Synthesis and Biophysical Analysis of Modified Cell-Penetrating Peptides

Cell-penetrating peptides (CPPs) are a family of peptides that have the ability to penetrate biological membranes. They were discovered in the late 1980s and have been the topic of many studies. Much of the interest in CPPs has been due to their ability to translocate biological membranes, and the possibility that they could offer a novel drug delivery method by conjugation to biologically active molecules. Linear CPPs can be modified to form cyclic structures. This change in structure has been observed to enhance the stability and penetrative ability of the CPPs which have been studied. The current thesis focuses on the biophysical properties of CPPs modified to allow for cyclization. Penetratin (primary sequence: RQIKIWFQNRRMKWKK) and the Tat peptide (primary sequence: YGRKKRRQRRR) are two examples of linear CPPs that interact with and translocate across biological membranes. Fmoc based solid-phase peptide synthesis (SPPS) was used to synthesize cyclizable analogs of these two peptides by adding glycine and cysteine residues to the peptides’ termini. Reversed-phase high performance liquid chromatography (RP-HPLC) was used to purify and analyze the homogeneity of the protected linear analogs of the Tat peptide and penetratin (pTatL and pPenL, respectively). Fluorescence emission spectroscopy and circular dichroism (CD) spectroscopy were used to observe the conformational differences between the cyclizable analogs, and their original peptide constructs in different (aqueous, organic solvent and lipidic) environments. Dithiothreitol was required to measure the fluorescence and CD spectra of the peptides in the presence of lipid vesicles, to prevent the precipitation which might occur in the absence of the reducing agent. The CD and fluorescence spectra of pPenL were similar to the previously reported spectra of the native penetratin peptide; it displayed an unordered conformation in aqueous environments and α-helical conformations in organic solvents hexafluoroisopropanol and lipidic phosphatidylcholine/phosphatidylglycerol and phosphatidylethanolamine/phosphatidylglycerol (PC/PG and PE/PG) environments. The Tat peptide has been reported to maintain an unordered secondary structure in all environments and when conjugated to biologically active molecules. The spectra of pTatL in aqueous buffer agreed with the previous reports, but the spectra in HFIP displayed partial α-helical conformations, likely due to the modifications made to the sequence to enable cyclization

Collison avoidance with another individual: the influence of person-specific characteristics

Collision avoidance during locomotion is an important skill that people must master to successfully navigate through dynamically changing environments. Environments are cluttered with objects that are either goals (attraction points) or obstacles (repulsion points), such that locomotion must be guided towards goals and away from obstacles. While navigating towards a goal, individuals maintain an elliptically shaped ‘personal space’ between their own body and that of the obstacle(s). The size of personal space (degree of repulsion) is modulated depending on the specific situation. Collision avoidance research has typically utilized inanimate objects such as poles, however recent findings suggest that the amount of personal space required with inanimate objects is distinct from that used to avoid another person. Historically, person-to-person collision avoidance research has examined avoidance behaviours during different situation-specific scenarios, such as mutual or joint-task avoidance, passing through apertures, and interacting on various angles. Person-person research has not, however, fully taken person-specific characteristics into consideration as factors that may contribute to different avoidance behaviours. It is unknown whether humans perceive all humans the same way or if certain external-characteristics (i.e., one’s perception of others) dictate how collisions are strategically avoided with another human. Furthermore, it is unknown if behaviours are robust across all individuals or if there are certain internal-characteristics (i.e., one’s perception of self) that influence collision avoidance behaviours. The overarching goal of my PhD was to identify the person-specific characteristics that mediate changes in avoidance behaviours, in a young adult population. To address this, five collision avoidance studies were conducted in the real world or virtual reality. The first study (conducted at Wilfrid Laurier University) examined collision avoidance behaviours when circumventing two physically different sized individuals. Results from Study 1 revealed that individuals circumvent people with a larger body size with more space at the time of crossing from the center of mass compared to a person with a smaller body size. The second study (conducted at Wilfrid Laurier University) was a follow-up focused on avoidance behaviours when circumventing an individual whose body size was artificially increased using shoulder pads. Study 2 demonstrated that when an artificial extension (shoulder pads) is added to a stationary person, avoidance behaviours are unchanged. Instead, results determined a side-bias where clearance was smaller for left-side avoidance. The third study (conducted at University Rennes II, FR), focused on determining the influence of a virtual human’s age-related (older vs younger) appearance and gait characteristics on collision avoidance strategies. Study 3 found that young adults circumvent with a larger clearance when interacting with a virtual pedestrian who possesses older adult-like characteristics. Study 4 (conducted at Université Laval) determined differences in the avoidance and gaze behaviours of athletes and non-athletes during an avoidance task with a virtual pedestrian who unpredictably steered to a new direction. Avoidance and gaze behaviours were different between athletes and non-athletes during early planning, but similar during late planning. Unpredictable steering behaviours of an approaching pedestrian led to a larger clearance at the time of crossing. Study 5 (conducted at Wilfrid Laurier University) was aimed at determining if an acute nociceptive stimulus (via topical capsaicin cream) alters avoidance behaviours. Cutaneous discomfort on the lateral aspect of the arm did not alter young adults’ avoidance behaviours. However, a learning effect was observed as avoidance was different during the first trial. Together, these studies suggest that additional perceptual factors are considered when avoiding collisions with other people. The results of this dissertation demonstrate that during obstacle avoidance tasks, one’s personal space is influenced by, 1) the external-characteristics of an opposing pedestrian, and 2) the internal-characteristics of oneself. Understanding the typical behaviours for circumventing pedestrians and knowing how specific external- and internal-factors influence personal space provides the necessary groundwork for understanding how these behaviours are altered with age or disease. Furthermore, this work provides valuable information about human inter-personal distances (i.e., proxemics), which may be applicable to re-designing the simulation models of interactions between pedestrians used by engineers to expand crowd simulations, to develop architectural plans for urban centers, design robots to safely navigate unfamiliar environments, or properly plan exit routes in buildings

