Development Of Alzheimer's Disease Research Articles

Enhancing Early Alzheimer's Disease Detection: Leveraging Pre-trained Networks and Transfer Learning

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder affecting millions worldwide. Early and accurate AD detection is crucial for timely intervention and improving patient outcomes. Lately, there have been notable advancements in using deep learning approaches to classify neuroimaging data associated with Alzheimer's disease. These methods have shown substantial progress in achieving accurate classification results. Nevertheless, the concept of end-to-end learning, which has the potential to harness the benefits of deep learning fully, has yet to garner extensive focus in the realm of neuroimaging. This is attributed mainly to the persistent challenge in neuroimaging, namely the limited data availability. This study employs neuroimages and Transfer Learning (TL) to identify early signs of AD and different phases of cognitive impairment. By employing transfer learning, the study uses Magnetic Resonance Imaging (MRI) images from the Alzheimer's Disease Neuroimaging (ADNI) database to classify images into various categories, such as Cognitively Normal (CN), Early Mild Cognitive Impairment (EMCI), Mild Cognitive Impairment (MCI), Late Mild Cognitive Impairment (LMCI), and Alzheimer's Disease (AD). The classification task involves training and testing three pre-trained networks: VGG-19, ResNet-50, and Inception V3. The study evaluates the performance of these networks using the confusion matrix and its associated metrics. Among the three models, ResNet-50 achieves the highest recall rate of 99.25%, making it more efficient in detecting the early stages of AD development. The study further examines the performance of the pre-trained networks on a class-by-class basis using the parameters derived from the confusion matrix. This comprehensive analysis provides insights into how each model performs for different classes within the AD classification framework. Overall, the research underscores the potential of deep learning and transfer learning in advancing early AD detection and emphasizes the significance of utilizing pre-trained models for this purpose.

Does gut microbiota have an impact on the origin of Alzheimer's and Parkinson's disease? – literature review

Introduction and purpose:
 Among neurodegenerative disorders, Alzheimer's disease (AD) and Parkinson's disease (PD) are the most prevalent. It has been observed recently that alterations in the gut microbiota are associated with the onset of neurodegenerative disorders. This research aims to estimate the pathomechanisms and disease courses associated with the gut microbiota that lead to AD and PD development.
 Material and methods
 The following review was based on articles from the PubMed and Google Scholar databases. Key search terms included Alzheimer’s disease; Parkinson’s disease; gut microbiota; neurodegenerative diseases.
 State of knowledge
 The advancement of neurodegenerative processes is linked to the varying progressive course of both disorders. There are numerous likely reasons that connect the development of AD and PD and the gut microbiome. These include the hypotheses on inflammation, the decrease in the quantity of bacteria that produce short-chain fatty acids, and hygiene. The researchers' suggested treatment plans for the two illnesses are comparable.
 Conclusions
 A major influence on the development of neurodegenerative disorders is the gut microbiome. To clarify the precise connections between the gut microbiota and the development of AD and PD, further thorough research is required. More human research is required. Furthermore, it's possible that early interventions, such switching to a Mediterranean diet, are anticipated to lower the risk of AD or PD.

Bioinformatics to analyze the differentially expressed genes in different degrees of Alzheimer's disease and their roles in progress of the disease.

Employing bioinformatics approaches, this investigation pinpointed pivotal differentially expressed genes (DEGs) across the spectrum of Alzheimer's disease (AD), from incipient to severe stages, using the GSE28146 dataset from the GEO repository. Analytical methods included DEG identification via the limma package in R, coupled with GO and KEGG pathway analyses through clusterProfiler, to discern biological processes and pathway involvements. Key findings spotlighted the roles of proteasome subunits PSMB4, PSMB8, PSMC4, and PSMD6 in the early stage, ribosomal proteins RPS3 and RPL11 during moderate AD, and mitochondrial components COX5B, COX6B2, and COX7A2 in severe AD, underscoring their importance in the disease's pathogenesis. Conclusively, these results not only delineate the dynamic genetic shifts accompanying AD progression but also propose critical biomarkers for potential therapeutic targeting, offering a consolidated basis for future AD research and treatment development. This offered a novel idea for analyzing the pathogenesis and development of AD and investigation of targeted drugs.

