SACM - Canada

Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9651

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General And Special Education Teachers’ Perceptions Of Knowledge And Beliefs About Dyslexia
(Concordia University, 2013-11-07) Alsaig, Alaa; Alagar, Vangalur; Mohammad, Mubarak
Modern societies have become very dependent on information and services. Technology is adapting to the increasing demands of people and businesses. Context-Aware Systems are becoming ubiquitous. These systems comprise mechanisms to acquire knowledge about the surrounding environment and adapt its behaviour and service provision accordingly. Service oriented computing is the main stream software development methodology. In Service-oriented Applications (SOA), service providers publish the services created by them in service registries. These services are accessed by service requesters during discovery process. For large scale SOA, the registry structure and the type of quires that it can handle are central to efficient service discovery. Moreover, the role of context in determining services and affecting execution is central. This thesis investigates the structure of a context-aware service registry in which context-aware services are stored by service producers and retrieved by service requesters in different contexts. The thesis builds on an existing rich theoretical service model in which contract, functionality, and contexts are bundled together. The thesis investigates generic models and structures for context, context history, and context-aware registry. Also, it studies state of the arts database technologies to analyse its suitability for implementing a registry for rich services. Specifically, the thesis provides a thorough study of the structures, implementation, performance, limitations, and features of Key-Value, Documented Oriented, and Column Oriented databases while considering options for implementing a rich service registry. Database models of contexts and context-aware services are discussed and implemented. The relative performance of the models are discussed after evaluating the test results run on large data sets. Based upon test results a justification for the selected model is given.
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The impact of nurse work environment on nurse outcomes, nurse-perceived quality of care and patient safety in Saudi Arabia
(University of British Columbia, 2018) Alharbi, Amal Ali; Dahinten, Susan
Background: The current shortage of nurses jeopardizes the quality and safety of patient care globally, and is particularly serious in Saudi Arabia. There is ample evidence that nurse work environments are important to nurses’ job satisfaction, burnout, and retention, and the quality and safety of patient care. However, most of this research has been conducted in the United States and Europe with very little emanating from Saudi Arabia or the Middle East. Purpose: This study investigated relationships between components of nurse work environment and nurse outcomes and nurse-perceived quality of care and patient safety. Methods: This correlational study was conducted using cross-sectional data collected from 496 registered nurses working in a large tertiary hospital in Riyadh, Saudi Arabia. Participants completed an online survey similar to that used in RN4Cast studies. Nurse-reported measures were used to assess nurses’ perceptions of their work environments, nurse-outcomes (i.e., job satisfaction, burnout, and intent to leave), and nurses’ perceptions of quality of care and patient safety. Hierarchical logistic regression was conducted to examine the relationships between components of nurse work environment and nurse and patient outcomes, after controlling for nurse and patient characteristics. Findings: Nurses’ perceptions of staffing and resource adequacy was predictive of all nurse outcomes except for intent to leave whereas nurse manager ability and leadership was found to be predictive only of job satisfaction. In terms of patient outcomes, staffing and resources adequacy and nursing foundation for quality of care were found to be the only independent predictors of quality of care and patient safety. Implications for Nurse Leaders: Nurse leaders in Saudi Arabia should give special attention to staffing and resources adequacy, nursing management and leadership, and nursing foundation for care delivery at the unit level. Hospitals in Saudi Arabia should strive for magnet-like qualities as they play a critical role in the recruitment and retention of nurses and contribute to better quality and safe care delivery. Conclusion: Magnet-like work environments that are culturally sensitive are critical to attracting and retaining Saudi nurses and nurses from other countries who are currently vital to alleviating the nursing shortage in Saudi Arabia.
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Investigating Targeted Driver Mutations And Pd-L1 Expression For Improved Therapy Of Non-Small Cell Lung Cancer
(Dalhousie University, 2018-05-24) Alwithenani, Akram Ibrahim; Xu, Zhaolin; Marcato, Paola
Most lung cancer patients are diagnosed at an advanced stage, limiting their treatment options to chemotherapy with very low response rate or other palliative managements. New therapies that target driver gene mutations (e.g. EGFR, ALK, BRAF), are being used to treat patients who have tumours with these mutations. In addition, a type of immunotherapy called immune checkpoint inhibitor is being used to treat lung cancer patients. For instance, patients with tumours that express PD-L1 may be responsive to anti PD-1/PD-L1 therapy. Thus, being able to identify the presence of driver mutations and PD-L1 in tumours will help patients to benefit from different therapies. A total of 851 cases of non-small cell lung cancer samples have been profiled for the presence of EGFR, KRAS, BRAF, and PIK3CA mutations by SNaPshot/sizing genotyping. Immunohistochemistry was used to identify the protein expression of ALK and PD-L1. Histological examination was performed to determine the pathological type, grade, and lymphatic/vascular invasion. Moreover, PD-L1 mRNA expression was quantified by RT-qPCR in a sub-group of the cohort to assess its correlation with PD-L1 protein level. Statistical analysis revealed correlations between the presence of the mutations, PD-L1 expression, and the pathological data. Specifically, it was determined that women had lung tumours with a significantly greater number of EGFR mutations than men. EGFR mutations were significantly linked to the absence of vascular invasion and PD-L1, and KRAS mutations do not associate with PD-L1 expression. Moreover, we found a positive correlation between mRNA levels of PD-L1 by RT-qPCR with PD-L1 expression by IHC. Together, these data provide insights into driver gene mutations and immune checkpoint status in relation to lung cancer subtypes and pathological characteristics and provide useful information for clinical implications.
