Recent Submissions

Item
Restricted
Identification And Development Of Chemical Probes Targeting Growth Factor Receptor-Bound Protein 2 (Grb-2)
(2019-12-20) Mohammed, Albuhluli; Anindya Ghosh
Grb2 is an essential signaling adaptor protein that takes an extraordinary place to regulate the enzymatic activity intercellularly. It can maintain the intercellular reactivities through its interaction with receptor tyrosine kinases (RTKs). Grb2 contains two domains called Src homology 3 (SH3) and one domain named Src homology 2 (SH2). In cell membrane, Grb2-SH3 domain is binding to the target effectors, whilst the Grb2-SH2 domain is binding to receptors. Grb2-SH2 domain has critical roles in binding to peptides containing phosphotyrosine (pY). Whereas Grb2-SH3 domain assists the activation of the cyclic process of the Ras-GTPase from Ras-GDP to Ras-GTP. The research goal is to identify and the development of novel non-peptide small molecules associated with Grb2 and tests them on mice. The various Grb2 complexes provide specific information to study the properties on the binding site of Grb2. This leads to the shut down of oncogenic pathways and thus prevent hyperproliferative diseases.
Item
Restricted
Toward Leveraging Artificial Intelligence to Support the Identification of Accessibility Challenges
(2023) Aljedaani, Wajdi Mohammed; Ludi, Stephanie; Wiem Mkaouer, Mohamed
Context: Today, mobile devices provide support to disabled people to make their life easier due to their high accessibility and capability, e.g., finding accessible locations, picture and voice-based communication, customized user interfaces, and vocabulary levels. These accessibility frameworks are directly integrated, as libraries, in various apps, providing them with accessibility functions. Just like any other software, these frameworks regularly encounter errors. App developers report these errors in the form of bug reports or by the user in user reviews. User reviews include insights that are useful for app evolution. These reports related to accessibility faults/issues need to be urgently fixed since their existence significantly hinders the usability of apps. However, recent studies have shown that developers may incorporate accessibility strategies in inspecting manually or partial reports to investigate if there are accessibility reports that exist. Unfortunately, these studies are limited to the developer. With the increase in the number of received reviews, manually analyzing them is tedious and time-consuming, especially when searching for accessibility reviews. Objective: The goal of this thesis is to support the automated identification of accessibility in user reviews or bug reports, to help technology professionals prioritize their handling, and, thus, to create more inclusive apps. Particularly, we propose a model that takes as input accessibility user reviews or bug reports and learns their keyword-based features to make a classification decision, for a given review, on whether it is about accessibility or not. To complement this goal, we aim to reveal insights from deaf and hard-of-hearing students about Blackboard, which is one of the most common Learning Management systems (LMS) used by many universities, especially in the current COVID-19 pandemic. This occurs to explore how deaf and hard-of-hearing students have challenges and concerns in e-learning experiences during the sudden shift to online learning during COVID-19 in terms of accessibility. Method: Our empirically-driven study follows a mixture of qualitative and quantitative methods. We text mine user reviews and bug reports documentation. We identify the accessibility reports and categorize them based on the BBC standards and guidelines for mobile accessibility and Web Content Accessibility Guidelines (WCAG 2.1). Then, we automatically classify a large set of user reviews and bug reports and identify among the various accessibility models presented in the literature. After that, we used a mixed-methods approach by conducting a survey and interviews to get the information we needed. This was done on deaf and hard-of-hearing students to identify the challenges and concerns in terms of accessibility in the e-learning platform Blackboard. Result: We introduced models that can accurately identify accessibility reviews and bug reports and automate detecting them. Our models (1) outperform two baselines, namely a keyword-based detector and a random classifier; (2) our model achieves an accuracy of 91% with a relatively small training dataset; however, the accuracy improves as we increase the size of the training dataset. Our mixed methods with deaf and hard-of-hearing students have revealed several difficulties, such as inadequate support and inaccessibility of content from learning systems. Conclusion: Our models can automatically classify app reviews and bug reports as accessibility-related or not so developers can easily detect accessibility issues with their products and improve them to more accessible and inclusive apps utilizing the users' input. Our goal is to create a sustainable change by including a model in the developer’s software maintenance pipeline and raising awareness of existing errors that hinder the accessibility of mobile apps, which is a pressing need. In light of our findings from the Blackboard case study, Blackboard and the course material are not easily accessible to deaf students and hard of hearing. Thus, deaf students find that learning is extremely stressful during the pandemic.
