Biomedical Commons^™

Cell Bioprinting: A Novel Approach For Alpha Cell To Beta Cell Transdifferentiation, Atzimba Casas

Open Access Theses & Dissertations

Diabetes is a chronic disease that occurs in the body when the pancreas fails to either produce insulin (TID) or does not effectively use the insulin produced (TIID) and poses further health complications as well as an insurmountable economic impact.[1] Type I diabetes is an autoimmune disease characterized by a deficient amount of insulin production on account of the body’s immune system destroying its own β-cells.[2] Current diabetes treatment methods include the administration of insulin via injections or islet transplantation therapy. However, although both are viable options, they come with limitations that make the managing of this disease difficult. It …

Evaluation Of Varying Graphene Oxides Through Their Physicochemical Characterizations On Erythrocytes, Hs27 Cells, Escherichia Coli And Staphylococcus Aureus Bacteria Cell Lines, To Assess Graphene Oxides Cytotoxicity., Miriam Montana

Open Access Theses & Dissertations

Research on the toxicity of Graphene Oxides (GO) has captivated interest in the field of material science, environmental sciences, and medicine for their avail significance in biomedical engineer applications either as integrates, enhancements, or in the making of medical devices. Moreover, there is still a lack of understanding as to what characteristics on GOs causes them to be cytotoxic at a cellular level. In our study we synthesized four different GOs by varying in both the method used for oxidation (Modified Hummer’s method & Improved Marcano-Tour’s method), and the precursor parent graphite, for a standardization approach to aid in the …

Classifying Electrocardiogram With Machine Learning Techniques, Hillal Jarrar

Master's Theses

Classifying the electrocardiogram is of clinical importance because classification can be used to diagnose patients with cardiac arrhythmias. Many industries utilize machine learning techniques that consist of feature extraction methods followed by Naive- Bayesian classification in order to detect faults within machinery. Machine learning techniques that analyze vibrational machine data in a mechanical application may be used to analyze electrical data in a physiological application. Three of the most common feature extraction methods used to prepare machine vibration data for Naive-Bayesian classification are the Fourier transform, the Hilbert transform, and the Wavelet Packet transform. Each machine learning technique consists of …

The Factors Influencing The Acceptance Of Web-Based E-Learning System Among Academic Staffs Of Saudi Arabia, Ikhlas Zamzami

Future Computing and Informatics Journal

It is possible to learn more quickly and effectively with e-learning software development because it provides learners with convenient and flexible learning environments. This allows them to progress further in their careers. Reports on web-based e-learning systems for in-service education have frequently neglected to include the viewpoint of the instructor. In order to conduct quantitative research, a sample of 50 academic staff members was selected. The purpose of this study was to investigate various factors that influence the intention to use web-based e-learning, with the theoretical foundation being provided by university lecturers. According to the findings of the study, the …

A Statistical-Mining Techniques’ Collaboration For Minimizing Dimensionality In Ovarian Cancer Data, Mohamed Attia, Maha Farghaly, Mohamed Hamada, Amira M. Idrees Ami

Future Computing and Informatics Journal

A feature is a single measurable criterion to an observation of a process. While knowledge discovery techniques successfully contribute in many fields, however, the extensive required data processing could hinder the performance of these techniques. One of the main issues in processing data is the dimensionality of the data. Therefore, focusing on reducing the data dimensionality through eliminating the insignificant attributes could be considered one of the successful steps for raising the applied techniques’ performance. On the other hand, focusing on the applied field, ovarian cancer patients continuously suffer from the extensive analysis requirements for detecting the disease as well …

Development Of Sensor, Sensory System And Signal Processing Algorithm For Intelligent Sensing Applications, Xingzhe Zhang

Dissertations

Sensors have been receiving significant attention in the last decade and the demand for sensory systems has increased in recent years due to the rapid growth in the field of artificial intelligence (AI). Sensors can improve people’s awareness by providing them with real-time information on the environment and their immediate health conditions. This dissertation presents the fulfilment of three main projects and focuses on the development of a sensor, a sensory system, and a sensor signal recognition system for AI applications by employing printed electronics, analog circuit design, and digital signal processing techniques.