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A Tool For Indexing And Classifying Unstructured Textual Documents Based on Product Family Algebra
(2020-08-01) Alomair, Deemah; Khedri, Ridha
Unstructured textual documents comprise the bulk of the data used and archived by organizations within all sectors of the economy. The need to index and classify these documents became an interesting topic that gained more attention in the field of data analytic. Different approaches are used to perform indexing and classification of textual documents. They range from supervised Machine Learning (ML) approaches to rule-based ones. There is a need for exploring novel classification approaches that exhibit better effectiveness and performance in classifying the increasing volume of this kind of data. In this thesis, we propose a novel approach to index and classify unstructured textual documents based on Product Family Algebra (PFA) and implemented using Binary Decision Diagram (BDD). In the proposed approach, a signature is first constructed for a document or a family of documents. The signature is relative to a dictionary of the typical words used in the category under consideration. Then, using operations on product family implemented using BDDs, we carry the classification of a document or families of documents using their signatures. Since ML methods are considered to be the de facto standard in document classification and to compare our method performance to their, we implement four ML classification methods: Support Vector Machine (SVM), Naive Bayes (NB), K-Nearest Neighbor (K-NN), and Decision Tree (DT). After that, we merge these modules into one software system called Smart Document Classification System (SDCS). The assessment of our approach to the classification of textual documents shows its f lexibility in indexing and classifying families of textual documents. The classification is deterministic and on a single document (not families of documents), it compares very well with the SVM ML-classifier. Using rules articulated in the language of PFA, It offers a variety of ways for classifying families of documents
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INJECTION OF RAT MESENCHYMAL STEM CELLS LEADS TO HOMING AND DIFFERENTIATION IN THE LIVER IN A BLUNT LIVER TRAUMA MODEL
(Saudi Digital Library, 2020-12-02) Alhabboubi, Mostafa; Razek, Tarek; Shum Tim, Dominique; Gao, Zu Ha; Khwaja, Kosar; Khwaja, Kosar
Background: The liver heals remarkably after different forms of injuries. However, healing time can be lengthy following high-grade blunt injuries. We hypothesize that injected bone marrow derived mesenchymal stem cells (MSC) could locate and differentiate to hepatocytes after blunt trauma using a rat liver trauma model. Methods: Blunt liver trauma was induced to Lewis rats. MSC were extracted from Lewis rats’ femurs and transfected with LacZ retrovirus so that they express B- galactosidase enzyme, giving their nuclei a blue color on light microscopy. Each rat received a single dose of BMDS (n=6 x 106) within 24 hours of trauma. Through different steps of the experiment, route of injection was the tail vein (TV) in 9 rats, the portal vein (PV) in 19 rats and directly to the injured liver (DI) in 6 rats. Rats were euthanized at 2, 7 days after injection of MSC. Livers were harvested and examined under light microscopy to identify the MSC. Results: Liver sections showed localization and active migration of MSC to trauma sites in the PV group euthanized at 48 hours (3/10 rats). Furthermore, some stem cells differentiated to hepatocytes. Although with fewer cells, similar findings were present in 1/9 rats euthanized at 7 days in the PV group. There was no evidence of MSC localization in TV and DI groups. 4 Conclusions: MSC can locate and differentiate to hepatocytes at blunt trauma site and may contribute to liver regeneration process. Portal vein injection of MSC has emerged as the most effective method of delivery to the liver following trauma among different delivery methods studied. This technique has the potential to become an effective therapeutic strategy to improve liver regeneration after severe blunt trauma. Methods of optimizing homing to injured tissue and evaluation of differentiated stem cell functionality are future areas of research.
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Surgical Performance Analysis in a Simulated Virtual Reality Anterior Cervical Discectomy and Fusion Task
(2021-08-06) Bakhaidar, Mohamad; Maestro, Rolando Del; Gregory Berry
Introduction: Multiple studies have demonstrated the effectiveness of virtual reality (VR) simulators in surgical skills training and assessment. Anterior cervical discectomy and fusion (ACDF) is among the most common spine procedures and requires trainees to master a broad spectrum of surgical techniques. The Sim-ortho VR simulator provides a validated anterior cervical discectomy and fusion (ACDF) simulated task. This validated tool can be used in the evaluation and assessment of surgical skill. Objective This thesis aims to analyze the three-dimensional data recorded by the Sim-Ortho VR simulator platform during the discectomy component of the ACDF task. We aim to use the generated data to develop novel metrics to assess the performance of participants with different levels of expertise. Hypothesis We hypothesize that the results of this analysis would establish a methodology to develop novel metrics that can identify performance variability between different groups of expertise and provide new insights into surgical expertise. Methods We recruited participants with different levels of expertise to perform a standardized ACDF simulation task. The three-dimensional structural data were generated from the simulator and recorded after each step. We collected and analyzed different data including volumes of each 5 structure at different stages of the procedure and rate of removal of the disc. Statistical significance was set as p < 0.05. Results Twenty-seven participants were included and divided into three groups based on their surgical expertise: medical student, resident, and post-resident groups. Medical students took longer to perform the discectomy compared to the other groups and left almost three times of disc residual as the resident and post-resident groups (p = 0.068). During the annulotomy component, the post-resident group removed 47.4% more disc than the resident and 102% more than the medical student group (p = 0.03). No statistically significant differences between groups were found during the second stage of the discectomy regarding disc residual and rate of removal. The post-resident group spent 19.1% of their surgical time actively working on areas adjacent to the dura, compared to 13.7% and 5.1% in the resident and medical student groups, respectively (p = 0.017). Conclusion Expert performance is associated with higher efficiency compared to resident and medical student groups. The amount removed and rate of removal represent other features of expertise during the annulotomy stage of the discectomy. These differences expose some of the features of experts’ performance that can be further studied and taught to junior trainees.