Genome-Based Pathogenicity Potential of Salmonella Isolated from Diverse Sources

Bacterial human pathogens are among the leading causes of death around the world, especially in low income and developing countries. One important element in a bacterium’s ability to cause disease are genes that directly contribute to pathogenicity called virulence factors. A second significant aspect are antimicrobial resistance genes which allow microorganisms to persist in the presence of antimicrobial agents. In this project I aimed to determine if Salmonella isolated from different sources differed in pathogenicity profiles based on the complement of genes identified through genomic analysis. Accordingly, Salmonella genomes were organized into 8 groups: animal, clinical, human, environmental, food, water source, plant, and nut. A negative control, consisting primarily of non-pathogenic E. coli, was also included. To determine disease-causing potential, the proteins encoded by these genomes were compared against the Virulence Factor Database (VFDB), the PathFam database, and the Comprehensive Antimicrobial Database (CARD). The negative controls coded for significantly fewer proteins matching the VFDB and PathFams, but significantly more matching the CARD, than all other groups. Though visibly overlapping, most isolation sources were found to be significantly different to each other (p value \u3c 0.05), aside from the very small nut and plant groups. When clustered by their specific matches to the VFDB and CARD, genomes from the same environmental groups did not cluster together. Therefore, while the groups were statistically different from each other in number of matches, those differences were not due to group-specific virulence factors. Though most isolation source groups were found to be significantly different in VFDB, CARD and PathFam matches, further analyses are needed to determine if that difference is large enough to influence Salmonella’s disease-causing potential. Methods and results from this analysis can be built upon in the future to better identify potential pathogens isolated from different environments

Grammatical Aspect, Temporal Adverbs, and Situation Models

Grammatical aspect and temporal cues have been shown to impact discourse processing. To explore this further, we contrasted temporal adverbs that move narrative timelines forward or backward. Although previous research has examined timelines independently, it was yet to be explored how timeline adverbs impact discourse processing when grammatical aspect and temporal cues are also manipulated. The experiment involved a sentence-completion task which allowed us to measure availability of target discourse concepts in situation models. Results showed main effects for grammatical aspect, temporal shifts, and narrative timeline directions. Three two-way interactions were found. The results demonstrated support for the iconicity assumption and determined that grammatical aspect, time shifts, and narrative timeline direction in texts impact discourse processing

The Wilderness Which Never Was: A History of the Białowieża Forest 1850–1947

Located on both sides of the Polish-Belarusian border in north-eastern Poland, the Białowieża forest is the largest remaining remnant of the vast primeval forest that once covered most of Europe. It is also home to Europe’s biggest land animal—the European bison. Over the past century Polish governments, as well as modern-day Polish and European environmental groups, have promoted the forest as the “last European wilderness.” Even today, the public regularly protests and decries news of human encroachment on the forest. Yet in reality, the Białowieża forest has been exploited and studied by humans for centuries, making it one of the best-known places on earth. Despite clear evidence of human intrusion into Białowieża through successive political regimes and both world wars, the myth of a wild Białowieża nevertheless persists in Poland and Europe. This dissertation explores the history behind the myth of the wild forest as well as the myth-making process. Based on extensive research using archival material and published primary and secondary sources, this dissertation asks where the myth of a wild Białowieża came from and why it emerged, and explores how this myth shaped the history of the forest from the second half of the 19th century through to the first half of the 20th century. This dissertation argues that the myth was powerful enough to dictate various government policies related to the forest and ultimately to determine the fate of the forest itself

