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Full-Text Articles in Medicine and Health Sciences
Pairwise Correlation Analysis Of The Alzheimer’S Disease Neuroimaging Initiative (Adni) Dataset Reveals Significant Feature Correlation, Erik D. Huckvale, Matthew W. Hodgman, Brianna B. Greenwood, Devorah O. Stucki, Katrisa M. Ward, Mark T. W. Ebbert, John S. K. Kauwe, The Alzheimer’S Disease Neuroimaging Initiative, The Alzheimer’S Disease Metabolomics Consortium, Justin B. Miller
Pairwise Correlation Analysis Of The Alzheimer’S Disease Neuroimaging Initiative (Adni) Dataset Reveals Significant Feature Correlation, Erik D. Huckvale, Matthew W. Hodgman, Brianna B. Greenwood, Devorah O. Stucki, Katrisa M. Ward, Mark T. W. Ebbert, John S. K. Kauwe, The Alzheimer’S Disease Neuroimaging Initiative, The Alzheimer’S Disease Metabolomics Consortium, Justin B. Miller
Sanders-Brown Center on Aging Faculty Publications
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) contains extensive patient measurements (e.g., magnetic resonance imaging [MRI], biometrics, RNA expression, etc.) from Alzheimer’s disease (AD) cases and controls that have recently been used by machine learning algorithms to evaluate AD onset and progression. While using a variety of biomarkers is essential to AD research, highly correlated input features can significantly decrease machine learning model generalizability and performance. Additionally, redundant features unnecessarily increase computational time and resources necessary to train predictive models. Therefore, we used 49,288 biomarkers and 793,600 extracted MRI features to assess feature correlation within the ADNI dataset to determine the …
Broad Kinase Inhibition Mitigates Early Neuronal Dysfunction In Tauopathy, Shon A. Koren, Matthew J. Hamm, Ryan Cloyd, Sarah N. Fontaine, Emad Chishti, Chiara Lanzillotta, Jennifer Rodriguez-Rivera, Alexandria Ingram, Michelle Bell, Sara M. Galvis-Escobar, Nicholas Zulia, Fabio Di Domenico, Duc Duong, Nicholas T. Seyfried, David K. Powell, Moriel Vandsburger, Tal Frolinger, Anika M. S. Hartz, John Koren Iii, Jeffrey M. Axten, Nicholas J. Laping, Jose F. Abisambra
Broad Kinase Inhibition Mitigates Early Neuronal Dysfunction In Tauopathy, Shon A. Koren, Matthew J. Hamm, Ryan Cloyd, Sarah N. Fontaine, Emad Chishti, Chiara Lanzillotta, Jennifer Rodriguez-Rivera, Alexandria Ingram, Michelle Bell, Sara M. Galvis-Escobar, Nicholas Zulia, Fabio Di Domenico, Duc Duong, Nicholas T. Seyfried, David K. Powell, Moriel Vandsburger, Tal Frolinger, Anika M. S. Hartz, John Koren Iii, Jeffrey M. Axten, Nicholas J. Laping, Jose F. Abisambra
Sanders-Brown Center on Aging Faculty Publications
Tauopathies are a group of more than twenty known disorders that involve progressive neurodegeneration, cognitive decline and pathological tau accumulation. Current therapeutic strategies provide only limited, late-stage symptomatic treatment. This is partly due to lack of understanding of the molecular mechanisms linking tau and cellular dysfunction, especially during the early stages of disease progression. In this study, we treated early stage tau transgenic mice with a multi-target kinase inhibitor to identify novel substrates that contribute to cognitive impairment and exhibit therapeutic potential. Drug treatment significantly ameliorated brain atrophy and cognitive function as determined by behavioral testing and a sensitive imaging …
Β-Amyloid And Tau Drive Early Alzheimer's Disease Decline While Glucose Hypometabolism Drives Late Decline, Tyler C. Hammond, Xin Xing, Chris Wang, David Ma, Kwangsik Nho, Paul K. Crane, Fanny Elahi, David A. Ziegler, Gongbo Liang, Qiang Cheng, Lucille M. Yanckello, Nathan Jacobs, Ai-Ling Lin
Β-Amyloid And Tau Drive Early Alzheimer's Disease Decline While Glucose Hypometabolism Drives Late Decline, Tyler C. Hammond, Xin Xing, Chris Wang, David Ma, Kwangsik Nho, Paul K. Crane, Fanny Elahi, David A. Ziegler, Gongbo Liang, Qiang Cheng, Lucille M. Yanckello, Nathan Jacobs, Ai-Ling Lin
Sanders-Brown Center on Aging Faculty Publications
