scholarly journals Early Detection of MCI

2020 ◽  
Vol 9 (1) ◽  
pp. 1928-1931
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Learning Algorithm ◽  
Early Stage ◽  
Memory Loss ◽  
Brain Disorder ◽  
Clinical Impairment ◽  
Short Memory ◽  
Last Stage ◽  
The Brain

Dementia is the brain disorder, that effects the mental cognitive function. Dementia has different stages. when the person is in the early stage they have short memory, losing or misplacing things, the person have more memory loss in moderate stage. During last stage patient completely depends on other for everyday activities. MCI has come to be recognized as an intermediate state of clinical impairment where an individual has mild cognitive symptoms but generally continue to function normally in the community. it is important to determine AD at an earlier stage which is Mild Cognitive Impairment (MCI). Toxic changes may start in the brain at the beginning stage of Alzheimer's disease. MRI Images are used to detect disease at the earlies stage. Wavelet Transform is applied on the MRI Images followed by any feature selection. Machine learning algorithm is used to make prediction. This paper goes through all those studies and techniques used by scientists to unravel the progression of Alzheimer's disease.

Circulatory GSK-3β: Blood-Based Biomarker and Therapeutic Target for Alzheimer’s Disease

2021 ◽  
pp. 1-12
Author(s):  
Shiwani Kumari ◽  
Ambica Singh ◽  
Abhinay Kumar Singh ◽  
Yudhishthir Yadav ◽  
Swati Bajpai ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Stage ◽  
Memory Loss ◽  
Amyloid Β ◽  
Clear Understanding ◽  
Dependent Manner ◽  
Brain Disorder ◽  
Gsk 3Β ◽  
Dose Dependent

Background: Alzheimer’s disease (AD) is the progressive brain disorder which degenerates brain cells connection and causes memory loss. Although AD is irreversible, it is not impossible to arrest or slow down the progression of the disease. However, this would only be possible if the disease is diagnosed at an early stage, and early diagnosis requires clear understanding of the pathogenesis at molecular level. Overactivity of GSK-3β and p53 accounts for tau hyperphosphorylation and the formation of amyloid-β plaques. Objective: Here, we explored GSK-3β and p53 as blood-based biomarkers for early detection of AD. Methods: The levels of GSK-3β, p53, and their phosphorylated states were measured using surface plasmon resonance and verified using western blot in serum from AD, mild cognitive impairment (MCI), and geriatric-control (GC) subjects. The neurotoxic SH-SY5Y cell line was treated with antioxidant Emblica Officinalis (EO) for rescue effect. Results: GSK-3β, p53, and their phosphorylated states were significantly over expressed (p >  0.001) in AD and MCI compared to GC and can differentiate AD and MCI from GC. The expression level of GSK-3β and p53 proteins were found to be downregulated in a dose-dependent manner after the treatment with EO in amyloid-b-induced neurotoxic cells. Conclusion: These proteins can serve as potential blood markers for the diagnosis of AD and EO can suppress their level. This work has translational value and clinical utility in the future.

scholarly journals Microglia-Based Sex-Biased Neuropathology in Early-Stage Alzheimer’s Disease Model Mice and the Potential Pharmacologic Efficacy of Dioscin

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3261
Author(s):  
Xiao Liu ◽  
Qian Zhou ◽  
Jia-He Zhang ◽  
Xiaoying Wang ◽  
Xiumei Gao ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Stage ◽  
Disease Model ◽  
Amyloid Β ◽  
Brain Lesions ◽  
Synaptic Dysfunction ◽  
Synaptic Loss ◽  
And Function ◽  
The Brain