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Best Practice Using Ex Vivo Animal Brain Modelling in Neurosurgical Education to Assess Surgical Expertise
(2022-01-19) Alsayegh, Ahmad; Del Maestro, Rolando
Background: Ex vivo animal brain simulation models are increasingly utilized for neurosurgical training since these models can replicate human brain conditions. This communication aims to provide the neurosurgical community interested in utilizing ex vivo animal brain simulation models with guidelines for comprehensively and rigorously conducting, documenting, and assessing this type of research. Methods: In consultation with an interdisciplinary group of physicians and researchers involved in ex vivo models, and a review of the literature on best practice guidelines for simulation research, we developed the “Ex Vivo Brain Model to Assess Surgical Expertise” (EVBMASE) checklist. This checklist provides a comprehensive quantitative framework to analyze and report studies involving brain simulation models. We apply this checklist to articles published on ex vivo animal brain models to document how good or bad current ex vivo brain simulation models are in training surgical expertise. Results: The EVBMASE checklist utilizes defined subsections and a total score, which can help researchers to better assess the quality of, and determine deficiencies in any simulation research model. Conclusions: This work contributes to a more rigorous application, documentation, and thorough assessment of ex vivo brain simulation research.
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Evaluation of the Prescription Patterns of Antibiotics among Oral and Maxillofacial Surgeons in Canada
(2022-06) Alhumaid, Jabir; Azarpazhooh, Amir
Background: The rise in bacterial resistance is attributed to the inappropriate or unnecessary use of antibiotics. Objectives: The aim of this study was to evaluate the current knowledge and antibiotic prescription patterns among Canadian oral and maxillofacial surgeons. Methods: A web-based survey featuring 17 clinical scenarios was distributed to active oral and maxillofacial surgeons in Canada. The sample group was asked questions about their management these clinical scenarios. Descriptive and multivariate logistic regression analyses were performed (P ≤ .05). Results: More than half of the prescriptions were generated in clinical scenarios where there is little evidence to support their use. Most prescriptions followed the correct antibiotic regimen. Clinicians with a limited scope of practice had a significantly higher overprescribing index rate than those with a more extensive scope of practice. Conclusion: Improving the available evidence and ensuring that all practitioners have up-to-date, evidence-based guidelines could help minimize unnecessary antibiotic use.
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An ethnographic study on the oral health and access to dental care of Indigenous people in Montreal
(McGill University, 2022-11-06) Danish, Basem; Bedos, Christophe
Background: Although the population of Indigenous people living in urban centres has significantly increased over the past decades, limited research exists about their oral health and access to dental services. We thus know very little about their perspectives, experiences, and needs concerning oral health. However, this knowledge is needed to guide oral health policies and service delivery for urban Indigenous people. Objectives: Our objectives were to (i) understand how urban Indigenous people perceived and experienced oral health and (ii) describe their dental care pathway, including their experiences with dental professionals. Methodology: We conducted a focused ethnography, a useful and practical approach that is sensitive to cultural and social diversity and enables researchers to understand how people from certain cultures integrate health beliefs and practices into their lives. We organized individual in depth interviews with a purposeful sample of 20 Indigenous people living in Montreal, Québec. The interviews were in English, lasted approximately 90 minutes, and were audio-recorded to be transcribed verbatim and analyzed. In addition, we conducted participant observation of various Indigenous cultural events and health conferences in Montreal. Field notes were taken during these events and analyzed. The data analytic process comprised several stages, including summarizing the text, coding it into categories, and merging these categories to create themes. Findings: The participants had a bicultural perception of oral health, although the Western perspective seemed to dominate the Indigenous culture. Through the Indigenous lens, participants tended to understand oral health around the concepts of holism and balance. According to them, good oral health was important to achieve well-being and equilibrium between the physical, mental, emotional, and spiritual aspects of life. Applied to oral health, participants emphasized eating and drinking in moderation to maintain equilibrium and stressed the role of teeth in eatingtraditional diets. In agreement with Western culture, they mentioned the importance of teeth for function and aesthetics and valued personal oral hygiene as well as regular visits to the dentist. Concerning access to dental care, participants reported experiencing challenges in their lives, such as discrimination, unemployment, or chaotic life experiences, which prevented them from searching for a dentist. Finding a dentist was another issue, with participants indicating a shortage of dentists who accepted Non-Insured Health Benefits (NIHB) program beneficiaries. Because of this limited availability of dentists, some participants would return to their home communities to access dental services. Regarding the dental care episode, participants mentioned preferring dental professionals who knew and respected Indigenous culture and had good interpersonal skills. While the NIHB covered the cost of most dental treatments, some participants were required to pay for ineligible services, and some dentists refused to accept NIHB eligibility documents. Conclusions and recommendations: Urban Indigenous people face challenges and needs that require recognition by oral health professionals and policymakers. We invite these stakeholders to draw on our findings to support policies and services that facilitate access to and improve the oral health of urban Indigenous people
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Knowledge of Molar Incisor Hypomineralization among Physicians and Dentists
(Saudi Digital Library, 2023) Ghazal, Ebtehal; Kulkarni, Gajanan
Objectives: To assess the knowledge of physicians and dentists on Molar Incisor Hypomineralization (MIH) and its association with antibiotic exposure during early childhood. Methods: A cross-sectional survey design was utilized. The study was electronically advertised through professional organizations with a hyperlink provided to the questionnaire. Chi-square test was used to compare differences in levels of knowledge between the study groups. Results: There were 335 participants in the study; general physicians (n=79), pediatricians (n=98) and dentists (n=158). A significantly lower proportion of general physicians (19%) and pediatricians (18%) had knowledge of molar incisor hypomineralization compared to dentists (82%, P<0.001). There was no statistically significant difference between the groups regarding the association between antibiotics prescribed during the first years of life and MIH development (P=0.07). Conclusions: Physicians lacked knowledge about the MIH dental condition. Most study respondents did not know the potential association between MIH and frequent antibiotic intake during early childhood.
