Life Sciences Commons^™

The Role Of Semaphorins In Response To Injury In C. Elegans Neurons, Maria Belen Harreguy Alfonso

Dissertations

When neural tissue is injured by trauma, delicate neuronal processes such as axons and dendrites are prone to lesion damage and often disconnect. The molecular, cellular, and circuit mechanisms that underlie the regrowth and reconnection of these processes and the recovery of behavior are major challenges in the fields of neuroscience, regeneration, and resilience. At the molecular and cellular levels, signaling pathways that mediate neuronal growth cone guidance during development can play a role in neuronal regeneration and recovery from injury. One family of signaling proteins involved in this process comprises the highly conserved semaphorins and their receptors, the plexins. …

Model-Based Deep Autoencoders For Clustering Single-Cell Rna Sequencing Data With Side Information, Xiang Lin

Dissertations

Clustering analysis has been conducted extensively in single-cell RNA sequencing (scRNA-seq) studies. scRNA-seq can profile tens of thousands of genes' activities within a single cell. Thousands or tens of thousands of cells can be captured simultaneously in a typical scRNA-seq experiment. Biologists would like to cluster these cells for exploring and elucidating cell types or subtypes. Numerous methods have been designed for clustering scRNA-seq data. Yet, single-cell technologies develop so fast in the past few years that those existing methods do not catch up with these rapid changes and fail to fully fulfil their potential. For instance, besides profiling transcription …

Novel Photobase Generators For Photoinduced Polymerization And Ph Regulation, Shupei Yu

Dissertations

Photochemistry encompasses the investigation of chemical processes instigated by light absorption. As important branches of photochemistry, photosensitive and optical materials have attracted extensive research interests in both academia and industry. Photosensitive and optical materials are composed of polymers / small molecules with photo-responsive properties. These materials not only can absorb light in the desired energy spectrum, but also exhibit chemical / physical reactions, which can be applied to different fields such as photoredox, photo-heat, phototherapy, solar cells, diodes, etc. Among them, photobase generators (PBGs) are a series of photosensitive compounds, which absorb the incident light, then release the basic species …

Molecular Mechanisms Of Amyloid-Like Fibril Formation, Sharareh Jalali

Dissertations

Proteins play a critical role in living systems by performing most of the functions inside cells. The latter is determined by the protein's three-dimensional structure when it is folded in its native state. However, under pathological conditions, proteins can misfold and aggregate, accounting for the formation of highly ordered insoluble assemblies known as amyloid fibrils. These assemblies are associated with diseases like Parkinson's and Alzheimer's. Strong evidence suggests that three mechanisms are critical for forming amyloid fibrils. These mechanisms are the nucleation of amyloid fibrils in solution (primary nucleation) as well as on the surface of existing fibrils (secondary nucleation) …

Exploring Topological Phonons In Different Length Scales: Microtubules And Acoustic Metamaterials, Ssu-Ying Chen

Dissertations

The topological concepts of electronic states have been extended to phononic systems, leading to the prediction of topological phonons in a variety of materials. These phonons play a crucial role in determining material properties such as thermal conductivity, thermoelectricity, superconductivity, and specific heat. The objective of this dissertation is to investigate the role of topological phonons at different length scales.

Firstly, the acoustic resonator properties of tubulin proteins, which form microtubules, will be explored The microtubule has been proposed as an analog of a topological phononic insulator due to its unique properties. One key characteristic of topological materials is the …

Quantifying Balance: Computational And Learning Frameworks For The Characterization Of Balance In Bipedal Systems, Kubra Akbas

Dissertations

In clinical practice and general healthcare settings, the lack of reliable and objective balance and stability assessment metrics hinders the tracking of patient performance progression during rehabilitation; the assessment of bipedal balance plays a crucial role in understanding stability and falls in humans and other bipeds, while providing clinicians important information regarding rehabilitation outcomes. Bipedal balance has often been examined through kinematic or kinetic quantities, such as the Zero Moment Point and Center of Pressure; however, analyzing balance specifically through the body's Center of Mass (COM) state offers a holistic and easily comprehensible view of balance and stability.