Prognostic Value of Gut Microbiome for Conversion from Mild Cognitive Impairment to Alzheimer's Disease Dementia within 4 Years: Results from the AlzBiom Study.

Alterations in the gut microbiome are associated with the pathogenesis of Alzheimer's disease (AD) and can be used as a diagnostic measure. However, longitudinal data of the gut microbiome and knowledge about its prognostic significance for the development and progression of AD are limited. The aim of the present study was to develop a reliable predictive model based on gut microbiome data for AD development. In this longitudinal study, we investigated the intestinal microbiome in 49 mild cognitive impairment (MCI) patients over a mean (SD) follow-up of 3.7 (0.6) years, using shotgun metagenomics. At the end of the 4-year follow-up (4yFU), 27 MCI patients converted to AD dementia and 22 MCI patients remained stable. The best taxonomic model for the discrimination of AD dementia converters from stable MCI patients included 24 genera, yielding an area under the receiver operating characteristic curve (AUROC) of 0.87 at BL, 0.92 at 1yFU and 0.95 at 4yFU. The best models with functional data were obtained via analyzing 25 GO (Gene Ontology) features with an AUROC of 0.87 at BL, 0.85 at 1yFU and 0.81 at 4yFU and 33 KO [Kyoto Encyclopedia of Genes and Genomes (KEGG) ortholog] features with an AUROC of 0.79 at BL, 0.88 at 1yFU and 0.82 at 4yFU. Using ensemble learning for these three models, including a clinical model with the four parameters of age, gender, body mass index (BMI) and Apolipoprotein E (ApoE) genotype, yielded an AUROC of 0.96 at BL, 0.96 at 1yFU and 0.97 at 4yFU. In conclusion, we identified novel and timely stable gut microbiome algorithms that accurately predict progression to AD dementia in individuals with MCI over a 4yFU period.

Abnormal amyloid precursor protein processing in periodontal tissue in a murine model of periodontitis induced by Porphyromonas gingivalis.

The study aimed to investigate the change of amyloid precursor protein (APP) processing and amyloid β (Aβ) metabolites in linking periodontitis to Alzheimer's disease (AD). Aβ is one of the main pathological features of AD, and few studies have discussed changes in its expression in peripheral tissues or analyzed the relationship between the peripheral imbalance of Aβ production and clearance. A murine model of periodontitis was established by oral infection with Porphyromonas gingivalis (P. gingivalis). Micro-computed tomography (Micro-CT) was used to observe the destruction of the alveolar bone. Nested quantitative polymerase chain reaction (qPCR) was used to measure small quantities of P.gingivalis DNA in different tissues. Behavioral experiments were performed to measure cognitive function in the mice. The mRNA levels of TNF-α, IL-6, IL-8, RANKL, OPG, APP695, APP751, APP770, and BACE1 in the gingival tissues or cortex were detected by RT-PCR. The levels of Aβ1-40 and Aβ1-42 in gingival crevicular fluid (GCF) and plasma were tested by ELISA. P. gingivalis oral infection was found to cause alveolar bone resorption and impaired learning and memory. P.gingivalis DNA was detected in the gingiva, blood and cortex of the P.gingivalis group by nested qPCR (p < .05). The mRNA expression of TNF-α, IL-6, IL-8, RANKL/OPG, and BACE1 in the gingival tissue was significantly higher than that in the control group (p < .05). Similarly, upregulated mRNA levels of APP695 and APP770 were observed in the gingival tissuses and cortex of the P. gingivalis group (p < .05). The levels of Aβ1-40 and Aβ1-42 in the GCF and plasma of the P. gingivalis group were significantly higher than those in the control group (p < .05). P. gingivalis can directly invade the brain via hematogenous infection. The invasion of P. gingivalis could trigger an immune response and lead to an imbalance between Aβ production and clearance in peripheral tissues, which may trigger an abnormal Aβ metabolite in the brain, resulting in the occurrence and development of AD.

