Accumulating neuroimaging studies in humans have shown that acupuncture can modulate a widely distributed brain network in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients. Acupuncture at different acupoints could exert different modulatory effects on the brain network. However, whether acupuncture at real or sham acupoints can produce different effects on the brain network in MCI or AD patients remains unclear. Using resting-state fMRI, we reported that acupuncture at Taixi (KI3) induced amplitude of low-frequency fluctuation (ALFF) change of different brain regions in MCI patients from those shown in the healthy controls. In MCI patients, acupuncture at KI3 increased or decreased ALFF in the different regions from those activated by acupuncture in the healthy controls. Acupuncture at the sham acupoint in MCI patients activated the different brain regions from those in healthy controls. Therefore, we concluded that acupuncture displays more significant effect on neuronal activities of the above brain regions in MCI patients than that in healthy controls. Acupuncture at KI3 exhibits different effects on the neuronal activities of the brain regions from acupuncture at sham acupoint, although the difference is only shown at several regions due to the close distance between the above points.
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http://dx.doi.org/10.1155/2015/529675 | DOI Listing |
Eur J Nucl Med Mol Imaging
January 2025
Reina Sofia Alzheimer Center, CIEN Foundation, ISCIII, Madrid, Spain.
Purpose: Imaging biomarkers bear great promise for improving the diagnosis and prognosis of cognitive impairment in Parkinson's disease (PD). We compared the ability of three commonly used neuroimaging modalities to detect cortical changes in PD patients with mild cognitive impairment (PD-MCI) and dementia (PDD).
Methods: 53 cognitively normal PD patients (PD-CN), 32 PD-MCI, and 35 PDD underwent concurrent structural MRI (sMRI), diffusion-weighted MRI (dMRI), and [F]FDG PET.
Alzheimers Dement
January 2025
Department of Neuroscience, Imaging, and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
Introduction: Machine learning (ML) helps diagnose the mild cognitive impairment-Alzheimer's disease (MCI-AD) spectrum. However, ML is fed with data unavailable in standard clinical practice. Thus, we tested a novel multi-step ML approach to predict cognitive worsening.
View Article and Find Full Text PDFSci Rep
January 2025
School of Medicine, Yan'an University, Yan'an, 716000, China.
The study aims to develop and validate an effective model for predicting frailty risk in individuals with mild cognitive impairment (MCI). The cross-sectional analysis employed nationally representative data from CHARLS 2013-2015. The sample was randomly divided into training (70%) and validation sets (30%).
View Article and Find Full Text PDFSci Rep
January 2025
Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, 474-8511, Aichi, Japan.
The prevalence of Alzheimer's disease (AD) is increasing as society ages. The details of AD pathogenesis have not been fully elucidated, and a comprehensive gene expression analysis of the process leading up to the onset of AD would be helpful for understanding the mechanism. We performed an RNA sequencing analysis on a cohort of 1227 Japanese blood samples, representing 424 AD patients, 543 individuals with mild cognitive impairment (MCI), and 260 cognitively normal (CN) individuals.
View Article and Find Full Text PDFIntroduction: Dysphagia and cognitive impairment are prevalent in older individuals. This study aimed to understand the characteristics of dysphagia through fluoroscopy in older adults with mild cognitive impairment (MCI) and dementia.
Methods: A cross-sectional study was conducted at a memory clinic in a tertiary hospital in Mexico City.
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