Abstract Introduction: Alzheimer's disease dementia (ADD) has now become a crucial concern for modern society as a result of increased life expectancy. However, it is often difficult for a majority of the population to afford expensive medical imaging tests for accurate diagnosis. As a solution, quantitative analysis of electroencephalography (EEG) that aids in a sufficient description of brain activities can be employed as a cost-effective, safe and objective diagnostic tool. In the presented research, we employed diverse QEEG features at both channel- and source-level to enhance the robustness of our previously established artificial intelligence (AI) model that distinguishes non-ADD (NADD) data from ADD data. Method 594 NADD and 137 ADD subjects’ EEG data were employed for the presented research. artifact-free data were obtained through the application of independent component analysis (ICA) and bad epoch rejection. Absolute and relative power spectra at 19 channels were first computed, followed by the estimation of source-level power spectra through standardized low-resolution brain electromagnetic tomography (s-LORETA). Through further feature engineering, functional brain networks were also obtained. The established channel-level features were transformed into images that spatially allocate absolute and relative spectral powers, which were utilized for the training of deep neural network structures. Moreover, source-level spectral powers and functional brain networks were adopted for the training of a tree-based machine learning algorithm. Prediction probabilities of the established classification models were ensembled through the voting method and returned the final classification result. Results The best classification accuracies of the absolute and relative channel-level spectral power image-based deep neural network models were 85.3% and 86.5% respectively. The tree-based model that has been trained with source-level features resulted in an accuracy of 87.7%. The accuracy of the ensemble model was 88.5%, which demonstrates the compensatory interaction among the models. Conclusions The promising classification results indicate the potential behind EEG-AI models for the analysis of neurodegenerative disorders. Through continuous analysis of several independent QEEG features of varying aspects, we may soon be able to more aptly diagnose several neurological disorders.
Abstract Background Roles for extracellular vesicles (EVs) enriched with micro-RNAs (miRNAs) have been proposed in Alzheimer’s disease (AD) pathogenesis, leading to the discovery of blood miRNAs as AD biomarkers. However, the diagnostic utility of specific miRNAs is not consistent. This study aimed to discover blood miRNAs that are differentially expressed in Korean AD patients, evaluate their clinical performance, and investigate their role in amyloidogenesis. Methods We discovered miRNAs differentially expressed in AD (N = 8) from cognitively normal participants (CN, N = 7) or Parkinson’s disease (PD) patients (N = 8). We evaluated the clinical performance of these miRNAs in plasma of subgroup (N = 99) and in plasma EVs isolated from the total cohort (N = 251). The effects of miRNAs on amyloidogenesis and on the regulation of their target genes were investigated in vitro. Results Among 17 upregulated and one downregulated miRNAs in AD (>twofold), miR-122-5p, miR-210-3p, and miR-590-5p were differentially expressed compared with CN or PD. However, the diagnostic performance of the selected plasma or EV miRNAs in total participants were limited (area under the curve < 0.8). Nevertheless, levels of 3 miRNAs in plasma or plasma EVs of participants who were amyloid positron emission tomography (Aβ-PET) positive were significantly higher than those from the Aβ-PET negative participants (p < .05). The selected miRNAs induced Aβ production (p < .05) through activation of β-cleavage of amyloid precursor protein (CTF-β; p < .01), and downregulated their target genes (ADAM metallopeptidase domain 10, Brain-derived neurotrophic factor, and Jagged canonical notch ligand 1; p < .05), which was further supported by pathway enrichment analysis of target genes of the miRNAs. Conclusion In conclusion, despite of the limited diagnostic utility of selected miRNAs as plasma or plasma EV biomarkers, the discovered miRNAs may play a role in amyloidogenesis during AD onset and progression.
We investigated the demographic, clinical, and neuropsychological characteristics of frontotemporal dementia (FTD) from the Clinical Research Center for Dementia of South Korea (CREDOS)-FTD registry.A total of 200 consecutive patients with FTD recruited from 16 neurological clinics in Korea were evaluated by cognitive and functional assessments, a screening test for aphasia, behavioral questionnaires, motor assessments, and brain MRI or PET.In our registry, 78 patients were classified as having been diagnosed with behavioral-variant FTD (bvFTD), 70 with semantic dementia (SD), 33 with progressive nonfluent aphasia (PNFA), and 8 with motor neuron disease plus syndrome (MND-plus). The patients with language variants of dementia were older than those with bvFTD. There were no differences in sex ratio, duration of illness, or level of education among the four subgroups. Overall, the patients with bvFTD showed a significantly better performance in cognitive tests. A higher frequency of motor symptoms and a lower frequency of behavioral symptoms were found in PNFA than in bvFTD and SD. The Global Language Index was significantly lower in SD than in bvFTD and PNFA. The MND-plus group had a poorer performance than all the others in all cognitive domains.The neuropsychological, behavioral, motor, and language characteristics of the four subtypes are comparable with those from other series. However, the proportion of SD (37.0%), which was similar to that of bvFTD (41.3%), was higher in our registry than in other series.