Building upon …

Machine Learning And Network Embedding Methods For Gene Co-Expression Networks, Niloofar Aghaieabiane

Dissertations

High-throughput technologies such as DNA microarrays and RNA-seq are used to measure the expression levels of large numbers of genes simultaneously. To support the extraction of biological knowledge, individual gene expression levels are transformed into Gene Co-expression Networks (GCNs). GCNs are analyzed to discover gene modules. GCN construction and analysis is a well-studied topic, for nearly two decades. While new types of sequencing and the corresponding data are now available, the software package WGCNA and its most recent variants are still widely used, contributing to biological discovery.

The discovery of biologically significant modules of genes from raw expression data is …

Neural Correlates Of Post-Traumatic Brain Injury (Tbi) Attention Deficits In Children, Meng Cao

Dissertations

Traumatic brain injury (TBI) in children is a major public health concern worldwide. Attention deficits are among the most common neurocognitive and behavioral consequences in children post-TBI which have significant negative impacts on their educational and social outcomes and compromise the quality of their lives. However, there is a paucity of evidence to guide the optimal treatment strategies of attention deficit related symptoms in children post-TBI due to the lack of understanding regarding its neurobiological substrate. Thus, it is critical to understand the neural mechanisms associated with TBI-induced attention deficits in children so that more refined and tailored strategies can …

Biomechanical And Psychophysical Underpinnings Of Balance Dysfunction In Individuals With Traumatic Brain Injury, Naphtaly Ehrenberg

Dissertations

Falls are a major burden on healthcare infrastructure, especially in older adults and even more so in older individuals that are living in institutions. According to data from the Centers for Disease Control and Prevention (CDC), from 2010 to 2020, unintentional falls were the leading cause of nonfatal emergency department visits for all age groups except among individuals from 15-24 years of age, where unintentional falls ranked a very close second to being unintentionally struck by or against. Among older individuals living in the community, approximately 30-35% fall at least once in a given year, and around three times as …

Continuum Modeling Of Active Nematics Via Data-Driven Equation Discovery, Connor Robertson

Dissertations

Data-driven modeling seeks to extract a parsimonious model for a physical system directly from measurement data. One of the most interpretable of these methods is Sparse Identification of Nonlinear Dynamics (SINDy), which selects a relatively sparse linear combination of model terms from a large set of (possibly nonlinear) candidates via optimization. This technique has shown promise for synthetic data generated by numerical simulations but the application of the techniques to real data is less developed. This dissertation applies SINDy to video data from a bio-inspired system of mictrotubule-motor protein assemblies, an example of nonequilibrium dynamics that has posed a significant …

Deep Hybrid Modeling Of Neuronal Dynamics Using Generative Adversarial Networks, Soheil Saghafi

Dissertations

Mechanistic modeling and machine learning methods are powerful techniques for approximating biological systems and making accurate predictions from data. However, when used in isolation these approaches suffer from distinct shortcomings: model and parameter uncertainty limit mechanistic modeling, whereas machine learning methods disregard the underlying biophysical mechanisms. This dissertation constructs Deep Hybrid Models that address these shortcomings by combining deep learning with mechanistic modeling. In particular, this dissertation uses Generative Adversarial Networks (GANs) to provide an inverse mapping of data to mechanistic models and identifies the distributions of mechanistic model parameters coherent to the data.

Chapter 1 provides background information on …

Improving The Stimulation Selectivity In The Human Cochlea By Strategic Selection Of The Current Return Electrode, Ozan Cakmak

Dissertations

The hearing quality provided by cochlear implants are poorly predicted by computer simulations. A realistic cochlear anatomy is crucial for the accuracy of predictions. In this study, the standard multipolar stimulation paradigms are revisited and Rattay’s Activating Function is evaluated in a finite element model of a realistic cochlear geometry that is based on µ-CT images and a commercial lead. The stimulation thresholds across the cochlear fibers were investigated for monopolar, bipolar, tripolar, and a novel (distant) bipolar electrode configuration using an active compartmental nerve model based on Schwartz-Eikhof-Frijns membrane dynamics. The results suggest that skipping of the stimulation point …

