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Alzheimer's disease (AD) is a progressive neurological disorder characterized by the gradual deterioration of cognitive functions, leading to dementia and significantly impacting the quality of life for millions of people worldwide. Early and accurate diagnosis is crucial for the effective management and treatment of this debilitating condition. This study introduces a novel framework based on Spectral Graph Convolutional Neural Networks (SGCNN) for diagnosing AD and categorizing multiple diseases through the analysis of functional changes in brain structures captured via magnetic resonance imaging (MRI). To assess the effectiveness of our approach, we systematically analyze structural modifications to the SGCNN model through comprehensive ablation studies. The performance of various Convolutional Neural Networks (CNNs) is also evaluated, including SGCNN variants, Base CNN, Lean CNN, and Deep CNN. We begin with the original SGCNN model, which serves as our baseline and achieves a commendable classification accuracy of 93%. In our investigation, we perform two distinct ablation studies on the SGCNN model to examine how specific structural changes impact its performance. The results reveal that Ablation Model 1 significantly enhances accuracy, achieving an impressive 95%, while Ablation Model 2 maintains the baseline accuracy of 93%. Additionally, the Base CNN model demonstrates strong performance with a classification accuracy of 93%, whereas both the Lean CNN and Deep CNN models achieve 94% accuracy, indicating their competitive capabilities. To validate the models' effectiveness, we utilize multiple evaluation metrics, including accuracy, precision, recall, and F1-score, ensuring a thorough assessment of their performance. Our findings underscore that Ablation Model 1 (SGCNN Model 1) delivers the highest predictive accuracy among the tested models, highlighting its potential as a robust approach for Alzheimer's image classification. Ultimately, this research aims to facilitate early diagnosis and treatment of AD, contributing to improved patient outcomes and advancing the field of neurodegenerative disease diagnosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Alharbi, Juanatas, Al Hejaili and Lim.)

Introduction: White matter hyperintensities (WMHs) are frequently observed on magnetic resonance (MR) images in older adults, commonly appearing as areas of high signal intensity on fluid-attenuated inversion recovery (FLAIR) MR scans. Elevated WMH volumes are associated with a greater risk of dementia and stroke, even after accounting for vascular risk factors. Manual segmentation, while considered the ground truth, is both labor-intensive and time-consuming, limiting the generation of annotated WMH datasets. Un-annotated data are relatively available; however, the requirement of annotated data poses a challenge for developing supervised machine learning models., Methods: To address this challenge, we implemented a multi-stage semi-supervised learning (M3SL) approach that first uses un-annotated data segmented by traditional processing methods ("bronze" and "silver" quality data) and then uses a smaller number of "gold"-standard annotations for model refinement. The M3SL approach enabled fine-tuning of the model weights with the gold-standard annotations. This approach was integrated into the training of a U-Net model for WMH segmentation. We used data from three scanner vendors (over more than five scanners) and from both cognitively normal (CN) adult and patients cohorts [with mild cognitive impairment and Alzheimer's disease (AD)]., Results: An analysis of WMH segmentation performance across both scanner and clinical stage (CN, MCI, AD) factors was conducted. We compared our results to both conventional and transfer-learning deep learning methods and observed better generalization with M3SL across different datasets. We evaluated several metrics ( F -measure, IoU , and Hausdorff distance) and found significant improvements with our method compared to conventional ( p < 0.001) and transfer-learning ( p < 0.001)., Discussion: These findings suggest that automated, non-machine learning, tools have a role in a multi-stage learning framework and can reduce the impact of limited annotated data and, thus, enhance model performance., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Duarte, Sidhu, Barros, Gobbi, McCreary, Saad, Camicioli, Smith, Bento and Frayne.)

Introduction: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and impaired daily functioning. Despite significant research, AD remains incurable, highlighting the critical need for early diagnosis and intervention to improve patient outcomes. Timely detection plays a crucial role in managing the disease more effectively. Pretrained convolutional neural networks (CNNs) trained on large-scale datasets, such as ImageNet, have been employed for AD classification, providing a head start for developing more accurate models., Methods: This paper proposes a novel hybrid deep learning approach that combines the strengths of two specific pretrained architectures. The proposed model enhances the representation of AD-related patterns by leveraging the feature extraction capabilities of both networks. We validated this model using a large dataset of MRI images from AD patients. Performance was evaluated in terms of classification accuracy and robustness against noise, and the results were compared to several commonly used models in AD detection., Results: The proposed hybrid model demonstrated significant performance improvements over individual models, achieving an accuracy classification rate of 99.85%. Comparative analysis with other models further revealed the superiority of the new architecture, particularly in terms of classification rate and resistance to noise interference., Discussion: The high accuracy and robustness of the proposed hybrid model suggest its potential utility in early AD detection. By improving feature representation through the combination of two pretrained networks, this model could provide clinicians with a more reliable tool for early diagnosis and monitoring of AD progression. This approach holds promise for aiding in timely diagnoses and treatment decisions, contributing to better management of Alzheimer's disease., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer [ZM] declared a shared affiliation with the authors to the handling editor at the time of review., (Copyright © 2024 Slimi, Balti, Abid and Sayadi.)

Alzheimer's disease (AD) is a progressive neurodegenerative disorder pathologically characterized by the deposition of amyloid beta (Aβ) plaques and neurofibrillary tangles (NFTs) in the brain. The accumulation of these aggregated proteins causes memory and synaptic dysfunction, neuroinflammation, and oxidative stress. This research study is significant as it aims to assess the neuroprotective properties of vitamin E (VE) analog Trolox in an Aβ 1 - 42 -induced AD mouse model. Aβ 1 - 42 5μL/5min/mouse was injected intracerebroventricularly (i.c.v.) into wild-type adult mice brain to induce AD-like neurotoxicity. For biochemical analysis, Western blotting and confocal microscopy were performed. Remarkably, intraperitoneal (i.p.) treatment of Trolox (30 mg/kg/mouse for 2 weeks) reduced the AD pathology by reducing the expression of Aβ, phosphorylated tau (p-tau), and β-site amyloid precursor protein cleaving enzyme1 (BACE1) in both cortex and hippocampus regions of mice brain. Furthermore, Trolox-treatment decreased neuroinflammation by inhibiting Toll-like receptor 4 (TLR4), phosphorylated nuclear factor-κB (pNF-κB) and interleukin-1β (IL-1β), and other inflammatory biomarkers of glial cells [ionized calcium-binding adaptor molecule 1 (Iba1) and glial fibrillary acidic protein (GFAP)]. Moreover, Trolox reduced oxidative stress by enhancing the expression of nuclear factor erythroid-related factor 2 (NRF2) and heme oxygenase 1 (HO1). Similarly, Trolox-induced synaptic markers, including synaptosomal associated protein 23 (SNAP23), synaptophysin (SYN), and post-synaptic density protein 95 (PSD-95), and memory functions in AD mice. Our findings could provide a useful and novel strategy for investigating new medications to treat AD-associated neurodegenerative diseases., Competing Interests: MOK was employed by Alz-Dementia Korea Co. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Tahir, Kang, Park, Ali, Choe, Park and Kim.)

