ObjectiveTo investigate the quality of life of family caregivers of patients with Alzheimer's disease (AD) and to explore the related factors. MethodsTwenty family caregivers of patients with Alzheimer's disease were surveyed with short form 36 health survey questionnaire between October 2013 and August 2014. ResultsThe subjects who were over 60 years old had lower scores in the dimensions of physical functioning, role limitations due to physical problem and role limitations due to emotional problem than those below 60 years old. Female subjects scored better than male subjects in the dimension of vitality. The sons and daughters had higher scores than the wives and husbands in the dimensions of physical functioning, role limitations due to physical problem and role limitations due to emotional problem. The subjects whose patients had medical insurance scored better than those whose patients with no insurance. The differences above were all statistically significant. The scores of caregivers with senior middle school edudation or above were higher than the caregivers with lower education level in the dimensions of mental health, vitality and general health perceptions. ConclusionThe quality of life of the family members of AD patients is obviously affected by many factors. It is very important to implement planned, targeted, reasonable and effective interventions to enhance the quality of life of these people.
Wavelet entropy is a quantitative index to describe the complexity of signals. Continuous wavelet transform method was employed to analyze the spontaneous electroencephalogram (EEG) signals of mild, moderate and severe Alzheimer's disease (AD) patients and normal elderly control people in this study. Wavelet power spectrums of EEG signals were calculated based on wavelet coefficients. Wavelet entropies of mild, moderate and severe AD patients were compared with those of normal controls. The correlation analysis between wavelet entropy and MMSE score was carried out. There existed significant difference on wavelet entropy among mild, moderate, severe AD patients and normal controls (P<0.01). Group comparisons showed that wavelet entropy for mild, moderate, severe AD patients was significantly lower than that for normal controls, which was related to the narrow distribution of their wavelet power spectrums. The statistical difference was significant (P<0.05). Further studies showed that the wavelet entropy of EEG and the MMSE score were significantly correlated (r=0.601-0.799, P<0.01). Wavelet entropy is a quantitative indicator describing the complexity of EEG signals. Wavelet entropy is likely to be an electrophysiological index for AD diagnosis and severity assessment.
It is generally considered that various regulatory activities between genes are contained in the gene expression datasets. Therefore, the underlying gene regulatory relationship and the biologically useful information can be found by modeling the gene regulatory network from the gene expression data. In our study, two unsupervised matrix factorization methods, independent component analysis (ICA) and nonnegative matrix factorization (NMF), were proposed to identify significant genes and model the regulatory network using the microarray gene expression data of Alzheimer's disease (AD). By bio-molecular analyzing of the pathways, the differences between ICA and NMF have been explored and the fact, which the inflammatory reaction is one of the main pathological mechanisms of AD, is also emphasized. It was demonstrated that our study gave a novel and valuable method for the research of early detection and pathological mechanism, biomarkers' findings of AD.
We in the present research proposed a classification method that applied infomax independent component analysis (ICA) to respectively extract single modality features of structural magnetic resonance imaging (sMRI) and positron emission tomography (PET). And then we combined these two features by using a method of weight combination. We found that the present method was able to improve the accurate diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Compared AD to healthy controls (HC): the study achieved a classification accuracy of 93.75%, with a sensitivity of 100% and a specificity of 87.64%. Compared MCI to HC: classification accuracy was 89.35%, with a sensitivity of 81.85% and a specificity of 99.36%. The experimental results showed that the bi-modality method performed better than the individual modality in comparison to classification accuracy.
With the intensified aging problem, the study of age-related diseases is becoming more and more significant. Alzheimer's disease is a kind of dementia, with senile plaques and neurofibrillary tangles as the main pathological features, and has become one of the major diseases that endanger the health of the elderly. This review is concentrated on the research of the early assessment of Alzheimer's disease. The current situation of early diagnosis of the disease is analyzed, and a prospect of the future development of early assessment means of the disease is also made in the paper.
Alzheimer's disease (AD) is the most common type of dementia and a neurodegenerative disease with progressive cognitive dysfunction as the main feature. How to identify the early changes of cognitive dysfunction and give appropriate treatments is of great significance to delay the onset of dementia. Some other researches have shown that AD is associated with abnormal changes of brain networks. To study human brain functional connectivity characteristics in AD, 16 channels electroencephalogram (EEG) were recorded under resting and eyes-closed condition in 15 AD patients and 15 subjects in the control group. The synchronization likelihood of the full-band and alpha-band (8-13 Hz) data were evaluated, which resulted in the synchronization likelihood coefficient matrices. Considering a threshold T, the matrices were converted into binary graphs. Then the graphs of two groups were measured by topological parameters including the clustering coefficient and global efficiency. The results showed that the global efficiency of the network in full-band EEG was significantly smaller in AD group for the values of T=0.06 and T=0.07, but there was no statistically significant difference in the clustering coefficients between the two groups for the values of T (0.05-0.07). However, the clustering coefficient and global efficiency were significantly lower in AD patients at alpha-band for the same threshold range than those of subjects in the control group. It suggests that there may be decreases of the brain connectivity strength in AD patients at alpha-band of the resting-state EEG. This study provides a support for quantifying functional brain state of AD from the brain network perspective.
