanol were added to the PLA shell phase to alter the porosity and release characteristics of the BSA. Different amounts of ethanol varied the total loading percentage of the BSA, the release profile, surface morphology, size distribution, and the localization of the protein within the particles. Scanning electron microscopy images detailed the surface morphology of the different particles. Loading the particles with fluorescently tagged insulin and imaging the particles through confocal microscopy supported the localization of the protein inside the particle. The study suggest that ethanol alters the release characteristics of the loaded BSA encapsulated in the microparticles supporting the use of a polar, protic solvent as a tool for tuning the delayed release profile of biological proteins.
ContributorsFauer, Chase Alexander (Author) / Stabenfeldt, Sarah (Thesis director) / Ankeny, Casey (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2015-05
133170-Thumbnail Image.png
Description
With microspheres growing in popularity as viable systems for targeted drug therapeutics, there exist a host of diseases and pathology induced side effects which could be treated with poly(lactic-co-glycolic acid) [PLGA] microparticle systems [6,10,12]. While PLGA systems are already applied in a wide variety the clinical setting [11], microparticles still

With microspheres growing in popularity as viable systems for targeted drug therapeutics, there exist a host of diseases and pathology induced side effects which could be treated with poly(lactic-co-glycolic acid) [PLGA] microparticle systems [6,10,12]. While PLGA systems are already applied in a wide variety the clinical setting [11], microparticles still have some way to go before they are viable systems for drug delivery. One of the main reasons for this is a lack of fabrication processes and systems which produce monodisperse particles while also being feasible for industrialization [10]. This honors thesis investigates various microparticle fabrication techniques \u2014 two using mechanical agitation and one using fluid dynamics \u2014 with the long term goal of incorporating norepinephrine and adenosine into the particles for metabolic stimulatory purposes. It was found that mechanical agitation processes lead to large values for dispersity and the polydispersity index while fluid dynamics methods have the potential to create more uniform and predictable outcomes. The research concludes by needing further investigation into methods and prototype systems involving fluid dynamics methods; however, these systems yield promising results for fabricating monodisperse particles which have the potential to encapsulate a wide variety of therapeutic drugs.
ContributorsRiley, Levi Louis (Author) / Vernon, Brent (Thesis director) / VanAuker, Michael (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
136851-Thumbnail Image.png
Description
Morphine is a commonly used analgesic in pain management. Opioid administration to a patient after surgery, such as spinal decompression surgery, can lead to adverse side effects. To demonstrate these adverse side effects could be decreased we created a model of how morphine and its metabolites are transported

Morphine is a commonly used analgesic in pain management. Opioid administration to a patient after surgery, such as spinal decompression surgery, can lead to adverse side effects. To demonstrate these adverse side effects could be decreased we created a model of how morphine and its metabolites are transported and excreted from the body. Using the of morphine and a standard compartment approach this thesis aimed at projecting pharmacokinetics trends of morphine overtime. A Matlab compartment model predicting the transport of morphine through the body can contribute to a better understanding of the concentrations at the systemic level, specifically with respect to a CSF, and what happens when you compare an intravenous injection to a local delivery. Other studies and models commonly utilized patient data over small periods of time2,3,5. An extended period of time will provide information into morphine’s time course after surgery. This model focuses on a compartmentalization of the major organs and the use of a simple Mechalis-Menten enzyme kinetics for the metabolites in the liver. Our results show a CSF concentration of about 1.086×〖10〗^(-12) nmol/L in 6 weeks and 1.0097×〖10〗^(-12) nmol/L in 12 weeks. The concentration profiles in this model are similar to what was expected. The implications of this suggest that patients who reported effects of morphine paste, a locally administered opioid, weeks after the surgery were due to other reasons. In creating a model we can determine important variables and dosage information. This information allows for a greater understanding of what is happening in the body and how to improve surgical outcomes. We propose this study has implications in general research in the pharmacokinetics and dynamics of pharmacology through the body.
ContributorsJacobs, Danielle Renee (Author) / Caplan, Michael (Thesis director) / Giers, Morgan (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
133517-Thumbnail Image.png
Description
Traumatic brain injury (TBI) is a major concern in public health due to its prevalence and effect. Every year, about 1.7 million TBIs are reported [7]. According to the According to the Centers for Disease Control and Prevention (CDC), 5.5% of all emergency department visits, hospitalizations, and deaths from 2002

