40 Hz light flicker stimulation is deemed to hold considerable promise in the treatment of Alzheimer’s disease (AD). However, whether its long-term effect can improve working memory and its related mechanisms remains to be further explored. In this study, 21 adult Wistar rats were randomly divided into the AD light-stimulation group, the AD group and the control group. AD models were established in the first two of these groups, with the light-stimulation group receiving long-term 40 Hz light flicker stimulation. Working memory performance across groups was subsequently evaluated using the T-maze task. To investigate the potential neural mechanisms underlying the effects of 40 Hz light stimulation on working memory, we examined changes in neuronal excitability within the hippocampus (HPC) and medial prefrontal cortex (mPFC), as well as alterations in inter-regional synchronization of neural activity. The findings demonstrated that prolonged 40 Hz light stimulation significantly improved working memory performance in AD model rats. Furthermore, the intervention enhanced the synchronization of neural activity between the hippocampus (HPC) and medial prefrontal cortex (mPFC), as well as the efficiency of information transfer, primarily mediated by theta and low-frequency gamma oscillations. This study provides theoretical support for exploring the mechanisms of 40 Hz light flicker stimulation and its further clinical application in the prevention and treatment of Alzheimer’s disease.
ObjectivesTo systematically review the efficacy and safety of butylphthalide soft capsule with routine treatment for Alzheimer’s disease (AD).MethodsDatabases including CNKI, WanFang Data, VIP, CBM, PubMed, EMbase, and The Cochrane Library were electronically searched from September 2002 to July 2018 to collect randomized controlled trials of butylphthalide soft capsule with routine treatment for Alzheimer’s disease. The trial was screened based on inclusion and exclusion criteria, and the methodological quality of the included trial was assessed. Meta-analysis was then performed by Revman 5.3 software.ResultsA total of 8 studies involving 576 patients were included. The butylphthalide soft capsule group included 283 patients and the control group included 293 patients. The result of meta-analysis showed that butylphthalide soft capsule with routine treatment (Donepezil hydrochloride or Memantine or EGb761) significantly improved the score of mini-mental state examination (MMSE) (MD=3.19, 95% CI 2.69 to 3.69, P<0.001) and clinical efficacy (RR=1.36, 95%CI 1.21 to 1.53, P<0.001). There was no significant difference in number of adverse events between the butylphthalide group and the control group (RR=1.13, 95%CI 0.77 to 1.67, P=0.52).ConclusionsBased on the routine treatment, combining with butylphthalide soft capsule can further facilitate cognitive function of AD and improve clinical efficacy. At the same time, no increase in adverse reactions has been found. However, due to the low quality of the included studies, more high quality randomized controlled trials are required to verify the results.
Objective To generate eukaryotic expression vector of pcDNA3.1-β-site amyloid precursor protein cleaving enzyme (BACE) and obtain its transient expression in COS-7 cells. Methods A 1.5 kb cDNA fragment was amplified from the total RNA of the human neuroblastoma cells by the RT-PCR method and was cloned into the plasmid pcDNA3.1. The vector was identified by the double digestion with restriction enzymes BamHI and XhoI and was sequenced by the Sanger-dideoxy-mediated chain termination. The expression of the BACE gene was detected by immunocytochemistry. Results The results showed that the cDNA fragment included 1.5 kb total coding region. The recombinant eukaryotic cell expression vector of pcDNA3.1-BACE was constructed successfully, and the sequence of insert was identical to the published sequence. The COS-7 cells transfected with the pcDNA3.1BACE plasmid expressed a high level of the BACE protein in the cytoplasm. Conclusion The recombinant plasmid pcDNA3.1-BACE can provide a very useful tool for the research on the cause of Alzheimer’s disease and lay an important foundation for preventing Alzheimer’s disease.
Krüppel-like factor 4 (KLF4) is a member of the sample Kruppel transcription factor protein family, is an evolutionary conservative contain zinc finger transcription factors, involved in regulating many cellular processes, such as cell growth, proliferation, differentiation and invasion, KLF4 expression in a variety of tissues and cells in the body, has widely in many physiological and pathological conditions. Many studies have shown that KLF4 is involved in neurobiological processes such as neuroinflammation, oxidative stress, apoptosis and axon regeneration, and is closely related to a variety of nervous system diseases such as epilepsy, stroke, and Alzheimer’s disease. Now KLF4 in its role in the development of nervous system diseases were reviewed, help to understand the pathogenesis of the disease and clinical treatment for diseases of the nervous system to provide potential targets.
