Muchová, A.: Antiplatelet activity of alkaloids and its potential use in the Alzheimer's disease therapy. Diploma thesis, Charles University in Prague, Faculty of Pharmacy in Hradec Králové, Department of Pharmaceutical Botany, Hradec Králové, 2020. According to recent studies, the pathophysiology of Alzheimer's disease, as a neurodegenerative disease, has been implicated in platelets and the associated haemostasis disorder, the release of inflammatory cells, which may result in the facilitation of amyloid plaque formation. Alkaloids as alkaline nitrogen compounds, which have many effects on humans or animals. In connection with this issue, researchers are investigating the antiplatelet effect of many structural types of alkaloids. The isoquinoline alkaloids of the families Lauraceae, Annonaceae, Piperaceae, Magnoliaceae and Papaveraceae are perpective for the study. In addition to their antiplatelet effects, they also have an antioxidant and inhibitory effect on acetylcholinesterase, which is also used in Alzheimer's disease therapy. Another promising substance is the pyrrolidinoindoline alkaloid Psm2, which was isolated from the plant Selaginella moellendorffii Hieron. It has an antiplatelet effect higher than the reference substance acetylsalicylic acid and is also associated with a lower risk...

Amyloids are fibrous protein aggregates associated with age-related diseases, such as Alzheimer’s disease and Parkinson’s disease. The role of amyloids in the etiology of neurodegeneration is debatable, but genetic and molecular evidence supports a causative relationship between amyloidogenesis and disease. Amyloidogenic proteins are constitutively expressed throughout the lifespan of an organism, and yet only become pathogenic in certain situations. This led to a hunt to understand how amyloidogenic proteins could be modified in order to become aggregation-prone. One possibility that has garnered attention is phosphorylation, primarily because several amyloid aggregates such as tau and α-synuclein are often highly phosphorylated in disease. However, the contribution of phosphorylation to disease progression remains unclear.While amyloid aggregates are typically described as irreversible and pathogenic, some cells utilize reversible amyloid-like structures that serve important functions. One example is the RNA-binding protein Rim4 which forms amyloid-like assemblies that are essential for translational control during S. cerevisiae meiosis. If Rim4 is unable to translationally repress its mRNA targets, cells mis-segregate chromosomes during meiosis resulting in aneuploid gametes. Importantly, Rim4 amyloid-like assemblies are disassembled in a phosphorylation-dependent manner at meiosis II onset which allows previously repressed transcripts to become translated. In Chapter 1, I describe the significance and complexity of protein phosphorylation as it relates to disease-associated amyloids and why Rim4 is an ideal model for studying this phenomenon. The objective of this thesis is to examine the mechanisms underlying clearance of Rim4 amyloid-like assemblies. The work described in Chapter 2 focuses on identifying co-factors that mediate clearance of amyloid-like assemblies in a physiological setting. I demonstrate that yeast 14-3-3 proteins, Bmh1 and Bmh2, bind to Rim4 assemblies and facilitate their subsequent phosphorylation and timely clearance. Furthermore, distinct 14-3-3 proteins play non-redundant roles in facilitating phosphorylation and clearance of amyloid-like Rim4. In Chapter 3, I explore the mechanism underlying 14-3-3 contribution to Rim4 amyloid-like disassembly. I find that 14-3-3 proteins are critical for the interaction between Rim4 and its primary kinase Ime2, thus facilitating downstream multi-site phosphorylation of Rim4. In Chapter 4, I explore additional roles for 14-3-3 proteins in general protein aggregate homeostasis. I find that 14-3-3 mutants exhibit greater protein aggregate burdens. Additionally, 14-3-3 mutants accumulate ubiquitinated proteins and are sensitized to proteasome mutations, suggesting a role for 14-3-3 proteins in proteasome function. Collectively, the studies described in this thesis support a protective role for 14-3-3 proteins in protein aggregation that may have implications for amyloid biology in human disease.

