Rotaxane Ligands for Incorporation into Metal-Organic Framework Materials

This dissertation focuses on studies of mechanically interlocked molecules (MIMs) specifically [2]rotaxanes in three principle areas: (1) creating [2]rotaxane linkers to incorporate into metal-organic frameworks (MOFs); (2) studying the rate of shuttling motion in solution and finally (3) investigating the shuttling motion inside the MOF. Chapter 1 provides a brief introduction to MIMs, rotaxanes, MOFs and all previous studies on dynamic motions of MIMs in MOFs. Chapter 2 describes a [2]rotaxane linker with donor atoms attached to both the axle and the wheel. The linker contains four carboxylate groups attached to a rigid, H-shaped axle and two carboxylate units appended to a crown ether wheel. In the resulting Zn-based MOF, three independent 3-periodic frameworks (threefold interpenetration) are interconnected only by virtue of the threading of their individual components in the rotaxane linker. In Chapter 3, a [2]rotaxane linker was synthesized which combines an H-shaped axle containing four 3-carboxyphenyl groups and a macrocyclic wheel with two 4-pyridyl groups. The synthesized Zn and Cu MOFs showed two independent lattices threaded together by interlocking of the linker. In Chapter 4, a series of [2]rotaxane molecular shuttles was synthesized with varying track lengths between recognition sites. The rates of shuttling of the macrocycle along the rigid track were measured by variable temperature 1H NMR spectroscopy for the neutral compounds and EXSY experiments for the dicationic species. It was determined that the length of the axle does not affect the shuttling rate. In Chapter 5, molecular shuttling inside Zr-based MOFs under acid-base conditions was studied. 13C SSNMR studies on the first MOF, UWDM-6 (University of Windsor Dynamic Material) consisting of two linkers 2′,3′,5′,6′-tetramethylterphenyl-4,4″ dicarboxylic acid (H4TTTP) and [2]rotaxane demonstrated no shuttling because of steric hindrance of methyl groups of H4TTTP linker. This steric hindrance limitation was eliminated for UWDM-7 by changing the linear ligand to terphenyl dicarboxylate (TPDC). In Chapter 6, a bistable [2]rotaxane molecular shuttle inside a Zr-based MOFs was studied. The synthesized MOF, UWDM-8 consisted of [2]rotaxane with two non-equivalent recognition sites and linear linker H4TTTP. Switching was driven by the addition of acid or lithium ions and monitored by 15N SSNMR spectroscopy

Correction of Retinal Nerve Fiber Layer Thickness Measurement on Spectral-Domain Optical Coherence Tomographic Images Using U-net Architecture

Purpose: In this study, an algorithm based on deep learning was presented to reduce the retinal nerve fiber layer (RNFL) segmentation errors in spectral domain optical coherence tomography (SD-OCT) scans using ophthalmologists’ manual segmentation as a reference standard. Methods: In this study, we developed an image segmentation network based on deep learning to automatically identify the RNFL thickness from B-scans obtained with SD-OCT. The scans were collected from Farabi Eye Hospital (500 B-scans were used for training, while 50 were used for testing). To remove the speckle noise from the images, preprocessing was applied before training, and postprocessing was performed to fill any discontinuities that might exist. Afterward, output masks were analyzed for their average thickness. Finally, the calculation of mean absolute error between predicted and ground truth RNFL thickness was performed. Results: Based on the testing database, SD-OCT segmentation had an average dice similarity coefficient of 0.91, and thickness estimation had a mean absolute error of 2.23 ± 2.1 μm. As compared to conventional OCT software algorithms, deep learning predictions were better correlated with the best available estimate during the test period (r2 = 0.99 vs r2 = 0.88, respectively; P < 0.001). Conclusion: Our experimental results demonstrate effective and precise segmentation of the RNFL layer with the coefficient of 0.91 and reliable thickness prediction with MAE 2.23 ± 2.1 μm in SD-OCT B-scans. Performance is comparable with human annotation of the RNFL layer and other algorithms according to the correlation coefficient of 0.99 and 0.88, respectively, while artifacts and errors are evident

Measuring promotors of school functioning: Informing school-based psychosocial support for crisis-affected students in Lebanon

The evolving situation in Lebanon is characterized by multiple crises that affect education and can negatively affect a student’s school-functioning and mental health. The Ministry of Education and Higher Education decided in 2019 to further intensify and upscale implementation of school-based psychosocial support. This study is a contextualization and validation of the Student Learning in Emergencies Checklist for use in Lebanon. A 27-item questionnaire was proposed and tested to explore categories for measuring the effect of psychosocial support on academic functioning and academic performance and build evidence for program design. Promotors for school functioning were also explored. The participants (N = 1048) were divided between Lebanese students (N = 573) and non-Lebanese students (N = 520) with a mean age of 11.77 and gender balance. Multiple regression analysis demonstrated that the combined proposed categories explained 33.7% of the variance of school functioning as opposed to other factors. The new categories for safety and support at school and safety and support at home were found to predict academic functioning alone. Lebanese students reported significantly reduced scores in safety and support at school compared to non-Lebanese students. The need for psychosocial and educational support increased significantly with age, and males reported lower scores than females. Content and strategies for school-based psychosocial support for students are discussed

Exosomal microRNAs in breast cancer and their potential in diagnosis, prognosis and treatment prediction

The significance of exosomal microRNAs (EmiRs) in breast cancer (BC) diagnosis has been widely addressed over the past decades. However, little information is still available regarding these reliable biomarkers’ impacts on BC early diagnosis, prognosis, and treatment outcome predictions, but their great potential in spotting BC early and their predictive essence in BC prognosis and treatment results are promising against this common cancer. The present review focuses on the most recent findings and advancements of EmiRs applications in BC early diagnosis and treatment prediction and identifies current helpful EmiRs that are widely used in this regard

Automatic Detection of Laryngeal Pathology on Sustained Vowels Using Short-Term Cepstral Parameters: Analysis of Performance and Theoretical Justification

The majority of speech signal analysis procedures for automatic detection of laryngeal pathologies mainly rely on parameters extracted from time domain processing. Moreover, calculation of these parameters often requires prior pitch period estimation; therefore, their validity heavily depends on the robustness of pitch detection. Within this paper, an alternative approach based on cepstral- domain processing is presented which has the advantage of not requiring pitch estimation, thus providing a gain in both simplicity and robustness. While the proposed scheme is similar to solutions based on Mel-frequency cepstral parameters, already present in literature, it has an easier physical interpretation while achieving similar performance standards