جستجوی مقالات مرتبط با کلیدواژه "زوال عقل" در نشریات گروه "پزشکی"

Alzheimer’s disease (AD) is the leading cause of dementia, and there is growing evidence that exercise programs may help improve some symptoms of the disease. This study aimed to compare the effects of endurance and resistance training on acetylcholine and interleukin-1 beta levels in AD-model male rats.

Twenty-eight male Wistar rats were selected and randomly assigned to four groups: healthy control, AD control, AD + resistance training, and AD + endurance training. AD was induced using an 8 mg dose of trimethyltin chloride. The endurance training consisted of swimming in water at 30–33°C, five days a week, for sessions gradually increasing from 15 to 60 minutes over 12 weeks. Resistance training involved rats climbing a one-meter ladder with weights attached to their tails, consisting of 26 steps at an 85-degree incline, also performed five days a week for twelve weeks. After the exercise period, blood levels of acetylcholine and interleukin-1 beta were measured using the ELISA method.

The results showed that acetylcholine levels in the AD control group were significantly lower than in both the AD + endurance group and the healthy control group. Following the exercise intervention, interleukin-1 beta levels in the healthy control group were significantly lower than in the AD control, AD + resistance, and AD + endurance groups. However, there was no significant difference in interleukin-1 beta levels between the endurance and resistance training groups.

These findings suggest that exercise may be beneficial in reducing inflammation associated with AD, with endurance training showing slightly greater effectiveness than resistance training in this context. This suggests that specific types of exercise might play a role in managing the inflammatory state of AD, potentially offering therapeutic benefits.

The primary aim of this article is to critically assess and compare conventional diagnostic methods for Alzheimer's disease (AD), with a particular focus on the promising capabilities of biomarkers and brain mapping techniques. As the incidence of AD rises globally, novel diagnostic strategies are needed to improve upon traditional methods, which often lack predictive accuracy and precision. This study provides an in-depth review of advanced diagnostic tools, including Artificial Intelligence (AI) applications (e.g., machine learning and deep learning), brain mapping techniques (e.g., electroencephalography and Magnetic Resonance Imaging), and biomarkers (e.g., tau protein and beta-amyloid), which can be identified through innovative visual and manual techniques. Additionally, the research explores the potential of identifying precursor proteins in the blood of patients with AD before symptom onset, presenting a significant opportunity for early intervention that could greatly impact treatment outcomes.

The findings underscore the potential of combining brain mapping methods with manual analysis to facilitate transformational advancements in the diagnostics of AD. This combined approach enhances the detection of structural and functional brain changes associated with AD, contributing to more accurate and earlier diagnoses. Furthermore, brain-derived proteins are present at significantly higher levels in cerebrospinal fluid than in blood, where they are diluted by abundant plasma proteins, such as albumin and immunoglobulins. This observation raises questions about the reliability of current clinical diagnostic practices and emphasizes the importance of validating new diagnostic markers with AI-based manual techniques against neuropathological standards. Finally, the study concludes that AI, when used in conjunction with cognitive assessments, biomarkers, brain mapping approaches, and molecular testing, can substantially enhance diagnostic accuracy and reliability, which are essential for managing and treating patients with AD effectively.

Early detection and reliable differentiation of the Alzheimer’s diseases from normal aging dementia provide optimal rehabilitation. MRI is a convenient imaging method for interpreting dementia caused by brain atrophy. Visual interpretation of brain MRI for atrophy is a qualitative procedure which un able to discriminate Alzheimer atrophy from aging brain atrophy. In recent years, Quantitative texture analysis of the medical imaging represent important biological information from pixels of the digital imaging for differential diseases discrimination. Quantitative texture analysis of the brain atrophy is not yet available for routine clinical use. The aim of this study is to evaluate performance of the applied automated texture analysis methods in discrimination Alzheimer versus normal aging by brain MRI.

In this approach, a total of 26 brain MRI (13 Alzheimer and 13 normal aging) images were analyzed By MaZda software. About 26 suitable regions of interest (ROI) were selected from hippocampal on MR images. Up to 270 texture features parameters were computed per ROI. The sets of 10 features parameters as a best differential descriptor are selected by applying Fisher and or POE+ACC algorithms. Under two standard / nonstandard states, both sets of features were discriminated by PCA, LDA and NDA. The confuse matrix applied for determination sensitivity, specificity and accuracy of applied texture analysis methods. The ROC cure analysis was used for examining the discrimination performance of the applied texture analysis methods.

In comparison with PCA and LDA, in general, NDA has the best result for discriminating Alzheimer from normal aging dementia with sensitivity 100%, specificity of 100% and accuracy 100%.

our results indicate that the computerize brain atrophy discrimination in MR image can be an auxiliary tool in diagnosing Alzheimer's in early stages.