The dissertation consists of a critical analysis as well as the novel Tigers Born in the Same Year. The critical analysis interrogates the relationship between Asian American subject position in the United States, the history of Asian American literatures, and the conflict between inherited binary narratives and nuanced, specific story-telling. In order to move beyond such narratives as struggling with the label "model minority," wrestling between "Asian" and "American," and being "Asian enough," it is necessary to synthesize these literary and sociocultural inheritances with nuanced, specific lenses. From synthesis may arise a new space, one where rather than alienation and measuring up, there can be a sense of home. Tigers Born in the Same Year seeks language for social reckoning through personal discovery, representing a challenge to established narratives while recognizing the need to explore how they were built, the impacts they have, and what exists in the spaces beyond them. In Tigers Born in the Same Year, when 13-year Minyoung Walsh witnesses the molestation of her sister by their older brother, she must make one of three choices: stay silent, fight back, or shout. Based on these three possibilities, three lives are braided together in the novel. All three Mins must reckon with who they have become and why following the illness and passing of their father. Whether or not the Mins in these lives are ultimately able to find a sense of home will largely depend on how they have been able to reckon with themselves, and on building a selfhood through they can live, grow, and seek the choices that will lead them forward. All the while, a fourth Min wanders in an endless bardo, between lives, seeking that same sense of rest, of wholeness, of knowing she has come to the right end of her path.

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Brain atrophy measurement is increasingly important in studies of neurodegenerative diseases such as Alzheimer’s disease. From this perspective, a regional segmentation framework for magnetic resonance images has recently been developed by the team that I joined for my master thesis. It combines an atlas fusion and a tissue classification. A graph-cuts optimization step is then applied to obtain the final segmentation from the combination probability maps. To begin with neighboring constraints were integrated into the optimization step so as to prevent some labels to be adjacent in accordance with anatomical criteria. They were successfully tested on a restricted list of patient images which previously presented segmentation errors. Secondly, a multigrid tissue classification was implemented in order to compensate for the effects of intensity inhomogeneities. However, the visual observations on a few cases showed little improvement compared to the increased computation time. Consequently another possibility was investigated to modify the classification. An atlas-based classification was implemented and tested both on a small-scale and a large-scale. The efficiency of the proposed method was visually assessed on a few patients, especially regarding the separation between grey and white matter. The process was then applied on a database containing several hundreds patients and the results demonstrated an improved group separation based on grey matter volume, whose reduction is particularly significant with patients suffering from Alzheimer’s Disease. To conclude, several links of the segmentation framework have been upgraded, which promises good results for future regional atrophy studies.

Alzheimer's disease (AD) is the most common form of dementia, afflicting almost 5 million patients in the US, and impacting millions more, financially, physically and emotionally. Coming in as the 6th leading cause of death in the US, and showing no signs of slowing its annually increasing rates, the world is in desperate need of improved understanding of the disease's multifaceted pathogenesis and progression, more accurate forms of detection and diagnosis, and more effective prevention and treatment. While many are focused on the noble pursuit of understanding the genetic contributions to the appearance of the pathological amyloid beta (Aβ)) plaques and tau tangles seen in AD, the majority of cases are not explained by genes or allele risk. Instead environmental, dietary and lifestyle contributors may be the key to understanding, diagnosing and treating this awful disease. Diet especially may impact the body's ability to regulate oxidative stress, which will cause damage within the cell and lead to further dysregulation of iron storage and metabolism. Iron storage is heavily monitored through cellular mechanisms, and the way in which the body reacts involves creation of the Aβ plaques and tau tangles as receptacles for the molecule it has deemed as the cause of the problem, iron. We have aptly named our theory, the Iron Hypothesis, and in the following document will outline the evidence for this hypothesis, and the experiments designed and performed to prove it.First, we aimed to examine the impacts that various treatments would have on a transgenic in-vivo model, examining the cohorts' behavior over several time points. We report a significant difference in the behavioral measures of time, distance, errors and failed trials in the radial arm maze existed between genotype, treatment and sex of the mice. Tissue of the experimental mice was collected, but will be processed and analyzed at a later date.Secondly, we aimed to examine the same cohorts of the in-vivo mouse model for minute anatomical changes that took place over the course of the aforementioned behavioral trials using novel MRI scanning sequences sensitive to the low levels of iron build up. We report significant differences in the UTE scan measures for our western diet treatment at TE's of 1.2ms. Additionally, further investigation and optimization of the protocol may be required to further expand the findings.

