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- All Subjects: Alzheimer's Disease
- All Subjects: Psychobiology
- Creators: Bimonte-Nelson, Heather A.
Description
Each year, millions of aging women will experience menopause, a transition from reproductive capability to reproductive senescence. In women, this transition is characterized by depleted ovarian follicles, declines in levels of sex hormones, and a dysregulation of gonadotrophin feedback loops. Consequently, menopause is accompanied by hot flashes, urogenital atrophy, cognitive decline, and other symptoms that reduce quality of life. To ameliorate these negative consequences, estrogen-containing hormone therapy is prescribed. Findings from clinical and pre-clinical research studies suggest that menopausal hormone therapies can benefit memory and associated neural substrates. However, findings are variable, with some studies reporting null or even detrimental cognitive and neurobiological effects of these therapies. Thus, at present, treatment options for optimal cognitive and brain health outcomes in menopausal women are limited. As such, elucidating factors that influence the cognitive and neurobiological effects of menopausal hormone therapy represents an important need relevant to every aging woman. To this end, work in this dissertation has supported the hypothesis that multiple factors, including post-treatment circulating estrogen levels, experimental handling, type of estrogen treatment, and estrogen receptor activity, can impact the realization of cognitive benefits with Premarin hormone therapy. We found that the dose-dependent working memory benefits of subcutaneous Premarin administration were potentially regulated by the ratios of circulating estrogens present following treatment (Chapter 2). When we administered Premarin orally, it impaired memory (Chapter 3). Follow-up studies revealed that this impairment was likely due to the handling associated with treatment administration and the task difficulty of the memory measurement used (Chapters 3 and 4). Further, we demonstrated that the unique cognitive impacts of estrogens that become increased in circulation following Premarin treatments, such as estrone (Chapter 5), and their interactions with the estrogen receptors (Chapter 6), may influence the realization of hormone therapy-induced cognitive benefits. Future directions include assessing the mnemonic effects of: 1) individual biologically relevant estrogens and 2) clinically-used bioidentical hormone therapy combinations of estrogens. Taken together, information gathered from these studies can inform the development of novel hormone therapies in which these parameters are optimized.
ContributorsEngler-Chiurazzi, Elizabeth (Author) / Bimonte-Nelson, Heather A. (Thesis advisor) / Sanabria, Federico (Committee member) / Olive, Michael F (Committee member) / Hoffman, Steven (Committee member) / Arizona State University (Publisher)
Created2013
Description
Cognitive function declines with normal age and disease states, such as Alzheimer's disease (AD). Loss of ovarian hormones at menopause has been shown to exacerbate age-related memory decline and may be related to the increased risk of AD in women versus men. Some studies show that hormone therapy (HT) can have beneficial effects on cognition in normal aging and AD, but increasing evidence suggests that the most commonly used HT formulation is not ideal. Work in this dissertation used the surgically menopausal rat to evaluate the cognitive effects and mechanisms of progestogens proscribed to women. I also translated these questions to the clinic, evaluating whether history of HT use impacts hippocampal and entorhinal cortex volumes assessed via imaging, and cognition, in menopausal women. Further, this dissertation investigates how sex impacts responsiveness to dietary interventions in a mouse model of AD. Results indicate that the most commonly used progestogen component of HT, medroxyprogesterone acetate (MPA), impairs cognition in the middle-aged and aged surgically menopausal rat. Further, MPA is the sole hormone component of the contraceptive Depo Provera, and my research indicates that MPA administered to young-adult rats leads to long lasting cognitive impairments, evident at middle age. Natural progesterone has been gaining increasing popularity as an alternate option to MPA for HT; however, my findings suggest that progesterone also impairs cognition in the middle-aged and aged surgically menopausal rat, and that the mechanism may be through increased GABAergic activation. This dissertation identified two less commonly used progestogens, norethindrone acetate and levonorgestrel, as potential HTs that could improve cognition in the surgically menopausal rat. Parameters guiding divergent effects on cognition were discovered. In women, prior HT use was associated with larger hippocampal and entorhinal cortex volumes, as well as a modest verbal memory enhancement. Finally, in a model of AD, sex impacts responsiveness to a dietary cognitive intervention, with benefits seen in male, but not female, transgenic mice. These findings have clinical implications, especially since women are at higher risk for AD diagnosis. Together, it is my hope that this information adds to the overarching goal of optimizing cognitive aging in women.