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A FLASH radiotherapy modeling study using water radiolysis by irradiating fast protons delivered at ultra-high dose rates
(Université de Sherbrooke, 2023) Alanazi, Ahmed Mohammed Abar; Jay-Gerin, Jean-Paul
Radiation therapy is an important part of the care of cancer patients. Theoretically, cancer could be cured by high doses of ionizing radiation. However, its practical application at high doses causes undesirable side effects in normal tissues. For this reason, most therapeutic improvements have focused on reducing side effects on healthy tissues. In 2014, a novel irradiation technique called "FLASH-RT" was proposed to more effectively kill cancer cells while protecting healthy tissue. Since little is known about the physicochemical mechanism underlying the effects of FLASH, e.g., the early events that occur after energy deposition, the aim of this project was to find out how the early physical and physicochemical stages along the radiation tracks are affected by high dose rates. To verify our approach, we first used our Monte Carlo code to study the effect of low dose rates of protons on radiolysis of water in the 150 keV-500 MeV energy range. The good agreement between the experimental data and our simulation results (our yield calculations for the primary radiolytically generated species) at low dose rates shows that we can use our code to study the effects of high dose rates on proton irradiation-induced radiolysis of water. As a second step, we were able to determine the critical point in time when the interaction between tracks starts in the track stage of radiolysis. The "onset" of dose-rate effects is shown to be inversely proportional to the dose rate, as demonstrated by our simulation results using our cylinder model. Based on a comparison with experiments/models using pulsed electrons, it appears that the geometry of the irradiation volume significantly affects both the time period over which dose-rate effects develop and the radiolytic yields. Finally, we extended our previous work to study the effect of linear energy transfer on oxygen depletion with protons at high dose rates. We found that in contrast to what is observed with low LET irradiation, the transient O2 consumption that occurs with high LET irradiation is quite significant. Taken together, our modeling demonstrates its suitability to study the effects of ultra-high dose rates on the initial physicochemical stages of water radiolysis.
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Biomass Derived Laser-Induced Graphene with Embedded Catalysts: Towards Enhanced Oxygen Reduction Reaction Catalytic Performance
(Acs applied nanomaterial, 2023-05-04) Aldhafeeri, Tahani; Pope, Michael
Zinc-air batteries are viewed as one of the most promising energy storage technologies for consumer electronics, electric vehicles, and grid storage due to a number of benefits including relatively high theoretical specific energy density (1350 Wh/kgactive material ) compared to lithium-ion batteries (1000 Wh/kgactive material), the abundance of zinc in the earth, and its inherent safety and ease of handling. Zinc-air batteries (ZAB) include an air-breathing cathode in addition to more standard battery components including a metal (zinc) anode, polymer separator, and alkaline electrolyte. This makes ZABs a unique technological advancement. Unlike other common battery systems like lithium-ion batteries, which store active material in the cathode, the air cathode of a ZAB uses gaseous oxygen molecules in the air as the fuel for an energy-generating process. The oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) processes that take place during battery discharge and charge, respectively, largely control the overall energy efficiency of the ZAB system due to their inherently slow kinetics. Nevertheless, the most significant obstacles to the largescale industrial deployment of ZABs are their low round-trip energy efficiency and performance deterioration. Both issues are directly connected to the poor activity and stability of the electrocatalysts used to catalyze the reactions at the air electrode and the reactions at the zinc electrode. In order to substitute precious metal catalysts, a variety of hybrid catalysts, transition metal-based catalysts, and metal free catalysts have been studied. However, the majority involve complex fabrication processes that demand special conditions and multiple, often energy intensive steps. This has hindered scale-up and can result in additional costs. Consequently, a straightforward technique for creating air electrodes with active catalysts is essential. Laser induced carbonization has emerged as a promising, furnace-free approach to create carbonbased materials and electrodes in one step. However, little work has been carried out to determine whether precious and non-precious metal catalysts can also be formed during this rapid laser conversion process and whether such methods could result in high activity electrocatalysts for the air-cathode of a zinc-air battery. Thus, in this thesis, we sought to develop composites of carbon forming resins containing various precious and non-precious metal catalyst precursors that could be laser converted to high surface area carbon/catalyst composites. We successfully designed a simple approach to prepare air cathodes consisting of laser biomassinduced graphene (LIG) decorated by different catalysts; platinum based, manganese oxides, and v metal free catalysts. We used furfuryl alcohol (FA) as a LIG precursor and CO2 laser to carbonize poly furfuryl alcohol instead of furnace in all the three projects. We demonstrate a facile approach to reduce platinum content to less than 2 wt.% by interfacing Pt with CoOx as well-dispersed nanoparticles entrapped within a highly conductive laser-induced graphene (LIG) matrix as an aircathode for ZABs. Furfuryl alcohol was used as the monomer of poly furfuryl alcohol (LIG precursor) and as a reducing agent. Laser-induced carbonization of polymerized furfural alcohol pre-loaded with Co, and Pt precursors resulted in the formation of a mixture of spherical nanoalloys and core-shell Pt-CoOx structures with ultra-small size less than 2 nm. SEM, TEM and EDS analysis indicated excellent distribution of the nanoparticles consisting of core-shell (CoOx-Pt) and mixed spherical nanoalloys throughout the three-dimensional LIG. Moreover, the onset potential of LIGPtCoOx air cathode is ~ +20 mV (vs. Hg/HgO) in alkaline media which indicates fast ORR kinetics when compared to commercial Pt/C (-30 mV vs. Hg/HgO) with the same catalyst concentration. The half-wave potential is -150 mV (vs. Hg/HgO) which is 30 mV more positive than commercial Pt/C. ZAB cycling using LIG-PtCoOx as catalyst material showed improved stability and rechargeability compared to the commercial Pt/C electrode. A greater peak power density of 67.1 mW/cm2 is also delivered by the LIG-PtCoOx cathode-assembled ZAB compared to the pricey Pt/C electrode (52.3 mW/cm2 ). Moreover, commercial manganese oxide (MnO2) was loaded in LIG via a facile one-pot polymerization reaction. Carbonization was accomplished by optimizing laser irradiation to produce a mixed-phase catalyst material supported by a highly conductive carbon matrix. Optimal loading of MnO/Mn3O4 vs LIG was determined via rotating ring disk electrode measurements where the samples that contained 10 wt.