CoQ10 and Mitochondrial Dysfunction in Alzheimer's Disease.

The progress in understanding the pathogenesis and treatment of Alzheimer's disease (AD) is based on the recognition of the primary causes of the disease, which can be deduced from the knowledge of risk factors and biomarkers measurable in the early stages of the disease. Insights into the risk factors and the time course of biomarker abnormalities point to a role for the connection of amyloid beta (Aβ) pathology, tau pathology, mitochondrial dysfunction, and oxidative stress in the onset and development of AD. Coenzyme Q10 (CoQ10) is a lipid antioxidant and electron transporter in the mitochondrial electron transport system. The availability and activity of CoQ10 is crucial for proper mitochondrial function and cellular bioenergetics. Based on the mitochondrial hypothesis of AD and the hypothesis of oxidative stress, the regulation of the efficiency of the oxidative phosphorylation system by means of CoQ10 can be considered promising in restoring the mitochondrial function impaired in AD, or in preventing the onset of mitochondrial dysfunction and the development of amyloid and tau pathology in AD. This review summarizes the knowledge on the pathophysiology of AD, in which CoQ10 may play a significant role, with the aim of evaluating the perspective of the pharmacotherapy of AD with CoQ10 and its analogues.

Non-coding RNAs in Regulation of Protein Aggregation and Clearance Pathways: Current Perspectives Towards Alzheimer's Research and Therapy.

Alzheimer's disease (AD) is the leading cause of dementia, affecting approximately 45.0 million people worldwide and ranking as the fifth leading cause of mortality. AD is identified by neurofibrillary tangles (NFTs), which include abnormally phosphorylated tau-protein and amyloid protein (amyloid plaques). Peptide dysregulation is caused by an imbalance between the production and clearance of the amyloid-beta (Aβ) and NFT. AD begins to develop when these peptides are not cleared from the body. As a result, understanding the processes that control both normal and pathological protein recycling in neuronal cells is critical. Insufficient Aβ and NFT clearance are important factors in the development of AD. Autophagy, lysosomal dysfunction, and ubiquitin-proteasome dysfunction have potential roles in the pathogenesis of many neurodegenerative disorders, particularly in AD. Modulation of these pathways may provide a novel treatment strategy for AD. Non-coding RNAs (ncRNAs) have recently emerged as important biological regulators, with particular relevance to the emergence and development of neurodegenerative disorders such as AD. ncRNAs can be used as potential therapeutic targets and diagnostic biomarkers due to their critical regulatory functions in several biological processes involved in disease development, such as the aggregation and accumulation of Aβ and NFT. It is evident that ncRNAs play a role in the pathophysiology of AD. In this communication, we explored the link between ncRNAs and AD and their regulatory mechanisms that may help in finding new therapeutic targets and AD medications.

An explainable machine learning approach for Alzheimer’s disease classification

The early diagnosis of Alzheimer’s disease (AD) presents a significant challenge due to the subtle biomarker changes often overlooked. Machine learning (ML) models offer a promising tool for identifying individuals at risk of AD. However, current research tends to prioritize ML accuracy while neglecting the crucial aspect of model explainability. The diverse nature of AD data and the limited dataset size introduce additional challenges, primarily related to high dimensionality. In this study, we leveraged a dataset obtained from the National Alzheimer’s Coordinating Center, comprising 169,408 records and 1024 features. After applying various steps to reduce the feature space. Notably, support vector machine (SVM) models trained on the selected features exhibited high performance when tested on an external dataset. SVM achieved a high F1 score of 98.9% for binary classification (distinguishing between NC and AD) and 90.7% for multiclass classification. Furthermore, SVM was able to predict AD progression over a 4-year period, with F1 scores reached 88% for binary task and 72.8% for multiclass task. To enhance model explainability, we employed two rule-extraction approaches: class rule mining and stable and interpretable rule set for classification model. These approaches generated human-understandable rules to assist domain experts in comprehending the key factors involved in AD development. We further validated these rules using SHAP and LIME models, underscoring the significance of factors such as MEMORY, JUDGMENT, COMMUN, and ORIENT in determining AD risk. Our experimental outcomes also shed light on the crucial role of the Clinical Dementia Rating tool in predicting AD.

