Alterations in zinc transporter protein-1 (ZnT-1) in the brain of subjects with mild cognitive impairment, early, and late-stage alzheimer’s disease

2005 ◽  
Vol 7 (4) ◽  
pp. 265-271 ◽  
Author(s):  
Mark A. Lovell ◽  
Jennifer L. Smith ◽  
Shuling Xiong ◽  
William R. Markesbery
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Late Stage ◽  
Zinc Transporter ◽  
Transporter Protein ◽  
The Brain

scholarly journals Group-level progressive alterations in brain connectivity patterns revealed by diffusion-tensor brain networks across severity stages in Alzheimer’s disease

2017 ◽  
Author(s):  
J. Rasero ◽  
C. Alonso-Montes ◽  
I. Diez ◽  
L. Olabarrieta-Landa ◽  
L. Remaki ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Disease Severity ◽  
Diffusion Tensor ◽  
Brain Networks ◽  
Stage Ii ◽  
Group Level ◽  
The Brain

AbstractAlzheimer’s disease (AD) is a chronically progressive neurodegenerative disease highly correlated to aging. Whether AD originates by targeting a localized brain area and propagates to the rest of the brain across disease-severity progression is a question with an unknown answer. Here, we aim to provide an answer to this question at the group-level by looking at differences in diffusion-tensor brain networks. In particular, making use of data from Alzheimer's Disease Neuroimaging Initiative (ADNI), four different groups were defined (all of them matched by age, sex and education level): G1 (N1=36, healthy control subjects, Control), G2 (N2=36, early mild cognitive impairment, EMCI), G3 (N3=36, late mild cognitive impairment, LMCI) and G4 (N4=36, AD). Diffusion-tensor brain networks were compared across three disease stages: stage I 3(Control vs EMCI), stage II (Control vs LMCI) and stage III (Control vs AD). The group comparison was performed using the multivariate distance matrix regression analysis, a technique that was born in genomics and was recently proposed to handle brain functional networks, but here applied to diffusion-tensor data. The results were three-fold: First, no significant differences were found in stage I. Second, significant differences were found in stage II in the connectivity pattern of a subnetwork strongly associated to memory function (including part of the hippocampus, amygdala, entorhinal cortex, fusiform gyrus, inferior and middle temporal gyrus, parahippocampal gyrus and temporal pole). Third, a widespread disconnection across the entire AD brain was found in stage III, affecting more strongly the same memory subnetwork appearing in stage II, plus the other new subnetworks,including the default mode network, medial visual network, frontoparietal regions and striatum. Our results are consistent with a scenario where progressive alterations of connectivity arise as the disease severity increases and provide the brain areas possibly involved in such a degenerative process. Further studies applying the same strategy to longitudinal data are needed to fully confirm this scenario.

Multi-Objective Genetic Algorithms to Find Most Relevant Volumes of the Brain Related to Alzheimer's Disease and Mild Cognitive Impairment

2018 ◽  
Vol 28 (09) ◽  
pp. 1850022 ◽  
Author(s):  
Olga Valenzuela ◽  
Xiaoyi Jiang ◽  
Antonio Carrillo ◽  
Ignacio Rojas
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Algorithms ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Support Vector ◽  
Significant Information ◽  
Multi Objective ◽  
3D Dwt ◽  
The Brain

