Advances in Alzheimer's Disease

Journal Information
ISSN / EISSN : 2169-2459 / 2169-2467
Published by: Scientific Research Publishing, Inc. (10.4236)
Total articles ≅ 104
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William R. Lenderking, Cristina Abel, Ella Brookes, Nashmel Sargalo, Dina Filipenko, Charlie Smith, Rachel Lo
Advances in Alzheimer's Disease, Volume 10, pp 19-32; https://doi.org/10.4236/aad.2021.102002

Abstract:
The current pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), commonly referred to as COVID-19, brings myriad challenges to research conducted among those more susceptible to the virus. According to the United States (US) Centers for Disease Control (CDC), eight out of ten re-ported COVID-19 deaths are among people > 65 years of age and older. Nonetheless, researchers must continue the crucial work of investigating and understanding diseases that affect the elderly. The focus of this white paper is to assess the challenges associated with research within the elderly population with neurocognitive conditions. Specifically, this paper addresses the need for the standardized administration of performance measures (e.g., neurocognitive assessments) among a dementia population while ensuring the physical safety of participants. Consideration is given to the administration of performance measures and the availability and feasibility of administering these measures remotely to a population that may have difficulty using novel technologies. In implementing remote research assessments, it is suggested that researchers fol-low a GAMMA approach by: 1) establishing clear Guidance on remote visit expectations and processes; 2) establishing Appropriate exclusionary criteria in the development of the study design; 3) providing subjects Appropriate study Materials for visual processing; 4) incorporating Multiple data sources in the overall study design (e.g., caregiver input); and 5) Acknowledging that there will be study limitations as researchers use emerging technology with this patient population, and using mitigation strategies for these limitations where possible.
Aligizakis Eftychios, Sivaropoulos Nektarios, Gryllaki Nikoleta
Advances in Alzheimer's Disease, Volume 10, pp 1-18; https://doi.org/10.4236/aad.2021.101001

Abstract:
Aim: The aim of this study is to highlight the effectiveness of music therapy in Alzheimer’s Disease (AD) and their caregivers. Methods: The biennial 2019 to 2020, 32 patients, with AD (ICD-10), were examined, by a research group composed by a Neurologist, a GP and a Music-psychotherapist. All patients were under pharmaceutical care. The patients’ medical record and musical profile was assessed. The answers were provided by the patients themselves or by their tutors. Then, personal or family sessions were organized with the participation of musical instruments. The patients staging and evaluation were made through MMSE. The test was repeated every six months under the Neurologist’s supervision. Finally, 31 totally patients succeeded to complete our intervention and to be estimated. Results: The duration of follow-up of the patients was 30 months. At the beginning and end of the sessions we obtained the following data: In a total of 32 patients with AD, initially 3 patients (9.37%) had Mild AD, 19 patients (59.37%) had Moderate AD, 10 patients (31.25%) severe AD, based on the MMSE evaluation. After 30 months, 11 patients had Mild AD (35.48%), number resulting from the music benefit of cognitive function in patients with moderate AD. 15 patients with Moderate AD (48.38%) were observed, out of the initial 19 (59.37%) patients with Moderate AD, a number attributed to the sum of patients who improved from severe AD and those who were transferred, benefiting from treatment, from Moderate AD disease to Mild AD. Finally 5 patients with severe AD disease were evaluated (16.12%), while before the treatment we had 10 patients (31.25%) with severe AD. Conclusions: Music therapy is a tool to increase the life quality of the participants. The results expected in the treatment of AD are obtained by means of good collaboration among the research team.
Yukinori Okada, Norikazu Ohno, Koji Tanaka
Advances in Alzheimer's Disease, Volume 10, pp 33-45; https://doi.org/10.4236/aad.2021.103003