Targeting blood brain barrier-Remote ischemic conditioning alleviates cognitive impairment in female APP/PS1 rats.

Alzheimer's disease (AD) is a significant global health concern, and it is crucial that we find effective methods to prevent or slow down AD progression. Recent studies have highlighted the essential role of blood vessels in clearing Aβ, a protein that contributes to AD. Scientists are exploring blood biomarkers as a potential tool for future AD diagnosis. One promising method that may help prevent AD is remote ischemic conditioning (RIC). RIC involves using sub-lethal ischemic-reperfusion cycles on limbs. However, a comprehensive understanding of how RIC can prevent AD and its long-term effectiveness is still lacking. Further research is essential to fully comprehend the potential benefits of RIC in preventing AD. Female wild-type (WT) and APP/PS1 transgenic rats, aged 12 months, underwent ovariectomy and were subsequently assigned to WT, APP/PS1, and APP/PS1 + RIC groups. RIC was conducted five times a week for 4 weeks. The rats' depressive and cognitive behaviors were evaluated using force swimming, open-field tests, novel objective recognition, elevated plus maze, and Barnes maze tests. Evaluation of the neurovascular unit (NVU), synapses, vasculature, astrocytes, and microglia was conducted using immunofluorescence staining (IF), Western blot (WB), and transmission electron microscopy (TEM). Additionally, the cerebro-vasculature was examined using micro-CT, and cerebral blood flow (CBF) was measured using Speckle Doppler. Blood-brain barrier (BBB) permeability was determined by measuring the Evans blue leakage. Finally, Aβ levels in the rat frontal cortex were measured using WB, ELISA, or IF staining. RIC enhanced memory-related protein expression and rescued depressive-like behavior and cognitive decline in APP/PS1 transgenic rats. Additionally, the intervention protected NVU in the rat frontal cortex, as evidenced by (1) increased expression of TJ (tight junction) proteins, pericyte marker PDGFRβ, and glucose transporter 1 (GLUT1), as well as decreased VCAM1; (2) mitigation of ultrastructure impairment in neuron, cerebral vascular, and astrocyte; (3) upregulation of A2 astrocyte phenotype markers and downregulation of A1 phenotype markers, indicating a shift toward a healthier phenotype. Correspondingly, RIC intervention alleviated neuroinflammation, as evidenced by the decreased Iba1 level, a microglia marker. Meanwhile, RIC intervention elevated CBF in frontal cortex of the rats. Notably, RIC intervention effectively suppressed Aβ toxicity, as demonstrated by the enhancement of α-secretase and attenuation of β-secretase (BACE1) and γ- secretase and Aβ1-42 and Aβ1-40 levels as well. Chronic RIC intervention exerts vascular and neuroprotective roles, suggesting that RIC could be a promising therapeutic strategy targeting the BBB and NVU during AD development.

Role of NLRP3 inflammasome in prevention and treatment of cognitive impairment-related diseases and traditional Chinese medicine intervention: a review

Alzheimer's disease(AD), vascular dementia(VD), and traumatic brain injury(TBI) are more common cognitive impairment diseases characterized by high disability and mortality rates, imposing a heavy burden on individuals and their families. Although AD, VD, and TBI have different specific mechanisms, their pathogenesis is closely related to the nucleotide-binding oligome-rization domain-like receptor protein 3(NLRP3). The NLRP3 inflammasome is involved in neuroinflammatory responses, mediating microglial polarization, regulating the reduction of amyloid β-protein(Aβ) deposition, neurofibrillary tangles(NFTs) formation, autophagy regulation, and maintaining brain homeostasis, and synaptic stability, thereby contributing to the development of AD, VD, and TBI. Previous studies have shown that traditional Chinese medicine(TCM) can alleviate neuroinflammation, promote microglial polarization towards the M2 phenotype, reduce Aβ deposition and NFTs formation, regulate autophagy, and maintain brain homeostasis by intervening in NLRP3 inflammasome, hence exerting a role in preventing and treating cognitive impairment-related diseases, reducing psychological and economic pressure on patients, and improving their quality of life. Therefore, this article elucidated the role of NLRP3 inflammasome in AD, VS, and TBI, and provided a detailed summary of the latest research results on TCM intervention in NLRP3 inflammasome for the prevention and treatment of these diseases, aiming to inherit the essence of TCM and provide references and foundations for clinical prevention and treatment of cognitive impairment-related diseases with TCM. Meanwhile, this also offers insights and directions for further research in TCM for the prevention and treatment of cognitive impairment-related diseases.

