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Background: Dementia occurring before age 65 is known as young-onset dementia (YOD), with Alzheimer's disease being the most common type. YOD poses unique challenges for persons and families, impacting their working-age years and family responsibilities. Person-centered interventions and services are essential to improve their quality of life and social engagement. Objective: This study aims to synthesize non-pharmacological interventions for persons with YOD and their families to inform future targeted interventions. Methods: We conducted a systematic literature search across four databases: PubMed, PsycINFO, Scopus, and CINAHL. The included articles were carefully screened, categorized, and synthesized by following Arksey and O'Malley's five stages framework. Results: We included 20 studies reported in 24 papers, with 11 studies (14 papers) on persons with YOD and nine studies (10 papers) on families. Quantitative intervention results vary, but qualitative interviews show positive feedback. Stakeholders provided positive evaluations, stating these interventions provided a sense of normalcy, facilitated communication among families, enhanced the independence of persons with YOD, and improved the families' caregiving self-efficacy, thereby reducing care burden and psychological distress. The heterogeneity among the studies posed integration challenges. Conclusions: Interventions for YOD can improve the quality of life for both persons with YOD and their families. More extensive intervention studies are urgently needed, especially in developing countries, with a focus on family-centered and life course perspectives. In future intervention research design, a more extensive incorporation of stakeholder involvement is essential for successful implementation. Moreover, the integration of new technologies shows promise as a potential avenue for intervention advancement. [ABSTRACT FROM AUTHOR]

Advances in biomarker-based diagnostic modalities, recent approval of anti-amyloid monoclonal antibodies for early Alzheimer's disease (AD; mild cognitive impairment or mild dementia due to AD) and late-stage clinical development of other disease-modifying therapies for AD necessitate a significant paradigm shift in the early detection, diagnosis and management of AD. Anti-amyloid monoclonal antibodies target the underlying pathophysiological mechanisms of AD and have demonstrated a significant reduction in the rate of clinical decline in cognitive and functional outcome measures in patients with early AD. With growing recognition of the benefit of early interventions in AD, an increasing number of people may seek diagnosis for their subjective cognitive problems in an already busy medical system. Various factors such as limited examination time, lack of expertise for cognitive assessment and limited access to specialized tests can impact diagnostic accuracy and timely detection of AD. To overcome these challenges, a new model of care will be required. In this paper, we provide practical guidance for institutional readiness for anti-amyloid therapies for early AD in Asia, in terms of best practices for identifying eligible patients and diagnosing them appropriately, safe administration of anti-amyloid monoclonal antibodies and monitoring of treatment, managing potential adverse events such as infusion reactions and amyloid-related imaging abnormalities, and cross-disciplinary collaboration. Education and training will be the cornerstone for the establishment of new pathways of care for the identification of patients with early AD and delivery of anti-amyloid therapies in a safe and efficient manner to eligible patients. [ABSTRACT FROM AUTHOR]

Background: Dementia is a general term for several progressive neurodegenerative disorders including Alzheimer's disease. Timely and accurate detection is crucial for early intervention. Advancements in artificial intelligence present significant potential for using machine learning to aid in early detection. Objective: Summarize the state-of-the-art machine learning-based approaches for dementia prediction, focusing on non-invasive methods, as the burden on the patients is lower. Specifically, the analysis of gait and speech performance can offer insights into cognitive health through clinically cost-effective screening methods. Methods: A systematic literature review was conducted following the PRISMA protocol (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The search was performed on three electronic databases (Scopus, Web of Science, and PubMed) to identify the relevant studies published between 2017 to 2022. A total of 40 papers were selected for review. Results: The most common machine learning methods employed were support vector machine followed by deep learning. Studies suggested the use of multimodal approaches as they can provide comprehensive and better prediction performance. Deep learning application in gait studies is still in the early stages as few studies have applied it. Moreover, including features of whole body movement contribute to better classification accuracy. Regarding speech studies, the combination of different parameters (acoustic, linguistic, cognitive testing) produced better results. Conclusions: The review highlights the potential of machine learning, particularly non-invasive approaches, in the early prediction of dementia. The comparable prediction accuracies of manual and automatic speech analysis indicate an imminent fully automated approach for dementia detection. [ABSTRACT FROM AUTHOR]

