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RISS 인기검색어
- 검색키워드
- 저자 : Chih-Chiang Chiu (검색결과 2 건)
- 무료
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Trough Melatonin Levels Differ between Early and Late Phases of Alzheimer Disease
Chieh-Hsin Lin,Chih-Chiang Chiu,Hsien-Yuan Lane 대한정신약물학회 2021 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.19 No.1
Objective: Melatonin has been considered to have an essential role in the pathophysiology of Alzheimer’s disease (AD) for its regulatory function on circadian rhythm and interaction with glutamate for the modulation of learning and memory. Previous studies revealed that melatonin levels decreased in patients with AD. However, melatonin supplement didn’t show promising efficacy for AD. This study compared trough melatonin levels among elderly people with different severities of cognitive deficits. Methods: We enrolled 270 elder individuals (consisting four groups: healthy elderly, amnestic mild cognitive impairment [MCI], mild AD, and moderate-severe AD) in the learning cohort. Trough melatonin levels in plasma were measured using ELISA. Cognitive function was evaluated by Clinical Dementia Rating Scale (CDR) and Mini-Mental State Examination (MMSE). An independent testing cohort, also consisting of four groups, was enrolled for ascertainment. Results: In the learning cohort, trough melatonin levels decreased in the MCI group but elevated in the mild and moderate to severe AD groups. Trough melatonin levels were associated with CDR and MMSE in MCI or AD patients significantly. In the testing cohort, the results were similar to those in the learning cohort. Conclusion: This study demonstrated that trough melatonin levels in the peripheral blood were decreased in MCI but increased with the severity of AD. The finding supports the trials indicating that melatonin showed efficacy only in MCI but not in AD. Whether trough melatonin level has potential to be a treatment response biomarker for AD, especially its early phase needs further studies.
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A Hybrid Grey Model to Forecast the Annual Maximum Daily Rainfall
Yong-Jun Lin,Pin-Chan Lee,Kuo-Chen Ma,Chih-Chiang Chiu 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.11
This study proposes a hybrid grey model for forecasting annual maximum daily rainfall in order to determine long-term hydrological system trends. The proposed model uses an integral form of background value to improve accuracy, and applies two residual operators, the Fourier series and the exponential smoothing technique, to correct periodic and stochastic errors. The annual maximum daily rainfall measured by 5 stations around Taiwan are used to validation the proposed model. The performance of the proposed hybrid grey model is compared with those of the autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models. By evaluation of different indicators, it is shown that the proposed model outperforms both compared models. With more precise information, the proposed model will allow government officials and civil engineering-related industries to better prepare for heavy rainfall, averting potential disasters.
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