Alzheimer's disease (AD), a progressive neurodegenerative disease, is the most common type of dementia. Polycystic ovary syndrome (PCOS) is associated with metabolic and hormonal disorders, obesity, inflammation, gut microbiota dysbiosis, and an elevated risk of mood disorders and depression. Therefore, patients with this syndrome may be exposed to cognitive and memory disorders, followed by AD. The aim of this review was to focus on the cognitive function, memory, and the risk of dementia and AD in women with PCOS and to identify the factors affecting the risk of progression to these complications in women with this syndrome. Reviewing the literature on the relationship between PCOS and the occurrence of cognitive and memory disorders showed that several disorders linked with PCOS and some drugs used to treat these patients could positively or negatively affect the risk of the development of cognitive and memory disorders. While some reports have declared positive effects for androgens and oral contraceptive drugs on cognitive function and memory, others have argued that insulin resistance, obesity, inflammation, oxidative stress, gut microbiota dysbiosis, and depression may negatively affect cognitive and memory function in women with PCOS, predisposing them to AD. More studies are needed to estimate the risk of cognitive disorders, memory deficits, and AD in women with PCOS and to identify the factors involved in the development of these disorders. The early identification of PCOS patients at risk of developing these cognitive disorders can help prevent the progression of these conditions and appropriately treat them.

According to a global report, 47 million people are currently living with dementia, and due to the aging population, its prevalence is expected to triple by 2050. In the future, Iran is expected to experience a significant increase in the elderly population. Currently, in Iran, the prevalence of dementia among individuals over 60 years old is 7.9%. Therefore, this group represents a significant population that warrants further research (1). The best understanding and explanation of human experiences come from first-hand sources, specifically from people who have experienced those phenomena. Therefore, reliable research sources place great emphasis on including the voices of these individuals (2). Qualitative research out for its collaborative, inclusive, and flexible structure, enabling the exploration of complex issues, including mixed or ambiguous attitudes (2). It can reveal the profound experiences and core values of people with cognitive impairment that may not emerge in quantitative studies. Additionally, qualitative research excels in vividly portraying these experiences and values (3). Throughout history, people with cognitive impairments have been marginalized from engagement in health and social research, resulting in their voices being inadequately represented in such studies. (2, 4). Instead, their perspectives have been channeled through their legal representatives or guardians, a practice that often entails constraints. These limitations include the inability to accurately predict the patient's decision-making process, the amount and manner of information provided, and the weight of decision-making responsibility placed on them (5). Furthermore, excluding these individuals from the research process can dehumanize them and perpetuate negative stereotypes about people with cognitive disorders. This also contributes to power imbalances (2). Therefore, it is crucial to develop strategies that ensure the safe participation of these individuals in research endeavors. Through these efforts, we can improve our understanding of policy and measures aimed at promoting health and well-being (6).

Dementia is an age-related disease occurring in older people associated with symptoms like cognitive disorders, behavioral disturbance, and memory loss. The common types of dementia include Alzheimer's disease, vascular dementia, Lewy bodies’ disease, and frontotemporal dementia. With the growing body of medicine, there is still an unclear question about dementia pathology due to the multifactorial nature of dementia. One aspect is the damage to the brain white matter, which has attracted attention. Oligodendrocytes (OLs), the essential myelinating cells of the axons in the central nervous system, are one of the pivotal cells in the white matter. According to the literature, either oxidative stress or deposition of unfolded proteins cause OLs damage in dementia. On the other hand, dementia is ameliorated by proliferation and differentiation of the oligodendrocytes precursors (OLP) or preventing these cells from death. Therefore, showing the OLs' structure and function during various types of dementia can open a new window for researchers to conduct further investigations.
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The present study was carried out with the aim of assessing the psychometric properties of “Neuro-psychiatry Unit Cognitive Assessment Tool” (NUCOG) in patients with dementia.

In a descriptive-analytical study, patients presenting to Noor Hospital Neuropsychiatric Clinic and the Neurology Department of Ayatollah Kashani Hospital in Isfahan in autumn 2008 were evaluated and 33 individuals with dementia were selected using convenience sampling. The Mini-Mental State Examination (MMSE) and NUCOG were administered to the patients. Data were analyzed using descriptive statistics, Pearson correlation coefficient, Chi2 test, and Cronbach’s alpha.

Content validity of NUCOG was confirmed. The internal consistency of the NUCOG by Cronbach's alpha was 0.919. The convergent validity of the MMSE and the NUCOG was 0.922 (p<0.001). There was no significant correlation between age and education, and NUCOG total scores.

The Persian version of the NUCOG is a valid and reliable tool for screening patients with dementia in clinical psychiatric settings.