Polygalacic acid attenuates cognitive impairment by regulating inflammation through PPARγ/NF-κB signaling pathway.

We aimed to explore the role and molecular mechanism of polygalacic acid (PA) extracted from traditional Chinese medicine Polygala tenuifolia in the treatment of Alzheimer's disease (AD). The network pharmacology analysis was used to predict the potential targets and pathways of PA. Molecular docking was applied to analyze the combination between PA and core targets. Aβ42 oligomer-induced AD mice model and microglia were used to detect the effect of PA on the release of pro-inflammatory mediators and its further mechanism. In addition, a co-culture system of microglia and neuronal cells was constructed to assess the effect of PA on activating microglia-mediated neuronal apoptosis. We predict that PA might regulate inflammation by targeting PPARγ-mediated pathways by using network pharmacology. Invivo study, PA could attenuate cognitive deficits and inhibit the expression levels of inflammation-related factors. Invitro study, PA can also decrease the production of activated microglia-mediated inflammatory cytokines and reduce the apoptosis of N2a neuronal cells. PPARγ inhibitor GW9662 inversed the neuroprotective effect of PA. Both invivo and invitro studies showed PA might attenuate the inflammation through the PPARγ/NF-κB pathway. PA is expected to provide a valuable candidate for new drug development for AD in the future.

Up-regulation of lncRNA WT1-AS ameliorates Aβ-stimulated neuronal injury through modulation of miR-186-5p/CCND2 axis in Alzheimer's disease.

As a common neurodegenerative disorder, Alzheimer's disease (AD) seriously threatens human life. Long non-coding RNAs (lncRNAs) exhibit essential functions in AD development. Nevertheless, the detailed effects and possible mechanisms of lncRNA Wilms tumor 1 Antisense RNA (WT1-AS) in AD are largely unknown. In our studies, a total of 30 serum samples from AD patients were collected, and WT1-AS expressions were detected through qRT-PCR analysis. Additionally, an in vitro AD model was constructed by treating Aβ1-42 in human neuroblastoma cells. Functional assays were implemented to assess the impacts of WT1-AS on Aβ1-42-stimulated human neuroblastoma cell proliferation together with apoptosis. Moreover, relationship of WT1-AS, microRNA (miR)-186-5p as well as cyclin D2 (CCND2) could be predicted through bioinformatics tools as well as proved via dual-luciferase reporter experiments. Our results showed that WT1-AS together with CCND2 were low-expressed, while miR-186-5p presented high expression in AD serum samples together with Aβ1-42-stimulated human neuroblastoma cells. WT1-AS over-expression or miR-186-5p depletion notably promoted the proliferation, reduced the apoptosis, and decreased the p-Tau protein expressions of human neuroblastoma cells induced with Aβ1-42. Moreover, miR-186-5p combined with WT1-AS, and CCND2 was modulated by miR-186-5p. Furthermore, CCND2 elevation partially offsets the impacts of miR-186-5p elevation on Aβ1-42-stimulated cell proliferation as well as apoptosis mediated with WT1-AS up-regulation. Our results indicated that up-regulation of lncRNA WT1-AS ameliorated Aβ-stimulated neuronal damage through modulating miR-186-5p/CCND2 axis, offering a novel direction for AD therapy.

