On the impact of age, gender and educational level on cognitive function in Alzheimer's disease: A quantitative approach.

BACKGROUND: The Mini-Mental State Examination (MMSE) test is a brief and useful tool widely utilized to measure dementia severity. The effects of education, age and gender on the total MMSE scores are less well-understood. Also, there are few studies about cognitive domains involvement in Alzheimer's disease and the effects of demographic factors on it. The aim of this study is to assess the relationship between seven areas of cognitive function in the MMSE test with age, gender and education level. METHODS: In this study, 182 patients with Alzheimer (125 women and 57 men) were evaluated. We investigated the impact of age, sex and education on total score of MMSE and each areas of cognitive function. The results were analyzed by MATLAB software. RESULTS: The most cognitive domain that was impaired in the MMSE test was orientation to time. Moreover, the most involved cognitive areas based on age, gender and educational level were recall, orientation to place and language, respectively. CONCLUSION: We found that there were meaningful correlations between the demographic factors and subsets of the MMSE score.

A systematic review of EEG source localization techniques and their applications on diagnosis of brain abnormalities.

In recent years, multiple noninvasive imaging modalities have been used to develop a better understanding of the human brain functionality, including positron emission tomography, single-photon emission computed tomography, and functional magnetic resonance imaging, all of which provide brain images with millimeter spatial resolutions. Despite good spatial resolution, time resolution of these methods are poor and values are about seconds. Scalp electroencephalography recordings can be used to perform the inverse problem in order to specify the location of the dominant sources of the brain activity. In this paper, EEG source localization method, diagnosis of brain abnormalities using common EEG source localization methods, investigating the effect of the head model on EEG source imaging results have been studied. In this review we present enough evidence that provides motivation for consideration in the future research using EEG source localization methods.

Correction to: ABCA7 and EphA1 Genes Polymorphisms in Late-Onset Alzheimer's Disease.

The original version of this article unfortunately contained a mistake in the Authorgroup section. Author Azra Delpak's given name was misspelled as "Azar".

ABCA7 and EphA1 Genes Polymorphisms in Late-Onset Alzheimer's Disease.

Large-scale genome-wide studies have revealed the role of several genes and their respective single-nucleotide polymorphisms (SNPs) in the pathophysiology of late-onset Alzheimer's disease (LOAD). Here, the frequencies of ABCA7 SNPs rs3764650 and rs4147929 and EphA1 SNP rs11771145 were assessed and compared in LOAD patients and healthy subjects. In a case-control study, 110 patients with LOAD (case) and 88 healthy unrelated age- and gender-matched individuals (control), both from Azeri descent, were enrolled. DNA was extracted from blood samples using the salting out method, and the genotyping was performed by RFLP-PCR for rs3764650, rs4147929, and rs11771145 polymorphisms. Electrophoresis was carried out on agarose gel. Sequencing was utilized for confirmation of the results. No differences were found in the frequencies of ABCA7 SNP rs3764650 and EphA1 SNP rs11771145 between healthy subjects and LOAD patients. However, a significant difference was revealed in the frequencies of AA (p = 0.042, OR = 0.150; 95%CI = 0.005-1.410) and GG (p = 0.009, OR = 1.716; 95%CI = 0.918-3.218) genotypes of ABCA7 SNP rs4147929 between the mentioned groups. This study showed that ABCA7 SNP rs4147929 might be a predisposing factor for LOAD. However, such an association was not found between ABCA7 SNP rs3764650 as well as EphA1 SNP rs11771145 and LOAD. These results must be confirmed in other ethnic groups.