Icariin ameliorates memory deficits through regulating brain insulin signaling and glucose transporters in 3×Tg-AD mice

Icariin,a major prenylated flavonoid found in Epimedium spp.,is a bioactive constituent of Herba Epimedii and has been shown to exert neuroprotective effects in experimental models of Alzheimer’s disease.In this study,we investigated the neuroprotective mechanism of icariin in an APP/PS1/Tau triple-transgenic mouse model of Alzheimer’s disease.We performed behavioral tests,pathological examination,and western blot assay,and found that memory deficits of the model mice were obviously improved,neuronal and synaptic damage in the cerebral cortex was substantially mitigated,and amyloid-βaccumulation and tau hyperphosphorylation were considerably reduced after 5 months of intragastric administration of icariin at a dose of 60 mg/kg body weight per day.Furthermore,deficits of proteins in the insulin signaling pathway and their phosphorylation levels were significantly reversed,including the insulin receptor,insulin receptor substrate 1,phosphatidylinositol-3-kinase,protein kinase B,and glycogen synthase kinase 3β,and the levels of glucose transporter 1 and 3 were markedly increased.These findings suggest that icariin can improve learning and memory impairments in the mouse model of Alzheimer’s disease by regulating brain insulin signaling and glucose transporters,which lays the foundation for potential clinical application of icariin in the prevention and treatment of Alzheimer’s disease.

Homeostatic regulation of brain functions by endocannabinoid signaling

Humans have been using Cannabis and its extracts for a few thousand years as a medicinal and recreational drug. How- ever, the chemical component in Cannabis sativa, △9-tet- rahydrocannabinol （△9-THC）, an exogenous cannabinoid, remained unknown until it was isolated and identified as the main psychoactive ingredient （Gaoni and Mechoulam, 1964）.

Electromagnetic Fields and Calcium Signaling by the Voltage Dependent Anion Channel

Electromagnetic fields (EMFs) can interact with biological tissues exerting positive as well as negative effects on cell viability, but the underlying sensing and signaling mechanisms are largely unknown. So far in excitable cells EMF exposure was postulated to cause Ca2+ influx through voltage-dependent Ca channels (VDCC) leading to cell activation and an antioxidant response. Upon further activation oxidative stress causing DNA damage or cell death may follow. Here we report collected evidence from literature that voltage dependent anion channels (VDAC) located not only in the outer microsomal membrane but also in the cytoplasmic membrane convert to Ca2+ conducting channels of varying capacities upon subtle changes of the applied EMF even in non-excitable cells like erythrocytes. Thus, VDAC can be targeted by external EMF in both types of membranes to release Ca2+ into the cytosol. The role of frequency, pulse modulation or polarization remains to be investigated in suitable cellular models. VDACs are associated with several other proteins, among which the 18 kDa translocator (TSPO) is of specific interest since it was characterized as the central benzodiazepine receptor in neurons. Exhibiting structural similarities with magnetoreceptors we propose that TSPO could sense the magnetic component of the EMF and thus together with VDAC could trigger physiological as well as pathological cellular responses. Pulsed EMFs in the frequency range of the brain-wave communication network may explain psychic disturbances of electromagnetic hypersensitive persons. An important support is provided from human psychology that states deficits like insomnia, anxiety or depression can be treated with diazepines that indicates apparent connections between the TSPO/VDAC complex and organismic responses to EMF.

Susceptibility-weighted imaging is suitable for evaluating signal strength in different brain regions of a rabbit model of acute hemorrhagic anemia

Acute hemorrhagic anemia can decrease blood flow and oxygen supply to brain, and affect its physiological function. While detecting changes in brain function in patients with acute hemorrhagic anemia is helpful for preventing neurological complications and evaluating therapeutic effects, clinical changes in the nervous systems of these patients have not received much attention. In part, this is because current techniques can only indirectly detect changes in brain function following onset of anemia, which leads to lags between real changes in brain function and their detection.

Enhanced Adaptive Brain-Computer Interface Approach for Intelligent Assistance to Disabled Peoples

Assistive devices for disabled people with the help of Brain-Computer Interaction(BCI)technology are becoming vital bio-medical engineering.People with physical disabilities need some assistive devices to perform their daily tasks.In these devices,higher latency factors need to be addressed appropriately.Therefore,the main goal of this research is to implement a real-time BCI architecture with minimum latency for command actuation.The proposed architecture is capable to communicate between different modules of the system by adopting an automotive,intelligent data processing and classification approach.Neuro-sky mind wave device has been used to transfer the data to our implemented server for command propulsion.Think-Net Convolutional Neural Network(TN-CNN)architecture has been proposed to recognize the brain signals and classify them into six primary mental states for data classification.Data collection and processing are the responsibility of the central integrated server for system load minimization.Testing of implemented architecture and deep learning model shows excellent results.The proposed system integrity level was the minimum data loss and the accurate commands processing mechanism.The training and testing results are 99%and 93%for custom model implementation based on TN-CNN.The proposed real-time architecture is capable of intelligent data processing unit with fewer errors,and it will benefit assistive devices working on the local server and cloud server.

Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals

Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals;these signals can berecorded, processed and classified into different hand movements, which can beused to control other IoT devices. Classification of hand movements will beone step closer to applying these algorithms in real-life situations using EEGheadsets. This paper uses different feature extraction techniques and sophisticatedmachine learning algorithms to classify hand movements from EEG brain signalsto control prosthetic hands for amputated persons. To achieve good classificationaccuracy, denoising and feature extraction of EEG signals is a significant step. Wesaw a considerable increase in all the machine learning models when the movingaverage filter was applied to the raw EEG data. Feature extraction techniques likea fast fourier transform (FFT) and continuous wave transform (CWT) were usedin this study;three types of features were extracted, i.e., FFT Features, CWTCoefficients and CWT scalogram images. We trained and compared differentmachine learning (ML) models like logistic regression, random forest, k-nearestneighbors (KNN), light gradient boosting machine (GBM) and XG boost onFFT and CWT features and deep learning (DL) models like VGG-16, DenseNet201 and ResNet50 trained on CWT scalogram images. XG Boost with FFTfeatures gave the maximum accuracy of 88%.

On Similarities and Differences of Invasive and Non-Invasive Electrical Brain Signals in Brain-Computer Interfacing

We perceive that some Brain-Computer Interface (BCI) researchers believe in totally different origins of invasive and non-invasive electrical BCI signals. Based on available literature we argue, however, that although invasive and non-invasive BCI signals are different, the underlying origin of electrical BCIs signals is the same.

Understanding the link between type 2 diabetes mellitus and Parkinson's disease:role of brain insulin resistance

Type 2 diabetes mellitus and Parkinson's disease are chronic diseases linked to a growing pandemic that affects older adults and causes significant socio-economic burden.Epidemiological data supporting a close relationship between these two aging-related diseases have resulted in the investigation of shared pathophysiological molecular mechanisms.Impaired insulin signaling in the brain has gained increasing attention during the last decade and has been suggested to contribute to the development of Parkinson's disease through the dysregulation of several pathological processes.The contribution of type 2 diabetes mellitus and insulin resistance in neurodegeneration in Parkinson's disease,with emphasis on brain insulin resistance,is extensively discussed in this article and new therapeutic strategies targeting this pathological link are presented and reviewed.

Deregulation of brain insulin signaling in Alzheimer's disease

Contrary to the previous belief that insulin does not act in the brain, studies in the last three decades have demonstrated important roles of insulin and insulin signal transduction in various functions of the central nervous system. Deregulated brain insulin signaling and its role in molecular pathogenesis have recently been reported in Alzheimer＇s disease （AD）. In this article, we review the roles of brain insulin signaling in memory and cognition, the metabolism of amyloid 13 precursor protein, and tau phosphorylation. We further discuss deficiencies of brain insulin signaling and glucose metabolism, their roles in the development of AD, and recent studies that target the brain insulin signaling pathway for the treatment of AD. It is clear now that deregulation of brain insulin signaling plays an important role in the development of sporadic AD. The brain insulin signaling pathway also offers a promising therapeutic target for treating AD and probably other neurodegenerative disorders.

Effect of electroacupuncture on gene expression in calcium signaling pathway in hippocampal cells in mice with cerebral ischemia reperfusion

OBJECTIVE:To observe the regulation of electroacupuncture on gene expression at calcium signaling pathways in mice with cerebral ischemia reperfusion.METHODS:Sixty male, inbred Kunming mice were randomly assigned to three groups:repeated cerebral ischemia reperfusion group(RG, n = 24),sham-operated group(SG, n = 12), and electroacupuncture group(EG, n = 24).Mice in RG and EGgroups were modeled by repeated cerebral ischemia reperfusion surgery, and EG mice were treated with electroacupuncture for 30 min after recovery from anesthesia.Changes in gene expression profile of mice hippocampi were analyzed by global expression profile microarray.Genes that were up-regulated or down-regulated greater than 1.5folds were considered to be biologically meaningful.Real-time quantitative polymerase chain reaction(q-PCR) method was used to verify the expression of selected genes based on the algorithm [2^(ΔΔCt)].RESULTS:Compared with SG mice, 242 genes showed different in expressions in RG mice:107down-regulated and 135 up-regulated.Compared with RG mice, 609 genes showed a difference of expression in EG mice:315 down-regulated and 375up-regulated.Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated two pathways:calcium signaling and long-term potentiation in which 11 differentially expressed genes selected.Six of the 11 genes in the calcium signaling pathway were verified after real-time q-PCR testing.CONCLUSION:Electroacupuncture treatment of cerebral ischemia reperfusion appears to regulate Atp2a2, Cacna1 e, Camk2 a, Gnas, Grm1, Rapgef3 genes in the calcium signaling pathway.

Influence of chronic fluorosis on protein kinase Cβ/ p66shc signal pathway in the brain of rats

Objective To investigate the influence of chronic fluorosis on protein kinase Cβ(PKCβ)p66shc signal pathway in the brain of rats,and reveal the molecular mechanism of brain damage.Methods According to body weight by the random number table method thirty SD rats were divided into three groups of 10 each(half females and half males),the normal control group[less than0.5 mg/L of fluorine(prepared with Na F)in