Role Of Lncrna In Alzheimer’s Diseases

Long noncoding RNA (lncRNA) are a family of RNA molecules with over 200 nucleotides in size. They cannot code for proteins but still have biological activities. lncRNAs are abundantly expressed in the pathogenic process of neurological diseases like Alzheimer’s. The lncRNA EBF3-AS is more expressed in the brains of older Alzheimer's disease patients called late onset Alzheimer’s disease. NAT-Rad18, a lncRNA over synthesized in specific areas of the brain in AD rats. The lncRNA n336694 targets miR-106b which increases its expression. MiR-106b leads to apoptosis markers in cells. oxidative stress-induced injury to the neurons is caused by the lncRNA SOX21-AS1. The lncRNA-ATB is involved in AD pathophysiology and reducing its expression helps with oxidative stress-induced injury. lncRNA MEG3 inhibits inflammatory injury and oxidative stress in individuals suffering from AD. The increase of lncRNA 17A in cerebral tissues of AD patients affects Aβ secretion. BACE1-AS suppression reduces Aβ and BACE1 levels and inhibits tau protein phosphorylation (3). The lncRNA BC200, also known as BCYRN1 upregulates Aβ production through BACE1 modulation which leads to AD pathogenesis. NEAT1 regulates the miR-124/BACE1 axis and plays a role in AD development. Reduced SORL1 expression increases neurotoxic Aβ formation in AD brains. LRP1-AS negatively regulates systemic Aβ clearance during AD progression. GAS5 regulates insulin signaling, neuronal survival, tau phosphorylation, and neuroinflammation. MAGI2-AS3-miR-374b-5p axis modulates neuroinflammation and neurotoxicity caused by Aβ fragment. Upregulation of WT1-AS inhibits the miR-375/SIX4 axis, OSI, and neuronal apoptosis in AD. BDNF-AS is found to be important in AD though the mechanism has yet to be determined. This review study aims to enhance comprehension of the disease progression of Alzheimer's disease (AD) in relation to various long non-coding RNAs (lncRNA).

Diversity of amyloid beta peptide actions.

Fibril formation by amyloidogenic proteins and peptides is considered the cause of a number of incurable diseases. One of the most known amyloid diseases is Alzheimer's disease (AD). Traditionally, amyloidogenic beta peptides Aβ40 and Aβ42 (Aβs) are considered as main causes of AD and the foremost targets in AD fight. The main efforts in pharmacology are aimed at reducing Aβs concentration to prevent their accumulation, aggregation, formation of senile plaques, neuronal death, and neurodegeneration. However, a number of publications have demonstrated certain beneficial physiological effects of Aβs. Simultaneously, it is indicated that the effects of Aβs turn into pathological due to the development of certain diseases in the body. The accumulation of C- and N-terminal truncated Aβs under diverse conditions is supposed to play a role in AD development. The significance of transformation of glutamate residue at positions 3 or 11 of Aβs catalyzed by glutaminyl cyclase making them more degradation resistant, hydrophobic, and prone to aggregation, as well as the participation of dipeptidyl peptidase IV in these transformations are discussed. The experimental data presented confirm the maintenance of physiological, nonaggregated state of Aβs by plant preparations. In conclusion, this review suggests that in the fight against AD, instead of removing Aβs, preference should be given to the treatment of common diseases. Glutaminyl cyclase and dipeptidyl peptidase IV can be considered as targets in AD treatment. Flavonoids and plant preparations that possess antiamyloidogenic propensity are proposed as beneficial neuroprotective, anticancer, and antidiabetic food additives.

Review of the determinants contributing to the demographics of Alzheimer’s syndrome: Prevention techniques, risk factors, and insights for public health