In the first project, a multi-channel stethograph …

Creating Reel Designs: Reflecting On Arthrogryposis Multiplex Congenita In The Community, Iris Layadi

Purdue Journal of Service-Learning and International Engagement

Because of its extreme rarity, the genetic disease arthrogryposis multiplex congenita (AMC) and the needs of individuals with the diagnosis are often overlooked. AMC refers to the development of nonprogressive contractures in disparate areas of the body and is characterized by decreased flexibility in joints, muscle atrophy, and developmental delays. Colton Darst, a seven-year-old boy from Indianapolis, Indiana, was born with the disorder, and since then, he has undergone numerous surgical interventions and continues to receive orthopedic therapy to reduce his physical limitations. His parents, Michael and Amber Darst, have hopes for him to regain his limbic motion and are …

Assessing The Role Of The Pelvic Canal In Supporting The Gut In Humans, Jeanelle Uy, Natalie Laudicina

Peer Reviewed Articles

The human pelvic canal (true pelvis) functions to support the abdominopelvic organs and serves as a passageway for reproduction (females). Previous research suggests that these two functions work against each other with the expectation that the supportive role results in a narrower pelvic midplane, while fetal passage necessitates a larger opening. In this research, we examine how gut size relates to the size and shape of the true pelvis, which may have implications on how gut size can influence pelvic floor integrity. Pelves and in vivo gut volumes were measured from CT scans of 92 adults (48 female, 44 male). …

Using Bibliometrics To Evaluate Outcomes And Influence Of Translational Biomedical Research Centers, Kristine M. Bragg, Gwen C. Marchand, Jonathan C. Hilpert, Jeffrey L. Cummings

Educational Psychology, Leadership, and Higher Education Faculty Research

Introduction. Federal grant funding to support infrastructure development of translational biomedical research centers is a form of public health intervention. Establishing rigorous methods for measuring center success and outcomes is essential to justify continued funding. Methods. Bibliometric data compiled from a 5-year funding cycle of a neurodegeneration and translational neuroscience research center was analyzed using the package bibliometrix for open source software R and the NIH-developed research tool iCite. Results. The research team and their collaborators (n=485) produced 157 grant-citing publications from 2015-2020. The science was produced by small research teams clustered around three main communities of topics: Alzheimer's Disease, …

The Role Pde11a4 Signaling And Compartmentalization In Social Behavior, Kaitlyn Pilarzyk

Theses and Dissertations

People tend to be social by nature. Being socially connected not only helps people live longer and healthier lives, but being an engaged and contributing member of society strengthens our communities overall. Maintaining intact social behaviors is key to maintaining this wellbeing, with disruptions negatively affecting both mental and physical health. Indeed, social isolation and feelings of loneliness can significantly increase a person’s risk of premature death, heart disease, and stroke as well as depression, anxiety, suicide, and dementia. Maintaining the ability to create and store social memory with age is, therefore, key to maintaining proper social behaviors. Unfortunately, individuals …

Impact Of Acetylcholine On Internal Pathways To Basal Amygdala Pyramidal Neurons, Tyler Daniel Anderson-Sieg

Theses and Dissertations

The basolateral nuclear complex of the amygdala (BNC) – consisting of the lateral (LA), basolateral (BL), and basomedial nuclei (BM) – detects salient environmental stimuli (cue-detection) and motivates appropriate behavioral responses to their implied meaning (cue-guided behavior) via a precise pattern of internal circuitry. Glutamatergic signals representing environmental stimuli enter the LA and split into parallel streams that activate pyramidal neurons (PNs) in the anterior and posterior BL (BLa and BLp), which putatively mediate negative and positive emotions, respectively. The BL is the most densely innervated target of the cholinergic basal forebrain (CBF) and ACh transients (phasic ACh) in cortex …

Role Of Estrogen In Regulating Diet-Induced Obesity In Females, Ahmed Aladhami

Theses and Dissertations

Menopause puts a female at risk for several chronic diseases, including an increased risk of obesity. Estrogens are major sex hormones of females that dramatically decrease during menopause. Several murine studies have established the crucial role of estrogen and estrogen receptor alpha (ERα) on energy homeostasis, glucose metabolism, and insulin action. However, previous works have produced contradicting findings, hence, further work is needed to optimize better outcomes. Therefore, my dissertation focuses on optimizing and characterizing different estrogen-deficient models, as well as using novel double transgenic inducible and tissue-specific models that overexpress aromatase (estrogen producing enzyme) and estrogen receptor isomers alpha …

Study Of The Effect Of B-Cell-Intrinsic Mhcii Antigen Presentation On Germinal Center B Cell Evolution Using The Brainbow Mouse Model, Nia Hall

Theses and Dissertations

Major histocompatibility complex class II (MHCII) are molecules that are essential for B cell activation, as well as clonal competition among activated B cell clones during germinal center (GC) reactions. However, it is unknown to what extent MHCII drives the selection of some clones over others. This is of particular importance since MHCII is highly polymorphic with the ability to indirectly alter gutmicrobiome composition by altering the immunoglobulin A (IgA) repertoire. To study this, we utilized a novel triple-transgenic mouse model to assess how B-cellintrinsic MHCII influences GC responses and GC clonal diversity, with an eyeforward to understanding the relevance …

Impaired Metabolic Flexibility In A Mouse Model Of Leigh Syndrome, Richard Sterling Mccain Jr