Photonic Monitoring Of Atmospheric Fauna, Adrien P. Genoud

Dissertations

Insects play a quintessential role in the Earth’s ecosystems and their recent decline in abundance and diversity is alarming. Monitoring their population is paramount to understand the causes of their decline, as well as to guide and evaluate the efficiency of conservation policies. Monitoring populations of flying insects is generally done using physical traps, but this method requires long and expensive laboratory analysis where each insect must be identified by qualified personnel. Lack of reliable data on insect populations is now considered a significant issue in the field of entomology, often referred to as a “data crisis” in the field. …

Interactions Of Amyloid Peptides With Lipid Membranes, Yanxing Yang

Dissertations

The aggregation of amyloid proteins into fibrils is a hallmark of several diseases including Alzheimer’s (AD), Parkinson’s, and Type II diabetes. This aggregation process involves the formation of small size oligomers preceding the formation of insoluble fibrils. Recent studies have shown that these oligomers are more likely to be responsible for cell toxicity than fibrils. A possible mechanism of toxicity involves the interaction of oligomers with the cell membrane compromising its integrity. In particular, oligomers may form pore-like structures in the cell membrane affecting its permeability or they may induce lipid loss via a detergent-like effect. This dissertation aims to …

Angiogenic Supports For Microvascular Engineering, Zain Siddiqui

Dissertations

Ischemic tissue disease is caused by a lack of circulation / blood supply to tissue. This can be treated by introducing a number of angiogenic (pro-blood vessel forming) factors into the tissue. This work presents strategies for ischemic tissue treatment utilizing a novel proangiogenic self-assembling peptide hydrogel platform. To demonstrate the utility of this platform, its use alone as an angiogenic therapeutic (both alone as a self-assembling hydrogel and with two-component systems), and its ability to vascularize implants is explored. Due to these angiogenic scaffolds demonstrating efficacy to regenerate microvasculature, this work evaluates diseases that can be treated by the …

Brainless But Smart: Investigating Cognitive-Like Behaviors In The Acellular Slime Mold Physarum Polycephalum, Subash Kusum Ray

Dissertations

Evolutionary pressures to improve fitness, have enabled living systems to make adaptive decisions when faced with heterogeneous and changing environmental and physiological conditions. This dissertation investigated the mechanisms of how environmental and physiological factors affect the behaviors of non-neuronal organisms. The acellular slime mold Physarum polycephalum was used as the model organism, which is a macroscopic, unicellular organism, that self-organizes into a network of intersecting tubules. Without using neurons, P. polycephalum can solve labyrinth mazes, build efficient tubule networks, and make adaptive decisions when faced with complicated trade-offs, such as between food quality and risk, speed and accuracy, and exploration …

Flexibility Vs Consistency: Quantifying Differences In Neuromodulatory Elicited Patterns Of Activity, Elizabeth M. Cronin

Dissertations

Central pattern generating circuits underly fundamental behaviors such as respiration or locomotion and are under the influence of neuromodulators. The presence of neuromodulators is thought to confer flexibility to these circuits to generate distinct patterns of activity to meet distinct behavioral needs. Network output flexibility can be achieved by distinct classes of neuromodulators, those which have convergent cellular actions but divergent circuit actions or by those which have divergent cellular actions but convergent circuit actions.

Both classes of neuromodulator exist in the stomatogastric nervous system of the crab Cancer borealis and influence the activity of a central pattern generating circuit …

Sensorimotor Content Of Multi-Unit Activity In The Paramedian Lobule Of The Cerebellum, Esma Cetinkaya

Dissertations

Based on Center for Disease Control and Prevention report 2016, around 39.5 million people in the United States suffer from motor disabilities. These disabilities are due to traumatic conditions like traumatic brain injury (TBI), neurological diseases such as amyotrophic lateral sclerosis (ALS), or congenital conditions. One of the approaches for restoring the lost motor function is to extract the volitional information from the central nervous system (CNS) and control a mechanical device that can replace the function of a paralyzed limb through systems called Brain-Computer Interfaces (BCI).