Introduction: Alzheimer's disease (AD) prevalence has increased in the last century which can be attributed to increased lifespan, but environment is also important. Exposure to artificial light at night is one environmental factor that may influence AD., Methods: This study evaluated the relationship between outdoor nighttime light exposure and AD prevalence in the United States using satellite acquired outdoor nighttime light intensity and Medicare data., Results: Higher outdoor nighttime light was associated with higher prevalence of AD. While atrial fibrillation, diabetes, hyperlipidemia, hypertension, and stroke were associated more strongly with AD prevalence than nighttime light intensity, nighttime light was more strongly associated with AD prevalence than alcohol abuse, chronic kidney disease, depression, heart failure, and obesity. Startlingly, nighttime light exposure more strongly associated with AD prevalence in those under the age of 65 than any other disease factor examined., Discussion: These data suggest light exposure at night may influence AD, but additional studies are needed., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Voigt, Ouyang and Keshavarzian.)

Identifying disease-specific imaging features of idiopathic Normal Pressure Hydrocephalus (iNPH) is crucial to develop accurate diagnoses, although the abnormal brain anatomy of patients with iNPH creates challenges in neuroimaging analysis. We quantified cortical thickness and volume using FreeSurfer 7.3.2 in 19 patients with iNPH, 28 patients with Alzheimer's disease (AD), and 30 healthy controls (HC). We noted the frequent need for manual correction of the automated segmentation in iNPH and examined the effect of correction on the results. We identified statistically significant higher proportion of volume changes associated with manual edits in individuals with iNPH compared to both HC and patients with AD. Changes in cortical thickness and volume related to manual correction were also partly correlated with the severity of radiological features of iNPH. We highlight the challenges posed by the abnormal anatomy in iNPH when conducting neuroimaging analysis and emphasise the importance of quality checking and correction in this clinical population., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor VC declared a past co-authorship with the author DS., (Copyright © 2024 Del Giovane, David, Kolanko, Gontsarova, Parker, Hampshire, Sharp, Malhotra and Carswell.)

Background: Dementia with Lewy bodies (DLB) can be difficult to distinguish from Alzheimer's disease (AD) and Parkinson's disease dementia (PDD) at different stages of its progression due to some overlaps in the clinical and neuropathological presentation of these conditions compared with DLB. Metallomic changes have already been observed in the AD and PDD brain-including widespread decreases in Cu levels and more localised alterations in Na, K, Mn, Fe, Zn, and Se. This study aimed to determine whether these metallomic changes appear in the DLB brain, and how the metallomic profile of the DLB brain appears in comparison to the AD and PDD brain., Methods: Brain tissues from ten regions of 20 DLB cases and 19 controls were obtained. The concentrations of Na, Mg, K, Ca, Zn, Fe, Mn, Cu, and Se were determined using inductively coupled plasma-mass spectrometry (ICP-MS). Case-control differences were evaluated using Mann-Whitney U tests. Results were compared with those previously obtained from AD and PDD brain tissue, and principal component analysis (PCA) plots were created to determine whether cerebral metallomic profiles could distinguish DLB from AD or PDD metallomic profiles., Results: Na was increased and Cu decreased in four and five DLB brain regions, respectively. More localised alterations in Mn, Ca, Fe, and Se were also identified. Despite similarities in Cu changes between all three diseases, PCA plots showed that DLB cases could be readily distinguished from AD cases using data from the middle temporal gyrus, primary visual cortex, and cingulate gyrus, whereas DLB and PDD cases could be clearly separated using data from the primary visual cortex alone., Conclusion: Despite shared alterations in Cu levels, the post-mortem DLB brain shows very few other similarities with the metallomic profile of the AD or PDD brain. These findings suggest that while Cu deficiencies appear common to all three conditions, metal alterations otherwise differ between DLB and PDD/AD. These findings can contribute to our understanding of the underlying pathogenesis of these three diseases; if these changes can be observed in the living human brain, they may also contribute to the differential diagnosis of DLB from AD and/or PDD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Scholefield, Church, Xu and Cooper.)

Alzheimer's disease (AD) affects the elderly population by causing memory impairments, cognitive and behavioral abnormalities. Currently, no curative treatments exist, emphasizing the need to explore therapeutic options that modify the progression of the disease. MicroRNAs (miRNAs), as non-coding RNAs, demonstrate multifaceted targeting potential and are known to be dysregulated in AD pathology. This mini review focuses on two promising miRNAs, hsa-miR-132 and hsa-miR-129, which consistently exhibit differential regulation in AD. By employing computational predictions and referencing published RNA sequencing dataset, we elucidate the intricate miRNA-mRNA target relationships associated with hsa-miR-132 and hsa-miR-129. Our review consistently identifies the downregulation of hsa-miR-132 and hsa-miR-129 in AD brains as a non-coding RNA molecular signature across studies conducted over the past 15 years in AD research., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Nagaraj, Quintanilla-Sánchez, Ando, Lopez-Gutierrez, Doeraene, Kosa, Aydin, Brion and Leroy.)

Objective: Early Alzheimer's disease (AD) diagnosis remains challenging, necessitating specific biomarkers for timely detection. This study aimed to identify such biomarkers and explore their associations with cognitive decline., Methods: A cohort of 1759 individuals across cognitive aging stages, including healthy controls (HC), mild cognitive impairment (MCI), and AD, was examined. Utilizing nine biomarkers from structural MRI (sMRI), diffusion tensor imaging (DTI), and positron emission tomography (PET), predictions were made for Mini-Mental State Examination (MMSE), Clinical Dementia Rating Scale Sum of Boxes (CDRSB), and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS). Biomarkers included four sMRI (e.g., average thickness [ATH]), four DTI (e.g., mean diffusivity [MD]), and one PET Amyloid-β (Aβ) measure. Ensemble regression tree (ERT) technique with bagging and random forest approaches were applied in four groups (HC/MCI, HC/AD, MCI/AD, and HC/MCI/AD)., Results: Aβ emerged as a robust predictor of cognitive scores, particularly in late-stage AD. Volumetric measures, notably ATH, consistently correlated with cognitive scores across early and late disease stages. Additionally, ADAS demonstrated links to various neuroimaging biomarkers in all subject groups, highlighting its efficacy in monitoring brain changes throughout disease progression. ERT identified key brain regions associated with cognitive scores, such as the right transverse temporal region for Aβ, left and right entorhinal cortex, left inferior temporal gyrus, and left middle temporal gyrus for ATH, and the left uncinate fasciculus for MD., Conclusion: This study underscores the importance of an interdisciplinary approach in understanding AD mechanisms, offering potential contributions to early biomarker development., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Hojjati and Babajani-Feremi.)