Computer-Aided Diagnosis (CAD) represents a relevant instrument to automatically classify between patients with and without Alzheimer's Disease (AD) using several actual imaging techniques. This study analyzes the optimization of volumes of interest (VOIs) to extract three-dimensional (3D) textures from Magnetic Resonance Image (MRI) in order to diagnose AD, Mild Cognitive Impairment converter (MCIc), Mild Cognitive Impairment nonconverter (MCInc) and Normal subjects. A relevant feature of the proposed approach is the use of 3D features instead of traditional two-dimensional (2D) features, by using 3D discrete wavelet transform (3D-DWT) approach for performing feature extraction from T-1 weighted MRI. Due to the high number of coefficients when applying 3D-DWT to each of the VOIs, a feature selection algorithm based on mutual information is used, as is the minimum Redundancy Maximum Relevance (mRMR) algorithm. Region optimization has been performed in order to discover the most relevant regions (VOIs) in the brain with the use of Multi-Objective Genetic Algorithms, being one of the objectives to be optimize the accuracy of the system. The error index of the system is computed by the confusion matrix obtained by the multi-class support vector machine (SVM) classifier. Principal Component Analysis (PCA) is used with the purpose of reducing the number of features to the classifier. The cohort of subjects used in the study consisted of 296 different patients. A first group of 206 patients was used to optimize VOI selection and another group of 90 independent subjects (that did not belong to the first group) was used to test the solutions yielded by the genetic algorithm. The proposed methodology obtains excellent results in multi-class classification achieving accuracies of 94.4% and also extracting significant information on the location of the most relevant points of the brain. This suggests that the proposed method could aid in the research of other neurodegenerative diseases, improving the accuracy of the diagnosis and finding the most relevant regions of the brain associated with them.

scholarly journals Altered 8-oxoguanine glycosylase in mild cognitive impairment and late-stage Alzheimer's disease brain

2008 ◽  
Vol 45 (6) ◽  
pp. 813-819 ◽  
Author(s):  
Changxing Shao ◽  
Shuling Xiong ◽  
Guo-Min Li ◽  
Liya Gu ◽  
Guogen Mao ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Late Stage

scholarly journals The brain structural and cognitive basis of odor identification deficits in mild cognitive impairment and Alzheimer's disease

BMC Neurology ◽  
2014 ◽  
Vol 14 (1) ◽  
Author(s):  
Grete Kjelvik ◽  
Ingvild Saltvedt ◽  
Linda R White ◽  
Pål Stenumgård ◽  
Olav Sletvold ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Odor Identification ◽  
The Brain

scholarly journals Relation of Plasma Selenium and Lipid Peroxidation End Products in Patients With Alzheimer’s Disease

2017 ◽  
pp. 1049-1056 ◽  
Author(s):  
Z. CHMATALOVA ◽  
M. VYHNALEK ◽  
J. LACZO ◽  
J. HORT ◽  
R. POSPISILOVA ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Radical Reaction ◽  
Free Radical Reaction ◽  
Plasma Selenium ◽  
End Products ◽  
The Brain

Increased oxidative stress in the brain during the course of Alzheimer’s disease (AD) leads to an imbalance of antioxidants and formation of free radical reaction end-products which may be detected in blood as fluorescent lipofuscin-like pigments (LFPs). The aim of this study was to evaluate and compare LFPs with plasma selenium concentrations representing an integral part of the antioxidant system. Plasma samples from subjects with AD dementia (ADD; n=11), mild cognitive impairment (MCI; n=17) and controls (n=12), were collected. The concentration of selenium was measured using atomic absorption spectroscopy. LFPs were analyzed by fluorescence spectroscopy and quantified for different fluorescent maxima and then correlated with plasma selenium. Lower levels of selenium were detected in MCI and ADD patients than in controls (P=0.003 and P=0.049, respectively). Additionally, higher fluorescence intensities of LFPs were observed in MCI patients than in controls in four fluorescence maxima and higher fluorescence intensities were also observed in MCI patients than in ADD patients in three fluorescence maxima, respectively. A negative correlation between selenium concentrations and LFPs fluorescence was observed in the three fluorescence maxima. This is the first study focused on correlation of plasma selenium with specific lipofuscin-like products of oxidative stress in plasma of patients with Alzheimer´s disease and mild cognitive impairment.

P2-180: IDENTIFICATION OF A WIDE VARIETY OF BACTERIA IN THE BRAIN TISSUE OF INDIVIDUALS WITH EITHER MILD COGNITIVE IMPAIRMENT (MCI) OR ALZHEIMER'S DISEASE

2006 ◽  
Vol 14 (7S_Part_13) ◽  
pp. P737-P737
Author(s):  
Garilyn Jentarra ◽  
Ping Chu ◽  
T. Bucky Jones ◽  
Jason Kaufman ◽  
Johana Vallejo ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Brain Tissue ◽  
The Brain
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