% MnO2 catalyst precursor (10MnxOy) had the best bifunctional performance towards ORR and OER and followed a four electron ORR pathway. While ZAB testing at 50 mA/cm2 indicated a voltage gap was 1.72 and 1.47 for the 10MnxOy composite and 20 wt.% Pt/C, respectively. The calculated power density showed peak powers at 48.3 and 69.0 mW/cm2 for 10MnxOy and 20 wt.% Pt/C, respectively. Finally, the synthesis method to fabricate metal free catalysts was studied using precursors entirely derived from waste biomass. Nitrogen doping of the LIG was achieved using chitosan as a biomass-based nitrogen source and furfuryl alcohol as the carbon precursor. The resulting nitrogen-doped LIG (N-LIG) samples were tested towards ORR performance. Reducing the size of the chitosan by ball milling was found to be a necessary pretreatment step to improve the ORR performance. To the best of our knowledge, this is the first work to utilize a nitrogen dopant in LIG for metal-free ORR electrocatalysis. In summary, we demonstrated the feasibility of preparing high performance ORR catalysis by laser-induced carbonization and reduction of various one-pot synthesized composite resins based on the biomass-derived poly furfuryl alcohol system. Recipes for low Pt-content Pt-Co-based alloys, manganese oxides and nitrogen doped carbons were found to achieve performance comparable or exceeding many literature studies and will, hopefully, form the basis of future advancement for practical air cathodes recipes which hold promise for low-cost zinc-air batteries and related electrochemical systems.
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A Tight Coupling Context-Based Framework for Dataset Discovery
(Concordia University, 2023-05-15) Alsaig, Alaa; Alagar, Vangalur; Ormandjieva, Olga
Discovering datasets of relevance to meet research goals is at the core of different analysis tasks in order to prove proposed hypothesis and theories. In particular, researchers in Artificial Intelligence (AI) and Machine Learning (ML) research domains where relevant datasets are essential for precise predictions have identified how the absence of methods to discover quality datasets are leading to delay and in many cases failure, of ML projects. Many research reports have brought out the absence of dataset discovery methods that fills the gap between analysis requirements and available datasets, and have given statistics to show how it hinders the process of analysis, with completion rate less than 2\%. To the best of our knowledge, removing the above inadequacies remains “an open problem of great importance”. It is in this context that the thesis is making a contribution on context-based tightly coupled framework that will tightly couple dataset providers and data analytics teams. Through this framework, dataset providers publish the metadata descriptions of their datasets and analysts formulate and submit rich queries with goal specifications and quality requirements. The dataset search engine component tightly couples the query specification with metadata specifications datasets through a formal contextualized semantic matching and quality-based ranking and discover all datasets that are relevant to analyst requirements. The thesis gives a proof of concept prototype implementation and reports on its performance and efficiency through a case study.
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The current state of clinical diagnostic algorithms for mucosal oral lesions: a scoping review
(2023-06) Al-Shehri, Mohammed; Madathil, Sreenath; Nicolau, Belinda
Background: Annually, oral cancer is responsible for more than 177,000 deaths worldwide. The majority of these cancers are squamous cell carcinomas that initially manifest as benign oral lesions that later undergo malignant transformation. Delay in diagnosis is a significant contributing factor to advanced-stage diagnosis and treatment of oral cancer. Early-stage diagnosis of oral lesions remains challenging for many clinicians. While some diagnostic algorithms have been proposed in the literature to assist with a clinical diagnosis and minimize delay, there is a dearth of comprehensive evidence synthesis and a discussion on their clinical and pedagogical applicability. Objectives: This review aims to systematically map out the literature for clinical diagnostic algorithms of oral lesions to identify gaps in knowledge and compile these algorithms for diagnosing oral lesions. Methods: We conducted a scoping review using the Arksey and O’Malley framework. Following this framework, a search was conducted, including studies that contained: 1) algorithms or flow diagrams that help clinicians to diagnose oral lesions in a clinical setting without additional software devices; 2) that were published in English; 3) all age groups; 4) algorithms for oral lesions of soft tissue only. We also excluded any articles where algorithms are: 1) black-box (do not provide an interpretable or human readable logic for diagnosis, i.e., machine learning-based models); 2) algorithms that required additional tests (e.g., algorithms for histopathologic assessment, laboratory tests); 3) older versions of an algorithm already included; 4) algorithms of oral lesions related to hard tissues such as bone and teeth; 5) any flow charts or algorithms intended to be used by the general public for self-screening. A list of keyword combinations was developed with the help of a librarian related to diagnostic algorithms of oral lesions, oral benign lesions, oral potentially malignant disorders, etc. The following databases were searched: Medline (Ovid), Embase (Ovid), and Web of Science, along with grey literature. Each included algorithm was reviewed by two oral pathology experts in the team to evaluate their completeness and correctness. Results: 17 clinical diagnostic algorithms from 15 peer-reviewed manuscripts and 1 online course were identified. All included papers were targeting their algorithms to be used by clinicians. Interestingly, most of the studies did not mention how the algorithms were developed, and none performed validation of these algorithms in a clinical setting. The algorithms often only covered one of two types of lesions and were found to be incomplete in the potential list of differential diagnoses. Conclusion: Very few clinical diagnostic algorithms for oral lesions are currently available in the literature. There is no standardized universal algorithm that is present for clinical application. The clinical and pedagogical utility of these algorithms needs to be evaluated.