Abstract:
The objective of the study was to explore the relationship between the indicators of Alzheimer’s disease and dementia with Lewy bodies using the voxel-based specific regional analysis system for Alzheimer’s Disease (VSRAD) advance. Among 36 patients with suspected dementia, patients with Alzheimer’s disease and dementia with Lewy bodies were identified using VSRAD advance from March 1 to October 30, 2019. All patients underwent brain Magnetic Resonance Imaging (MRI). We diagnosed Alzheimer’s disease using Volume of Interest (VOI) in the Medial Temporal Lobe (MTL) atrophy ratio > 2 and dementia with Lewy bodies using both VOI in the MTL atrophy ratio ≤ 2 and gray/white matter atrophy ratio ≥ 0.2. The correlation between the indicators of Alzheimer’s disease and dementia with Lewy bodies was calculated. The number of patients classified as having Alzheimer’s disease and dementia with Lewy bodies was 25 and 11, respectively. In the Alzheimer’s disease group, the correlation coefficient between the extent of gray matter atrophy and the severity of atrophy in the dorsal brainstem gray matter was r = -0.40 (p = 0.045). In dementia with Lewy bodies group, the correlation coefficient between the extent of gray matter atrophy and the severity of atrophy in the dorsal brainstem white matter was r = -0.78 (p < 0.01). Using VSRAD advance, gray matter atrophy and dorsal brainstem grey/white matter atrophy were found to be negatively correlated in Alzheimer’s disease and dementia with Lewy bodies.
Anthony R. White
Advances in Alzheimer's Disease, Volume 10, pp 46-51; https://doi.org/10.4236/aad.2021.103004

Abstract:
Despite many decades of researches and large numbers of clinical trials, there remain no effective treatments for Alzheimer’s disease, a major degenerative ageing brain disorder. The potential treatments have focused on targeting the accumulation of amyloid beta-peptide in the brains of patients, but without success in slowing the disease. Many studies have now identified a large range of pathological changes (i.e. altered immune activity, mitochondrial impairment, abnormal microbiome), and links to the external environment (i.e. associations with infections, the influence of air pollution). While the concept of One Health (which considers links between the environment and human disease) has traditionally been applied to the understanding of the human infectious disease, it is argued here that the One Health approach should be adopted for Alzheimer’s disease. This would provide a far more holistic understanding of the disease, and its relationship to a growing number of exogenous factors, as well as could potentially lead to new treatment options targeted at the confluence of external influences, and internal molecular pathways.
Robert Logan, Sabrina S. Zerbey, Sean J. Miller
Advances in Alzheimer's Disease, Volume 10, pp 53-59; https://doi.org/10.4236/aad.2021.104005

Abstract:
Alzheimer’s disease (AD) is a leading cause of death, yet there is no disease-modifying drug therapy currently available. It is critical to establish a diagnosis of AD before clinical system onset so that drug therapies can start earlier. Unfortunately, this is not the current standard practice. Artificial intelligence (AI) holds tremendous promise for identifying AD related structural changes in brain scan images. This paper discusses the recent applications and potential future directions for AI in AD diagnostics. Annual brain scanning and computer vision-assisted early diagnosis is encouraged, so that disease-modifying drug therapy could begin earlier in the progressive pathology.
Maryam Habadi, Christos P. Tsokos
Advances in Alzheimer's Disease, Volume 09, pp 77-86; https://doi.org/10.4236/aad.2020.94006

Abstract:
As the population ages, Alzheimer’s disease is rapidly increasing, and the diagnosis of the disease is still poorly understood. In comparison to cancer, 90% of patients become aware of their diagnosis, but only 45% of the people with Alzheimer’s are aware. Thus, the need for biomarkers for reliable diagnosis is tremendous to help in finding treatment for this serious disease. Hence, the main aim of this paper is to utilize information from baseline measurements to develop a statistical prediction model using multiple logistic regression to distinguish Alzheimer’s disease patients from cognitively normal individuals. Our optimal predictive model includes six risk factors and two interaction terms and has been evaluated using classification accuracy, sensitivity, specificity values and area under the curve.
Ahmed Shata, Wagdi Elkashef, Manal A. Hamouda, Hanan Eissa
Advances in Alzheimer's Disease, Volume 09, pp 1-19; https://doi.org/10.4236/aad.2020.91001

