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Alzheimer Disease: HELP
Articles from Los Alamos
Based on 5 articles published since 2010
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These are the 5 published articles about Alzheimer Disease that originated from Los Alamos during 2010-2020.
 
+ Citations + Abstracts
1 Review MicroRNAs as diagnostic and therapeutic tools for Alzheimer's disease: advances and limitations. 2019

Martinez, Bridget / Peplow, Philip V. ·Department of Molecular & Cellular Biology, University of California, Merced, CA, USA; Department of Medicine, St. Georges University School of Medicine, Grenada; Department of Physics and Engineering, Los Alamos National Laboratory, Los Alamos, NM, USA. · Department of Anatomy, University of Otago, Dunedin, New Zealand. ·Neural Regen Res · Pubmed #30531004.

ABSTRACT: Alzheimer's disease (AD) is the most common age-related, progressive neurodegenerative disease. It is characterized by memory loss and cognitive decline and responsible for most cases of dementia in the elderly. Late-onset or sporadic AD accounts for > 95% of cases, with age at onset > 65 years. Currently there are no drugs or other therapeutic agents available to prevent or delay the progression of AD. The cellular and molecular changes occurring in the brains of individuals with AD include accumulation of β-amyloid peptide and hyperphosphorylated tau protein, decrease of acetylcholine neurotransmitter, inflammation, and oxidative stress. Aggregation of β-amyloid peptide in extracellular plaques and the hyperphosphorylated tau protein in intracellular neurofibrillary tangles are characteristic of AD. A major challenge is identifying molecular biomarkers of the early-stage AD in patients as most studies have been performed with blood or brain tissue samples (postmortem) at late-stage AD. Subjects with mild cognitive impairment almost always have the neuropathologic features of AD with about 50% of mild cognitive impairment patients progressing to AD. They could provide important information about AD pathomechanism and potentially also highlight minimally or noninvasive, easy-to-access biomarkers. MicroRNAs are dysregulated in AD, and may facilitate the early detection of the disease and potentially the continual monitoring of disease progression and allow therapeutic interventions to be evaluated. Four recent reviews have been published of microRNAs in AD, each of which identified areas of weakness or limitations in the reported studies. Importantly, studies in the last three years have shown considerable progress in overcoming some of these limitations and identifying specific microRNAs as biomarkers for AD and mild cognitive impairment. Further large-scale human studies are warranted with less disparity in the study populations, and using an appropriate method to validate the findings.

2 Article Deep residual learning for neuroimaging: An application to predict progression to Alzheimer's disease. 2020

Abrol, Anees / Bhattarai, Manish / Fedorov, Alex / Du, Yuhui / Plis, Sergey / Calhoun, Vince / Anonymous3051200. ·Joint (GSU/GaTech/Emory) Center for Transational Research in Neuroimaging and Data Science, Atlanta, GA, 30303, USA; The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM, 87106, USA; Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, 87131, USA. Electronic address: aabrol@gsu.edu. · Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, 87131, USA; Los Alamos National Laboratory, Los Alamos, NM, 87545, USA. · Joint (GSU/GaTech/Emory) Center for Transational Research in Neuroimaging and Data Science, Atlanta, GA, 30303, USA; The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM, 87106, USA; Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, 87131, USA. · Joint (GSU/GaTech/Emory) Center for Transational Research in Neuroimaging and Data Science, Atlanta, GA, 30303, USA; The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM, 87106, USA; School of Computer and Information Technology, Shanxi University, Taiyuan, China. · Joint (GSU/GaTech/Emory) Center for Transational Research in Neuroimaging and Data Science, Atlanta, GA, 30303, USA; The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM, 87106, USA. ·J Neurosci Methods · Pubmed #32275915.

ABSTRACT: BACKGROUND: The unparalleled performance of deep learning approaches in generic image processing has motivated its extension to neuroimaging data. These approaches learn abstract neuroanatomical and functional brain alterations that could enable exceptional performance in classification of brain disorders, predicting disease progression, and localizing brain abnormalities. NEW METHOD: This work investigates the suitability of a modified form of deep residual neural networks (ResNet) for studying neuroimaging data in the specific application of predicting progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). Prediction was conducted first by training the deep models using MCI individuals only, followed by a domain transfer learning version that additionally trained on AD and controls. We also demonstrate a network occlusion based method to localize abnormalities. RESULTS: The implemented framework captured non-linear features that successfully predicted AD progression and also conformed to the spectrum of various clinical scores. In a repeated cross-validated setup, the learnt predictive models showed highly similar peak activations that corresponded to previous AD reports. COMPARISON WITH EXISTING METHODS: The implemented architecture achieved a significant performance improvement over the classical support vector machine and the stacked autoencoder frameworks (p <  0.005), numerically better than state-of-the-art performance using sMRI data alone (> 7% than the second-best performing method) and within 1% of the state-of-the-art performance considering learning using multiple neuroimaging modalities as well. CONCLUSIONS: The explored frameworks reflected the high potential of deep learning architectures in learning subtle predictive features and utility in critical applications such as predicting and understanding disease progression.