Alzheimer's disease (AD) is the leading cause of memory loss, accounting for 80% of cases and severely impacting daily life and social interactions. The prevalence of AD is expected to grow over the globe as life expectancy improves and the population ages in developing countries will result in a costly disease burden. A combination of societal circumstances and inherent sensitivity that extends throughout a person’s lifetime can cause AD, a challenging and varied disorder. This study aims to provide a comprehensive analysis of the factors that shape the demographics of AD, with a focus on prevention measures. risk factors and their public health consequences. Interventions aimed at addressing multiple risk indicators in non-demented older adults, including those in their middle age, can be able to prevent or postpone the development of AD since the illness is thought to begin generations before clinical evidence appears. Addressing the intricate connection between social and psychological characteristics and Alzheimer’s demography is critical for devising effective preventative measures, early treatments and individualized care for at-risk communities. AD is known to be associated with genetic variables, particularly the APOE ε4 allele. Identifying the disease’s genetic causes is essential for specific preventive and early intervention methods. A balanced diet, frequent physical exercise, cognitive stimulation and social involvement are the preventative treatments for AD. Early identification and intervention hold promise for reducing disease development and public health measures that promote knowledge as well as healthy lives are essential.

Microbial infection promotes amyloid pathology in a mouse model of Alzheimer's disease via modulating γ-secretase.

Microbial infection as a type of environmental risk factors is considered to be associated with long-term increased risk of dementia, including Alzheimer's disease (AD). AD is characterized by two neuropathologically molecular hallmarks of hyperphosphorylated tau and amyloid-β (Aβ), the latter generated by several biochemically reactive enzymes, including γ-secretase. However, how infectious risk factors contribute to pathological development of the AD core molecules remains to be addressed. In this work, we utilized a modified herpes simplex virus type 1 (mHSV-1) and found that its hippocampal infection locally promotes Aβ pathology in 5 × FAD mice, the commonly used amyloid model. Mechanistically, we identified HSV-1 membrane glycoprotein US7 (Envelope gI) that interacts with and modulates γ-secretase and consequently facilitates Aβ production. Furthermore, we presented evidence that adenovirus-associated virus-mediated locally hippocampal overexpression of the US7 aggravates Aβ pathology in 5 × FAD mice. Collectively, these findings identify a herpesviral factor regulating γ-secretase in the development and progression of AD and represent a causal molecular link between infectious pathogens and neurodegeneration.

Hotspots and trends of microglia in Alzheimer's disease: a bibliometric analysis during 2000–2022

BackgroundAlzheimer's disease is one common type of dementia. Numerous studies have suggested a correlation between Alzheimer's disease and inflammation. Microglia mainly participate in the inflammatory response in the brain. Currently, ample evidence has shown that microglia are closely related to the occurrence and development of Alzheimer's disease.ObjectiveWe opted for bibliometric analysis to comprehensively summarize the advancements in the study of microglia in Alzheimer's disease, aiming to provide researchers with current trends and future research directions.MethodsAll articles and reviews pertaining to microglia in Alzheimer's disease from 2000 to 2022 were downloaded through Web of Science Core Collection. The results were subjected to bibliometric analysis using VOSviewer 1.6.18 and CiteSpace 6.1 R2.ResultsOverall, 7449 publications were included. The number of publications was increasing yearly. The United States has published the most publications. Harvard Medical School has published the most papers of all institutions. Journal of Alzheimer’s Disease and Journal of Neuroscience were the journals with the most studies and the most commonly cited, respectively. Mt Heneka is the author with the highest productivity and co-citation. After analysis, the most common keywords are neuroinflammation, amyloid-beta, inflammation, neurodegeneration. Gut microbiota, extracellular vesicle, dysfunction and meta-analysis are the hotspots of research at the present stage and are likely to continue.ConclusionNLRP3 inflammasome, TREM2, gut microbiota, mitochondrial dysfunction, exosomes are research hotspots. The relationship between microglia-mediated neuroinflammation and Alzheimer's disease have been the focus of current research and the development trend of future research.

Impact of stalling events on microcirculatory hemodynamics in the aged brain.