Abstract:
Alzheimer disease is one of the commonest neurological diseases which is characterized by amyloid plaques accumulation in multiple brain regions. This study investigated the potential neuroprotective effect of artesunate on aluminum induced neurotoxicity vs memantine in rats. 40 male albino Wistar rats were divided randomly into 4 groups as follow: Group 1 negative control, group 2 positive control group induced by ammonium chloride, group 3 rats treated by NH4Cl + artesunate solution, group 4 rats treated by NH4Cl + memantine S.C. spatial Memory and Learning were evaluated using Morris Water Maze (MWM) test. Malondialdehyde (MDA) and reduced glutathione (GSH) levels were measured in cerebral cortex tissue homogenate. Tumor necrosis factor-α (TNFα) and interleukin-1 beta (IL-1β) concentrations were measured in rat cerebral cortex tissue homogenate using rat enzyme linked immunosorbent assay (ELISA) kits. Real-time quantitative reverse transcription-polymerase chain reaction (Real-time qRT-PCR) for Caspase-3, Bcl-2 and iNOS gene expression was measured in rat cerebral cortex. Slices from cerebral cortex were studied by histopathological examination. Artesunate significantly decreased MDA level and inhibited iNOS, caspase and upregulated Bcl-2 gene expression in cerebral cortex. ART increased significantly antioxidant level GSH, and decreased significantly TNF-alpha and IL-B levels. It reduced significantly 1ry retention latency, 2ry retention latency and initial acquisition latency. It also improved brain histopathology and decreased amyloid plaque deposition. ART exerted neuroprotective effect through oxidative stress correction and enhancement of antiapoptotic markers in neuronal cells of the cerebral cortex.
Roya Golestani, Akbar Gharbali, Surena Nazarbaghi
Advances in Alzheimer's Disease, Volume 09, pp 21-32; https://doi.org/10.4236/aad.2020.92002

Abstract:
Introduction: The purpose of this study is to evaluate discriminating power of two texture analysis, linear discriminant analysis and nonlinear discriminant analysis, in classifying atrophy of Alzheimer’s disease and atrophy of aging. Methods: The database included 24 regions of interest of Alzheimer patients and 24 regions of interest of aging people in hippocampus region. Linear discriminant analysis and nonlinear discriminant analysis were used for texture analysis. The first nearest neighbor classifier was applied to features resulting from linear discriminant analysis. Nonlinear discriminant analysis features were classified by using an artificial neural network. The confusion matrix and Receiver Operating Characteristic (ROC) curve analysis were used to examine the performance of texture analysis method. Result: Nonlinear discriminant analysis indicates the best performance for classification of atrophy of Alzheimer’s disease and atrophy of aging. Conclusion: Our result showed computer aided diagnosis has high potential discriminating power in classifying Alzheimer’s disease in early stage.
Brian T. Reiss, Meade C. Eggleston, Arah C. Godbole, Julia A. Marut, Cecelia M. McCann, Jessica A. Cottrell, , Sulie L. Chang
Advances in Alzheimer's Disease, Volume 09, pp 57-75; https://doi.org/10.4236/aad.2020.93005

Kazuhiro Kojima, , Hisanao Izumi, Sei-Ichi Yoshihara, Katsuyuki Oki,
Advances in Alzheimer's Disease, Volume 09, pp 47-56; https://doi.org/10.4236/aad.2020.93004

Abstract:
Alzheimer’s disease (AD) is the common cause of dementia which shows the neuro-pathologies like an accumulation of amyloid-β (Aβ) and degeneration of cholinergic neuron. Olfactory bulbectomized (OBX) mice show some of AD features, so they have been used to research as AD model. Mesenchymal stem cells (MSCs) can differentiate into many kinds of cells, including neuronal cells. In this study, we intranasally administrated the conditioned medium derived from cultured umbilical cord (UC) MSCs. The intranasal administration of the MSCs medium restored the cognitive impairment observed in OBX mice. In addition, the decreased number of choline acetyltransferase-positive cells in the medial septum was restored by the conditioned medium administration. In conclusion, MSCs-derived conditioned medium may have protective effects of cholinergic neurons in the medial septum, thereby rescuing the cognitive impairment of OBX.
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