Background: Currently, no evidence exists on the expression of apoptosis (CASP3), autophagy (BECN1), and mitophagy (BNIP3) genes in the CA3 area after ischemia with long-term survival. Objective: The goal of the paper was to study changes in above genes expression in CA3 area after ischemia in the period of 6–24 months. Methods: In this study, using quantitative RT-PCR, we present the expression of genes associated with neuronal death in a rat ischemic model of Alzheimer's disease. Results: First time, we demonstrated overexpression of the CASP3 gene in CA3 area after ischemia with survival ranging from 0.5 to 2 years. Overexpression of the CASP3 gene was accompanied by a decrease in the activity level of the BECN1 and BNIP3 genes over a period of 0.5 year. Then, during 1-2 years, BNIP3 gene expression increased significantly and coincided with an increase in CASP3 gene expression. However, BECN1 gene expression was variable, increased significantly at 1 and 2 years and was below control values 1.5 years post-ischemia. Conclusions: Our observations suggest that ischemia with long-term survival induces neuronal death in CA3 through activation of caspase 3 in cooperation with the pro-apoptotic gene BNIP3. This study also suggests that the BNIP3 gene regulates caspase-independent pyramidal neuronal death post-ischemia. Thus, caspase-dependent and -independent death of neuronal cells occur post-ischemia in the CA3 area. Our data suggest new role of the BNIP3 gene in the regulation of post-ischemic neuronal death in CA3. This suggests the involvement of the BNIP3 together with the CASP3 in the CA3 in neuronal death post-ischemia. [ABSTRACT FROM AUTHOR]

Dementia is a syndrome characterized by cognitive and neuropsychiatric symptoms associated with progressive functional decline (FD). FD is a core diagnostic criterion for dementia, setting the threshold between its prodromal stages and the full-blown disease. The operationalization of FD continues to generate a great deal of controversy. For instance, the threshold of FD for the diagnosis of dementia varies across diagnostic criteria, supporting the need for standardization of this construct. Moreover, there is a need to reconsider how we are measuring FD to set boundaries between normal aging, mild cognitive impairment, and dementia. In this paper, we propose a multidimensional framework that addresses outstanding issues in the assessment of FD: i) What activities of daily living (ADLs) are necessary to sustain an independent living in aging? ii) How to assess FD in individuals with suspected neurocognitive disorders? iii) To whom is the assessment directed? and iv) How much does FD differentiate healthy aging from mild and major neurocognitive disorders? Importantly, the To Whom Question introduces a person-centered approach that regards patients and caregivers as active agents in the assessment process of FD. Thus, once impaired ADLs have been identified, patients can indicate how significant such impairments are for them in daily life. We envisage that this new framework will guide future strategies to enhance functional assessment and treatment of patients with dementia and their caregivers. [ABSTRACT FROM AUTHOR]

Alzheimer's disease and related dementias (ADRD) present significant challenges including cognitive and functional loss, behavioral disruption, emotional distress, and significant financial burden. These stressors are amplified in minority groups, who experience higher rates of ADRD but less frequent and later diagnosis. There is therefore a critical need to identify tangible approaches to culturally informed dementia assessment and care for patients from diverse communities. Muslim patients and particularly Muslim women are among the populations most understudied in the ADRD space. Muslim patients may hold unique religious, spiritual, and cultural beliefs and practices that can impact care-seeking for dementia symptoms, diagnostic accuracy, and treatment uptake. This paper outlines culturally informed approaches to assessing and treating Muslim women and families at each stage of ADRD care, though many recommendations extend to the broader Muslim community and others of diverse racial-ethnic backgrounds. We provide concrete suggestions for building rapport within and leveraging common family structures, respecting principles of modesty and privacy for all women including those who observe hijab or niqab, and communicating dementia diagnosis and care in the context of spiritual and ethical beliefs. While not intended as a comprehensive and prescriptive guide, this review provides important points of consideration and discussion with patients of Muslim backgrounds. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive neurodegenerative disease with limited therapeutic strategies. NB-02 is a novel botanical drug that has shown promise as a protective and therapeutic treatment for AD in an APP/PS1 preclinical mouse model. In this paper, we investigate the underlying mechanisms by which NB-02 provides these therapeutic advantages using in vitro neuron-astrocyte co-cultures. Pretreatment with NB-02 prevented pathological calcium elevations in neurons and astrocytes after application of toxic soluble amyloid-β (Aβ) oligomers. NB-02 also prevented cell death associated with the addition of soluble Aβ oligomers suggesting NB-02 is effective at protecting both neurons and astrocytes from Aβ-mediated damage. [ABSTRACT FROM AUTHOR]

