• Journal of Multimedia Information System
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• 제9권1호
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• pp.21-32
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• 2022

Early-stage diagnosis of Alzheimer's Disease (AD) from Cognitively Normal (CN) patients is crucial because treatment at an early stage of AD can prevent further progress in the AD's severity in the future. Recently, computer-aided diagnosis using magnetic resonance image (MRI) has shown better performance in the classification of AD. However, these methods use a traditional machine learning algorithm that requires supervision and uses a combination of many complicated processes. In recent research, the performance of deep neural networks has outperformed the traditional machine learning algorithms. The ability to learn from the data and extract features on its own makes the neural networks less prone to errors. In this paper, a dense neural network is designed for binary classification of Alzheimer's disease. To create a classifier with better results, we studied result of different activation functions in the prediction. We obtained results from 5-folds validations with combinations of different activation functions and compared with each other, and the one with the best validation score is used to classify the test data. In this experiment, features used to train the model are obtained from the ADNI database after processing them using FreeSurfer software. For 5-folds validation, two groups: AD and CN are classified. The proposed DNN obtained better accuracy than the traditional machine learning algorithms and the compared previous studies for AD vs. CN, AD vs. Mild Cognitive Impairment (MCI), and MCI vs. CN classifications, respectively. This neural network is robust and better.

• BMB Reports
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• 제43권10호
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• pp.649-655
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• 2010

Alzheimer's disease (AD) is the most common age-dependent neurodegenerative disorder and shows progressive memory loss and cognitive decline. Intraneuronal filaments composed of aggregated hyperphosphorylated tau protein, called neurofibrillary tangles, along with extracellular accumulations of amyloid $\beta$ protein (A$\beta$), called senile plaques, are known to be the neuropathological hallmarks of AD. In light of recent studies, epigenetic modification has emerged as one of the pathogenic mechanisms of AD. Epigenetic changes encompass an array of molecular modifications to both DNA and chromatin, including transcription factors and cofactors. In this review, we summarize how DNA methylation and changes to DNA chromatin packaging by post-translational histone modification are involved in AD. In addition, we describe the role of SIRTs, histone deacetylases, and the effect of SIRT-modulating drugs on AD. Lastly, we discuss how amyloid precursor protein (APP) intracellular domain (AICD) regulates neuronal transcription. Our understanding of the epigenomes and transcriptomes of AD may warrant future identification of novel biological markers and beneficial therapeutic targets for AD.

• 생물정신의학
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• 제17권4호
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• pp.194-202
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• 2010

Alzheimer's disease(AD) is the most common neurodegenerative disorder and constitutes about two thirds of dementia. Despite a lot of effort to find drugs for AD worldwide, an efficient medicine that can cure AD has not come yet, which is due to the complicated pathogenic pathways and progressively degenerative properties of AD. In its early clinical phase, it is important to find the subtle alterations in synapses responsible for memory because symptoms of AD patients characteristically start with pure impairment of memory. Attempts to find the target synaptic proteins and their pathogenic pathways will be the most powerful alternative strategy for developing AD medicine. Here we review recent progress in deciphering the role of target synaptic proteins related to AD in hippocampal glutamatergic synapses.

• 대한의용생체공학회:의공학회지
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• 제31권1호
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• pp.27-32
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• 2010

Noninvasive detection of patients with probable Alzheimer's disease (AD) is of great importance for assisting a medical doctor's decision for early treatment of AD patients. In the present study, we have extracted quantitative electroencephalogram (qEEG) variables, which can be potentially used to diagnose AD, from resting eyes-closed continuous EEGs of 22 AD patients and 27 age-matched normal control (NC) subjects. We have extracted qEEG variables from mean phase coherence (MPC) and EEG coherence, evaluated for all possible combinations of electrode pairs. Preliminary trials to discriminate the two groups with the extracted qEEG variables demonstrated that the use of MPC as a supplementary or alternative measure for the EEG coherence may enhance the accuracy of noninvasive diagnosis of AD.