Traumatic brain injury (TBI) is a major concern in public health due to its prevalence and effect. Every year, about 1.7 million TBIs are reported [7]. According to the According to the Centers for Disease Control and Prevention (CDC), 5.5% of all emergency department visits, hospitalizations, and deaths from 2002 to 2006 are due to TBI [8]. The brain's natural defense, the Blood Brain Barrier (BBB), prevents the entry of most substances into the brain through the blood stream, including medicines administered to treat TBI [11]. TBI may cause the breakdown of the BBB, and may result in increased permeability, providing an opportunity for NPs to enter the brain [3,4]. Dr. Stabenfeldt's lab has previously established that intravenously injected nanoparticles (NP) will accumulate near the injury site after focal brain injury [4]. The current project focuses on confirmation of the accumulation or extravasation of NPs after brain injury using 2-photon microscopy. Specifically, the project used controlled cortical impact injury induced mice models that were intravenously injected with 40nm NPs post-injury. The MATLAB code seeks to analyze the brain images through registration, segmentation, and intensity measurement and evaluate if fluorescent NPs will accumulate in the extravascular tissue of injured mice models. The code was developed with 2D bicubic interpolation, subpixel image registration, drawn dimension segmentation and fixed dimension segmentation, and dynamic image analysis. A statistical difference was found between the extravascular tissue of injured and uninjured mouse models. This statistical difference proves that the NPs do extravasate through the permeable cranial blood vessels in injured cranial tissue.
ContributorsIrwin, Jacob Aleksandr (Author) / Stabenfeldt, Sarah (Thesis director) / Bharadwaj, Vimala (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
135480-Thumbnail Image.png
Description
Compressed sensing magnetic resonance spectroscopic imaging (MRSI) is a noninvasive and in vivo potential diagnostic technique for cancer imaging. This technique undersamples the distribution of specific cancer biomarkers within an MR image as well as changes in the temporal dimension and subsequently reconstructs the missing data. This technique has been

Compressed sensing magnetic resonance spectroscopic imaging (MRSI) is a noninvasive and in vivo potential diagnostic technique for cancer imaging. This technique undersamples the distribution of specific cancer biomarkers within an MR image as well as changes in the temporal dimension and subsequently reconstructs the missing data. This technique has been shown to retain a high level of fidelity even with an acceleration factor of 5. Currently there exist several different scanner types that each have their separate analytical methods in MATLAB. A graphical user interface (GUI) was created to facilitate a single computing platform for these different scanner types in order to improve the ease and efficiency with which researchers and clinicians interact with this technique. A GUI was successfully created for both prospective and retrospective MRSI data analysis. This GUI retained the original high fidelity of the reconstruction technique and gave the user the ability to load data, load reference images, display intensity maps, display spectra mosaics, generate a mask, display the mask, display kspace and save the corresponding spectra, reconstruction, and mask files. Parallelization of the reconstruction algorithm was explored but implementation was ultimately unsuccessful. Future work could consist of integrating this parallelization method, adding intensity overlay functionality and improving aesthetics.
ContributorsLammers, Luke Michael (Author) / Kodibagkar, Vikram (Thesis director) / Hu, Harry (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
148276-Thumbnail Image.png
Description

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

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%.

ContributorsSeo, Jinpyo (Author) / Vernon, Brent (Thesis director) / Pal, Amrita (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

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

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.

ContributorsHan, Priscilla (Author) / Vernon, Brent (Thesis director) / Nickle, Jacob (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
132664-Thumbnail Image.png
Description
Human potential is characterized by our ability to think flexibly and develop novel solutions to problems. In cognitive neuroscience, problem solving is studied using various tasks. For example, IQ can be tested using the RAVEN, which measures abstract reasoning. Analytical problem solving can be tested using algebra, and insight can

