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Full-Text Articles in Medicine and Health Sciences

A Novel Consumer-Centric Metric For Evaluating Hearing Device Audio Performance, Vinaya Manchaiah, Steve Taddei, Abram Bailey, De Wet Swanepoel, Hansapani Rodrigo May 2024

A Novel Consumer-Centric Metric For Evaluating Hearing Device Audio Performance, Vinaya Manchaiah, Steve Taddei, Abram Bailey, De Wet Swanepoel, Hansapani Rodrigo

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Background and Aim: The emergence of direct-to-consumer hearing devices has introduced confusion in making appropriate choices, highlighting the need for users to be well-informed for optimal device selection. Currently, no established metric offers insights into the sound performance of these devices. This study aimed to introduce and assess a novel consumer-centric metric (i.e., SoundScore) for hearing device audio performance.

Method: The SoundScore metric was created based on five dimensions of hearing device audio performance (i.e., speech benefit in quiet and moderate, speech benefit in loud, own voice perception, feedback control, streamed music sound quality). Tests were conducted under lab conditions …


Mechanistic Investigation Of C—C Bond Activation Of Phosphaalkynes With Pt(0) Complexes, Roberto M. Escobar, Abdurrahman C. Ateşin, Christian Müller, William D. Jones, Tülay Ateşin Mar 2024

Mechanistic Investigation Of C—C Bond Activation Of Phosphaalkynes With Pt(0) Complexes, Roberto M. Escobar, Abdurrahman C. Ateşin, Christian Müller, William D. Jones, Tülay Ateşin

Research Symposium

Carbon–carbon (C–C) bond activation has gained increased attention as a direct method for the synthesis of pharmaceuticals. Due to the thermodynamic stability and kinetic inaccessibility of the C–C bonds, however, activation of C–C bonds by homogeneous transition-metal catalysts under mild homogeneous conditions is still a challenge. Most of the systems in which the activation occurs either have aromatization or relief of ring strain as the primary driving force. The activation of unstrained C–C bonds of phosphaalkynes does not have this advantage. This study employs Density Functional Theory (DFT) calculations to elucidate Pt(0)-mediated C–CP bond activation mechanisms in phosphaalkynes. Investigating the …


La1-Xsrxcoo3 Perovskite Nanomaterial: Synthesis, Characterization, And Its Biomedical Application, Adhira Tippur, Anyet Shohag, Luke Franco, Ahmed Touhami, Swati Mohan, Mohammed Uddin Mar 2024

La1-Xsrxcoo3 Perovskite Nanomaterial: Synthesis, Characterization, And Its Biomedical Application, Adhira Tippur, Anyet Shohag, Luke Franco, Ahmed Touhami, Swati Mohan, Mohammed Uddin

Research Symposium

Early cancer detection is paramount for effective treatment and potential cures. This research explores the application of perovskite materials, specifically Sr2+-doped Lanthanum Cobaltite (La1-xSrxCoO3) nanomaterials, in cancer detection, with a focus on rats as an experimental model. The ferroelectric nature of these materials, synthesized through a combination of sol-gel and molten-salt processes, was examined at varying Sr2+ doping levels (1-20 wt%). Rigorous characterization, employing X-ray diffraction and scanning electron microscopy, confirmed the uniform morphology of nano cubes, laying the foundation for subsequent investigations. The magnetic properties of the perovskite nanoparticles were probed, suggesting their potential as a diagnostic tool for …


Assessing Gait Metrics For Early Parkinson's Disease Prediction: A Preliminary Analysis Of Underfit Models, Daniel Salinas, Gerardo Medellin, Katherine Bolado, Tomas Gomez, Kelsey Potter-Baker, Nawaz Khan Abdul Hack, Ramu Vadukapuram Mar 2024

Assessing Gait Metrics For Early Parkinson's Disease Prediction: A Preliminary Analysis Of Underfit Models, Daniel Salinas, Gerardo Medellin, Katherine Bolado, Tomas Gomez, Kelsey Potter-Baker, Nawaz Khan Abdul Hack, Ramu Vadukapuram