Clinical trials focusing on therapeutic candidates that modify β-amyloid (Aβ) have repeatedly failed to treat Alzheimer’s disease (AD), suggesting that Aβ may not be the optimal target for treating AD. The evaluation of Aβ, tau, and neurodegenerative (A/T/N) biomarkers has been proposed for classifying AD. However, it remains unclear whether disturbances in each arm of the A/T/N framework contribute equally throughout the progression of AD. Here, using the random forest machine learning method to analyze participants in the Alzheimer’s Disease Neuroimaging Initiative dataset, we show that A/T/N biomarkers show varying importance in predicting AD development, with elevated biomarkers of Aβ …
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang
FIU Electronic Theses and Dissertations
Alzheimer’s disease (AD) is the most common form of dementia affecting 10% of the population over the age of 65 and the growing costs in managing AD are estimated to be $259 billion, according to data reported in the 2017 by the Alzheimer's Association. Moreover, with cognitive decline, daily life of the affected persons and their families are severely impacted. Taking advantage of the diagnosis of AD and its prodromal stage of mild cognitive impairment (MCI), an early treatment may help patients preserve the quality of life and slow the progression of the disease, even though the underlying disease cannot …
In Vivo Brainstem Imaging In Alzheimer’S Disease: Potential For Biomarker Development, David J. Braun, Linda J. Van Eldik
In Vivo Brainstem Imaging In Alzheimer’S Disease: Potential For Biomarker Development, David J. Braun, Linda J. Van Eldik
Neuroscience Faculty Publications
The dearth of effective treatments for Alzheimer’s disease (AD) is one of the largest public health issues worldwide, costing hundreds of billions of dollars per year. From a therapeutic standpoint, research efforts to date have met with strikingly little clinical success. One major issue is that trials begin after substantial pathological change has occurred, and it is increasingly clear that the most effective treatment regimens will need to be administered earlier in the disease process. In order to identify individuals within the long preclinical phase of AD who are likely to progress to dementia, improvements are required in biomarker development. …
Neuroimaging Biomarkers Of Mtor Inhibition On Vascular And Metabolic Functions In Aging Brain And Alzheimer’S Disease, Jennifer Lee, Lucille M. Yanckello, David Ma, Jared D. Hoffman, Ishita Parikh, Scott Thalman, Bjoern Bauer, Anika M. S. Hartz, Fahmeed Hyder, Ai-Ling Lin
Neuroimaging Biomarkers Of Mtor Inhibition On Vascular And Metabolic Functions In Aging Brain And Alzheimer’S Disease, Jennifer Lee, Lucille M. Yanckello, David Ma, Jared D. Hoffman, Ishita Parikh, Scott Thalman, Bjoern Bauer, Anika M. S. Hartz, Fahmeed Hyder, Ai-Ling Lin
Pharmacology and Nutritional Sciences Faculty Publications
The mechanistic target of rapamycin (mTOR) is a nutrient sensor of eukaryotic cells. Inhibition of mechanistic mTOR signaling can increase life and health span in various species via interventions that include rapamycin and caloric restriction (CR). In the central nervous system, mTOR inhibition demonstrates neuroprotective patterns in aging and Alzheimer’s disease (AD) by preserving mitochondrial function and reducing amyloid beta retention. However, the effects of mTOR inhibition for in vivo brain physiology remain largely unknown. Here, we review recent findings of in vivo metabolic and vascular measures using non-invasive, multimodal neuroimaging methods in rodent models for brain aging and AD. …
Multimodal Imaging Evidence For Axonal And Myelin Deterioration In Amnestic Mild Cognitive Impairment, Brian T. Gold, Yang Jiang, David K. Powell, Charles D. Smith
Multimodal Imaging Evidence For Axonal And Myelin Deterioration In Amnestic Mild Cognitive Impairment, Brian T. Gold, Yang Jiang, David K. Powell, Charles D. Smith
Neuroscience Faculty Publications
White matter (WM) microstructural declines have been demonstrated in Alzheimer's disease and amnestic mild cognitive impairment (aMCI). However, the pattern of WM microstructural changes in aMCI after controlling for WM atrophy is unknown. Here, we address this issue through joint consideration of aMCI alterations in fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, as well as macrostructural volume in WM and gray matter compartments. Participants were 18 individuals with aMCI and 24 healthy seniors. Voxelwise analyses of diffusion tensor imaging data was carried out using tract-based spatial statistics (TBSS) and voxelwise analyses of high-resolution structural data was conducted using …