Alzheimer’s disease (AD), the most common form of dementia, is characterized by amyloid-β (Aβ) accumulation, microglia-associated neuroinflammation, and synaptic loss. The detailed neuropathologic characteristics in early-stage AD, however, are largely unclear. We evaluated the pathologic brain alterations in young adult App knock-in model AppNL-G-F mice at 3 and 6 months of age, which corresponds to early-stage AD. At 3 months of age, microglia expression in the cortex and hippocampus was significantly decreased. By the age of 6 months, the number and function of the microglia increased, accompanied by progressive amyloid-β deposition, synaptic dysfunction, neuroinflammation, and dysregulation of β-catenin and NF-κB signaling pathways. The neuropathologic changes were more severe in female mice than in male mice. Oral administration of dioscin, a natural product, ameliorated the neuropathologic alterations in young AppNL-G-F mice. Our findings revealed microglia-based sex-differential neuropathologic changes in a mouse model of early-stage AD and therapeutic efficacy of dioscin on the brain lesions. Dioscin may represent a potential treatment for AD.

scholarly journals The Diagnosis of Alzheimer’s Disease: An Ensemble Approach

2020 ◽  
Author(s):  
Jingyan Qiu ◽  
Linjian Li ◽  
Yida Liu ◽  
Yingjun Ou ◽  
Yubei Lin
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Large Scale ◽  
Early Stage ◽  
Training Transfer ◽  
Detection And Diagnosis ◽  
Magnetic Resonance Imaging Mri ◽  
Deep Learning Model ◽  
The Brain

Alzheimer’s disease (AD) is one of the most common forms of dementia. The early stage of the disease is defined as Mild Cognitive Impairment (MCI). Recent research results have shown the prospect of combining Magnetic Resonance Imaging (MRI) scanning of the brain and deep learning to diagnose AD. However, the CNN deep learning model requires a large scale of samples for training. Transfer learning is the key to enable a model with high accuracy by using limited data for training. In this paper, DenseNet and Inception V4, which were pre-trained on the ImageNet dataset to obtain initialization values of weights, are, respectively, used for the graphic classification task. The ensemble method is employed to enhance the effectiveness and efficiency of the classification models and the result of different models are eventually processed through probability-based fusion. Our experiments were completely conducted on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) public dataset. Only the ternary classification is made due to a higher demand for medical detection and diagnosis. The accuracies of AD/MCI/Normal Control (NC) of different models are estimated in this paper. The results of the experiments showed that the accuracies of the method achieved a maximum of 92.65%, which is a remarkable outcome compared with the accuracies of the state-of-the-art methods.

MR Brain Screening using Optimization Techniques – A survey

2021 ◽  
Vol 17 ◽  
Author(s):  
Chitradevi D ◽  
Prabha S.
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Symptoms ◽  
Memory Loss ◽  
Amyloid Β ◽  
Cell Loss ◽  
Optimization Techniques ◽  
Amyloid Β Protein ◽  
The Brain ◽  
Brain Tissues

Background: Alzheimer’s disease (AD) is associated with Dementia, and it is also a memory syndrome in the brain. It affects the brain tissues and causes major changes in day-to-day activities. Aging is a major cause of Alzheimer's disease. AD is characterized by two pathological hallmarks as, Amyloid β protein and neurofibrillary tangles of hyperphosphorylated tau protein. The imaging hallmarks for Alzheimer’s disease are namely, swelling, shrinkage of brain tissues due to cell loss, and atrophy in the brain due to protein dissemination. Based on the survey, 60% to 80% of dementia patients belong to Alzheimer’s disease. Introduction: AD is now becoming an increasing and important brain disease. The goal of AD pathology is to cause changes/damage in brain tissues. Alzheimer's disease is thought to begin 20 years or more before symptoms appear, with tiny changes in the brain that are undetectable to the person affected. The changes in a person's brain after a few years are noticeable through symptoms such as language difficulties and memory loss. Neurons in different parts of the brain have detected symptoms such as cognitive impairments and learning disabilities. In this case, neuroimaging tools are necessary to identify the development of pathology which relates to the clinical symptoms. Methods: Several approaches have been tried during the last two decades for brain screening to analyse AD with the process of pre-processing, segmentation and classification. Different individual such as Grey Wolf optimization, Lion Optimization, Ant Lion Optimization and so on. Similarly, hybrid optimization techniques are also attempted to segment the brain sub-regions which helps in identifying the bio-markers to analyse AD. Conclusion: This study discusses a review of neuroimaging technologies for diagnosing Alzheimer's disease, as well as the discovery of hallmarks for the disease and the methodologies for finding hallmarks from brain images to evaluate AD. According to the literature review, most of the techniques predicted higher accuracy (more than 90%), which is beneficial for assessing and screening neurodegenerative illness, particularly Alzheimer's disease.