Alzheimer's disease is the leading cause of dementia in the world. It affects 6 million people in the United States and 50 million people worldwide. Alzheimer's disease is characterized by the accumulation of amyloid-β plaques (Aβ), an increase in tau protein neurofibrillary tangles, and a loss of synapses. Since the 1990s, removing and reducing Aβ has been the focus of Alzheimer's treatment and prevention research. The accumulation of Aβ can lead to oxidative stress, inflammation, neurotoxicity, and eventually apoptosis. These insults impair signaling systems in the brain, potentially leading to memory loss and cognitive decline. Aniracetam is a safe, effective, cognitive-enhancing drug that improves memory in both human and animal studies. Aniracetam may prevent the production and accumulation of Aβ by increasing α-secretase activity through two distinct pathways: 1) increasing brain derived neurotrophic factor expression and 2) positively modulating metabotropic glutamate receptors. This is the first paper to propose an evidence-based model for aniracetam reducing the accumulation and production of Aβ. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease that is not easily detected in the early stage. Handwriting and walking have been shown to be potential indicators of cognitive decline and are often affected by AD. Objective: This study proposes an assisted screening framework for AD based on multimodal analysis of handwriting and gait and explores whether using a combination of multiple modalities can improve the accuracy of single modality classification. Methods: We recruited 90 participants (38 AD patients and 52 healthy controls). The handwriting data was collected under four handwriting tasks using dot-matrix digital pens, and the gait data was collected using an electronic trail. The two kinds of features were fused as inputs for several different machine learning models (Logistic Regression, SVM, XGBoost, Adaboost, LightGBM), and the model performance was compared. Results: The accuracy of each model ranged from 71.95% to 96.17%. Among them, the model constructed by LightGBM had the best performance, with an accuracy of 96.17%, sensitivity of 95.32%, specificity of 96.78%, PPV of 95.94%, NPV of 96.74%, and AUC of 0.991. However, the highest accuracy of a single modality was 93.53%, which was achieved by XGBoost in gait features. Conclusions: The research results show that the combination of handwriting features and gait features can achieve better classification results than a single modality. In addition, the assisted screening model proposed in this study can achieve effective classification of AD, which has development and application prospects. [ABSTRACT FROM AUTHOR]

Activation of cell-cycle machinery in Alzheimer's disease (AD) brain was reported by Mark Smith and colleagues and by other researchers. Among other biochemical processes underlying this activation, the notion that AD brain, under the onslaught of oxidative and nitrosative damage leading to neuronal loss, neurons would attempt to replenish their numbers by entering the cell cycle. However, being post-mitotic, neurons entering the cell cycle would become trapped therein, ultimately leading to death of these neurons. Yang and co-workers and the Butterfield laboratory first reported that similar activation of the cell cycle was present in the brains of individuals with amnestic mild cognitive impairment (MCI), arguably the earliest clinical stage of AD, but who demonstrate normal activities of daily living and no dementia. Activation of the cell cycle in MCI brain is consonant with the concept that this process is an early aspect in the progression of AD. This brief review article discusses these findings and recognizes the contribution of Dr. Mark Smith to the investigation of cell-cycle activation in AD brain and other aspects of AD neuropathology. [ABSTRACT FROM AUTHOR]

Background: Increased understanding of dementia risk-reduction and early detection of Alzheimer's disease and related disorders has spurred interest in the identification of risks for dementia, underlying putative biologies, or dementia itself. Implementation of such approaches require acceptability to the public. Research prior to 2012 indicated limited acceptability for population dementia screening. The changing landscape of dementia prevention research may influence recent perceptions. Additionally, perspectives from underserved populations, such as ethnic minorities and low socio-economic groups, are lacking. Objective: In this systematic review, we sought published studies since 2012 on attitudes and preferences of people with dementia, carers and the general public from ethnic minorities and low socio-economic groups regarding dementia screening. Methods: This review was preregistered on PROSPERO (CRD42023384115) and followed PRISMA guidelines. Key search terms were entered into five databases. Articles were included if they focused on population or risk screening for dementia via primary/community care-based assessments, and which included majority ethnic minority or low socio-economic groups or discretely considered these groups in data analysis. Data were synthesized narratively. Results: Seven studies reported perspectives of ethnic minorities regarding dementia screening; one study included people from low socio-economic groups. Results indicated that participants from ethnic minorities were willing to undergo dementia screening. Predictors of willingness included belief in benefits, desire to boost diversity, and to implement lifestyle changes. Unwillingness was associated with anxiety regarding results. Conclusions: Although there seems to be high acceptability for screening in the studied groups, more research is necessary to explore the practical considerations for screening such as cultural and economic barriers, trust, and post-screening actions. [ABSTRACT FROM AUTHOR]