Introduction: Alzheimer's disease (AD) is associated with disturbed metabolism, prompting investigations into specific metabolic pathways that may contribute to its pathogenesis and pathology. Sphingolipids have garnered attention due to their known physiological impact on various diseases., Methods: We conducted comprehensive profiling of sphingolipids to understand their possible role in AD. Sphingolipid levels were measured in AD brains, Cerad score B brains, and controls, as well as in induced pluripotent stem (iPS) cells (AD, PS, and control), using liquid chromatography mass spectrometry., Results: AD brains exhibited higher levels of sphingosine (Sph), total ceramide 1-phosphate (Cer1P), and total ceramide (Cer) compared to control and Cerad-B brains. Deoxy-ceramide (Deoxy-Cer) was elevated in Cerad-B and AD brains compared to controls, with increased sphingomyelin (SM) levels exclusively in Cerad-B brains. Analysis of cell lysates revealed elevated dihydroceramide (dhSph), total Cer1P, and total SM in AD and PS cells versus controls. Multivariate analysis highlighted the relevance of Sph, Cer, Cer1P, and SM in AD pathology. Machine learning identified Sph, Cer, and Cer1P as key contributors to AD., Discussion: Our findings suggest the potential importance of Sph, Cer1P, Cer, and SM in the context of AD pathology. This underscores the significance of sphingolipid metabolism in understanding and potentially targeting mechanisms underlying AD., Competing Interests: The present study was a collaborative research project undertaken by The University of Tokyo and Nihon Waters Masayuki Kubota. ES is now an employee of Japan Waters Corporation. ES and MKb were employed by Nihon Waters K.K. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Uranbileg, Isago, Sakai, Kubota, Saito and Kurano.)

Introduction: Alzheimer's disease (AD), the most common form of dementia, is characterized by progressive cognitive decline. To address this, we conducted a randomized, double-blinded, sham-controlled study to investigate the therapeutic potential of transcranial direct current stimulation (tDCS) on patients with amyloid positron emission tomography (PET)- positive AD., Methods: Participants already undergoing pharmacological treatment and testing positive for amyloid PET were divided into Active-tDCS ( n  = 8) and Sham-tDCS ( n  = 8) groups. For 12 weeks, participants or their caregivers administered daily bi-frontal tDCS (YMS-201B+, Ybrain Inc., Seongnam, Korea) at home (2 mA, 30 min). Pre- and post-intervention assessments included neuropsychological tests and blood sample measurements for oligomerized beta-amyloid., Results: The Active-tDCS group demonstrated significant improvements in cognitive domains such as language abilities, verbal memory, and attention span and in frontal lobe functions compared to the Sham-tDCS group. Furthermore, the Active-tDCS group showed a marked reduction in post-intervention plasma Aβ oligomerization tendency level, suggesting changes in pivotal AD-associated biomarkers., Discussion: Our results emphasize the potential therapeutic benefits of tDCS for mild AD patients with amyloid PET positivity and stress the urgency for broader research, considering the global challenges of dementia and the need to pursue innovative therapeutic strategies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Kim and Yang.)

Background: Alzheimer's disease (AD) is the most common neurogenerative disorder, making up 70% of total dementia cases with a prevalence of more than 55 million people. Electroencephalogram (EEG) has become a suitable, accurate, and highly sensitive biomarker for the identification and diagnosis of AD., Methods: In this study, a public database of EEG resting state-closed eye recordings containing 36 AD subjects and 29 normal subjects was used. And then, three types of signal features of resting-state EEG, i.e., spectrum, complexity, and synchronization, were performed by applying various signal processing and statistical methods, to obtain a total of 18 features for each signal epoch. Next, the supervised machine learning classification algorithms of decision trees, random forests, and support vector machine (SVM) were compared in categorizing processed EEG signal features of AD and normal cases with leave-one-person-out cross-validation., Results: The results showed that compared to normal cases, the major change in EEG characteristics in AD cases was an EEG slowing, a reduced complexity, and a decrease in synchrony. The proposed methodology achieved a relatively high classification accuracy of 95.65, 95.86, and 88.54% between AD and normal cases for decision trees, random forests, and SVM, respectively, showing that the integration of spectrum, complexity, and synchronization features for EEG signals can enhance the performance of identifying AD and normal subjects., Conclusion: This study recommended the integration of EEG features of spectrum, complexity, and synchronization for aiding the diagnosis of AD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zheng, Wang, Liu, Wu, Sun, Fang, Jiang, Hu, Jin, Wei and Chen.)

Introduction: Diagnosing Alzheimer's disease (AD) lesions via visual examination of Electroencephalography (EEG) signals poses a considerable challenge. This has prompted the exploration of deep learning techniques, such as Convolutional Neural Networks (CNNs) and Visual Transformers (ViTs), for AD prediction. However, the classification performance of CNN-based methods has often been deemed inadequate. This is primarily attributed to CNNs struggling with extracting meaningful lesion signals from the complex and noisy EEG data., Methods: In contrast, ViTs have demonstrated proficiency in capturing global signal patterns. In light of these observations, we propose a novel approach to enhance AD risk assessment. Our proposition involves a hybrid architecture, merging the strengths of CNNs and ViTs to compensate for their respective feature extraction limitations. Our proposed Dual-Branch Feature Fusion Network (DBN) leverages both CNN and ViT components to acquire texture features and global semantic information from EEG signals. These elements are pivotal in capturing dynamic electrical signal changes in the cerebral cortex. Additionally, we introduce Spatial Attention (SA) and Channel Attention (CA) blocks within the network architecture. These attention mechanisms bolster the model's capacity to discern abnormal EEG signal patterns from the amalgamated features. To make well-informed predictions, we employ a two-factor decision-making mechanism. Specifically, we conduct correlation analysis on predicted EEG signals from the same subject to establish consistency., Results: This is then combined with results from the Clinical Neuropsychological Scale (MMSE) assessment to comprehensively evaluate the subject's susceptibility to AD. Our experimental validation on the publicly available OpenNeuro database underscores the efficacy of our approach. Notably, our proposed method attains an impressive 80.23% classification accuracy in distinguishing between AD, Frontotemporal dementia (FTD), and Normal Control (NC) subjects., Discussion: This outcome outperforms prevailing state-of-the-art methodologies in EEG-based AD prediction. Furthermore, our methodology enables the visualization of salient regions within pathological images, providing invaluable insights for interpreting and analyzing AD predictions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Chen, Wang, Zhang, Zhang and Tao.)

Participation in psychosocial enrichment activities, such as music and arts programming, have shown potential to delay or reduce functional decline - without adverse effects that can be associated with pharmaceuticals. The performing-arts programming described in this community case study was inspired by a community music program called B-Sharp Music Wellness, located in Phoenix, Arizona, which involved small groups of musicians who provided symphony performances for people with dementia. Our community programming sought to engage people with dementia and their informal care partner (typically a spouse) in existing performing-arts programs in their local community, providing social hours and season tickets for either symphony, dance (ballet), or non-musical theater performances. This case study describes the program history and design, including outcomes and lessons learned from the program evaluation of the last full season (2018-19) and partial season (2019-20), when the program was halted due to the COVID-19 pandemic. Program outcomes suggest strategies for, and benefits of, design for performing-arts programs as psychosocial interventions in other communities., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Malinin, Faw and Davalos.)