Aim: Donepezil has not been evaluated in Korean patients with Alzheimer's disease (AD) for up to 1 year. The objectives of this study were to evaluate the differential efficacy of donepezil in Korean AD patients with and without concomitant cerebrovascular lesions (CVL). Methods: This study was a 48-week open-label trial of donepezil in patients with probable AD of mild to moderate severity. CVL were evaluated through magnetic resonance imaging (MRI) findings within 3 months. Efficacy analyses were performed for cognitive, behavioral and functional outcome measures. Results: Concomitant CVL were documented in 35 (30.7%) of the patients on MRI. Seventy-nine (69.3%) of the patients were considered not to have concomitant CVL. The mean Mini-Mental State Examination scores of both patients with and without CVL showed improvement at each evaluation. However, there was no statistical difference in improvement between the groups. Conclusion: The presence of CVL should not deter clinicians from treating AD with donepezil. Geriatr Gerontol Int 2011; 11: 90–97.
Cholinesterase inhibitors or memantine are being used for increasingly long periods of time, even inpatients with extremely severe Alzheimer's disease. However, there has been little previous study of the outcomes associated with discontinuingthese medications. The primary aim ofthis study was to evaluate the clinical effect of discontinuation of antidementia medication in extremely severe stage AD patients receiving longer-term antidementia medications and to develop consensus criteria for discontinuing medications The subjects were 52 inpatients who had been diagnosed with AD according to the Diagnostic and Statistical Manual of Mental Disorders IV (DSM-IV) and taking with fixed dosage of donepzil or memantine past two months. They were randomized to the discontinuation or the control groups. The primary outcome measures were Clinical Global Impression of change (CGI-C), Baylor profound mental status examination (BPMSE). Behavioral psychological symptoms of dementia (BPSD) were assessed using the Cohen-Mansfield Agitation Inventory (CMAI) and the Neuropsychiatric Inventory (NPI) Medical complications, morbidity and mortality were also assessed. There were no significant differences in CGI-C between the discontinuation and the control groups. However, there was the tendency of maintaining cognitive functions measured by BPMSE in the control group. Furthermore, the remedication of antidementia medication due to aggravated BPSD occurred in three of the discontinuation group. The results of this study suggest that the discontinuation of antidementia medication in with extremely severe AD patients may affect the clinical status of the patients.
Mild cognitive impairment (MCI) is a heterogeneous disorder which refers to the transitional state between the cognitive changes of normal aging and very early dementia. The most common clinical feature of MCI is impairment of episodic memory so that named amnestic MCI. A few studies have been reported that verbal episodic memory closely correlated with left hippocampus, but not yet established neuroanatomocal differences between verbal and visual episodic memory. The aim of this study is to identify the structural changes measured by voxel-based morphometry (VBM) in correlation to verbal and visual memory deficits in amnestic MCI. 20 participants with MCI and 12 elderly control subjects with unimpaired memory participated in this study. MCI patients divided to two groups according to patterns of memory deficit; Group I (decreased verbal memory), Group II (decreased visual memory) and Group III (decreased visual and verbal memory). Elderly normal control subjects belonged to control group(CN). All subjects were interviewed, taken neurological exams and brain magnetic resonance imaging (MRI), detailed neuropsychological tests. Seoul verbal learning test (S-VLT) and Rey figure complex test (RFCT) were administrated to estimate for verbal and visual memory deficit separately. The 1.5-T brain MRI was performed in all subjects. We estimated difference of gray matter density by VBM among groups I, II and III then analyzed by using stastical parametric mapping (SPM). Significant brain atrophy that showed a correlation with decreased verbal memory (group I
This study attempted to investigate the effects of perception of professionalism on job satisfaction and job engagement against cosmetology instructors. The goal is to enhance the efficiency of human resources management by increasing job satisfaction and job engagement. For this, an online questionnaire survey was performed against cosmetology instructors from across the country from May 1 to Jun 4, 2020 (33 days), and a total of 424 copies were used for final analysis. The collected data were analyzed by frequency analysis, factor analysis, correlation analysis and multiple regression analysis, using SPSS 23.0, and the results found the followings: First, according to analysis of correlations among perception of professionalism, job satisfaction and job engagement, all sub-factors of the perception of professionalism revealed a statistically significant correlation with job satisfaction and job engagement factors. In addition, job satisfaction and job engagement factors were correlated to each other with statistical significance. Second, in terms of the influence of perception of professionalism on job satisfaction, all sub-factors of perception of professionalism had an effect on teaching profession consciousness and development. Third, regarding the influence of perception of professionalism on job engagement, ‘social status and competence’, ‘social service’, ‘systematic instruction’ and ‘code of ethics’ affected all sub-factors of job engagement. Fourth, concerning the effects of job satisfaction on job engagement, ‘innovation’, ‘autonomy’ and ‘teaching profession consciousness’ had an influence on ‘devotion’ and ‘commitment’. All sub-factors of job satisfaction affected ‘vitality’. It is anticipated that the study results would help cosmetology instructors build self-confidence through perception of professionalism and provide basic data for high-quality educational services by enhancing job satisfaction and engagement.
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