One of the major challenges being faced in BCIs and also in general …

One-Stage Blind Source Separation Via A Sparse Autoencoder Framework, Jason Anthony Dabin

Dissertations

Blind source separation (BSS) is the process of recovering individual source transmissions from a received mixture of co-channel signals without a priori knowledge of the channel mixing matrix or transmitted source signals. The received co-channel composite signal is considered to be captured across an antenna array or sensor network and is assumed to contain sparse transmissions, as users are active and inactive aperiodically over time. An unsupervised machine learning approach using an artificial feedforward neural network sparse autoencoder with one hidden layer is formulated for blindly recovering the channel matrix and source activity of co-channel transmissions. The BSS sparse autoencoder …

Repeated Low-Level Blast Induces Chronic Neuroinflammation And Neurobehavioral Changes In Rat Models, Arun Reddy Ravula

Dissertations

Blast-induced neurotrauma (bTBI) is a signature medical concern for military personnel when they are exposed to explosions in active combat zones. However, soldiers as well as law enforcement personnel are also repeatedly exposed to low-level blasts during training sessions with heavy weaponries as part of combat readiness. Service personnel who sustain brain injuries from repeated low-level blasts (rLLBs) do not display overt pathological symptoms immediately but rather develop cognitive impairments, attention deficits, anxiety, and sleep disturbances over time. An improved rat model of rLLB was developed in this thesis by applying controlled low-level blast pressures (10 psi) repeated five times …

Assessing Structural And Functional Brain Alterations And Work-Related Fatigue In Non-Hyposmic And Hyposmic Covid-19 Survivors, Rakibul Hafiz

Dissertations

In the year 2019, life began to change at the advent of a global pandemic caused by the novel coronavirus. Mask mandates and mass vaccinations have mitigated the effects significantly, yet cases keep rising with new variants, especially, in densely populated countries, like India. Recent neuroimaging evidence shows the virus can attack the central nervous system (CNS). However, exactly which brain regions undergo structural and functional changes remain largely unknown. Many patients experience 'loss of/reduced sense of smell' (i.e., hyposmic) and an alarming number of survivors develop persistent symptoms ('long-COVID') for several months after initial infection. Fatigue is the most …

The Interplay Of The Physical Landscape And Social Dynamics In Shaping Movement Of African Savanna Elephants (Loxodonta Africana), Maggie Wisniewska

Dissertations

Free ranging African savanna elephants (Loxodonta africana) are increasingly impacted by human-induced habitat loss and poaching for ivory. Because elephants live in tightly knit groups, this combination of threats not only reduces the size of their populations but also degrades their social interactions. Long-term relationships with socially competent individuals, such as experienced seniors, benefit the ability of other group members to access limiting resources and avoid danger. Understanding how anthropogenic pressure may affect persistence of elephant populations is important, because elephants are an economically important keystone species. This doctoral thesis characterizes how individual elephants influence the movement of their social …

Towards Understanding The Role Of Central Processing In Release From Masking, Nima Alamatsaz

Dissertations

People with normal hearing have the ability to listen to a desired target sound while filtering out unwanted sounds in the background. However, most patients with hearing impairment struggle in noisy environments, a perceptual deficit which current hearing aids and cochlear implants cannot resolve. Even though peripheral dysfunction of the ears undoubtedly contribute to this deficit, surmounting evidence has implicated central processing in the inability to detect sounds in background noise. Therefore, it is essential to better understand the underlying neural mechanisms by which target sounds are dissociated from competing maskers. This research focuses on two phenomena that help suppress …

Exploring Fused Deposition Modeling (Fdm) Three-Dimensional Printing Tablet Design Options For Pharmaceutical Dosage Forms, Guluzar Gorkem Buyukgoz

Dissertations

This dissertation examines the use of Fused Deposition Modeling (FDM) based three-dimensional (3D) printing approach for developing patient-specific dosage forms and addressing related technical challenges in such drug delivery systems. The first main objective is to explore pharmaceutical tablet design options using novel FDM 3D printing technology as the drug delivery platform such that drug form and tablet properties are tailored by considering patient age-specific formulations and dissolution control. Of the five different design options, two proposed options meet the main objective of providing similar drug release, whereas the popular option of fixed drug concentration but differing tablet size could …

Alcohol As A Catalyst For Hiv-Associated Neuroinflammation And Tbi-Induced Iron Toxicity, Agnieszka Agas

Dissertations

Alcohol has long been considered an exacerbator of diseases, disorders, and injuries as well as many of the accompanying symptoms. As an alternative approach, this dissertation explores alcohol as a catalyst for two different human disease conditions, human immunodeficiency virus (HIV)-associated neuroinflammation and traumatic brain injury (TBI)-induced iron toxicity. In HIV-1 infection, this dissertation presents a novel anti-viral drug, called Drug-S, for a possible inhibition and treatment of HIV-1 disease progression.