Item
Restricted
Optimization Of Enantiopure Tetrahydro-Β-Carbolines as Potent Antimalarials & Exploration of Salicylic Acid Analogs for Combating Multidrug-Resistant Neisseria Gonorrhoeae
(2023-05-13) Almolhim, Hanan; Carlier, Paul
The emergence of drug resistance towards existing drugs is a constant challenge in the fight against many diseases including Malaria and gonorrhoeae. To evade resistance, new targets must be engaged, and to do that, new structural classes of anti-infective must be prepared and evaluated. During the course of my PhD journey, I had the opportunity to investigate and optimize the antimalarial candidate (Å})-2-3b, and salicylic acid (4-1a) as an anti-gonorrhea treatment. Malaria is a life-threatening mosquito-borne disease. In 2021, there were 247 million cases of malaria and the estimated number of malaria deaths stood at 619,000. Because of the rapid development of resistance to all current antimalarials, discovery of antimalarials with unexploited mechanisms of action is critical to reduce malaria mortality. In the Carlier group, our initial approach focused on discovery of inhibitors of the methylerythritol phosphate (MEP) pathway for isoprenoid precursor biosynthesis, since this pathway is essential for Plasmodium falciparum and absent in human. Application of the isopentenyl pyrophosphate (IPP) chemical rescue screen to the compounds of the Malaria Box, a collection of 400 antimalaria candidates with unknown mechanisms of action, identified tetrahydro-β-carboline 2-1 (MMV008138) as an inhibitor of the MEP pathway. Chapter 2 of this work discusses similarity searching of the Novartis portion of the hit set (5K compounds), from the original 20K compound hit set of the Malaria Box, and identifying tetrahydro-β-carboline GNF-Pf-5009, designated as (Å})-2-3b. Preparation of pure enantiomers, by resolution, demonstrated the pharmacological superiority of (R)-2-3b over (S)-2-3b, which was ound to have good asexual blood stage (ABS) inhibition potency against malarial parasites P. falciparum, and low general cytotoxicity. However, (R)-2-3b was found not orally efficacious in a P. berghei mouse model of malaria. We concluded that the lack of oral efficacy of (R)-2-3b was due to its poor drug-like qualities, in particular its high molecular weight and low solubility. Chapter 3 of this work explores modifications of (R)-2-3b ((R)-3-5Aa) that were expected to improve its properties. We show that the new compounds (R)-3-5Gm and (R)-3-5Gk not only are more potent in vitro than (R)-2-3b ((R)-3-5Aa), but also have molecular weights < 500 g/mol. Neisseria gonorrhoeae is the causative agent of the sexually transmitted disease gonorrhea. Due to the increased rates of infection as well as the prevalence of multidrug-resistant N. gonorrhoeae strains worldwide, the World Health Organization (WHO) and the U.S. Centers for Disease Control and Prevention (CDC) list N. gonorrhoeae at the highest possible threat level to public health. Dual therapy of azithromycin (AZM) and ceftriaxone has been the standard-of-care for treatment of gonococcal infections. However, due to increasing resistance to azithromycin (>33% in some regions) the CDC removed AZM from the treatment regimen for gonorrhea in 2020. Therefore, ceftriaxone remains the only recommended antibiotic for treatment of gonococcal infections. However, increasing resistance to this treatment option has been reported, consequently there is an urgent need to identify novel therapeutics against N. gonorrhoeae. Drug repurposing is a popular strategy that explores new therapeutic opportunities for approved drugs with available information on their pharmacokinetic data, dosages, and toxicity. Salicylic acid is a highly privileged chemical scaffold. Also, the use of salicylic acid to treat sexually transmitted diseases (including gonorrhea) was reported as early as the 19th century. Recently, Dr. Mohamed N. Seleem reported that salicylic acid (4-1a) exhibited modest activity against N. gonorrhoeae strains including the AZM-resistant strain (CDC-181). Chapter 4 of this work illustrates how the anti-gonococcal activity in this scaffold is easily lost by inopportune substitution. However, we found that substituted naphthyl analogs (4-3b,o,p) have superior activity to salicylic acid itself. In addition, the three analogs showed high selectivity, compared to AZM, against N. gonorrhoeae over the vaginal microbiota.