ObjectiveTo systematically review the correlation between apolipoprotein E (ApoE) polymorphism and sporadic Alzheimer's disease (SAD) in Chinese population. MethodsThe case-control studies about the relationship between ApoE polymorphism and SAD in Chinese population were electronically retrieved in PubMed, EMbase, CBM, The Cochrane Library (Issue 8, 2013), CNKI, VIP, and WanFang Data from the date of their establishment to August 2013. Literature screening according to the inclusion and exclusion criteria, data extraction and methodological quality assessment of the included stuides were completed by two reviewers independently. Meta-analysis was then conducted using Stata 12.0 software. ResultsA total of 50 case-control studies invovling 3 396 cases and 4 917 controls were finally included. The results of meta-analysis showed that, in Chinese, the risk of SAD was 2.89 times higher in population with allele ε4 than in population with allele ε3 (OR=2.89, 95%CI 2.61 to 3.19, P < 0.001); 7.24 times higher in those with ε4/ε4 genotype than in those with ε3/ε3 genotype (OR=7.24, 95%CI 5.11 to 10.24, P < 0.001); 2.90 times higher in ε3/ε4 genotype than in ε3/ε3 genotype (OR=2.90, 95%CI 2.56 to 3.29, P < 0.001); 2.11 times higher in ε2/ε4 genotype than in ε3/ε3 genotype (OR=2.11, 95%CI 1.64 to 2.72, P < 0.001); and no statistic significance was found in the risk of SAD compared ε2/ε3, ε2/ε2 genotypes and ε2 allele with ε3/ε3 genotype and ε3 allele. ConclusionFor Chinese population, ApoE allele ε4 is significantly associated with the onset of SAD, and genotype ε4/ε4 is a high risk factor of SAD. While allele ε2 is not associated with the onset of SAD. Since a great deal of current studies failed to conduct stratified analysis, it is suggested to further conduct relevant relevant studies according to clinical classification of SAD and patients' characteristics.
ObjectiveTo systematically review the relationship between Cadmium (Cd) level and Alzheimer's disease (AD). MethodWe searched PubMed, EMbase, CNKI, WanFang Data and CBM databases from inception to December 2014 to collect case-control studies about the relationship between Cd level and AD. Two reviewers screened literature, extracted data and evaluated the risk of bias of included studies, and then meta-analysis was performed by using RevMan 5.3 software. ResultsA total of 11 studies were included, among them 8 studies were included into final meta-analysis. Three studies including 154 patients and 141 controls reported the relationship of serum Cd concentrations and AD, and the result of meta-analysis showed that the higher serum Cd level was found in the AD group than the control group (SMD=0.36, 95%CI 0.12 to 0.59, P=0.003). Six studies including 358 patients and 423 controls reported the relationship of blood Cd concentrations and AD, and the result of meta-analysis showed that there was no significant difference of blood Cd levels between both groups (SMD=0.35, 95%CI -0.14 to 0.84, P=0.16). ConclusionSerum Cd concentrations may be associated with AD, but blood Cd concentrations not. Due to the limitation of quality and quantity of the included studies, more high quality studies are needed to verify the above conclusion.
This study aims to explore the diagnosis in patients with Alzheimer's disease (AD) based on magnetic resonance (MR) images, and to compare the differences of bilateral hippocampus in classification and recognition. MR images were obtained from 25 AD patients and 25 normal controls (NC) respectively. Three-dimensional texture features were extracted from bilateral hippocampus of each subject. The texture features that existed significant differences between AD and NC were used as the features in a classification procedure. Back propagation (BP) neural network model was built to classify AD patients from healthy controls. The classification accuracy of three methods, which were principal components analysis, linear discriminant analysis and non-linear discriminant analysis, was obtained and compared. The correlations between bilateral hippocampal texture parameters and Mini-Mental State Examination (MMSE) scores were calculated. The classification accuracy of nonlinear discriminant analysis with a neural network model was the highest, and the classification accuracy of right hippocampus was higher than that of the left. The bilateral hippocampal texture features were correlated to MMSE scores, and the relative of right hippocampus was higher than that of the left. The neural network model with three-dimensional texture features could recognize AD patients and NC, and right hippocampus might be more helpful to AD diagnosis.
Objective To observe the changes of retinal nerve fiber layer (RNFL) thickness in patients with Alzheimer's disease (AD). Methods Twenty eyes of 40 patients with mild and (or) moderate AD confirmed by clinical examination (AD group) were included in the study. There were 11 males and 9 females with an average age of (72.75±8.25) years. Age and gender-matched normal 20 objectives were in the normal control group. Among them, there were 11 males and 9 females with a mean age of (71.05±7.08) years. There was no significant difference in gender composition, age and intraocular pressure between the two groups (P＞0.05). There were significant differences in visual acuity, cup disc ratio and mini-mental state examination score (P＜0.05). All eyes underwent high-resolution optical coherence tomography (OCT) examination. With a diameter of 3.4 mm and a center on the center of the optic disc, circular fast scans on optic disc were performed to obtain an average disc RNFL thickness, signal threshold ＞6. Computer image analysis system was used to measure the RNFL thickness from superior, inferior, temporal and nasal quadrants, and the average RNFL thickness. The changes of RNFL thickness between the two groups and between different eyes of the same group were compared. Results Compared with the normal control group, the average (t=5.591), superior (t=8.169, 8.053) and inferior (t=12.596, 11.377) thickness of RNFL in both eyes in AD group were thinner, the differences were significant (P＜0.05); the temporal (t=1.966, 0.838）and nasal (t=2.071, 0.916) thickness of RNFL in both eyes of AD group were thinner, but the difference was not statistically significant (P＞0.05). There was no significant difference of the mean and different quadrant RNFL thickness between different eyes in AD group and normal control group (AD group: t=0.097, 0.821, 0.059, 0.020, 0.116; normal control group: t=0.791, 1.938, 1.806, 2.058, 1.005; P＞0.05). Conclusion The RNFL thickness around the optic disc in AD patients is thinner; This occurs first in superior and inferior quadrants of the optic disc.