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COMPLEMNT ACTIVATION DOES NOT PLAY A DIRECT ROLE IN MODEL CHEMOTHERAPUTIC- INDUCED MUCOSITIS
(2023-07-31) Aljamei, Hanan; Stadnyk, Andrew
Chemotherapeutic agents are highly efficient in the treatment of various cancers; however, many of the drugs also lead to unwanted toxicities. “Mucositis” describes the injury caused by these cytotoxic agents to the healthy mucosa of the digestive tract. Depending on the dose regimen and drug, mucositis afflicts a significant fraction of patients, from 40-100%. Currently, the underlying molecular mechanism(s) responsible for mucositis are not fully understood and there are no efficient treatments. Research into the mechanism underlying mucositis has identified superoxide radicals early followed by changes in mediators of inflammation and subsequent tissue injury. It was previously reported that complement becomes activated in the jejunum of mice injected with 5-fluorouracil to elicit mucositis and that properdin deficient mice, which should have compromised alternative pathway activation, were protected though in a complement-activation-independent mechanism. While that discovery implicated properdin in the inflammation, the experiment did not rule-out other pathways of complement activation possibly contributing to the inflammation. Therefore, the objective of this study was to determine whether activation of complement by other routes contributes to mucositis, and the hypothesis; that preventing complement activation would protect mice from mucositis. Mice were injected daily with 5-fluorouracil or methotrexate for 5 days then euthanized one day later. Each mouse’s jejunum, colon, tongue and cheek mucosae were harvested for histopathological analysis. To determine whether the lectin pathway was involved, mice lacking mannose binding lectins 1 and 2 were used. Deficient mice responded similar to wildtype mice to 5-fluorouracil and methotrexate, showing weight loss at the same rate and similar pathological features in both the jejunum and colon. Neither strain of mouse manifested with oral mucositis. Having ruled-out the mannose-binding lectin pathway, it was decided to use mice deficient in the molecule central to complement, C3. C3 deficient mice were bred with wild type mice, then the heterozygous offspring bred to a second generation which were used in experiments. The stool bacteria showed a pattern consistent with the F2 generation mice becoming more similar though different from their parent’s. C3 deficient and C3 wildtype drug-treated mice lost weight to a similar extent, while C3 heterozygotes lost weight beginning on the third day of the experiment. All the mice had similar histopathological features in their jejunums and colons after the treatments. No mice developed oral mucositis. One experiment extending the period of time the mice were treated was conducted but none of the mice developed oral mucositis. I conclude that complement activation does not contribute mechanistically to mucositis.
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Delineating the Molecular Mechanism Behind the Role of HuR in Cell Death and Drug Resistance
(Mcgill, 2023-08-31) Ashour, Kholoud; Gallouzi, Imed; Thomas, Davied
Apoptosis plays an essential role in the development and maintenance of tissue hemostasis. However, failure to undergo apoptosis is thought to represent the key to the development of several human diseases including cancers. The RNA-binding protein HuR (human antigen R) plays an important role in apoptosis and in carcinogenesis, as well as other cellular processes, including proliferation, and cell differentiation. We previously showed that HuR is required for both pro-survival and pro-apoptotic pathways, where the caspase-mediated cleavage of HuR determines the fate of the cell that is favored. Other posttranslational modifications such as phosphorylation and methylation have been shown to regulate the function of HuR. Recently, PARylation of HuR by PAR polymerase enzyme-1 (PARP1) was also shown to regulate the function of HuR during inflammation. However, the regulatory mechanism(s) of the pro-apoptotic function of HuR and the involvement of posttranslational modifications such as PARylation in this process is still elusive. In the first part of this thesis, I have identified PARylation as a regulatory mechanism that modulates the function of HuR in determining cell fate. My results showed that PARP1/2-mediated PARylation prevents the accumulation of HuR in the cytoplasm, subsequently resulting in a decrease in its cleavage, thereby inhibiting the pro-apoptotic function of HuR. I demonstrated that the combined depletion of PARP1 and PARP2 increases the cytoplasmic accumulation of HuR and thus increases its cleavage. HuR cleavage, consequently, increases its pro-apoptotic function as evidenced by the significant increase in the level of caspase-3 cleavage and in the number of apoptotic cells. Furthermore, I showed that the polymers of ADP-ribose (PAR), which is the product from PARPs’ catalytic activity, binds HuR non-covalently through a consensus motif and that this binding is required for the nuclear localization of HuR as well as its association with the import factor Transpotin-2 (TRN2). Indeed, mutating the HuR PAR-binding site (HuR-PBS) prevented PAR from binding to HuR, resulting in the cytoplasmic accumulation of HuR, and therefore advancing apoptosis. Thus, this work provides evidence for the importance of the PARP-mediated PARylation and the resulting PAR binding to HuR in regulating the function of HuR during apoptosis. For decades, chemotherapeutic drugs have been shown to induce apoptosis in several cancer cells and tumors, yet many cells conferred multidrug resistance (MDR) which represents a major obstacle in cancer treatment, usually associated with resistance to apoptosis. Several studies associated HuR with the development of chemotherapeutic resistance in a variety of tumors. However, the mechanism in which HuR affects drug resistance in cancer cells and mediates MDR1 mRNA expression, in particular, is not fully understood. In the second part of this thesis, using KB human cervical adenocarcinoma cells, I established the importance of HuR in the regulation of MDR1 mRNA expression. I showed that HuR knockdown decreased the expression of MDR1 mRNA and protein in the drug resistant KB-V1 cells. This effect, interestingly, is not due to a change in HuR expression nor a change in HuR cellular localization. Additionally, I showed that HuR binds an ARE in MDR1 mRNA in drug resistant KB-V1 cells. Together, this work reveals a new role for PARylation in cell fate determination and implicates the non-covalent interaction of PAR and HuR as an important regulatory process required for the regulation of the pro-apoptotic function of HuR. Additionally, this work provides further insight on the HuR-mediated regulation of the MDR1 mRNA thus linking HuR to the resistance of cells to drug treatment.