The Early Diagnosis of Alzheimer's Disease

2016 ◽  
pp. 1-16
Author(s):  
Yanna Ren ◽  
Weiping Yang ◽  
Xiaoyu Tang ◽  
Fengxia Wu ◽  
Satoshi Takahashi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Life Expectancy ◽  
Early Stage ◽  
Memory Loss ◽  
Cerebral Atrophy ◽  
Future Research ◽  
Research Perspectives ◽  
Genetic Examination ◽  
Imaging Detection

Alzheimer's disease, a common form of dementia, is a type of neurodegenerative disease that affects more than 30% of the population older than 85. Clinically, it is characterized as memory loss and cognitive decline. Pathologically, its symptoms include cerebral atrophy, amyloid plaques and NFTs. Generally, the life expectancy is no more than nine years after the definite diagnosis, and life expectancy exceeds 14 years in only 3% of patients. Presently, there is no effective treatment to stop the process; the only measures we can take are to ease or improve symptoms temporarily. Therefore, it is necessary to diagnosis the disease in the early stage, such as through imaging detection via CT, MRI, PET and MSR, or prediction before the disease (genetic examination). However, literature data have supported the notion that Alzheimer's disease patients show cognitive reserve abilities to some degree. In the future, research perspectives may focus on the cognitive training paradigms in compensatory and restorative strategies.

Assessment of Graph Metrics and Lateralization of Brain Connectivity in Progression of Alzheimer's Disease Using fMRI

2017 ◽  
Vol 9 (4) ◽  
pp. 46-66 ◽  
Author(s):  
Bhuvaneshwari Bhaskaran ◽  
Kavitha Anandan
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Default Mode Network ◽  
Brain Connectivity ◽  
Brain Network ◽  
Brain Disorder ◽  
Default Mode ◽  
Graph Metrics ◽  
Functional Topology ◽  
The Brain

Alzheimer's disease (AD) is a progressive brain disorder which has a long preclinical phase. The beta-amyloid plaques and tangles in the brain are considered as the main pathological causes. Functional connectivity is typically examined in capturing brain network dynamics in AD. A definitive underconnectivity is observed in patients through the progressive stages of AD. Graph theoretic modeling approaches have been effective in understanding the brain dynamics. In this article, the brain connectivity patterns and the functional topology through the progression of Alzheimer's disease are analysed using resting state fMRI. The altered network topology is analysed by graphed theoretical measures and explains cognitive deficits caused by the progression of this disease. Results show that the functional topology is disrupted in the default mode network regions as the disease progresses in patients. Further, it is observed that there is a lack of left lateralization involving default mode network regions as the severity in AD increases.

scholarly journals Low-Dose Ionizing Radiation Modulates Microglia Phenotypes in the Models of Alzheimer’s Disease

2020 ◽  
Vol 21 (12) ◽  
pp. 4532 ◽  
Author(s):  
Sujin Kim ◽  
Hyunju Chung ◽  
Han Ngoc Mai ◽  
Yunkwon Nam ◽  
Soo Jung Shin ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Ionizing Radiation ◽  
Cognitive Deficits ◽  
Low Dose ◽  
Memory Loss ◽  
M2 Polarization ◽  
Phenotype Switching ◽  
5Xfad Mice ◽  
The Brain