Human potential is characterized by our ability to think flexibly and develop novel solutions to problems. In cognitive neuroscience, problem solving is studied using various tasks. For example, IQ can be tested using the RAVEN, which measures abstract reasoning. Analytical problem solving can be tested using algebra, and insight can be tested using a nine-dot test. Our class of problem-solving tasks blends analytical and insight processes. This can be done by measuring multiply-constrained problem solving (MCPS). MCPS occurs when an individual problem has several solutions, but when grouped with simultaneous problems only one correct solution presents itself. The most common test for MCPS is known at the CRAT, or compound remote associate task. For example, when given the three target words “water, skate, and cream” there are many compound associates that can be assigned each of the target words individually (i.e. salt-water, roller-skate, whipped-cream), but only one that works with all three (ice-water, ice-skate, ice-cream).
This thesis is a tutorial for a MATLAB user-interface, known as EEGLAB. Cognitive and neural correlates of analytical and insight processes were evaluated and analyzed in the CRAT using EEG. It was hypothesized that different EEG signals will be measured for analytical versus insight problem solving, primarily observed in the gamma wave production. The data was interpreted using EEGLAB, which allows psychological processes to be quantified based on physiological response. I have written a tutorial showing how to process the EEG signal through filtering, extracting epochs, artifact detection, independent component analysis, and the production of a time – frequency plot. This project has combined my interest in psychology with my knowledge of engineering and expand my knowledge of bioinstrumentation.
ContributorsCobban, Morgan Elizabeth (Author) / Brewer, Gene (Thesis director) / Ellis, Derek (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
X-ray phase contrast imaging (XPCI) is a novel imaging method that utilizes phase information of X-rays in order to produce images. XPCI allows for highly resolved features that traditional X-ray imaging modalities cannot discern. The objective of this experiment was to model initial simulations predicting the output signal of the

X-ray phase contrast imaging (XPCI) is a novel imaging method that utilizes phase information of X-rays in order to produce images. XPCI allows for highly resolved features that traditional X-ray imaging modalities cannot discern. The objective of this experiment was to model initial simulations predicting the output signal of the future compact x-ray free electron laser (CXFEL) XPCI source. The signal was reported in tonal values (“counts”), where MATLAB and MATLAB App Designer were the computing environments used to develop the simulations. The experimental setup’s components included a yttrium aluminum garnet (YAG) scintillating screen, mirror, and Mako G-507C camera with a Sony IMX264 sensor. The main function of the setup was to aim the X-rays at the YAG screen, then measure its scintillation through the photons emitted that hit the camera sensor. The resulting quantity used to assess the signal strength was tonal values (“counts”) per pixel on the sensor. Data for X-ray transmission through water, air, and polyimide was sourced from The Center for X-ray Optics’s simulations website, after which the data was interpolated and referenced in MATLAB. Matrices were an integral part of the saturation calculations; field-of-view (FOV), magnification and photon energies were also necessary. All the calculations were compiled into a graphical user interface (GUI) using App Designer. The code used to build this GUI can be used as a template for later, more complex GUIs and is a great starting point for future work in XPCI research at CXFEL.
ContributorsDela Rosa, Trixia (Author) / Graves, William (Thesis director) / King, Dakota (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2022-05
164640-Thumbnail Image.png
Description

X-ray phase contrast imaging (XPCI) is a novel imaging method that utilizes phase information of X-rays in order to produce images. XPCI allows for highly resolved features that traditional X-ray imaging modalities cannot discern. The objective of this experiment was to model initial simulations predicting the output signal of the

X-ray phase contrast imaging (XPCI) is a novel imaging method that utilizes phase information of X-rays in order to produce images. XPCI allows for highly resolved features that traditional X-ray imaging modalities cannot discern. The objective of this experiment was to model initial simulations predicting the output signal of the future compact x-ray free electron laser (CXFEL) XPCI source. The signal was reported in tonal values (“counts”), where MATLAB and MATLAB App Designer were the computing environments used to develop the simulations. The experimental setup’s components included a yttrium aluminum garnet (YAG) scintillating screen, mirror, and Mako G-507C camera with a Sony IMX264 sensor. The main function of the setup was to aim the X-rays at the YAG screen, then measure its scintillation through the photons emitted that hit the camera sensor. The resulting quantity used to assess the signal strength was tonal values (“counts”) per pixel on the sensor. Data for X-ray transmission through water, air, and polyimide was sourced from The Center for X-ray Optics’s simulations website, after which the data was interpolated and referenced in MATLAB. Matrices were an integral part of the saturation calculations; field-of-view (FOV), magnification and photon energies were also necessary. All the calculations were compiled into a graphical user interface (GUI) using App Designer. The code used to build this GUI can be used as a template for later, more complex GUIs and is a great starting point for future work in XPCI research at CXFEL.

ContributorsDela Rosa, Trixia (Author) / Graves, William (Thesis director) / King, Dakota (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2022-05