Theses and Dissertations

Metabolic dysfunction burdens tissues with high energy demands, particularly the brain. Leigh syndrome is a mitochondrial encephalopathy stemming from genetic defects in the electron transport chain. Leigh syndrome patients develop lactic acidosis, ataxia, bilateral necrotizing lesions in the brainstem and basal ganglia, lesion microgliosis, and eventually death due to respiratory failure. The NADH dehydrogenase [ubiquinone] iron-sulfur protein 4 (NDUFS4) knockout mouse is an established model of Leigh syndrome due to impaired assembly of mitochondrial Complex I that develops motoric deficits and necrotizing lesions in the brainstem vestibular nuclei and olfactory bulb. In addition to the Complex I-derived bioenergetics defect, altered …

A Novel Model To Study Adipose-Derived Stem Cell Differentiation, Austin N. Worden

Theses and Dissertations

The use of three-dimensional (3D) culture systems (hydrogels) and adipose-derived stem cells (ADSCs) in regenerative medicine to advance early-stage investigation and modeling of the mechanisms of diseases, treatments, targets, etc. has recently increased. ADSCs, specifically, are utilized due to their innate programming during embryogenesis and in adult tissues in addition to their ability to differentiate into mesodermal, endodermal, and ectodermal cell-specific lineages. Of importance is that these advancements do not involve a model specimen (i.e. mice or rats) and simulate the numerous conflicting signals a migrating cell is exposed to in vivo such as chemokines, extracellular matrix (ECM), growth factors, …

The Effect Of Low Dose Penicillin On Tumor Development In ApcMin/+ Mice, Kinsey Ann Sierra Meggett

Theses and Dissertations

Antibiotics have been our most effective weapon against bacterial infections since their discovery in the early 1900s. Their use has been critical in reducing mortality rate from infectious diseases. However, in the last few decades, the overuse of antibiotics, beginning at an early age and into adulthood, has become a growing concern globally. Penicillin is one of many extensively used antibiotics in early childhood that has been used to treat childhood infections. Recent studies showed that exposure to low dose penicillin can have adverse effects leading to chronic illness such as diabetes, allergies, inflammation, and susceptibility to obesity, with the …

Computer-Aided Diagnosis Of Low Grade Endometrial Stromal Sarcoma (Lgess), Xinxin Yang, Mark Stamp

Faculty Research, Scholarly, and Creative Activity

Low grade endometrial stromal sarcoma (LGESS) accounts for about 0.2% of all uterine cancer cases. Approximately 75% of LGESS patients are initially misdiagnosed with leiomyoma, which is a type of benign tumor, also known as fibroids. In this research, uterine tissue biopsy images of potential LGESS patients are preprocessed using segmentation and stain normalization algorithms. We then apply a variety of classic machine learning and advanced deep learning models to classify tissue images as either benign or cancerous. For the classic techniques considered, the highest classification accuracy we attain is about 0.85, while our best deep learning model achieves an …

Oral Minimal Model For Gestational Diabetes, Sarah Peters

Symposium of Student Scholars

Gestational diabetes is one of the most common issues that a pregnant woman encounters that could result in harm to both the woman and child. Due to this issue, the woman’s glucose and insulin levels should be carefully monitored throughout her pregnancy to assess the need for prescribed diabetic medication to help regulate those levels. In this research, the objectives is to develop a MATLAB computer program of the Oral Minimal Model, which is a model that can be used to estimate a person’s insulin sensitivity from an oral glucose tolerance test (OGTT) where plasma glucose and insulin levels are …

Scatter Estimation And Correction For Experimental And Simulated Data In Multi-Slice Computed Tomography Using Machine Learning And Minimum Least Squares Methods, Cornelia Wang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Current research aims to reduce the stopping power ratio prediction error in the inputs to the proton therapy planning process to less than 1%, which allows for improved radiation therapy planning. Our present study on reducing SPR error neglects the effect of scattering, which can increase SPR error by as much as 1-1.5%. The idea is that for each source-to-detector pair, 24 mm collimation data is close to 3 mm collimation data but with increased signal due to scattering. The goal is to estimate 3 mm collimation data from 24 mm collimation data. Pairs of sinograms, both experimental data and …

Non-Invasive In-Vitro Glucose Monitoring Using Optical Sensor And Machine Learning Techniques For Diabetes Applications, Maryamsadat Shokrekhodaei

Open Access Theses & Dissertations

Diabetes is a major public health challenge affecting more than 451 million people. Physiological and experimental factors influence the accuracy of non-invasive glucose monitoring, and these need to be addressed before replacing the finger prick method with a non-invasive glucose measurement technique. Also, the suitable employment of machine learning techniques on experimental data can significantly improve the accuracy of glucose predictions.

This work includes the design, development, testing and data analysis of an optical based sensor for glucose measurements. The feasibility of non-invasive measurement of glucose within aqueous solutions that assimilate the composition of human blood plasma is investigated. The …