Item
Restricted
A Multimethod Approach To Identify Factors And Improve The Process Of Deprescribing Anticholinergics In Older Adults.
(HammerRR, 2023-04-28) Alamer, Khalid Ahmed A; Campbell, Noll
Polypharmacy in older adults presents several challenges, such as suboptimal therapeutic outcomes and increased adverse effects. Deprescribing, a clinically supervised process of decreasing dosage or stopping the medication when risks outweigh benefits, has emerged as one possible solution to these problems. However, the literature describing deprescribing intervention frameworks is heterogenous regarding targeted medications to deprescribe, population characteristics, clinical settings, and measured outcomes. This dissertation utilizes Linsky et al.'s deprescribing conceptual model, which details factors influencing decisions regarding initiating deprescribing interventions and their direct impact on the process. This dissertation utilizes a multimethod approach to investigate factors that facilitate and improve the deprescribing of anticholinergic medications for older adults, addressing gaps in this population's anticholinergic medication use. The three studies included in this dissertation provide a comprehensive understanding of deprescribing anticholinergic medications for this population, each contributing unique insights and results. The first study explores the feasibility of in-person and remote Home Medication Inventory Method (HMIM) approaches to evaluate over-the-counter (OTC) and prescription medication possession and use, including anticholinergics. Results demonstrate that both methods can accurately assess anticholinergic medication usage patterns, providing healthcare providers with reproducible methods and detailed medication profiles to make informed deprescribing decisions based on complete medication lists. The second study examined the intertwined roles of social determinants of health and health beliefs in predicting older adults' self-reported deprescribing behaviors, proposing the Deprescribing Health Belief Model (DeRx-HBM) framework that can be utilized for these efforts. These results emphasize the importance of considering these elements when creating a patient-centric and culturally sensitive intervention since they significantly shape deprescribing behaviors. In the third study, we explored the use of a symptom-specific scale for measuring the symptom burden in older adults during the deprescribing of anticholinergic medications prescribed for urinary incontinence, depression, and pain management. This research introduces a validated scale for assessing anticholinergic symptom burden prior to, throughout, and following the deprescribing attempt. The implementation of this scale has the potential to enhance the reproducibility and standardization of deprescribing decisions. Furthermore, it can improve communication between healthcare professionals and patients, as well as monitor the effectiveness of interventions during and after the deprescribing process. Collectively, these studies provide invaluable insights into factors influencing deprescribing decisions, obstacles to implementing deprescribing practices, and potential strategies to optimize medication management in older adults. The major takeaway from these studies is that addressing these factors leads to more informed decisions among healthcare professionals and patients - potentially leading to improved patient outcomes, ensure the ongoing effectiveness of deprescribing initiatives among older adults, and the promotion of health equity throughout the deprescribing process.
Item
Restricted
Essays on Saudi oil production, world oil production, and the response of the Saudi macroeconomy to oil shocks
(2023) ALbaqami, Meznah; Bachmeier, Lance J
This three-chapter dissertation examined the effect of Saudi Arabia’s oil supply shocks on non- OPEC and non-Saudi OPEC oil production and the effect of oil price shocks on the Saudi economy. The first chapter predicted how non-OPEC and non-Saudi OPEC oil supplies respond to Saudi oil supply shocks using a Bayesian structural vector autoregression (BSVAR) model on monthly data from 1993 to 2020. The examination of three different prior distributions using prior information found that the response to a Saudi oil shock depends heavily on the identification restrictions. The second chapter also used the BSVAR model to explore whether the CPI response to an oil price shock is offset by Saudi Arabia’s monetary policy. Based on monthly data from 1980 to 2014, the results confirmed that Saudi Arabia’s monetary policy is effective. Following Bernanke et al.’s (1997) methodology, we found that conducting an experiment that reduced the Saudi central bank's response to an oil shock resulted in a much larger response of Saudi inflation to that oil shock. Finally, the third chapter predicts the effect of the structural oil market shocks on sectoral inflation rates in Saudi Arabia using Kilian’s (2009) methodology to help Saudi Arabia’s policymakers overcome inflation rates. As Saudi Arabia’s policymakers seek to overcome the inflation rates, it is useful for them to know how to react in the face of oil market shocks (i.e., the source of oil price increases) to control the inflation rate as sector. The examination found that the effect of oil market shocks on the CPI differs by sector, with oil-specific demand shocks having the largest impact in most sectors compared to other structural oil market shocks.