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Efficient Clearance of Inhaled Nanoparticles Depends on Strong Adhesion to the Epithelium: The Role of Hydrophilicity, Coating, Size, and Shape
(Saudi Digital Library, 2023-09) Bogari, Nawaf; Amrein, Matthias
Health alerts regarding high levels of fine particles in ambient air are increasingly common, reflecting a significant worldwide crisis. These particles contribute substantially to premature death, a problem only expected to grow. Among these, nanoparticles pose a particular threat, linked to respiratory diseases such as chronic obstructive pulmonary disease (COPD), asthma, and cancer as well as extrapulmonary effects. The health implications of nanoparticles differ, rendering simple particle concentration nearly meaningless. In this thesis, we focused on understanding the accumulation of nanoparticles in the lung, which is a critical aspect of their toxicity. We developed in-vitro assays to predict whether particles remain in the alveolar lumen to be cleared through alveolar and airway pathways, and which particles traverse the alveolar epithelium to induce interstitial lung disease or enter the blood and lymphatic vessels to cause systemic effects. We hypothesized that the fate of inhaled nanoparticles in the alveolar lung primarily depends on their adhesion strength to alveolar epithelium and the physical/chemical characteristics of the particle. To test this, we employed atomic force microscopy (AFM) for adhesion force measurement, transmission electron microscopy (TEM) to correlate adhesion strength to nanoparticle uptake, and confocal laser scanning microscopy (CLSM) to study nanoparticle translocation. Characteristics of nanoparticles, including protein corona coating, alveolar surfactant coating, hydrophobicity/hydrophilicity, size and geometry were studied in the presence or absence of pharmacological blockers to determine endocytic mechanism(s) involved in the interaction with the epithelium. Results showed that the adhesion of nanoparticles to the epithelial cells was an active process, and the strength of adhesion to the epithelium correlated directly to their uptake and transcytosis. Amorphous silica nanoparticles (ASN) with 15 nm in diameter were found to adhere strongly and translocate across the epithelium, whereas nanocarbon black particles 15 nm in diameter (nCB15) exhibited weak adhesion and remained in the alveolar lumen. Interestingly, commonly studied zeta potential had no influence on the interaction, whereas particle coating with surfactant increased their potential to accumulate in the alveolar lumen. Rendering ASN particles hydrophobic reduced their adhesion to the epithelium. The size of nanoparticles was linked to how cells perceived nanoparticles, with particles larger than 150 nm being endocytosed in a clathrin-enhanced mechanism, while particles less than 150 nm were taken up in a caveolin-enhanced mechanism. The epithelium did not show a preferred endocytic mechanism with respect to clathrin or caveolin for silica nanorods (SNR) yet showed a cytotoxic response to these elongated particles. This work contributes to the development of an effective framework for assessing the potential risks of inhaled nanoparticles, and our novel approach of categorization can support public health policies aiming to reduce exposure to nanoparticles in various environments.