Background: Early screening of elderly individuals who are at risk of dementia allows timely medical interventions to prevent disease progression. The portable and low-cost electroencephalography (EEG) technique has the potential to serve it., Objective: We examined prefrontal EEG and event-related potential (ERP) variables in association with the predementia stages of Alzheimer's disease (AD)., Methods: One hundred elderly individuals were recruited from the GARD cohort. The participants were classified into four groups according to their amyloid beta deposition (A+ or A-) and neurodegeneration status (N+ or N-): cognitively normal (CN; A-N-, n = 27), asymptomatic AD (aAD; A + N-, n = 15), mild cognitive impairment (MCI) with AD pathology (pAD; A+N+, n = 16), and MCI with non-AD pathology (MCI(-); A-N+, n = 42). Prefrontal resting-state eyes-closed EEG measurements were recorded for five minutes and auditory ERP measurements were recorded for 8 min. Three variables of median frequency (MDF), spectrum triangular index (STI), and positive-peak latency (PPL) were employed to reflect EEG slowing, temporal synchrony, and ERP latency, respectively., Results: Decreasing prefrontal MDF and increasing PPL were observed in the MCI with AD pathology. Interestingly, after controlling for age, sex, and education, we found a significant negative association between MDF and the aAD and pAD stages with an odds ratio (OR) of 0.58. Similarly, PPL exhibited a significant positive association with these AD stages with an OR of 2.36. Additionally, compared with the MCI(-) group, significant negative associations were demonstrated by the aAD group with STI and those in the pAD group with MDF with ORs of 0.30 and 0.42, respectively., Conclusion: Slow intrinsic EEG oscillation is associated with MCI due to AD, and a delayed ERP peak latency is likely associated with general cognitive impairment. MCI individuals without AD pathology exhibited better cortical temporal synchronization and faster EEG oscillations than those with aAD or pAD., Significance: The EEG/ERP variables obtained from prefrontal EEG techniques are associated with early cognitive impairment due to AD and non-AD pathology. This result suggests that prefrontal EEG/ERP metrics may serve as useful indicators to screen elderly individuals' early stages on the AD continuum as well as overall cognitive impairment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Choi, Ku, Doan, Park, Cha, Kim and Lee.)

Vesicular Zn 2+ (zinc) is released at synapses and has been demonstrated to modulate neuronal responses. However, mechanisms through which dysregulation of zinc homeostasis may potentiate neuronal dysfunction and neurodegeneration are not well-understood. We previously reported that accumulation of soluble amyloid beta oligomers (AβO) at synapses correlates with synaptic loss and that AβO localization at synapses is regulated by synaptic activity and enhanced by the release of vesicular Zn 2+ in the hippocampus, a brain region that deteriorates early in Alzheimer's disease (AD). Significantly, drugs regulating zinc homeostasis inhibit AβO accumulation and improve cognition in mouse models of AD. We used both sexes of a transgenic mouse model lacking synaptic Zn 2+ (ZnT3KO) that develops AD-like cognitive impairment and neurodegeneration to study the effects of disruption of Zn 2+ modulation of neurotransmission in cognition, protein expression and activation, and neuronal excitability. Here we report that the genetic removal of synaptic Zn 2+ results in progressive impairment of hippocampal-dependent memory, reduces activity-dependent increase in Erk phosphorylation and BDNF mRNA, alters regulation of Erk activation by NMDAR subunits, increases neuronal spiking, and induces biochemical and morphological alterations consistent with increasing epileptiform activity and neurodegeneration as ZnT3KO mice age. Our study shows that disruption of synaptic Zn 2+ triggers neurodegenerative processes and is a potential pathway through which AβO trigger altered expression of neurotrophic proteins, along with reduced hippocampal synaptic density and degenerating neurons, neuronal spiking activity, and cognitive impairment and supports efforts to develop therapeutics to preserve synaptic zinc homeostasis in the brain as potential treatments for AD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Vogler, Mahavongtrakul, Sarkan, Bohannan, Catuara-Solarz and Busciglio.)

Introduction: Alzheimer's disease (AD) affects the whole brain from the cellular level to the entire brain network structure. The causal relationship among brain regions concerning the different AD stages is not yet investigated. This study used Dynamic Causal Modeling (DCM) method to assess effective connectivity (EC) and investigate the changes that accompany AD progression., Methods: We included the resting-state fMRI data of 34 AD patients, 31 late mild cognitive impairment (LMCI) patients, 34 early MCI (EMCI) patients, and 31 cognitive normal (CN) subjects selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The parametric Empirical Bayes (PEB) method was used to infer the effective connectivities and the corresponding probabilities. A linear regression analysis was carried out to test if the connection strengths could predict subjects' cognitive scores., Results: The results showed that the connections reduced from full connection in the CN group to no connection in the AD group. Statistical analysis showed the connectivity strengths were lower for later-stage patients. Linear regression analysis showed that the connection strengths were partially predictive of the cognitive scores., Discussion: Our results demonstrated the dwindling connectivity accompanying AD progression on causal relationships among brain regions and indicated the potential of EC as a loyal biomarker in AD progression., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Huang, Jung and Nam.)

Introduction: Down syndrome (DS) is a genetic disorder with an extra copy of chromosome 21 and DS remains one of the most common causes of intellectual disabilities in humans. All DS patients have Alzheimer's disease (AD)-like neuropathological changes including accumulation of plaques and tangles by their 40s, much earlier than the onset of such neuropathological changes in AD patients. Due to the lack of human samples and appropriate techniques, our understanding of DS neuropathology during brain development or before the clinical onset of the disease remains largely unexplored at the cellular and molecular levels. Methods: We used induced pluripotent stem cell (iPSC) and iPSC-derived 3D cortical organoids to model Alzheimer's disease in Down syndrome and explore the earliest cellular and molecular changes during DS fetal brain development. Results: We report that DS iPSCs have a decreased growth rate than control iPSCs due to a decreased cell proliferation. DS iPSC-derived cortical organoids have a much higher immunoreactivity of amyloid beta (Aß) antibodies and a significantly higher amount of amyloid plaques than control organoids. Although Elisa results did not detect a difference of Aß40 and Aß42 level between the two groups, the ratio of Aß42/Aß40 in the detergent-insoluble fraction of DS organoids was significantly higher than control organoids. Furthermore, an increased Tau phosphorylation (pTau S396) in DS organoids was confirmed by immunostaining and Western blot. Elisa data demonstrated that the ratio of insoluble Tau/total Tau in DS organoids was significantly higher than control organoids. Conclusion: DS iPSC-derived cortical organoids mimic AD-like pathophysiologyical phenotype in vitro , including abnormal Aß and insoluble Tau accumulation. The molecular neuropathologic signature of AD is present in DS much earlier than predicted, even in early fetal brain development, illustrating the notion that brain organoids maybe a good model to study early neurodegenerative conditions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhao and Haddad.)

Background: Alzheimer's disease (AD) is the most common form of age-related neurodegenerative disease. Unfortunately, due to the complexity of pathological types and clinical heterogeneity of AD, there is a lack of satisfactory treatment for AD. Previous studies have shown that microRNAs and transcription factors can modulate genes associated with AD, but the underlying pathophysiology remains unclear., Methods: The datasets GSE1297 and GSE5281 were downloaded from the gene expression omnibus (GEO) database and analyzed to obtain the differentially expressed genes (DEGs) through the "R" language "limma" package. The GSE1297 dataset was analyzed by weighted correlation network analysis (WGCNA), and the key gene modules were selected. Next, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis for the key gene modules were performed. Then, the protein-protein interaction (PPI) network was constructed and the hub genes were identified using the STRING database and Cytoscape software. Finally, for the GSE150693 dataset, the "R" package "survivation" was used to integrate the data of survival time, AD transformation status and 35 characteristics, and the key microRNAs (miRNAs) were selected by Cox method. We also performed regression analysis using least absolute shrinkage and selection operator (Lasso)-Cox to construct and validate prognostic features associated with the four key genes using different databases. We also tried to find drugs targeting key genes through DrugBank database., Results: GO and KEGG enrichment analysis showed that DEGs were mainly enriched in pathways regulating chemical synaptic transmission, glutamatergic synapses and Huntington's disease. In addition, 10 hub genes were selected from the PPI network by using the algorithm Between Centrality. Then, four core genes (TBP, CDK7, GRM5, and GRIA1) were selected by correlation with clinical information, and the established model had very good prognosis in different databases. Finally, hsa-miR-425-5p and hsa-miR-186-5p were determined by COX regression, AD transformation status and aberrant miRNAs., Conclusion: In conclusion, we tried to construct a network in which miRNAs and transcription factors jointly regulate pathogenic genes, and described the process that abnormal miRNAs and abnormal transcription factors TBP and CDK7 jointly regulate the transcription of AD central genes GRM5 and GRIA1. The insights gained from this study offer the potential AD biomarkers, which may be of assistance to the diagnose and therapy of AD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhang, Yang, Pang, Guo, Sun, Wei and Pang.)

