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- Creators: Harrington Bioengineering Program
- Creators: Harrell, Liz
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 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
Description
As the complexity of healthcare continues to rise, the need for change in healthcare delivery is more prominent than ever. One strategy identified by the World Health Organization (WHO) for responding to these increasing complexities is the use of interprofessional practice and education to improve patient outcomes, reduce costs, and enhance the patient experience of care (Triple Aim). Interprofessional collaboration among diverse disciplines is evident on the Phoenix Biomedical Campus, integrating a wide variety of institutions and multiple health profession programs; and at the Student Health Outreach for Wellness (SHOW) free clinic, -- a successful tri-university, student-led, faculty mentored, and community-based model of interprofessional learning and care -- based in downtown Phoenix. This project conducted a comparative analysis of interprofessional components of 6 different clinical models in order to provide recommendations for best practice implementation. These models were chosen based on availability of research on interprofessionalism with their clinics. As a result, three recommendations were offered to the SHOW clinic for consideration in their efforts to improve both patient and educational outcomes. Each recommendation was intentionally formulated for its capacity to increase: interprofessionalism and collaboration between multiple disciplines pertaining to healthcare, among healthcare professionals to promote positive patient and educational outcomes. These recommendations include implementing an interprofessional education (IPE) course as a core component in an academic program's curriculum, offering faculty and professional development opportunities for faculty and mentors immersed in the interprofessional clinics, and utilization of simulation centers. Further studies will be needed to evaluate the impact these specific interventions, if adopted, on patient and educational outcomes.
ContributorsMousa, Mohammad (Co-author) / Mousa, Bakir (Co-author) / Johnson, Ross (Co-author) / Harrell, Liz (Thesis director) / Saewert, Karen (Committee member) / Harrington Bioengineering Program (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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 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
Description
Introduction. Evidence shows that the United States' healthcare system is inefficient and lacks the quality and cost-effectiveness of other systems. The Institute for Healthcare Improvement outlined the Triple Aim to improve the healthcare system through 1) improvement of population health for a defined population, 2) enhance the patient care experience, and 3) reduce per capita cost of care. The World Health Organization has identified interprofessional practice (IPP) and interprofessional education (IPE) as a possible approach to achieve the Triple Aim. The Student Health Outreach for Wellness (SHOW) initiative is an interprofessional free clinic and outreach initiative for individuals experiencing homelessness. The goal of the current study was to evaluate whether interprofessional care delivery through SHOW moved SHOW's practice towards the Triple Aim for SHOW's defined population. Methods and Results. Data assessing adherence to Triple Aim goals of population health and costs of care were collected from voluntary post-visit patient satisfaction surveys, while data assessing patient experience were collected from shift rosters of SHOW versus a similar non-interprofessional clinic. SHOW, on average, provided access to more disciplines than a similar non-interprofessional clinic. Access to care cost savings was assessed by surveying patients on where they would have sought care elsewhere SHOW had not been available ; of the 53 patients surveyed, 14 indicated they would have gone to the emergency department (ED); in all, SHOW diverted a little over $30,000 in patient ED visits. Improved health outcomes were measured by each patient's self-perception of his/her health. 91% of patients agreed or strongly agreed that their health had been improved by coming to the clinic. Conclusion. Preliminary data suggest that SHOW's IPP care delivery results in high patient satisfaction rates and positive self-perception of health outcomes, thus may improve the patient experience and minimize costs of care by deterring ED visits within the population. Further studies are needed to determine how specific aspects of interprofessional care can further move towards Triple Aim objectives.
ContributorsSingh, Sukhdeep (Co-author) / Paode, Pooja (Co-author) / Harrell, Liz (Thesis director) / Wermers, Rita (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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 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
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 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.
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 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
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 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
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 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