Research Symposium

Background: Parkinson's Disease (PD) is characterized by both motor and non-motor symptoms, and its diagnosis primarily relies on clinical presentation. There is a growing need for diagnostic tools to identify the early signs of PD, particularly the initial motor impairments often manifested as gait abnormalities. Here we seek to present preliminary findings to address this need. Our study focuses on using Machine Learning techniques (ML) to predict the PD clinical stage most efficiently and accurately. Specifically, we have sought to evaluate how spatiotemporal characteristics and other locomotor performance variables obtained on a walkway system can be utilized to identify the …


Assessment Of Mucin 13 (Muc13) As An Imaging Target For Guiding Colorectal Cancer Treatment: A Pathway Towards Theranostic Development, Ryan P. Coll, Aiko Yamaguchi, Jianbo Wang, Xiaoxia Wen, Denise Hernandez, Subhash C. Chauhan, H. Charles Manning Mar 2024

Assessment Of Mucin 13 (Muc13) As An Imaging Target For Guiding Colorectal Cancer Treatment: A Pathway Towards Theranostic Development, Ryan P. Coll, Aiko Yamaguchi, Jianbo Wang, Xiaoxia Wen, Denise Hernandez, Subhash C. Chauhan, H. Charles Manning

Research Symposium

Background: A theranostic strategy combining diagnostic imaging and targeted therapy in a single regimen is proposed for improved management and treatment of colorectal cancer (CRC). Increased specificity in detection by the noninvasive imaging technique positron emission tomography (PET) can be achieved by radiolabeling antibodies (Abs) designed to target tumor-associated antigens with increased expression post-translational modifications present in cancer cells. In this study, an Ab designed to target the transmembrane glycoprotein mucin 13 (MUC13) was radiolabeled with the positron-emitting radionuclide zirconium-89 (89Zr) for PET imaging of a xenograft mouse model of CRC. Specified uptake of this radioimmunoconjugate was observed …


Possible Role Of Correlation Coefficients And Network Analysis Of Multiple Intracellular Proteins In Blood Cells Of Patients With Bipolar Disorder In Studying The Mechanism Of Lithium Responsiveness: A Proof-Concept Study, Keming Gao, Marzieh Ayati, Nicholas M. Kaye, Mehmet Koyutürk, Joseph R. Calabrese, Eric Christian, Hillard M. Lazarus, David Kaplan Mar 2024

Possible Role Of Correlation Coefficients And Network Analysis Of Multiple Intracellular Proteins In Blood Cells Of Patients With Bipolar Disorder In Studying The Mechanism Of Lithium Responsiveness: A Proof-Concept Study, Keming Gao, Marzieh Ayati, Nicholas M. Kaye, Mehmet Koyutürk, Joseph R. Calabrese, Eric Christian, Hillard M. Lazarus, David Kaplan

Computer Science Faculty Publications and Presentations

Background: The mechanism of lithium treatment responsiveness in bipolar disorder (BD) remains unclear. The aim of this study was to explore the utility of correlation coefficients and protein-to-protein interaction (PPI) network analyses of intracellular proteins in monocytes and CD4+ lymphocytes of patients with BD in studying the potential mechanism of lithium treatment responsiveness. Methods: Patients with bipolar I or II disorder who were diagnosed with the MINI for DSM-5 and at any phase of the illness with at least mild symptom severity and received lithium (serum level ≥ 0.6 mEq/L) for 16 weeks were divided into two groups, responders (≥50% …


Modeling The Effect Of Observational Social Learning On Parental Decision-Making For Childhood Vaccination And Diseases Spread Over Household Networks, Tamer Oraby, Andras Balogh Jan 2024

Modeling The Effect Of Observational Social Learning On Parental Decision-Making For Childhood Vaccination And Diseases Spread Over Household Networks, Tamer Oraby, Andras Balogh

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

In this paper, we introduce a novel model for parental decision-making about vaccinations against a childhood disease that spreads through a contact network. This model considers a bilayer network comprising two overlapping networks, which are either Erdős–Rényi (random) networks or Barabási–Albert networks. The model also employs a Bayesian aggregation rule for observational social learning on a social network. This new model encompasses other decision models, such as voting and DeGroot models, as special cases. Using our model, we demonstrate how certain levels of social learning about vaccination preferences can converge opinions, influencing vaccine uptake and ultimately disease spread. In addition, …