Background: Impaired driving ability in patients with Alzheimer's disease (AD) is associated with a decline in cognitive processes and a deterioration of their basic sensory visual functions. Although a variety of ocular abnormalities have been described in patients with AD, little is known about the impact of those visual disorders on their driving performance., Aim: Aim of this mini-review is to provide an update on the driving ability of patients with dementia and summarize the primary visual disorders affecting their driving behavior., Methods: Databases were screened for studies investigating dementia, associated visual abnormalities and driving ability., Results: There is consistent evidence that dementia affects driving ability. Patients with dementia present with a variety of visual disorders, such as visual acuity reduction, visual field defects, impaired contrast sensitivity, decline in color vision and age-related pathological changes, that may have a negative impact on their driving ability. However, there is a paucity in studies describing the impact of oculovisual decline on the driving ability of AD subjects. A bidirectional association between cognitive and visual impairment (VI) has been described., Conclusion: Given the bidirectional association between VI and dementia, vision screening and cognitive assessment of the older driver should aim to identify at-risk individuals and employ timely strategies for treatment of both cognitive and ocular problems. Future studies should characterize the basic visual sensory status of AD patients participating in driving studies, and investigate the impact of vision abnormalities on their driving performance., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Papageorgiou, Tsirelis, Lazari, Siokas, Dardiotis and Tsironi.)

Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The neurosensory retina is an outgrowth of the Central Nervous System (CNS), and the eye is considered "a window to the brain." Reelin glycoprotein is directly involved in neurodevelopment, in synaptic plasticity, learning and memory. Consequently, abnormal Reelin signaling has been associated with brain neurodegeneration but its contributing role in ocular degeneration is still poorly explored. To this aim, experimental procedures were assayed on vitreous or retinas obtained from Reeler mice (knockout for Reelin protein) at different postnatal days (p) p14, p21 and p28. At p28, a significant increase in the expression of Amyloid Precursor Protein (APP) and its amyloidogenic peptide (Aβ1-42 along with truncated tau fragment (i.e., NH 2 htau)- three pathological hallmarks of Alzheimer's disease (AD)-were found in Reeler mice when compared to their age-matched wild-type controls. Likewise, several inflammatory mediators, such as Interleukins, or crucial biomarkers of oxidative stress were also found to be upregulated in Reeler mice by using different techniques such as ELLA assay, microchip array or real-time PCR. Taken together, these findings suggest that a dysfunctional Reelin signaling enables the expression of key pathological features which are classically associated with AD neurodegenerative processes. Thus, this work suggests that Reeler mouse might be a suitable animal model to study not only the pathophysiology of developmental processes but also several neurodegenerative diseases, such as AD and Age-related Macular Degeneration (AMD), characterized by accumulation of APP and/or Aβ1-42, NH 2 htau and inflammatory markers., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Balzamino, Esposito, Marino, Calissano, Latina, Amadoro, Keller, Cacciamani and Micera.)

Background: Since 2011, three large-scale genome-wide association studies (GWAS) have confirmed that the CD2AP rs9349407 polymorphism is significantly connected with Alzheimer's disease (AD) in individuals of European descent. Subsequently, this association has been replicated in European populations, but is unclear whether it can be replicated in Chinese. Recently, the correlation between rs9349407 and AD in the Chinese population has become a research hotspot., Objective: To explore the association between rs9349407 polymorphism and AD in the Chinese population., Materials and Methods: Firstly, based on the exclusion and inclusion criteria, we selected 11 independent studies from 8 articles exploring the correlation between rs9349407 variation and AD in Chinese. Secondly, we conducted a meta-analysis based on fixed and random effect models and conducted a heterogeneity test. Thirdly, we used the additive model, dominant model, and recessive model for subgroup analysis., Results: We demonstrated that the CD2AP rs9349407 polymorphism increases AD susceptibility in Chinese populations (OR = 1.33, 95% CI = 1.08-1.64, P = 7.45E-03), which is consistent with the effect observed in Caucasian populations. Additionally, subgroup analysis showed that rs9349407 under the additive model (GG + CC vs. GC, OR = 0.76, 95% CI = 0.61-0.97, P = 2.04E-02) and dominant model (GG + GC vs. CC, OR = 0.49, 95% CI = 0.32-0.74, P = 8.51E-04) were also significantly correlated with AD susceptibility, but not under the recessive model (GG vs. GC + CC, OR = 0.77, 95% CI = 0.58-1.03, P = 7.44E-02)., Conclusion: These existing data suggest that rs9349307 is significantly correlated with the susceptibility to AD in the Chinese population, but future studies with large samples are needed to confirm our findings., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Gao, Hao, Zhao, Li, Wang, Han, Sun, Sun and Liu.)

Alzheimer's disease (AD) is a highly damaging disease that affects one's cognition and memory and presents an increasing societal and economic burden globally. Considerable research has gone into understanding AD; however, there is still a lack of effective biomarkers that aid in early diagnosis and intervention. The recent discovery of the glymphatic system and associated Perivascular Spaces (PVS) has led to the theory that enlarged PVS (ePVS) may be an indicator of AD progression and act as an early diagnostic marker. Visible on Magnetic Resonance Imaging (MRI), PVS appear to enlarge when known biomarkers of AD, amyloid-β and tau, accumulate. The central goal of ePVS and AD research is to determine when ePVS occurs in AD progression and if ePVS are causal or epiphenomena. Furthermore, if ePVS are indeed causative, interventions promoting glymphatic clearance are an attractive target for research. However, it is necessary first to ascertain where on the pathological progression of AD ePVS occurs. This review aims to examine the knowledge gap that exists in understanding the contribution of ePVS to AD. It is essential to understand whether ePVS in the brain correlate with increased regional tau distribution and global or regional Amyloid-β distribution and to determine if these spaces increase proportionally over time as individuals experience neurodegeneration. This review demonstrates that ePVS are associated with reduced glymphatic clearance and that this reduced clearance is associated with an increase in amyloid-β. However, it is not yet understood if ePVS are the outcome or driver of protein accumulation. Further, it is not yet clear if ePVS volume and number change longitudinally. Ultimately, it is vital to determine early diagnostic criteria and early interventions for AD to ease the burden it presents to the world; ePVS may be able to fulfill this role and therefore merit further research., Competing Interests: Outside of the present work, the authors report additional funding from: Author TO’B reported funding from the National Health and Medical Research Council (NHMRC), Medical Research Future Fund (MRFF), Department of Industry, Science and Resources, and the National Institute of Neurological Disorders and Stroke (NINDS). Author TO’B institution has also received consultancy and research funding from UCB Pharma, Eisai, ES Therapeutics, Zynerba, Praxis Pharmaceuticals, and Biogen. Author LV reported research funding from Biogen, Eisai, and Life Molecular Imaging and research grants from the National Health and Medical Research Council (NHMRC), Medical Research Future Fund (MRFF), National Institute of Health (NIH), Department of Industry, Science and Resources, Victorian Accelerator Fund, Medical Research Future Fund (MRFF), and Multiple Sclerosis Research Australia (MSRA). Author MLa reported funding from the National Health and Medical Research Council (NHMRC), Medical Research Future Fund (MRFF), National Institute of Health (NIH), Australian Research Council (ARC), the Australian National Imaging Facility (NIF), American Society of Neuroradiology, and the Aftershock Foundation. Author MLa institution has also received consultancy and research funding from Siemens Healthineers and GE Healthcare. Author BS reported funding from the Department of Industry, Science, Energy, and Resources. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Lynch, Pham, Sinclair, O’Brien, Law and Vivash.)

