Purpose The objective of this study is to investigate the hippocampal neurodegeneration and its associated aberrant functions in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients using simultaneous PET/MRI. Methods Forty-two cognitively normal controls (NC), 38 MCI, and 22 AD patients were enrolled in this study. All subjects underwent 18 F-FDG PET/functional MRI (fMRI) and high-resolution T1-weighted MRI scans on a hybrid GE Signa PET/ MRI scanner. Neurodegeneration in hippocampus and its subregions was quantified by regional gray matter volume and 18 F-FDG standardized uptake value ratio (SUVR) relative to cerebellum. An iterative reblurred Van Cittert iteration method was used for voxelwise partial volume correction on 18 F-FDG PET images. Regional gray matter volume was estimated from voxel-based morphometric analysis with MRI. fMRI data were analyzed after slice time correction and head motion correction using statistical parametric mapping (SPM12) with DPARSF toolbox. The regions of interest including hippocampus, cornu ammonis (CA1), CA2/3/dentate gyrus (DG), and subiculum were defined in the standard MNI space. Results Patient groups had reduced SUVR, gray matter volume, and functional connectivity compared to NC in CA1, CA2/3/ DG, and subiculum (AD < MCI < NC). There was a linear correlation between the left CA2/3DG gray matter volume and 18 F-FDG SUVR in AD patients (P < 0.001, r = 0.737). Significant correlation was also found between left CA2/3/DG-superior medial frontal gyrus functional connectivity and left CA2/3/DG hypometabolism in patients with AD. The functional connectivity of right CA1-precuneus in patients with MCI and right subiculum-superior frontal gyrus in patients with AD was positively correlated with mini mental status examination scores (P < 0.05). Conclusion Our findings demonstrate that the associations existed at subregional hippocampal level between the functional connectivity measured by fMRI and neurodegeneration measured by structural MRI and 18 F-FDG PET. Our results may provide a basis for precision neuroimaging of hippocampus in AD.
Background: Vascular factors contributing to cerebral hypoperfusion are implicated in the risk of developing Alzheimer's disease (AD). Purpose: To investigate the time-shift mapping created time-shift value of the brain by resting-state functional magnetic resonance imaging (rs-fMRI), and to determine the differences in time-shift value among AD, mild cognitive impairment (MCI), and normal control (NC) groups to better understand the disease. Study Type: Prospective. Subjects: Twenty-four AD, 24 MCI, and 24 age-matched NC participants. Field Strength/Sequence: T 2 *-weighted single-shot echo-planar imaging sequence was performed at 3T. In addition, a T 1 -weighted fast spoiled gradient-echo sequence was acquired for coregistration. Assessment: The brain time-shift value was determined from rs-fMRI-based blood oxygenation level-dependent (BOLD) signal in the three groups by time-shift mapping. The perfusion patterns were also investigated in the NC group. Statistical Tests: One-way analysis of variance and chi-squared tests were used to compare demographic information. The normalized time-shift maps were analyzed in a second-level test using SPM8. All analyses were evaluated with a significance level of P < 0.05 after false discovery rate (FDR) correction. Results: The time-shift maps obtained from rs-fMRI are consistent with the cerebral blood supply atlas. Compared with NC, both MCI and AD groups had less early perfusion arrival areas among the whole brain. In the delayed time-shift value for the AD group, the areas were located in the bilateral precuneus, the sensory-motor cortex in the left hemisphere, and the bilateral calcarine sulcus, which were different from the MCI group (both P < 0.05, FDR corrected). Data Conclusion: The time-shift mapping method could detect perfusion deficits in AD and MCI noninvasively. The perfusion deficits detected by rs-fMRI may provide new insight for understanding the mechanism of neurodegeneration. Level of Evidence: 2 Technical Efficacy: Stage 3
DFT investigations were employed to explore the complete reaction mechanism of the nickel‐catalyzed [3+2+2] cocyclization of ethyl cyclopropylideneacetate and alkynes. The lowest‐energy pathway involves the formation of a π complex between the methylenecyclopropane moiety and the nickel atom and occurs through a sequence of ring‐opening and ring‐closing reactions with C–C bond formation as the rate‐determining step. The crucial conversion of nickelacycloheptadiene to an eight‐membered nickelacycle was suggested to happen in a stepwise mechanism instead of the previously proposed cyclopropenyl–butenyl rearrangement.
Recent evidence suggests that the cerebellum is related to motor and non-motor cognitive functions, and that several coupled cerebro-cerebellar networks exist, including links with the limbic network. Since several limbic structures are affected by Alzheimer pathology, even in the preclinical stages of Alzheimer’s disease (AD), we aimed to investigate the cerebral limbic network activity from the perspective of the cerebellum. Twenty patients with mild cognitive impairment (MCI), 18 patients with AD, and 26 healthy controls (HC) were recruited to acquire Resting-state functional MRI (rs-fMRI). We used seed-based approach to construct the cerebro-cerebellar limbic network. Two-sample t-tests were carried out to explore the differences of the cerebellar limbic network connectivity. The first result, a sub-scale network including the bilateral posterior part of the orbitofrontal cortex (POFC) extending to the anterior insular cortex (AIC) and left inferior parietal lobule (L-IPL), showed greater functional connectivity in MCI than in HC and less functional connectivity in AD than in MCI. The location of this sub-scale network was in accordance with components of the ventral attention network. Second, there was decreased functional connectivity to the right mid-cingulate cortex (MCC) in the AD and MCI patient groups relative to the HC group. As the cerebellum is not compromised by Alzheimer pathology in the prodromal stage of AD, this pattern indicates that the sub-scale ventral attention network may play a pivotal role in functional compensation through the coupled cerebro-cerebellar limbic network in MCI, and the cerebellum may be a key node in the modulation of social cognition.
Background: Alzheimer’s disease (AD) is a progressive neurodegenerative disease characterized by cognitive decline and memory impairment. Amnestic mild cognitive impairment (aMCI) is the intermediate stage between normal cognitive aging and early dementia caused by AD. It can be challenging to differentiate aMCI patients from healthy controls (HC) and mild AD patients. Objective: To validate whether the combination of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) and diffusion tensor imaging (DTI) will improve classification performance compared with that based on a single modality. Methods: A total of thirty patients with AD, sixty patients with aMCI, and fifty healthy controls were included. AD was diagnosed according to the National Institute of Neurological and Communicative Diseases and Stroke/Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA) criteria for probable. aMCI diagnosis was based on Petersen’s criteria. The 18F-FDG PET and DTI measures were each used separately or in combination to evaluate sensitivity, specificity, and accuracy for differentiating HC, aMCI, and AD using receiver operating characteristic analysis together with binary logistic regression. The rate of accuracy was based on the area under the curve (AUC). Results: For classifying AD from HC, we achieve an AUC of 0.96 when combining two modalities of biomarkers and 0.93 when using 18F-FDG PET individually. For classifying aMCI from HC, we achieve an AUC of 0.79 and 0.76 using the best individual modality of biomarkers. Conclusion: Our results show that the combination of two modalities improves classification performance, compared with that using any individual modality.
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