ContributorsBraden, Brittany Blair (Author) / Bimonte-Nelson, Heather A. (Thesis advisor) / Neisewander, Janet L (Committee member) / Conrad, Cheryl D. (Committee member) / Baxter, Leslie C (Committee member) / Arizona State University (Publisher)
Created2012
Description
Chronic restraint stress impairs hippocampal-mediated spatial learning and memory, which improves following a post-stress recovery period. Here, we investigated whether brain derived neurotrophic factor (BDNF), a protein important for hippocampal function, would alter the recovery from chronic stress-induced spatial memory deficits. Adult male Sprague-Dawley rats were infused into the hippocampus with adeno- associated viral vectors containing the coding sequence for short interfering (si)RNA directed against BDNF or a scrambled sequence (Scr), with both containing the coding information for green fluorescent protein to aid in anatomical localization. Rats were then chronically restrained (wire mesh, 6h/d/21d) and assessed for spatial learning and memory using a radial arm water maze (RAWM) either immediately after stressor cessation (Str-Imm) or following a 21-day post-stress recovery period (Str-Rec). All groups learned the RAWM task similarly, but differed on the memory retention trial. Rats in the Str-Imm group, regardless of viral vector contents, committed more errors in the spatial reference memory domain than did non-stressed controls. Importantly, the typical improvement in spatial memory following recovery from chronic stress was blocked with the siRNA against BDNF, as Str-Rec-siRNA performed worse on the RAWM compared to the non-stressed controls or Str-Rec-Scr. These effects were specific for the reference memory domain as repeated entry errors that reflect spatial working memory were unaffected by stress condition or viral vector contents. These results demonstrate that hippocampal BDNF is necessary for the recovery from stress-induced hippocampal dependent spatial memory deficits in the reference memory domain.
ContributorsOrtiz, J. Bryce (Author) / Conrad, Cheryl D. (Thesis advisor) / Olive, M. Foster (Committee member) / Taylor, Sara (Committee member) / Bimonte-Nelson, Heather A. (Committee member) / Arizona State University (Publisher)
Created2013
Description
The apolipoprotein E (APOE) e4 genotype is the most prevalent known genetic risk factor for Alzheimer's disease (AD). In this paper, we examined the longitudinal effect of APOE e4 on hippocampal morphometry in Alzheimer's Disease Neuroimaging Initiative (ADNI). Generally, atrophy of hippocampus has more chance occurs in AD patients who carrying the APOE e4 allele than those who are APOE e4 noncarriers. Also, brain structure and function depend on APOE genotype not just for Alzheimer's disease patients but also in health elderly individuals, so APOE genotyping is considered critical in clinical trials of Alzheimer's disease. We used a large sample of elderly participants, with the help of a new automated surface registration system based on surface conformal parameterization with holomorphic 1-forms and surface fluid registration. In this system, we automatically segmented and constructed hippocampal surfaces from MR images at many different time points, such as 6 months, 1- and 2-year follow up. Between the two different hippocampal surfaces, we did the high-order correspondences, using a novel inverse consistent surface fluid registration method. At each time point, using Hotelling's T^2 test, we found significant morphological deformation in APOE e4 carriers relative to noncarriers in the entire cohort as well as in the non-demented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes.
ContributorsLi, Bolun (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Liang, Jianming (Committee member) / Arizona State University (Publisher)
Created2015
Description
Alzheimer's Disease (AD) is the most common form of dementia observed in elderly patients and has significant social-economic impact. There are many initiatives which aim to capture leading causes of AD. Several genetic, imaging, and biochemical markers are being explored to monitor progression of AD and explore treatment and detection options. The primary focus of this thesis is to identify key biomarkers to understand the pathogenesis and prognosis of Alzheimer's Disease. Feature selection is the process of finding a subset of relevant features to develop efficient and robust learning models. It is an active research topic in diverse areas such as computer vision, bioinformatics, information retrieval, chemical informatics, and computational finance. In this work, state of the art feature selection algorithms, such as Student's t-test, Relief-F, Information Gain, Gini Index, Chi-Square, Fisher Kernel Score, Kruskal-Wallis, Minimum Redundancy Maximum Relevance, and Sparse Logistic regression with Stability Selection have been extensively exploited to identify informative features for AD using data from Alzheimer's Disease Neuroimaging Initiative (ADNI). An integrative approach which uses blood plasma protein, Magnetic Resonance Imaging, and psychometric assessment scores biomarkers has been explored. This work also analyzes the techniques to handle unbalanced data and evaluate the efficacy of sampling techniques. Performance of feature selection algorithm is evaluated using the relevance of derived features and the predictive power of the algorithm using Random Forest and Support Vector Machine classifiers. Performance metrics such as Accuracy, Sensitivity and Specificity, and area under the Receiver Operating Characteristic curve (AUC) have been used for evaluation. The feature selection algorithms best suited to analyze AD proteomics data have been proposed. The key biomarkers distinguishing healthy and AD patients, Mild Cognitive Impairment (MCI) converters and non-converters, and healthy and MCI patients have been identified.