Alzheimer's disease is a progressive neurodegenerative disorder characterized histologically in postmortem human brains by the presence of dense protein accumulations known as amyloid plaques and tau tangles. Plaques and tangles develop over decades of aberrant protein processing, post-translational modification, and misfolding throughout an individual's lifetime. We present a foundation of evidence from the literature that suggests chronic stress is associated with increased disease severity in Alzheimer's patient populations. Taken together with preclinical evidence that chronic stress signaling can precipitate cellular distress, we argue that chronic psychological stress renders select circuits more vulnerable to amyloid- and tau- related abnormalities. We discuss the ongoing investigation of systemic and cellular processes that maintain the integrity of protein homeostasis in health and in degenerative conditions such as Alzheimer's disease that have revealed multiple potential therapeutic avenues. For example, the endogenous cannabinoid system traverses the central and peripheral neural systems while simultaneously exerting anti-inflammatory influence over the immune response in the brain and throughout the body. Moreover, the cannabinoid system converges on several stress-integrative neuronal circuits and critical regions of the hypothalamic-pituitary-adrenal axis, with the capacity to dampen responses to psychological and cellular stress. Targeting the cannabinoid system by influencing endogenous processes or exogenously stimulating cannabinoid receptors with natural or synthetic cannabis compounds has been identified as a promising route for Alzheimer's Disease intervention. We build on our foundational framework focusing on the significance of chronic psychological and cellular stress on the development of Alzheimer's neuropathology by integrating literature on cannabinoid function and dysfunction within Alzheimer's Disease and conclude with remarks on optimal strategies for treatment potential., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Shade, Ross and Van Bockstaele.)

Mitochondria are essential organelle required for neuronal homeostasis. Mitochondria supply ATP and buffer calcium at synaptic terminals. However, the complex structural geometry of neurons poses a unique challenge in transporting mitochondria to synaptic terminals. Kinesin motors supply mitochondria to the axonal compartments, while cytoplasmic dynein is required for retrograde transport. Despite the importance of presynaptic mitochondria, how and whether axonal mitochondrial transport and distribution are altered in tauopathy neurons remain poorly studied. In the current study, we have shown that anterograde transport of mitochondria is reduced in P301L neurons, while there is no change in the retrograde transport. Consistently, axonal mitochondrial abundance is reduced in P301L neurons. We further studied the possible role of two opposing motor proteins on mitochondrial transport and found that mitochondrial association of kinesin is decreased significantly in P301L cells. Interestingly, fitting our experimental data into mathematical equations suggested a possible rise in dynein activity to maintain retrograde flux in P301L cells. Our data indicate that decreased kinesin-mediated transport coupled with sustained retrograde transport might reduce axonal mitochondria in tauopathy neurons, thus contributing to the synaptic deficits in Alzheimer's disease (AD) and other tauopathies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Sabui, Biswas, Somvanshi, Kandagiri, Gorla, Mohammed and Tammineni.)

Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Introduction: Transcranial pulse stimulation (TPS) is a non-invasive neuromodulation therapy that uses short, repetitive shockwaves through a neuro-navigated device. Current research suggests that these pulses lead to a wide range of vascular, metabolic, and neurotrophic changes. This relatively new CE-marked treatment provided first promising results in a clinical pilot study for improving cognition in mild-to-moderate Alzheimer's. Data from other centers is lacking, so here we analyzed safety and pilot real-world short-term results of TPS from the first center in Germany. To gain information about effects in different stages, patients with not only mild but also moderate-to-severe Alzheimer's were analyzed., Methods: A total of 11 patients were retrospectively examined for cognitive and emotional function before and after the first stimulation series. The effect was assessed using several neuropsychological tests [Alzheimer's Disease Assessment Scale (ADAS), including the ADAS cognitive score (ADAS Cog) and ADAS affective scores, Mini-Mental Status Examination (MMSE), and Montreal Cognitive Assessment (MoCA)] including in comparison between the groups of mild-to-severe patients. Moreover, subjective improvement of symptom severity, potential effects on depressive symptoms, and side effects were analyzed using Numeric Rating Scales (NRS)., Results: Side effects were rare (in 4% of sessions) with moderate subjective severity and only transient. Patients significantly improved in the ADAS and ADAS Cog, while there was no significant effect in MMSE and MoCA. Patients' self-reported symptom severity improved significantly. The depressive symptoms measured in an ADAS subscale also improved significantly. Statistical data analyses revealed no significant correlation of clinical improvement with baseline symptom severity., Conclusion: TPS might be a safe and promising add-on therapy for Alzheimer's, even for moderate-to-severe patients. More research on long-term effects in patients as well as studies with sham control groups is needed. Moreover, translational research on the mechanisms of action and effects on cerebral network physiology will be needed to understand this new neuromodulation technique., Competing Interests: Author CC received travel fees from Storz Medical. LW has previously received funding grants and institutional support from the German Research Foundation, Hilde-Ulrichs-Stiftung für Parkinsonforschung, and the ParkinsonFonds Germany, BMBF/ERA-NETNEURON, DFG Forschergruppe (FOR1328), Deutsche Parkinson Vereinigung (DPV), Forschungskommission, Medizinische Fakultät, HHU Düsseldorf, UCB; Medtronic, UCB, Teva, Allergan, Merz, Abbvie, Roche, Bial, Merck, Novartis, Desitin, Spectrum. LW owned stock in company BioNTech SE. He is consultant to the following companies or received travel honarium from: TEVA, UCB Schwarz, Desitin, Medtronic, Abbott/Abbvie, MEDA, Boehringer I, Storz Medical, Kyowa Kirin, Guidepoint, Merck, Merz, Synergia, BIAL, Zambon, Sapio Life, STADA, Inomed, Vertanical. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Cont, Stute, Galli, Schulte, Logmin, Trenado and Wojtecki.)