Objective To systematically review the effect of vitamin D (VitD) supplementation on cognitive function in people with cognitive impairment and non-cognitive disorders. MethodsThe PubMed, Web of Science, Cochrane Library, EMbase, CBM, CNKI, WanFang Data and VIP databases were searched to collect randomized controlled trials (RCTs) about the effect of VitD supplementation on cognitive function of patients with cognitive impairment or non-cognitive disorders from inception to March, 2022. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. Meta-analysis was then performed using RevMan 5.4 software. Results A total of 19 articles including 8 684 cases were included. The results of meta-analysis showed that mini-mental state examination (MMSE) score (MD=1.70, 95%CI 1.20 to 2.21, P<0.01), Montreal cognitive assessment (MoCA) score (MD=1.51, 95%CI 1.00 to 2.02, P<0.01), Wechsler Adult Intelligence Scale-Revised (WAIS-RC) score (MD=9.12, 95%CI 7.77 to 10.47, P<0.01) and working memory (SMD=1.87, 95%CI 1.07 to 2.67, P<0.01) in the VitD group of patients with cognitive impairment were all better than those in the control group. However, the overall cognitive function and working memory of the non-cognitive impairment population were not significantly different compared with the control group. In terms of language fluency and language memory, there was no significant difference between the VitD group and the control group. In terms of the executive functions, at the intervention time of> 6 months, the VitD and control groups were statistically significant (SMD=0.15, 95%CI 0.01 to 0.28, P=0.03). Conclusion Current evidence suggests that VitD supplementation can effectively improve the overall cognitive function and working memory of patients with cognitive impairment, and has a positive effect on executive function at an intervention time of >6 months. Due to the limited quality and quantity of the included studies, more high-quality studies are needed to verify the above conclusion.
Objective To evaluate the relationship between genetic polymorphism of ApoE and Alzheimer’s disease in Chinese population. Methods Such databases as PubMed, EBSCO, CNKI, CBM, and WangFang Data were searched from their establishment to December 2010 to collect the literature about the relationship between genetic polymorphism of ApoE and Alzheimer’s disease in Chinese population. RevMan 5.0 was adopted to conduct consistency check and data merging, and to evaluate publication bias. Results ApoEε4 was the risky allele (Plt;0.05) in Chinese population, and its pooled odds ratios and 95%CI was 3.53 (2.49 to 5.00). ApoEε3 was the protective alleles (Plt;0.05) in Chinese population, and its pooled odds ratios and 95%CI was 0.52 (0.40 to 0.68). ApoEε4/ε4, ApoEε4/ε3, and ApoEε4/ε2 were the risky genotypes (all Plt;0.05) in Chinese population, and their pooled odds ratios and 95%CI were 10.17 (4.25 to 24.19), 2.57 (2.04 to 3.25), and 1.94 (1.13 to 3.34), respectively. ApoEε3/ε3 was the protective genotype (Plt;0.05) in Chinese population, and its pooled odds ratios and 95%CI was 0.67 (0.57 to 0.77). Conclusion In Chinese population, some ApoE alleles and genotypes are associated with Alzheimer’s disease.
Caveolin-1 (Cav-1) protein plays a very important role in the central nervous system, and is closely related to Alzheimer’s disease (AD). Through literature review, this article summarizes the present research status of Cav-1 protein in the field of AD from three aspects: the relationship between Cav-1 gene and AD; the relationship of Cav-1 protein with learning and memory; the relationship of Cav-1 protein with amyloid β-protein and Tau protein. And the aim of this paper is to provide a new thought and evidence for exploring the mechanism of AD via Cav-1 protein.