The theme of this dissertation is to improve the exploration of patient subgroups with a precision medicine lens, specifically using repeated measures data to evaluate longitudinal trajectories of clinical, biological, and lifestyle measures. Our proposed methodological contributions fall into two branches of statistical methodology: undirected graphical models and functional data analysis. In the first part of this dissertation, our goal was to study longitudinal networks of brain imaging biomarkers and clinical symptoms during the time leading up to manifest Huntington's disease diagnosis among patients with known genetic risk of disease. Understanding the interrelationships between measures may improve our ability to identify patients who are nearing disease onset and who therefore might be ideal patients for clinical trial recruitment. Gaussian graphical models are a powerful approach for network modeling, and several extensions to these models have been developed to estimate time-varying networks. We propose a time-varying Gaussian graphical model specifically for a time scale that is centered on an anchoring event such as disease diagnosis. Our method contains several novel components intended to 1) reduce bias known to stem from 𝑙₁ penalization, and 2) improve temporal smoothness in network edge strength and structure. These novel components include time-varying adaptive lasso weights, as well as a combination of 𝑙₁, 𝑙₂, and 𝑙₀ penalization. We demonstrated via simulation studies that our proposed approach, as well as more computationally efficient subsets of our full proposed approach, have superior performance compared to existing methods. We applied our proposed approach to the PREDICT-HD study and found that the network edges did change with time leading up to and beyond diagnosis, with change points occurring at different times for different edges. For clinical symptoms, bradykinesia became well-connected with symptoms from several other domains. For imaging measures, we observed a loss of connection over time among gray matter regions, white matter regions, and the hippocampus. In the second part of this dissertation, we consider time-varying network models for settings in which data are not all Gaussian. We sought to compare longitudinal clinical symptom networks between patients with neuropathologically-defined Alzheimer's disease (AD) vs. neuropathologically-defined Lewy body dementia (LBD), two common types of dementia which can often be clinically misdiagnosed. Given that the clinical measures of interest were largely non-Gaussian, we examined the literature for undirected graphical models for mixed data types. We then proposed an extension to the existing time-varying mixed graphical model by adding time-varying adaptive lasso weights, modeling time in reverse in order to treat neuropathological diagnoses as baseline covariates. The proposed adaptive lasso extension serves a two-fold purpose: they alleviate well-known bias of 𝑙₁ penalization and they encourage temporal smoothness in edge estimation. We demonstrated the improved performance of our extension in simulations studies. Applying our method to the National Alzheimer's Coordinating Center database, we found that the edge structure surrounding the Wechsler Memory Scale Revised (WMS-R) Logical Memory parts IA (immediate recall) and IIA (delayed recall) may contain important markers for discriminant analysis of AD and LBD populations. In the third part of this dissertation, we explored a methodologically distinct area of research from the first two parts, moving from graphical models to functional data analysis. Our goal was to extract meaningful chronotypes, or phenotypes of circadian rhythms, from activity count data collected from accelerometers. Existing approaches for analyzing diurnal patterns using these data, including the cosinor model and functional principal components analysis, have revealed and quantified population-level diurnal patterns, but considerable subject-level variability remained uncaptured in features such as wake/sleep times and activity intensity. This remaining informative variability could provide a better understanding of chronotypes, or behavioral manifestations of one’s underlying 24-hour rhythm. Curve registration, or alignment, is a technique in functional data analysis that separates "vertical" variability in activity intensity from "horizontal" variability in time-dependent markers like wake and sleep times. We developed a parametric registration framework for 24-hour accelerometric rest-activity profiles that are represented as dichotomized into epoch-level states of activity or rest. Specifically, we estimated subject-specific piecewise linear time-warping functions parametrized with a small set of parameters. We applied this method to data from the Baltimore Longitudinal Study of Aging and illustrated how estimated parameters can give a more flexible quantification of chronotypes compared to traditional approaches.