Age-related neurological disorders [AND] include neurodegenerative diseases [NDDs] such as Alzheimer's disease [AD] and Parkinson's disease [PD], which are the most prevalent types of dementia in the elderly. It also includes other illnesses such as migraine and epilepsy. ANDs are multifactorial, but aging is their major risk factor. The most frequent and vital pathological features of AND are oxidative stress, inflammation, and accumulation of misfolded proteins. As AND brain damage is a significant public health burden and its incidence is increasing, much has been done to overcome it. Pomegranate ( Punica granatum L .) is one of the polyphenol-rich fruits that is widely mentioned in medical folklore. Pomegranate is commonly used to treat common disorders such as diarrhea, abdominal pain, wound healing, bleeding, dysentery, acidosis, microbial infections, infectious and noninfectious respiratory diseases, and neurological disorders. In the current review article, we aimed to summarize the data on the pharmacotherapeutic potentials of pomegranate in ANDs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Emami Kazemabad, Asgari Toni, Tizro, Dadkhah, Amani, Akhavan Rezayat, Sheikh, Mohammadi, Alijanzadeh, Alimohammadi, Shahrokhi, Erabi, Noroozi, Karimi, Honari and Deravi.)

Despite the extensive knowledge of the beneficial effects of physical exercise, a sedentary lifestyle is still a predominant harm in our society. Sedentarism is one of the major modifiable risk factors for metabolic diseases such as diabetes mellitus, obesity and neurological disorders, including Alzheimer's disease (AD)-characterized by synaptic failure, amyloid protein deposition and memory loss. Physical exercise promotes neuroprotective effects through molecules released in circulation and mediates the physiological crosstalk between the periphery and the brain. This literature review summarizes the current understanding of the roles of exerkines, molecules released during physical exercise, as systemic and central factors that mediate the beneficial effects of physical exercise on cognition. We highlight the neuroprotective role of irisin-a myokine released from the proteolytic cleavage of fibronectin type III domain-containing protein 5 (FNDC5) transmembrane protein. Lastly, we review evidence pointing to physical exercise as a potential preventative and interventional strategy against cognitive decline in AD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Rody, De Amorim and De Felice.)

Alzheimer's disease (AD) is an intractable and progressive neurodegenerative disorder that can lead to severe cognitive decline, impaired speech, short-term memory loss, and finally an inability to function in daily life. For patients, their families, and even all of society, AD can impart great emotional pressure and economic costs. Therefore, this study aimed to investigate potential diagnostic biomarkers of AD. Using the Gene Expression Omnibus (GEO) database, the expression profiles of genes were extracted from the GSE5281, GSE28146, and GSE48350 microarray datasets. Then, immune-related genes were identified by the intersections of differentially expressed genes (DEGs). Functional enrichment analyses, including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Disease Ontology (DO), and Gene Set Enrichment Analysis (GSEA), were performed. Subsequently, random forest models and least absolute shrinkage and selection operator regression were used to further screen hub genes, which were then validated using receiver operating characteristic (ROC) curve analysis. Finally, 153 total immune-related DEGs were identified in relation to AD. DO analysis of these immune-related DEGs showed that they were enriched in "lung disease," "reproductive system disease," and "atherosclerosis." Single GSEA of hub genes showed that they were particularly enriched in "oxidative phosphorylation." ROC analysis of AGAP3 yielded an area under the ROC curve of 0.878 for GSE5281, 0.727 for GSE28146, and 0.635 for GSE48350. Moreover, immune infiltration analysis demonstrated that AGAP3 was related to follicular helper T cells, naïve CD4 T cells, naïve B cells, memory B cells, macrophages M0, macrophages M1, macrophages M2, resting natural killer (NK) cells, activated NK cells, monocytes, neutrophils, eosinophils, and activated mast cells. These results indicate that identifying immune-related DEGs might enhance the current understanding of the development and prognosis of AD. Furthermore, AGAP3 not only plays a vital role in AD progression and diagnosis but could also serve as a valuable target for further research on AD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer XD-P declared a shared parent affiliation with the author HZ to the handling editor at the time of review., (Copyright © 2022 Zhao, Zhang, Wu, Liu, Li and Lin.)

Background: Recent research has investigated the connection between Diabetes Mellitus (DM) and Alzheimer's Disease (AD). Insulin resistance plays a crucial role in this interaction. Studies have focused on dysregulated proteins to disrupt this connection. Non-coding RNAs (ncRNAs), on the other hand, play an important role in the development of many diseases. They encode the majority of the human genome and regulate gene expression through a variety of mechanisms. Consequently, identifying significant ncRNAs and utilizing them as biomarkers could facilitate the early detection of this cross-talk. On the other hand, computational-based methods may help to understand the possible relationships between different molecules and conduct future wet laboratory experiments., Materials and Methods: In this study, we retrieved Genome-Wide Association Study (GWAS, 2008) results from the United Kingdom Biobank database using the keywords "Alzheimer's" and "Diabetes Mellitus." After excluding low confidence variants, statistical analysis was performed, and adjusted p -values were determined. Using the Linkage Disequilibrium method, 127 significant shared Single Nucleotide Polymorphism (SNP) were chosen and the SNP-SNP interaction network was built. From this network, dense subgraphs were extracted as signatures. By mapping each signature to the reference genome, genes associated with the selected SNPs were retrieved. Then, protein-microRNA (miRNA) and miRNA-long non-coding RNA (lncRNA) bipartite networks were built and significant ncRNAs were extracted. After the validation process, by applying the scoring function, the final protein-miRNA-lncRNA tripartite network was constructed, and significant miRNAs and lncRNAs were identified., Results: Hsa-miR-199a-5p, hsa-miR-199b-5p, hsa-miR-423-5p, and hsa-miR-3184-5p, the four most significant miRNAs, as well as NEAT1, XIST, and KCNQ1OT1, the three most important lncRNAs, and their interacting proteins in the final tripartite network, have been proposed as new candidate biomarkers in the cross-talk between DM and AD. The literature review also validates the obtained ncRNAs. In addition, miRNA/lncRNA pairs; hsa-miR-124-3p/KCNQ1OT1, hsa-miR-124-3p/NEAT1, and hsa-miR-124-3p/XIST, all expressed in the brain, and their interacting proteins in our final network are suggested for future research investigation., Conclusion: This study identified 127 shared SNPs, 7 proteins, 15 miRNAs, and 11 lncRNAs involved in the cross-talk between DM and AD. Different network analysis and scoring function suggested the most significant miRNAs and lncRNAs as potential candidate biomarkers for wet laboratory experiments. Considering these candidate biomarkers may help in the early detection of DM and AD co-occurrence., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ghiam, Eslahchi, Shahpasand, Habibi-Rezaei and Gharaghani.)

This study aimed to investigate the effect of cognitive reserve (CR) on the rate of cognitive decline and cerebral glucose metabolism in amnestic mild cognitive impairment (MCI) using the Study on Diagnosis of Early Alzheimer's Disease-Japan (SEAD-J) dataset. The patients in SEAD-J underwent cognitive tests and fluorodeoxyglucose-positron emission tomography (FDG-PET). MCI to be studied was classified as amnestic MCI due to Alzheimer's disease (AD) with neurodegeneration. A total of 57 patients were visually interpreted as having an AD pattern (P1 pattern, Silverman's classification). The 57 individuals showing the P1 pattern were divided into a high-education group (years of school education ≥13, N = 18) and a low-education group (years of school education ≤12, N = 39). Voxel-based statistical parametric mapping revealed more severe hypometabolism in the high-education group than in the low-education group. Glucose metabolism in the hippocampus and temporoparietal area was inversely associated with the years of school education in the high- and low-education groups ( N = 57). General linear mixed model analyses demonstrated that cognitive decline was more rapid in the high-education group during 3-year follow-up. These results suggest that the cerebral glucose metabolism is lower and cognitive function declines faster in patients with high CR of amnestic MCI due to AD defined by FDG-PET., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Kato, Nishita, Otsuka, Inui, Nakamura, Kimura, Ito and SEAD-J Study Group.)