The role of cerebral microvasculature in cognitive dysfunction can be investigated by identifying the impact of blood flow on cortical tissue oxygenation. In this paper, the impact of capillary stalls on microcirculatory characteristics such as flow and hematocrit (Ht) in the cortical angioarchitecture is studied. Using a deterministic mathematical model to simulate blood flow in a realistic mouse cortex, hemodynamics parameters, including pressure, flow, vessel diameter-adjustable hematocrit, and transit time are calculated as a function of stalling events. Using a non-linear plasma skimming model, it is observed that Ht increases in the penetrating arteries from the pial vessels as a function of cortical depth. The incidence of stalling on Ht distribution along the blood network vessels shows reduction of RBCs around the tissue near occlusion sites and decreased Ht concentration downstream from the blockage points. Moreover, upstream of the occlusion, there is a noticeable increase of the Ht, leading to larger flow resistance due to higher blood viscosity. We predicted marked changes in transit time behavior due to stalls which match trends observed in mice invivo. These changes to blood cell quantity and quality may be implicated in the development of Alzheimer's disease and contribute to the course of the illness.

Higher amyloid is associated with greater loneliness among cognitively normal older adults during the COVID-19 pandemic.

Loneliness has been associated with several consequences, including increased risk of developing Alzheimer disease (AD). Loneliness may arise during the preclinical phase of AD, but little is known about the relationship between loneliness and amyloid accumulation consistent with preclinical AD. Therefore, the purpose of this study was to examine the relationship between amyloid accumulation and subjective experiences of loneliness among cognitively normal older adults during the COVID-19 pandemic. A global Clinical Dementia Rating ® Scale score of 0 was required for enrollment. Cortical amyloid burden was measured using [11C] Pittsburgh compound B or [18F]-Florbetapir PET tracers. Centiloids were used to synchronize measures. Demographic characteristics and measures of loneliness, anxiety, and depression were collected via self-report. Multiple linear regression was used to examine the relationship between loneliness and amyloid accumulation. The 108 participants had a mean age of 75.0 and an average amyloid accumulation of 22.2 ± 31.9. Mean UCLA Loneliness Scale scores were 31.6 ± 10.8. A significant positive association was detected between loneliness and amyloid accumulation (β = 0.064, SE = 0.027, 95% CI = [0.011, 0.118], p = 0.018). These findings highlight the relationship between higher amyloid accumulation and greater loneliness during the COVID-19 pandemic. Healthcare professionals should include routine assessments for characteristics of loneliness in routine clinical evaluations and integrate loneliness reduction and prevention treatments among older adults experiencing loneliness. Additional research is needed with a larger, more diverse sample to examine the relationship between loneliness and amyloid accumulation.

Ischemia-Reperfusion Programming of Alzheimer's Disease-Related Genes-A New Perspective on Brain Neurodegeneration after Cardiac Arrest.

The article presents the latest data on pathological changes after cerebral ischemia caused by cardiac arrest. The data include amyloid accumulation, tau protein modification, neurodegenerative and cognitive changes, and gene and protein changes associated with Alzheimer's disease. We present the latest data on the dysregulation of genes related to the metabolism of the amyloid protein precursor, tau protein, autophagy, mitophagy, apoptosis, and amyloid and tau protein transport genes. We report that neuronal death after cerebral ischemia due to cardiac arrest may be dependent and independent of caspase. Moreover, neuronal death dependent on amyloid and modified tau protein has been demonstrated. Finally, the results clearly indicate that changes in the expression of the presented genes play an important role in acute and secondary brain damage and the development of post-ischemic brain neurodegeneration with the Alzheimer's disease phenotype. The data indicate that the above genes may be a potential therapeutic target for brain therapy after ischemia due to cardiac arrest. Overall, the studies show that the genes studied represent attractive targets for the development of new therapies to minimize ischemic brain injury and neurological dysfunction. Additionally, amyloid-related genes expression and tau protein gene modification after cerebral ischemia due to cardiac arrest are useful in identifying ischemic mechanisms associated with Alzheimer's disease. Cardiac arrest illustrates the progressive, time- and area-specific development of neuropathology in the brain with the expression of genes responsible for the processing of amyloid protein precursor and the occurrence of tau protein and symptoms of dementia such as those occurring in patients with Alzheimer's disease. By carefully examining the common genetic processes involved in these two diseases, these data may help unravel phenomena associated with the development of Alzheimer's disease and neurodegeneration after cerebral ischemia and may lead future research on Alzheimer's disease or cerebral ischemia in new directions.