ContributorsDubey, Rashmi (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Wu, Tong (Committee member) / Arizona State University (Publisher)
Created2012
Description
The present series of studies examined whether a novel implementation of an
intermittent restraint (IR) chronic stress paradigm could be used to investigate hippocampal-dependent spatial ability in both sexes. In experiments 1 and 2, Sprague- Dawley male rats were used to identify the optimal IR parameters to assess spatial ability. For IR, rats were restrained for 2 or 6hrs/day (IR2, IR6, respectively) for five days and then given two days off, a process that was repeated for three weeks and compared to rats restrained for 6hrs/d for each day (DR6) and non-stressed controls (CON). Spatial memory was tested on the radial arm water maze (RAWM), object placement (OP), novel object recognition (NOR) and Y-maze. The results for the first two experiments revealed that IR6, but not IR2, was effective in impairing spatial memory in male rats and that task order impacted performance. In experiment 3, an extended IR paradigm for six weeks was implemented before spatial memory testing commenced in male and female rats (IR- M, IR-F). Unexpectedly, an extended IR paradigm failed to impair spatial memory in either males or females, suggesting that when extended, the IR paradigm may have become predictable. In experiment 4, an unpredictable IR (UIR) paradigm was implemented, in which restraint duration (30 or 60-min) combined with orbital shaking, time of day, and the days off from UIR were varied. UIR impaired spatial memory in males, but not females. Together with other reports, these findings support the interpretation that chronic stress negatively impairs hippocampal-dependent function in males, but not females, and that females appear to be resilient to spatial memory deficits in the face of chronic stress.
intermittent restraint (IR) chronic stress paradigm could be used to investigate hippocampal-dependent spatial ability in both sexes. In experiments 1 and 2, Sprague- Dawley male rats were used to identify the optimal IR parameters to assess spatial ability. For IR, rats were restrained for 2 or 6hrs/day (IR2, IR6, respectively) for five days and then given two days off, a process that was repeated for three weeks and compared to rats restrained for 6hrs/d for each day (DR6) and non-stressed controls (CON). Spatial memory was tested on the radial arm water maze (RAWM), object placement (OP), novel object recognition (NOR) and Y-maze. The results for the first two experiments revealed that IR6, but not IR2, was effective in impairing spatial memory in male rats and that task order impacted performance. In experiment 3, an extended IR paradigm for six weeks was implemented before spatial memory testing commenced in male and female rats (IR- M, IR-F). Unexpectedly, an extended IR paradigm failed to impair spatial memory in either males or females, suggesting that when extended, the IR paradigm may have become predictable. In experiment 4, an unpredictable IR (UIR) paradigm was implemented, in which restraint duration (30 or 60-min) combined with orbital shaking, time of day, and the days off from UIR were varied. UIR impaired spatial memory in males, but not females. Together with other reports, these findings support the interpretation that chronic stress negatively impairs hippocampal-dependent function in males, but not females, and that females appear to be resilient to spatial memory deficits in the face of chronic stress.