The first aim explores the influence of alcohol with HIV-associated neuroinflammation on macrophage migration across an in vitro model of the blood brain barrier. There is a gap in …

Selective Neural Stimulation By Leveraging Electrophysiological Diversity And Using Alternative Stimulus Waveforms, Bemin Ghobreal

Dissertations

Efforts on finding the principle mechanism for selective neural stimulation have concentrated on segregating the neurons based on their size and other geometric factors. However, neuronal subtypes found in different parts of the nervous system also differ in their electrophysiological properties. The primary objective of this study is to investigate the feasibility of selective activation of neurons by leveraging the diversity seen in passive and active membrane properties.

Using both a local membrane model and an axon model based on the CRRSS, the diversity of electrophysiological properties is simulated by varying four model parameters (membrane leakage-Gleak and capacitance-Cm, temperature coefficient-Ktemp, …

These Fish Were Made For Walking: Morphology And Walking Kinematics In Balitorid Loaches, Callie Hendricks Crawford

Dissertations

Terrestrial excursions have been observed in multiple lineages of marine and freshwater fishes. These ventures into the terrestrial environment may be used when fish are searching out new habitat during drought, escaping predation, laying eggs, or seeking food sources. The physiological demands for life under water and on land are vastly different and require different functional adaptations. Fish with terrestrial excursions must be capable of dealing with the stresses of both aquatic and terrestrial environments for varying periods of time. To deal with these stresses, amphibious fishes exhibit many morphological and behavioral adaptations. These adaptations have led to a range …

Methods For Extending Biomedical Reference Ontologies And Interface Terminologies For Ehrr Text Annotation, Vipina Kuttichi Keloth

Dissertations

Biomedical ontologies and terminologies are a cornerstone in various electronic health record systems (EHRs) for encoding information related to diseases, diagnoses, treatments, etc. Ontologies in general represent entities (concepts) and events along with all interdependent properties and relationships in an efficient way to facilitate easy access, retrieval and sharing. With the landscape of medicine rapidly changing, biomedical ontologies and terminologies need to rapidly evolve to support interoperability, medical coding, record keeping, and healthcare activities in general, and to facilitate interdisciplinary research. Extending ontologies by identifying new and missing concepts plays a vital role in the maintenance of ontologies to keep …

Reconstituting The Cyanobacterial Circadian Clock In Vitro, Pyong Hwa Kim

Dissertations

Cyanobacteria are photosynthetic organisms that are known to be responsible for oxygenating Earth’s early atmosphere. Having evolved to ensure optimal survival in the periodic light/dark cycle on this planet, their genetic codes are packed with various tools, including a sophisticated biological timekeeping system. Among the cyanobacteria is Synechococcus elongatus PCC 7942, the simplest clock-harboring organism with a powerful genetic tool that enabled the identification of its intricate timekeeping mechanism. The three central oscillator proteins—KaiA, KaiB, and KaiC—drive the 24 h cyclic gene expression rhythm of cyanobacteria, and the "ticking" of the oscillator can be reconstituted inside a test tube just …

Development Of Deep Learning Neural Network For Ecological And Medical Images, Shaobo Liu

Dissertations

Deep learning in computer vision and image processing has attracted attentions from various fields including ecology and medical image. Ecologists are interested in finding an effective model structure to classify different species. Tradition deep learning model use a convolutional neural network, such as LeNet, AlexNet, VGG models, residual neural network, and inception models, are first used on classifying bee wing and butterfly datasets. However, insufficient data sample and unbalanced samples in each class have caused a poor accuracy. To make improvement the test accuracy, data augmentation and transfer learning are applied. Recently developed deep learning framework based on mathematical morphology …