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Logic-Oriented Fuzzy Neural Networks: Optimization and Applications of Interpretable Models of Machine Learning
(Saudi Digital Library, 2023-10-02) Alateeq, Majed Mohammad; Pedrycz, Witold
With the rapid development of machine learning models along with increasingly complex data structures, it becomes difficult to ground the reliability of models’ predictions despite the substantial progress in favor of high approximation properties. The lack of interpretability remains a key barrier in order to fully leverage the tremendous success of intelligent systems since it delivers critical analysis abilities to the end user to achieve efficiency in decision-making processes. The purpose of Interpretability and transparency is to reveal interconnections of intelligent models leading to justifying decision-making process, eliminating vagueness and capturing a factor of uncertainty in data space. Therefore, any advancement made to the interpretability feature will positively impact overall models’ performance. In the presented considerations, this work relies on logic-oriented fuzzy neural networks to represent knowledge in a transparent way with the aid of information granules. In the synergistic collaboration with fuzzy logic, neural networks deliver a vast array of learning abilities that can be even augmented with various fuzzy analytical methods to discover hidden data patterns for better interpretability. The high modularity of the constructed networks (leading to multifunctionality and robustness) is inherited from the logic nature of AND/OR neurons. The logic-oriented neurons play a pivotal role in the developed models and realize a logic approximation of experimental data and reflect general decomposition of Boolean function in two-valued logic. Information granularity is a key component in building abstract concepts to humans for knowledge acquisition and reasoning. In fact, information granules serve as a vehicle to interpret and represent knowledge domain, offering efficient way to describe complex and nonlinear systems. Fuzzy sets, as a form of information granules, adequately handle imprecise and vague knowledge in systems and consequently are a key in building transparent and interpretable models. Thus, humans can easily comprehend real-world systems or natural phenomena. The overall model efficiency, expressed in terms of accuracy and interpretability when dealing with the design and validation of AND/OR networks, constitutes a focal point of this research, along with effective quantification of the extracted knowledge especially in the case of high-dimensional input–output space. The primary objective of this dissertation is to analyze and design a cohesive interpretable framework capable of maintaining high approximation capabilities. In this study, we used logic-oriented fuzzy AND\OR networks as a backbone of overall interpretable framework. Starting off with structural analysis of the network, the structure exhibits low efficiency caused by gradient-based learning algorithms. Therefore, other gradient-based learning alternatives are superior in improving convergence due to their adaptive learning mechanisms. We demonstrate that the rate of convergence can be improved significantly by integrating randomized learning techniques through generating random weight values of connectives. Furthermore, we proposed an innovative interpretable method to describe and quantify data using concepts. The approach describes reference information granules positioned in some space (output space) inducing fuzzy sets localized in the input space. The description is realized by running a conditional fuzzy clustering followed by a calibration process completed through logic networks. The synergy between conditional clustering and logic networks presents highly cohesive linguistic dependency between objects and their attributes. As for the interpretability, a thoroughly discussion of interpretation aspects of concept analysis and conceptual clustering is presented as a means for uncertainty quantification and rigorous explainability. Further enhancement of the interpretation framework is proposed by presenting a novel method of conditional clustering. We developed a mathematical model that takes into consideration multi conditions positioned in the output space to induce information granules in input space simultaneously making these types of models more reflective of reality. The experimental studies involve synthetic data machine learning datasets from publicly-available repositories.
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The Effect Of Dietary Protein On Satiety And Weight Loss During Intermittent Fasting In Overweight And Obese Women
(Saudi Digital Library, 2023-10-11) Alzhrani, Nada; Bryant, Jo; Rehman, Laurene
Energy restriction, including IER regimens, is one of the most important obesity treatment and weight-control strategies. These regimens provide health benefits associated with weight reduction. With energy restriction regimens, however, noncompliance and hunger- induced fatigue are common issues that may interfere with this diet’s success. According to evidence, dietary protein may impact satiety and therefore mitigate certain noncompliance-related difficulties. Therefore, this dissertation primarily investigated the effect of dietary protein on satiety and body weight, with a secondary focus on health indicators (i.e., lipid profile, HbA1c, and CRP) in overweight and obese women. The data showed that plant-based protein sources increase satiety at a level comparable to that of animal-based protein. Positive results were also observed with the higher protein diet: increased satiety, decreased body weight and waist circumference, and the improvement of other health indicators, including triglycerides and C-reactive protein. Nonetheless, the differences in effect between protein groups (high protein diet versus low protein diet) were not statistically significant, possibly due to the small sample size. We found that the telehealth method was effective in facilitating the research, despite some limitations in conducting dietary interventions using telehealth. Further studies with larger sample sizes are required to clearly demonstrate the effect of dietary protein content on satiety and weight under intermittent fasting conditions and over the long term among overweight and obese women.
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The role of child and parental factors on parents feeding practices in a clinical population of children with poor growth
(Saudi Digital Library, 2023-10-15) Almaatani, Dina; Bandsma, Robert H J; Van Den Heuvel, Meta
Failure to thrive (FTT) is a symptom of inadequate nutrition and growth. Parental feeding practices are important determinants in shaping weight and eating behaviors in children during a sensitive period of physical and cognitive development. The feeding interaction is a bidirectional relationship between the caregiver and the child and informed by different contextual factors such as family, parental and/or child characteristics. Responsive feeding has been found to promote children’s interest in feeding, as well as their awareness of hunger and satiety cues. This dissertation aims to explore parental beliefs and feeding practices in a clinical population of children with poor growth, as well as the contextual factors that influence parental feeding practices in this population. First, a systematic review and meta-analysis was conducted in order to synthesize the current literature examining association between parents’ stress and their feeding practices and/or styles, among parents of children ≤ 5 years old. Second, a clinical study with cross-sectional design was conducted among a clinical population of children with poor growth to examine the correlation between maternal concern about child weight or perceived feeding difficulties and feeding practices, and to investigate the role of child temperament and maternal mental health in a clinical population of children with poor growth. The findings from the two projects, showed that both general and parenting stress were associated with non-responsive feeding styles. Furthermore, higher maternal concern about child weight and perceived feeding difficulties were associated with less responsive feeding practices. Both child temperament and maternal mental health influenced the use of pressure feeding. Therefore, a review into current policies regarding parents’ mental health screening in a pediatric setting was conducted. The review suggests a lack of clear guidelines and recourse in order to support parents’ mental health screening in a pediatric setting. These findings provide a novel insight into the role of both the child and parents factors on parents’ beliefs and feeding practices. A better understanding of this relationship may provide pathways that could support and improve the clinical management of children with poor growth.
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