ContributorsPeay, Dylan (Author) / Conrad, Cheryl D. (Thesis advisor) / Bimonte-Nelson, Heather A. (Committee member) / Wynne, Clive (Committee member) / Arizona State University (Publisher)
Created2019
Description
Alzheimer’s disease (AD) is characterized by the degeneration of cholinergic basal forebrain (CBF) neurons in the nucleus basalis of Meynert (nbM), which provides the majority of cholinergic input to the cortical mantle and together form the basocortical cholinergic system. Histone deacetylase (HDAC) dysregulation in the temporal lobe has been associated with neuronal degeneration during AD progression. However, whether HDAC alterations play a role in cortical and cortically-projecting cholinergic nbM neuronal degeneration during AD onset is unknown. In an effort to characterize alterations in the basocortical epigenome semi-quantitative western blotting and immunohistochemistry were utilized to evaluate HDAC and sirtuin (SIRT) levels in individuals that died with a premortem clinical diagnosis of no cognitive impairment (NCI), mild cognitive impairment (MCI), mild/moderate AD (mAD), or severe AD (sAD). In the frontal cortex, immunoblots revealed significant increases in HDAC1 and HDAC3 in MCI and mAD, followed by a decrease in sAD. Cortical HDAC2 levels remained stable across clinical groups. HDAC4 was significantly increased in prodromal and mild AD compared to aged cognitively normal controls. HDAC6 significantly increased during disease progression, while SIRT1 decreased in MCI, mAD, and sAD compared to controls. Basal forebrain levels of HDAC1, 3, 4, 6 and SIRT1 were stable across disease progression, while HDAC2 levels were significantly decreased in sAD. Quantitative immunohistochemistry was used to identify HDAC2 protein levels in individual cholinergic nbM nuclei immunoreactive for the early phosphorylated tau marker AT8, the late-stage apoptotic tau marker TauC3, and Thioflavin-S, a marker of mature neurofibrillary tangles (NFTs). HDAC2 nuclear immunoreactivity was reduced in individual cholinergic nbM neurons across disease stages, and was exacerbated in tangle-bearing cholinergic nbM neurons. HDAC2 nuclear reactivity correlated with multiple cognitive domains and with NFT formation. These findings identify global HDAC and SIRT alterations in the cortex while HDAC2 dysregulation contributes to cholinergic nbM neuronal dysfunction and NFT pathology during the progression of AD.
ContributorsMahady, Laura Jean (Author) / Mufson, Elliott J (Thesis advisor) / Bimonte-Nelson, Heather A. (Thesis advisor) / Coleman, Paul (Committee member) / Bowser, Robert (Committee member) / Arizona State University (Publisher)
Created2018
Description
Alzheimer’s disease (AD), is a chronic neurodegenerative disease that usually starts slowly and gets worse over time. It is the cause of 60% to 70% of cases of dementia. There is growing interest in identifying brain image biomarkers that help evaluate AD risk pre-symptomatically. High-dimensional non-linear pattern classification methods have been applied to structural magnetic resonance images (MRI’s) and used to discriminate between clinical groups in Alzheimers progression. Using Fluorodeoxyglucose (FDG) positron emission tomography (PET) as the pre- ferred imaging modality, this thesis develops two independent machine learning based patch analysis methods and uses them to perform six binary classification experiments across different (AD) diagnostic categories. Specifically, features were extracted and learned using dimensionality reduction and dictionary learning & sparse coding by taking overlapping patches in and around the cerebral cortex and using them as fea- tures. Using AdaBoost as the preferred choice of classifier both methods try to utilize 18F-FDG PET as a biological marker in the early diagnosis of Alzheimer’s . Addi- tional we investigate the involvement of rich demographic features (ApoeE3, ApoeE4 and Functional Activities Questionnaires (FAQ)) in classification. The experimental results on Alzheimer’s Disease Neuroimaging initiative (ADNI) dataset demonstrate the effectiveness of both the proposed systems. The use of 18F-FDG PET may offer a new sensitive biomarker and enrich the brain imaging analysis toolset for studying the diagnosis and prognosis of AD.