Alzheimer’s disease (AD) is the most common type of dementia. AD involves major pathologies such as amyloid-β (Aβ) plaques and neurofibrillary tangles in the brain. During the progression of AD, microglia can be polarized from anti-inflammatory M2 to pro-inflammatory M1 phenotype. The activation of triggering receptor expressed on myeloid cells 2 (TREM2) may result in microglia phenotype switching from M1 to M2, which finally attenuated Aβ deposition and memory loss in AD. Low-dose ionizing radiation (LDIR) is known to ameliorate Aβ pathology and cognitive deficits in AD; however, the therapeutic mechanisms of LDIR against AD-related pathology have been little studied. First, we reconfirm that LDIR (two Gy per fraction for five times)-treated six-month 5XFAD mice exhibited (1) the reduction of Aβ deposition, as reflected by thioflavins S staining, and (2) the improvement of cognitive deficits, as revealed by Morris water maze test, compared to sham-exposed 5XFAD mice. To elucidate the mechanisms of LDIR-induced inhibition of Aβ accumulation and memory loss in AD, we examined whether LDIR regulates the microglial phenotype through the examination of levels of M1 and M2 cytokines in 5XFAD mice. In addition, we investigated the direct effects of LDIR on lipopolysaccharide (LPS)-induced production and secretion of M1/M2 cytokines in the BV-2 microglial cells. In the LPS- and LDIR-treated BV-2 cells, the M2 phenotypic marker CD206 was significantly increased, compared with LPS- and sham-treated BV-2 cells. Finally, the effect of LDIR on M2 polarization was confirmed by detection of increased expression of TREM2 in LPS-induced BV2 cells. These results suggest that LDIR directly induced phenotype switching from M1 to M2 in the brain with AD. Taken together, our results indicated that LDIR modulates LPS- and Aβ-induced neuroinflammation by promoting M2 polarization via TREM2 expression, and has beneficial effects in the AD-related pathology such as Aβ deposition and memory loss.

scholarly journals IL-33 ameliorates Alzheimer’s disease-like pathology and cognitive decline

2016 ◽  
Vol 113 (19) ◽  
pp. E2705-E2713 ◽  
Author(s):  
Amy K. Y. Fu ◽  
Kwok-Wang Hung ◽  
Michael Y. F. Yuen ◽  
Xiaopu Zhou ◽  
Deejay S. Y. Mak ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Immune Response ◽  
Innate Immune Response ◽  
Memory Loss ◽  
Neuronal Loss ◽  
Innate Immune ◽  
Therapeutic Role ◽  
Potential Therapeutic Role ◽  
The Brain

Alzheimer’s disease (AD) is a devastating condition with no known effective treatment. AD is characterized by memory loss as well as impaired locomotor ability, reasoning, and judgment. Emerging evidence suggests that the innate immune response plays a major role in the pathogenesis of AD. In AD, the accumulation of β-amyloid (Aβ) in the brain perturbs physiological functions of the brain, including synaptic and neuronal dysfunction, microglial activation, and neuronal loss. Serum levels of soluble ST2 (sST2), a decoy receptor for interleukin (IL)-33, increase in patients with mild cognitive impairment, suggesting that impaired IL-33/ST2 signaling may contribute to the pathogenesis of AD. Therefore, we investigated the potential therapeutic role of IL-33 in AD, using transgenic mouse models. Here we report that IL-33 administration reverses synaptic plasticity impairment and memory deficits in APP/PS1 mice. IL-33 administration reduces soluble Aβ levels and amyloid plaque deposition by promoting the recruitment and Aβ phagocytic activity of microglia; this is mediated by ST2/p38 signaling activation. Furthermore, IL-33 injection modulates the innate immune response by polarizing microglia/macrophages toward an antiinflammatory phenotype and reducing the expression of proinflammatory genes, including IL-1β, IL-6, and NLRP3, in the cortices of APP/PS1 mice. Collectively, our results demonstrate a potential therapeutic role for IL-33 in AD.