We have recently established that aberrant alkylacylglycerophosphocholine metabolism results in the increased tissue concentration of platelet activating factors (PAFs) in the temporal cortex of Alzheimer Disease (AD) patients and in TgCRND8 mice over-expressing mutant human amyloid precursor protein. PAF lipids activate a G-protein coupled receptor (PAFR) reported to be expressed by microglia and subsets of neurons in rat. It is not known whether this same expression pattern is recapitulated in mice however, as the expression has only been inferred by use of pharmacological PAFR antagonists, many of which impact on both PAFR-dependent and PAFR-independent signalling pathways. PAFR plays a role in long term potentiation (LTP) induction in rats. PAFR has also been implicated in behavioural indices of spatial learning and memory in rats. Contradictory reports using mice provide ambiguity regarding the role of PAFR in LTP induction in mice. To assess whether PAFR is expressed in murine neurons, I localized PAFR mRNA in wild-type C57BL/6 mice using PAFR KO mice as a negative control. I further showed that the loss of PAFR did not impair learning and memory although this assessment must be considered preliminary as the behavioural test employed was not optimized to detect changes in learning and memory of C57BL/6 mice over time adequately.Finally, I showed that the loss of PAFR in TgCRND8 mouse model of AD had no impact upon Aβ plaque number. My observations suggest that PAFR is restricted to microglial-like cells in mouse hippocampus and as such, it may not play a role in learning and memory.

This study investigated the effect of high-fat diet consumption on Alzheimer's disease-related pathology in the Tg6799 mouse model. We found that high-fat diet attenuates Alzheimer's disease-related pathology and cognitive dysfunction in Tg6799 mice and propose decreased beta-amyloid deposition due to improved autophagic-lysosomal flux as a potential, underlying mechanism.

Indiana University-Purdue University Indianapolis (IUPUI) / Over 5 million older adults have Alzheimer's disease (AD) in the US, and this number is projected to double by 2050. Clinical trials of potential pharmacological treatments for AD have largely shown that once cognitive decline has occurred, targeting AD pathology in the brain does not improve cognition. Therefore, it is likely that the most effective treatments for AD will need to be administered before cognitive symptoms occur, necessitating a biomarker for the early, preclinical stages of AD. Cerebral blood flow (CBF) is a promising early biomarker for AD. CBF is decreased in individuals with AD compared to their normally aging counterparts, and it has been shown that CBF is altered in mild cognitive impairment (MCI) and earlier stages and may occur prior to amyloid or tau aggregation. In addition, CBF can be measured using arterial spin labeled (ASL) MRI, a noninvasive imaging technique that can be safely repeated over time to track prognosis or treatment efficacy. The complex temporal and spatial patterns of altered CBF over the course of AD, as well as the relationships between CBF and AD-specific and -nonspecific factors, will be critical to elucidate in order for CBF to be an effective early biomarker of AD. Here, we begin to characterize the relationships between CBF and risk factors, pathologies, and symptoms of AD. Chapter 1 is a systematic review of published literature that compares CBF in individuals with AD and MCI to CBF in cognitively normal (CN) controls and assesses the relationship between CBF and cognitive function. Chapter 2 reports our original research assessing the relationships between CBF, hypertension, and race/ethnicity in older adults without dementia from the the Indiana Alzheimer’s Disease Research Center (IADRC) and Alzheimer’s Disease Neuroimaging Initiative (ADNI). Chapter 3 reports our original research assessing the relationships between CBF and amyloid beta and tau aggregation measured with PET, as well as whether hypertension or APOEε4 positivity affects these relationships, in older adults without dementia from the IADRC. Chapter 4 reports our original research assessing the relationship between the spatial distribution of tau and subjective memory concerns. / 2023-05-24