3 Article Membrane-mediated fibrillation and toxicity of the tau hexapeptide PHF6. 2019

Fanni, Adeline M / Vander Zanden, Crystal M / Majewska, Paulina V / Majewski, Jaroslaw / Chi, Eva Y. ·Center for Biomedical Engineering, University of New Mexico, Albuquerque, New Mexico 87131. · Biomedical Engineering Graduate Program, University of New Mexico, Albuquerque, New Mexico 87131. · Department of Chemical and Biological Engineering, University of New Mexico, Albuquerque, New Mexico 87131. · Department of Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545. · Division of Molecular and Cellular Biosciences, National Science Foundation, Alexandria, Virginia 22314. · Center for Biomedical Engineering, University of New Mexico, Albuquerque, New Mexico 87131 evachi@unm.edu. ·J Biol Chem · Pubmed #31439664.

ABSTRACT: The aggregation of the tau protein into neurofibrillary tangles is believed to correlate with cognitive decline in several neurodegenerative disorders, including Alzheimer's disease. Recent studies suggest that tau's interactions with the cell membrane could serve as a toxicity pathway and also enhance fibrillation into paired helical filaments (PHFs). Conformational changes associated with tau-membrane interactions are poorly understood, and their characterization could improve our understanding of tau pathogenicity. In this study, we investigated the molecular level structural changes associated with the interaction of the tau hexapeptide PHF6 with model lipid membranes and characterized the effects of these interactions on membrane stability and peptide fibrillation. We used two PHF6 forms, the aggregation-prone PHF6 with N-terminal acetylation (Ac-PHF6) and the non-aggregation prone PHF6 with a standard N terminus (NH

4 Article Amelioration of Alzheimer's disease pathology and cognitive deficits by immunomodulatory agents in animal models of Alzheimer's disease. 2019

Martinez, Bridget / Peplow, Philip V. ·Department of Molecular & Cellular Biology, University of California, Merced, Merced, CA, USA; Department of Medicine, St. Georges University School of Medicine, Grenada; Department of Physics and Engineering, Los Alamos National Laboratory, Los Alamos, NM, USA. · Department of Anatomy, University of Otago, Dunedin, New Zealand. ·Neural Regen Res · Pubmed #30804241.

ABSTRACT: The most common age-related neurodegenerative disease is Alzheimer's disease (AD) characterized by aggregated amyloid-β (Aβ) peptides in extracellular plaques and aggregated hyperphosphorylated tau protein in intraneuronal neurofibrillary tangles, together with loss of cholinergic neurons, synaptic alterations, and chronic inflammation within the brain. These lead to progressive impairment of cognitive function. There is evidence of innate immune activation in AD with microgliosis. Classically-activated microglia (M1 state) secrete inflammatory and neurotoxic mediators, and peripheral immune cells are recruited to inflammation sites in the brain. The few drugs approved by the US FDA for the treatment of AD improve symptoms but do not change the course of disease progression and may cause some undesirable effects. Translation of active and passive immunotherapy targeting Aβ in AD animal model trials had limited success in clinical trials. Treatment with immunomodulatory/anti-inflammatory agents early in the disease process, while not preventive, is able to inhibit the inflammatory consequences of both Aβ and tau aggregation. The studies described in this review have identified several agents with immunomodulatory properties that alleviated AD pathology and cognitive impairment in animal models of AD. The majority of the animal studies reviewed had used transgenic models of early-onset AD. More effort needs to be given to creat models of late-onset AD. The effects of a combinational therapy involving two or more of the tested pharmaceutical agents, or one of these agents given in conjunction with one of the cell-based therapies, in an aged animal model of AD would warrant investigation.

5 Article Analyzing and Modeling the Kinetics of Amyloid Beta Pores Associated with Alzheimer's Disease Pathology. 2015

Ullah, Ghanim / Demuro, Angelo / Parker, Ian / Pearson, John E. ·Department of Physics, University of South Florida, Tampa, FL 33620, United States of America. · Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA 92697, United States of America. · Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM 87545, United States of America. ·PLoS One · Pubmed #26348728.

ABSTRACT: Amyloid beta (Aβ) oligomers associated with Alzheimer's disease (AD) form Ca2+-permeable plasma membrane pores, leading to a disruption of the otherwise well-controlled intracellular calcium (Ca2+) homeostasis. The resultant up-regulation of intracellular Ca2+ concentration has detrimental implications for memory formation and cell survival. The gating kinetics and Ca2+ permeability of Aβ pores are not well understood. We have used computational modeling in conjunction with the ability of optical patch-clamping for massively parallel imaging of Ca2+ flux through thousands of pores in the cell membrane of Xenopus oocytes to elucidate the kinetic properties of Aβ pores. The fluorescence time-series data from individual pores were idealized and used to develop data-driven Markov chain models for the kinetics of the Aβ pore at different stages of its evolution. Our study provides the first demonstration of developing Markov chain models for ion channel gating that are driven by optical-patch clamp data with the advantage of experiments being performed under close to physiological conditions. Towards the end, we demonstrate the up-regulation of gating of various Ca2+ release channels due to Aβ pores and show that the extent and spatial range of such up-regulation increases as Aβ pores with low open probability and Ca2+ permeability transition into those with high open probability and Ca2+ permeability.