Multiscale Modelling of Brain Networks and the Analysis of Dynamic Processes in Neurodegenerative Disorders

The complex nature of the human brain, with its intricate organic structure and multiscale spatio-temporal characteristics ranging from synapses to the entire brain, presents a major obstacle in brain modelling. Capturing this complexity poses a significant challenge for researchers. The complex interplay of coupled multiphysics and biochemical activities within this intricate system shapes the brain\u27s capacity, functioning within a structure-function relationship that necessitates a specific mathematical framework. Advanced mathematical modelling approaches that incorporate the coupling of brain networks and the analysis of dynamic processes are essential for advancing therapeutic strategies aimed at treating neurodegenerative diseases (NDDs), which afflict millions of individuals worldwide. This thesis aims to develop novel multiscale brain network models to investigate the properties of biological processes spanning multiple spatial and temporal scales, potentially offering new insights into the fundamental aspects of brain networks in healthy and diseased states. Among various factors, our particular attention is devoted to brain electrical activity, which serves as a significant characteristic of NDDs such as Alzheimer\u27s disease (AD), cortical spreading depression (CSD), and Parkinson\u27s disease (PD). Our analysis starts with a focus on large-scale brain network models within the context of AD and PD. Importantly, AD is characterized by pathological accumulations of amyloid-beta plaques ($A\beta$) and neurofibrillary tangles ($\tau$). Specifically, the propagation of intracellular calcium ($Ca^{2+}$) signalling within non-neuronal cells, such as astrocytes, has an impact on the tripartite synapse propagation in neuronal cells, leading to synaptic failure and neuronal death. To gain insights into the pathogenesis of AD, particularly the role of astrocytes in the presence of misfolded proteins ($A\beta$ and $\tau$), we propose an improved large-scale brain network model. This model incorporates the concept of astrocytic clearance, which aids in the fragmentation and elimination of toxic $A\beta$. We obtained the data from the Human Connectome Project (HCP) and proposed a hybrid multiscale modelling strategy based on a large-scale brain network model. Furthermore, PD is characterized by involuntary or uncontrolled movements such as shaking, stiffness, and difficulties with balance and coordination. In our study, we have developed a small-scale brain network model that aims to shed light on the intricate dynamics of PD and its impact on the brain. Within the context of PD, we have explored the optimization of deep brain stimulation (DBS) procedures, a well-established neuromodulation technique for managing PD symptoms. By leveraging data from the HCP, we propose a closed-loop DBS approach based on a brain network model. Additionally, CSD is characterized by a slowly propagating wave that disrupts the brain\u27s homeostasis, leading to a temporary impairment in the normal functioning of neurons. In this thesis, our focus is to model the propagation of CSD in the brain using two different approaches found in the literature. Firstly, we employ a simplified model consisting of six coupled equations of the reaction-diffusion type in two spatial dimensions. Secondly, we utilize a more complex one-dimensional neuronal model that incorporates ionic currents and ionic pumps. Furthermore, we have developed a comprehensive coupled neuronal-glial model to investigate the impact of temperature on the activation and inactivation of ionic channels, specifically focusing on their influence on calcium-mediated exosomal dynamics in PD and AD. This model specifically examines controlled therapeutic exosomal release by evaluating the modulated release rate and the concentration of released exosomes. Importantly, it considers the temperature threshold dependence on $Ca^{2+}$ dynamics by incorporating cold-sensing neurons. The outcomes of our investigation highlight the significant role played by $TRPM8$ and voltage-gated $Ca^{2+}$ channels in determining temperature-dependent activation and inactivation at various threshold levels. Notably, the primary objective of this thesis is to develop multiscale deterministic and stochastic models that can capture the overall trends and average behaviour of the system, providing insights into the mechanisms underlying these diseases. The etiology of AD can be described as a multi-state disease process utilizing the approximate Bayesian computation (ABC) method. In this context, we employ ADNI data from 2-year visits for AD patients and apply this method to investigate the interplay between $A\beta$ and $Ca^{2+}$ levels at different stages of disease development. Astrocytes play a crucial role in NDDs as they secrete neurotrophins, regulate synaptogenesis, facilitate the formation of neural networks, and influence synaptic plasticity underlying learning, memory, and disease progression. Thus, we employ strong and weak astrocyte effect models on $A\beta$ dynamics to explore the biological mechanisms within the central nervous system. In this regard, we analyze ADNI data for $A\beta$ concentration and fit it to the developed stochastic models using the ABC technique, allowing us to refine and validate the model based on clinical data. It is expected that the coupled multiscale models developed in this thesis will provide novel insight into disease origin and progression and a better understanding of the key mechanisms underlying the dynamics of the pathological brain