• 생물정신의학
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• 제14권1호
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• pp.48-54
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• 2007

Objectives : This study aimed to examine the relationship between behavioral and psychological symptoms of dementia(BPSD) and patient and caregiver QOL in Alzheimer's disease(AD). Methods : Fifty-one AD patients and their caregivers participated. Measures about patients were Neuropsychiatric Inventory(NPI), Korean version of QOL-Alzheimer's Disease(KQOL-AD), Activities of Daily Living(ADL), Clinical Dementia Rating(CDR), and Korean version-Mini Mental State Examination(K-MMSE). Caregiver QOL was assessed with KQOL-AD and General Health Questionnaire/Quality of Life-12(GHQ/QOL-12). Results : Patient QOL-AD on patient ratings was negatively correlated with appetite/eating change and NPI scores. Patient QOL-AD on caregiver ratings was negatively correlated with hallucinations, depression/dysphoria, and NPI scores. Caregiver QOL assessed by the GHQ/QOL-12 was negatively correlated with agitation/aggression, depression/dysphoria, and NPI scores and was negatively correlated with distress related to agitation/aggression, depression/dysphoria, and NPI scores. Conclusion : BPSD of AD patients was associated with low QOL of both patients and caregivers. Thus, interventions of BPSD were needed to improve both patient and caregiver QOL.

• 한국멀티미디어학회논문지
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• 제24권5호
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• pp.667-675
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• 2021

The treatments for symptoms of Alzheimer's disease are being provided and for the early diagnosis several researches are undergoing. In this regard, by using T1-weighted images several classification techniques had been proposed to distinguish among AD, MCI, and Healthy Control (HC) patients. In this paper, we also used some traditional Machine Learning (ML) approaches in order to diagnose the AD. This paper consists of an improvised feature selection method which is used to reduce the model complexity which accounted an issue while utilizing the ML approaches. In our presented work, combination of subcortical and cortical features of 308 subjects of ADNI dataset has been used to diagnose AD using structural magnetic resonance (sMRI) images. Three classification experiments were performed: binary classification. i.e., AD vs eMCI, AD vs lMCI, and AD vs HC. Proposed Feature Selection method consist of a combination of Principal Component Analysis and Recursive Feature Elimination method that has been used to reduce the dimension size and selection of best features simultaneously. Experiment on the dataset demonstrated that SVM is best suited for the AD vs lMCI, AD vs HC, and AD vs eMCI classification with the accuracy of 95.83%, 97.83%, and 97.87% respectively.

• BMB Reports
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• 제53권1호
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• pp.35-46
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• 2020

Despite enduring diverse insults, mitochondria maintain normal functions through mitochondrial quality control. However, the failure of mitochondrial quality control resulting from excess damage and mechanical defects causes mitochondrial dysfunction, leading to various human diseases. Recent studies have reported that mitochondrial defects are found in Alzheimer's disease (AD) and worsen AD symptoms. In AD pathogenesis, mitochondrial dysfunction-driven generation of reactive oxygen species (ROS) and their contribution to neuronal damage has been widely studied. In contrast, studies on mitochondrial dysfunction-associated inflammatory responses have been relatively scarce. Moreover, ROS produced upon failure of mitochondrial quality control may be linked to the inflammatory response and influence the progression of AD. Thus, this review will focus on inflammatory pathways that are associated with and initiated through defective mitochondria and will summarize recent progress on the role of mitochondria-mediated inflammation in AD. We will also discuss how reducing mitochondrial dysfunction-mediated inflammation could affect AD.