scholarly journals The potential role for sphingolipids in neuropathogenesis of Alzheimer’s disease

2013 ◽  
Vol 59 (1) ◽  
pp. 25-50 ◽  
Author(s):  
A.V. Alessenko
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Role ◽  
Potential Role ◽  
Early Stage ◽  
New Drugs ◽  
Neuronal Function ◽  
Sphingosine 1 Phosphate ◽  
The Brain

The review discusses the functional role of sphingolipids in the pathogenesis of Alzheimer's disease. Certain evidence exist that the imbalance of sphingolipids such as sphingomyelin, ceramide, sphingosine, sphingosine-1-phosphate and galactosylceramide in the brain of animals and humans, in the cerebrospinal fluid and blood plasma of patients with Alzheimer's disease play a crucial role in neuronal function by regulating growth, differentiation and cell death in CNS. Activation of sphingomyelinase, which leads to the accumulation of the proapoptotic agent, ceramide, can be considered as a new mechanism for AD and may be a prerequisite for the treatment of this disease by using drugs that inhibit sphingomyelinase activity. The role of sphingolipids as biomarkers for the diagnosis of the early stage of Alzheimer's disease and monitoring the effectiveness of treatment with new drugs is discussed.

scholarly journals Imaging asparaginyl endopeptidase (AEP) in the live brain as a biomarker for Alzheimer’s disease

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Shan-Shan Wang ◽  
Zi-Kai Liu ◽  
Jing-Jing Liu ◽  
Qing Cheng ◽  
Yan-Xia Wang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Stage ◽  
Senile Plaques ◽  
Disease Stage ◽  
Assay Method ◽  
Imaging Probe ◽  
Asparaginyl Endopeptidase ◽  
Potential Biomarker ◽  
The Brain

Abstract Background Discovery of early-stage biomarkers is a long-sought goal of Alzheimer’s disease (AD) diagnosis. Age is the greatest risk factor for most AD and accumulating evidence suggests that age-dependent elevation of asparaginyl endopeptidase (AEP) in the brain may represent a new biological marker for predicting AD. However, this speculation remains to be explored with an appropriate assay method because mammalian AEP exists in many organs and the level of AEP in body fluid isn’t proportional to its concentration in brain parenchyma. To this end, we here modified gold nanoparticle (AuNPs) into an AEP-responsive imaging probe and choose transgenic APPswe/PS1dE9 (APP/PS1) mice as an animal model of AD. Our aim is to determine whether imaging of brain AEP can be used to predict AD pathology. Results This AEP-responsive imaging probe AuNPs-Cy5.5-A&C consisted of two particles, AuNPs-Cy5.5-AK and AuNPs-Cy5.5-CABT, which were respectively modified with Ala–Ala–Asn–Cys–Lys (AK) and 2-cyano-6-aminobenzothiazole (CABT). We showed that AuNPs-Cy5.5-A&C could be selectively activated by AEP to aggregate and emit strong fluorescence. Moreover, AuNPs-Cy5.5-A&C displayed a general applicability in various cell lines and its florescence intensity correlated well with AEP activity in these cells. In the brain of APP/PS1 transgenic mice , AEP activity was increased at an early disease stage of AD that precedes formation of senile plaques and cognitive impairment. Pharmacological inhibition of AEP with δ-secretase inhibitor 11 (10 mg kg−1, p.o.) reduced production of β-amyloid (Aβ) and ameliorated memory loss. Therefore, elevation of AEP is an early sign of AD onset. Finally, we showed that live animal imaging with this AEP-responsive probe could monitor the up-regulated AEP in the brain of APP/PS1 mice. Conclusions The current work provided a proof of concept that assessment of brain AEP activity by in vivo imaging assay is a potential biomarker for early diagnosis of AD. Graphical abstract

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