Neuropathologically, Alzheimer's disease (AD) is characterized by the accumulation of amyloid-beta peptide (Aβ) and subsequent formation of the so-called Aβ plaques. Along with neuronal loss, previous studies report white matter anomalies and corpus callosum (CC) atrophy in AD patients. Notably, perturbations in the white matter can be observed years before expected disease onset, suggesting that early stages of disease progression play a role in AD-associated loss of myelin integrity. Through seed-induced deposition of Aβ, we are able to examine alterations of central nervous system (CNS) integrity during the initial stages of plaque formation. In this study, we investigate the impact of Aβ seeding in the CC utilizing various imaging techniques as well as quantitative gene expression analysis and demonstrate that Aβ deposits result in an imbalance of glial cells in the CC. We found increased amounts of phagocytic microglia and reactive astrocytes, while oligodendrocyte progenitor cell (OPC) numbers were reduced. Moreover, white matter aberrations adjacent to the Aβ seeding were observed together with an overall decline in callosal myelination. This data indicate that the initial stages of plaque formation induce oligodendrocyte dysfunction, which might ultimately lead to myelin loss., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Aires, Ziegler-Waldkirch, Friesen, Reichardt, Erny, Loreth, Harborne, Kretz, von Elverfeldt and Meyer-Luehmann.)

Background: Alzheimer's disease (AD) and vascular dementia (VaD) are the two most common types of neurodegenerative dementia among the elderly with similar symptoms of cognitive decline and overlapping neuropsychological profiles. Biological markers to distinguish patients with VaD from AD would be very useful. We aimed to investigate the expression of blood-brain barrier (BBB)-related blood-borne factors of soluble low-density lipoprotein receptor-related protein 1 (sLRP1), cyclophilin A (CyPA), and matrix metalloproteinase 9 (MMP9) and its correlation with cognitive function between patients with AD and VaD., Materials and Methods: Plasma levels of sLRP1, CyPA, and MMP9 were analyzed in 26 patients with AD, 27 patients with VaD, and 27 normal controls (NCs). Spearman's rank correlation analysis was used to explore the relationships among biomarker levels, cognitive function, and imaging references. Receiver operating characteristic (ROC) curve analysis was used to discriminate the diagnosis of AD and VaD., Results: Among these BBB-related factors, plasma CyPA levels in the VaD group were significantly higher than that in the AD group ( p < 0.05). Plasma sLRP1 levels presented an increasing trend in VaD while maintaining slightly low levels in patients with AD ( p > 0.05). Plasma MMP9 in different diagnostic groups displayed the following trend: VaD group > AD group > NC group, but the difference was not statistically significant ( p > 0.05). Furthermore, plasma sLRP1 levels were positively related to MoCA scores, and plasma CyPA levels were significantly correlated with MTA scores ( p < 0.05) in the AD group. Plasma MMP9 levels were negatively correlated with MoCA scores ( p < 0.05) in the VaD groups. No significant correlation was detected between the other factors and different cognitive scores ( p > 0.05). ROC analysis showed a good preference of plasma CyPA [AUC = 0.725, 95% CI (0.586-0.865); p = 0.0064] in diagnosis., Conclusion: The plasma CyPA level is a reference index when distinguishing between an AD and subcortical ischemic vascular dementia (SIVD) diagnosis. Blood-derived factors associated with the BBB may provide new insights into the differential diagnosis of neurodegenerative dementia and warrant further investigation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Gong and Jia.)

Standardized tests of learning and memory are sensitive to changes associated with both aging and superimposed neurodegenerative diseases. Unfortunately, repeated behavioral test administration can be confounded by practice effects (PE), which may obscure declines in level of abilities and contribute to misdiagnoses. Growing evidence, however, suggests PE over successive longitudinal measurements may differentially predict cognitive status and risk for progressive decline associated with aging, mild cognitive impairment (MCI), and dementia. Thus, when viewed as a reflection of neurocognitive plasticity, PE may reveal residual abilities that can add to our understanding of age- and disease-related changes in learning and memory. The present study sought to evaluate differences in PE and verbal recall in a clinically characterized aging cohort assessed on multiple occasions over 3 years. Participants included 256 older adults recently diagnosed as cognitively unimpaired (CU; n = 126), or with MCI of amnestic ( n = 65) or non-amnestic MCI ( n = 2085), and multi-domain amnestic dementia of the Alzheimer's type (DAT; n = 45). We applied a continuous time structural equation modeling (ctsem) approach to verbal recall performance on the Hopkins Verbal Learning Test in order to distinguish PE from individual occasion performance, coupled random changes, age trends, and differing measurement quality. Diagnoses of MCI and dementia were associated with lower recall performance on all trials, reduced PE gain per occasion, and differences in non-linear dynamic parameters. Practice self-feedback is a dynamic measure of the decay or acceleration in PE process changes over longitudinal occasions. As with PE and mean recall, estimated practice self-feedback followed a gradient from positive in CU participants to null in participants with diagnosed MCI and negative for those with dementia diagnoses. Evaluation of sensitivity models showed this pattern of variation in PE was largely unmodified by differences in age, sex, or educational attainment. These results show dynamic modeling of PE from longitudinal performance on standardized learning and memory tests can capture multiple aspects of behavioral changes in MCI and dementia. The present study provides a new perspective for modeling longitudinal change in verbal learning in clinical and cognitive aging research., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Bender, Ganguli, Meiring, Hampstead and Driver.)

Prior studies have demonstrated a close association between brain insulin resistance and Alzheimer's disease (AD), while selenium supplementation was shown to improve insulin homeostasis in AD patients and to exert neuroprotective effects in a mouse model of AD. However, the mechanisms underlying the neuroprotective actions of selenium remain incompletely understood. In this study, we performed a label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) quantitative proteomics approach to analyze differentially expressed proteins (DEPs) in the hippocampus and cerebral cortex of Aβ precursor protein (APP)/presenilin-1 (PS1) mice following 2 months of treatment with sodium selenate. A total of 319 DEPs (205 upregulated and 114 downregulated proteins) were detected after selenium treatment. Functional enrichment analysis revealed that the DEPs were mainly enriched in processes affecting axon development, neuron differentiation, tau protein binding, and insulin/insulin-like growth factor type 1 (IGF1)-related pathways. These results demonstrate that a number of insulin/IGF1 signaling pathway-associated proteins are differentially expressed in ways that are consistent with reduced central insulin resistance, suggesting that selenium has therapeutic value in the treatment of neurodegenerative and metabolic diseases such as AD and non-alcoholic fatty liver disease (NAFLD)., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Xu, Qi, Zhang, Sun, Yan, Sun and Liu.)