Alzheimer’s disease (AD) is a progressive and irreversible neurodegenerative disease. Neuroimaging based on magnetic resonance imaging (MRI) is one of the most intuitive and reliable methods to perform AD screening and diagnosis. Clinical head MRI detection generates multimodal image data, and to solve the problem of multimodal MRI processing and information fusion, this paper proposes a structural and functional MRI feature extraction and fusion method based on generalized convolutional neural networks (gCNN). The method includes a three-dimensional residual U-shaped network based on hybrid attention mechanism (3D HA-ResUNet) for feature representation and classification for structural MRI, and a U-shaped graph convolutional neural network (U-GCN) for node feature representation and classification of brain functional networks for functional MRI. Based on the fusion of the two types of image features, the optimal feature subset is selected based on discrete binary particle swarm optimization, and the prediction results are output by a machine learning classifier. The validation results of multimodal dataset from the AD Neuroimaging Initiative (ADNI) open-source database show that the proposed models have superior performance in their respective data domains. The gCNN framework combines the advantages of these two models and further improves the performance of the methods using single-modal MRI, improving the classification accuracy and sensitivity by 5.56% and 11.11%, respectively. In conclusion, the gCNN-based multimodal MRI classification method proposed in this paper can provide a technical basis for the auxiliary diagnosis of Alzheimer’s disease.
Objective To investigate the effect of continuous positive airway pressure (CPAP) on sleep disorder and neuropsychological characteristics in patients with early Alzheimer’s disease (AD) combined with obstructive sleep apnea hypopnea syndrome (OSAHS). Methods A total of forty-two early AD patients with OSAHS were randomly divided into a CPAP combined treatment group (20 cases) and a simple medicine treatment group (22 cases). The changes of neurocognitive function were assessed by Montreal Cognitive Assessment (MoCA), Mini-mental State Examination (MMSE) and Hopkins Verbal Learning Test-revised (HVLT). Patient Health Questionnaire-9 (PHQ9) was used to evaluate the depression mood changes. The sleep characteristics and respiratory parameters were evaluated by polysomnography. The changes of the patients’ sleep status were assessed by Epworth Sleepiness Scale (ESS) and Pittsburgh Sleep Quality Index (PSQI). The changes of sleep status, cognitive function and mood in the CPAP combined treatment group were compared before and three months after CPAP treatment, and with the simple medicine treatment group. Results After three months of CPAP treatment, the ESS, PSQI and PHQ9 scores in the CPAP combined treatment group were significantly decreased compared with those before treatment, whereas MoCA, MMSE and HVLT (total scores and recall ) in the CPAP combined treatment group were increased compared with those before treatment (P<0.05). After CPAP treatment, the respiratory parameters apnea hypopnea index in the CPAP combined treatment group was significantly lower than that before treatment (P<0.05), and the minimum blood oxygen saturation was significantly higher than that before treatment (P<0.05). However, the sleep characteristics and parameters did not show statistically significant changes compared with those before treatment (P>0.05). The ESS, PSQI and PHQ9 scores were significantly reduced in the CPAP combined treatment group compared with the simple medicine treatment group (P<0.05), while there was no statistically significant changes of cognitive scores between the two groups (P>0.05). Conclusions The degree of low ventilation and hypoxia is alleviated, and the daytime sleepiness and depression is improved in early AD patients with OSAHS after three-month continuous CPAP treatment. Cognitive function is significantly improved, whereas there is no significant change in sleep structure disorder.
Alzheimer’s disease (AD) is an irreversible neurodegenerative disorder that damages patients’ memory and cognitive abilities. Therefore, the diagnosis of AD holds significant importance. The interactions between regions of interest (ROIs) in the brain often involve multiple areas collaborating in a nonlinear manner. Leveraging these nonlinear higher-order interaction features to their fullest potential contributes to enhancing the accuracy of AD diagnosis. To address this, a framework combining nonlinear higher-order feature extraction and three-dimensional (3D) hypergraph neural networks is proposed for computer-assisted diagnosis of AD. First, a support vector machine regression model based on the radial basis function kernel was trained on ROI data to obtain a base estimator. Then, a recursive feature elimination algorithm based on the base estimator was applied to extract nonlinear higher-order features from functional magnetic resonance imaging (fMRI) data. These features were subsequently constructed into a hypergraph, leveraging the complex interactions captured in the data. Finally, a four-dimensional (4D) spatiotemporal hypergraph convolutional neural network model was constructed based on the fMRI data for classification. Experimental results on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database demonstrated that the proposed framework outperformed the Hyper Graph Convolutional Network (HyperGCN) framework by 8% and traditional two-dimensional (2D) linear feature extraction methods by 12% in the AD/normal control (NC) classification task. In conclusion, this framework demonstrates an improvement in AD classification compared to mainstream deep learning methods, providing valuable evidence for computer-assisted diagnosis of AD.