ContributorsSrivastava, Anant (Author) / Wang, Yalin (Thesis advisor) / Bansal, Ajay (Thesis advisor) / Liang, Jianming (Committee member) / Arizona State University (Publisher)
Created2017
Description
Post-Traumatic Stress Disorder (PTSD) is characterized by intrusive memories from a traumatic event. Current therapies rarely lead to complete remission. PTSD can be modeled in rodents using chronic stress (creating vulnerable phenotype) combined with fear conditioning (modeling a traumatic experience), resulting in attenuated extinction learning and impaired recall of extinction. Studies typically investigate cognition soon after chronic stress ends; however, as days and weeks pass (“rest” period) some cognitive functions may improve compared to soon after stress. Whether a rest period between chronic stress and fear conditioning/extinction would lead to improvements is unclear. In Chapter 2, male rats were chronically stressed by restraint (6hr/d/21d), a reliable method to produce cognitive changes, or assigned to a non-stressed control group (CON). After chronic stress ended, fear conditioning occurred within a day (STR-IMM), or after three (STR-R3) or six weeks (STR-R6). During the first three extinction trials, differences emerged in fear to the non-shock context: STR-R3/R6 showed significantly less fear to the context than did STR-IMM or CON. Differences were unlikely attributable to generalization or to second-order conditioning. Therefore, a rest period following chronic stress may lead to improved fear extinction and discrimination between the conditioned stimulus and environment. In Chapter 3, the infralimbic cortex (IL) was investigated due to the IL’s importance in fear extinction. Rats were infused with chemogenetics to target IL glutamatergic neurons and then assigned to CON, STR-IMM or STR-R3. During the rest period of STR-R3 and the restraint for STR-IMM, the IL was inhibited using CNO (1mg/kg BW, i.p., daily), which ended before behavioral testing. STR-R3 with IL inhibition failed to demonstrate a tone-shock association as spontaneous recovery was not observed. CON with IL inhibition behaved somewhat like STR-IMM; freezing to the extinction context was enhanced. Consequently, inhibiting IL function during the rest period following chronic stress was particularly disruptive for learning in STR-R3, impaired freezing to a safe context for CON, and had no effect in STR-IMM. These studies show that time since the end of chronic stress (recently ended or with a delay) can interact with IL functioning to modify fear learning and response.
ContributorsJudd, Jessica Michelle (Author) / Conrad, Cheryl D. (Thesis advisor) / Sanabria, Federico (Committee member) / Olive, Michael F (Committee member) / Bimonte-Nelson, Heather A. (Committee member) / Arizona State University (Publisher)
Created2020
Description
Statistical Shape Modeling is widely used to study the morphometrics of deformable objects in computer vision and biomedical studies. There are mainly two viewpoints to understand the shapes. On one hand, the outer surface of the shape can be taken as a two-dimensional embedding in space. On the other hand, the outer surface along with its enclosed internal volume can be taken as a three-dimensional embedding of interests. Most studies focus on the surface-based perspective by leveraging the intrinsic features on the tangent plane. But a two-dimensional model may fail to fully represent the realistic properties of shapes with both intrinsic and extrinsic properties. In this thesis, severalStochastic Partial Differential Equations (SPDEs) are thoroughly investigated and several methods are originated from these SPDEs to try to solve the problem of both two-dimensional and three-dimensional shape analyses. The unique physical meanings of these SPDEs inspired the findings of features, shape descriptors, metrics, and kernels in this series of works. Initially, the data generation of high-dimensional shapes, here, the tetrahedral meshes, is introduced. The cerebral cortex is taken as the study target and an automatic pipeline of generating the gray matter tetrahedral mesh is introduced. Then, a discretized Laplace-Beltrami operator (LBO) and a Hamiltonian operator (HO) in tetrahedral domain with Finite Element Method (FEM) are derived. Two high-dimensional shape descriptors are defined based on the solution of the heat equation and Schrödinger’s equation. Considering the fact that high-dimensional shape models usually contain massive redundancies, and the demands on effective landmarks in many applications, a Gaussian process landmarking on tetrahedral meshes is further studied. A SIWKS-based metric space is used to define a geometry-aware Gaussian process. The study of the periodic potential diffusion process further inspired the idea of a new kernel call the geometry-aware convolutional kernel. A series of Bayesian learning methods are then introduced to tackle the problem of shape retrieval and classification. Experiments of every single item are demonstrated. From the popular SPDE such as the heat equation and Schrödinger’s equation to the general potential diffusion equation and the specific periodic potential diffusion equation, it clearly shows that classical SPDEs play an important role in discovering new features, metrics, shape descriptors and kernels. I hope this thesis could be an example of using interdisciplinary knowledge to solve problems.
ContributorsFan, Yonghui (Author) / Wang, Yalin (Thesis advisor) / Lepore, Natasha (Committee member) / Turaga, Pavan (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2021