• BMB Reports
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• 제52권12호
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• pp.679-688
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• 2019

The decrease of metabolism in the brain has been observed as the important lesions of Alzheimer's disease (AD) from the early stages of diagnosis. The cumulative evidence has reported that the failure of mitochondria, an organelle involved in diverse biological processes as well as energy production, maybe the cause or effect of the pathogenesis of AD. Both amyloid and tau pathologies have an impact upon mitochondria through physical interaction or indirect signaling pathways, resulting in the disruption of mitochondrial function and dynamics which can trigger AD. In addition, mitochondria are involved in different biological processes depending on the specific functions of each cell type in the brain. Thus, it is necessary to understand mitochondrial dysfunction as part of the pathological phenotypes of AD according to each cell type. In this review, we summarize that 1) the effects of AD pathology inducing mitochondrial dysfunction and 2) the contribution of mitochondrial dysfunction in each cell type to AD pathogenesis.

• 대한치매학회지
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• 제16권3호
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• pp.72-77
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• 2017

Background and Purpose Although sleep disturbances are common and considered a major burden for patients with Alzheimer's disease (AD), the fundamental mechanisms underlying the development and maintenance of sleep disturbance in AD patients have yet to be elucidated. The aim of this study was to examine the correlation between regional cerebral blood flow (rCBF) and sleep disturbance in AD patients using technetium-99m hexamethylpropylene amine oxime single-photon emission computed tomography (SPECT). Methods A total of 140 AD patients were included in this cross-sectional study. Seventy patients were assigned to the AD with sleep loss (SL) group and the rest were assigned to the AD without SL group. SL was measured using the sleep subscale of the Neuropsychiatric Inventory. A whole-brain voxel-wise analysis of brain SPECT data was conducted to compare the rCBF between the two groups. Results The two groups did not differ in demographic characteristics, severity of dementia, general cognitive function, and neuropsychiatric symptoms, with the exception of sleep disturbances. The SPECT imaging analysis displayed decreased perfusion in the bilateral inferior frontal gyrus, bilateral temporal pole, and right precentral gyrus in the AD patients with SL group compared with the AD patients without SL group. It also revealed increased perfusion in the right precuneus, right occipital pole, and left middle occipital gyrus in the AD with SL group compared with the AD without SL group. Conclusions The AD patients who experienced sleep disturbance had notably decreased perfusion in the frontal and temporal lobes and increased rCBF in the parietal and occipital regions. The findings of this study suggest that functional alterations in these brain areas may be the underlying neural correlates of sleep disturbance in AD patients.

• 대한의용생체공학회:의공학회지
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• 제44권6호
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• pp.377-383
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• 2023

Purpose: There is increasing attention to the application of transcranial direct current stimulation (tDCS) for enhancing cognitive functions in subjects to aging, mild cognitive impairment (MCI), and Alzheimer's disease (AD). Despite varying treatment outcomes in tDCS which depend on the amount of current reaching the brain, there is no general information on the impacts of anatomical features associated with AD on tDCS-induced electric field. Objective: The objective of this study is to examine how AD-related anatomical variation affects the tDCS-induced electric field using computational modeling. Methods: We collected 180 magnetic resonance images (MRI) of AD patients and healthy controls from a publicly available database (Alzheimer's Disease Neuroimaging Initiative; ADNI), and MRIs were divided into female-AD, male-AD, female-normal, and male-normal groups. For each group, segmented brain volumes (cerebrospinal fluid, gray matter, ventricle, rostral middle frontal (RMF), and hippocampus/amygdala complex) using MRI were measured, and tDCS-induced electric fields were simulated, targeting RMF. Results: For segmented brain volumes, significant sex differences were observed in the gray matter and RMF, and considerable disease differences were found in cerebrospinal fluid, ventricle, and hippocampus/amygdala complex. There were no differences in the tDCS-induced electric field among AD and normal groups; however, higher peak values of electric field were observed in the female group than the male group. Conclusions: Our findings demonstrated the presence of sex and disease differences in segmented brain volumes; however, this pattern differed in tDCS-induced electric field, resulting in significant sex differences only. Further studies, we will adjust the brain stimulation conditions to target the deep brain and examine the effects, because of significant differences in the ventricles and deep brain regions between AD and normal groups.