BACKGROUND: The term 'dementia' covers a range of progressive brain diseases from which many elderly people suffer. Traditional cognitive and pathological tests are currently used to detect dementia, however, applications using Artificial Intelligence (AI) methods have recently shown improved results from improved detection accuracy and efficiency. OBJECTIVE: This research paper investigates the efficacy of one type of data analytics called supervised learning to detect Alzheimer's disease (AD) – a common dementia condition. METHODS: The aim is to evaluate cognitive tests and common biological markers (biomarkers) such as cerebrospinal fluid (CSF) to develop predictive classification systems for dementia detection. RESULTS: A data analytics process has been proposed, implemented, and tested against real data obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) repository. CONCLUSION: The models showed good power in predicting AD levels, notably from specified cognitive tests' scores and tauopathy related features. [ABSTRACT FROM AUTHOR]

The goal of the study presented in the paper is to assess the knowledge about Alzheimer's Disease (AD), among library and information science students in Croatia. Understanding how much future librarians know about dementia is the first step towards providing them with relevant educational intervention which will equip them with required knowledge to develop dementia-friendly library services in a society which is increasingly affected by dementia. A total of 183 students participated in the study which used Alzheimer's Disease Knowledge Scale (ADKS), a validated instrument that measures what people know about AD using a 30-item questionnaire across seven knowledge domains: risk factors, symptoms, assessment and diagnosis, course of the disease, life impact, treatment, and management, and caregiving. The collected data were analysed using basic descriptive statistics and a parametric test (t -test). Findings show that respondents have poor AD knowledge. Only 35.78% questions were answered correctly and the mean knowledge score was 10.76. The findings revealed that participants with previous exposure to the disease have significantly better knowledge (P = 0.003). [ABSTRACT FROM AUTHOR]

Background: Even in severe states of Alzheimer's disease and related dementias (ADRD), accounts of an unexpected or paradoxical return of awareness and lucidity have been reported in some patients, documented formally, and studied. Objective: A scoping review was undertaken to survey the literature on the topic. Methods: Five databases were searched using pertinent search terms. Results were deduplicated and subsequently screened by title and abstract for relevance. Remaining reports were read and included or excluded using specific inclusion criteria. 30 results consisted of a mix of perspective papers, case reports, qualitative surveys of caregivers, law journal comments, and mechanistic speculation. Results: An equal mix of primary and secondary research was identified. Conclusions: The papers collected in this review provide a valuable methodological outline for researching the topic of lucid episodes in ADRD. The verified legitimacy and simultaneous inexplicability of these events promote philosophical discussion, mechanistic investigations, and sorely needed research in the field of ADRD. [ABSTRACT FROM AUTHOR]

Background: Rapidly growing healthcare demand associated with global population aging has spurred the development of new digital tools for the assessment of cognitive performance in older adults. Objective: To develop a fully automated Mini-Mental State Examination (MMSE) assessment model and validate the model's rating consistency. Methods: The Automated Assessment Model for MMSE (AAM-MMSE) was an about 10-min computerized cognitive screening tool containing the same questions as the traditional paper-based Chinese MMSE. The validity of the AAM-MMSE was assessed in term of the consistency between the AAM-MMSE rating and physician rating. Results: A total of 427 participants were recruited for this study. The average age of these participants was 60.6 years old (ranging from 19 to 104 years old). According to the intraclass correlation coefficient (ICC), the interrater reliability between physicians and the AAM-MMSE for the full MMSE scale AAM-MMSE was high [ICC (2,1)=0.952; with its 95% CI of (0.883,0.974)]. According to the weighted kappa coefficients results the interrater agreement level for audio-related items showed high, but for items "Reading and obey", "Three-stage command", and "Writing complete sentence" were slight to fair. The AAM-MMSE rating accuracy was 87%. A Bland-Altman plot showed that the bias between the two total scores was 1.48 points with the upper and lower limits of agreement equal to 6.23 points and −3.26 points. Conclusions: Our work offers a promising fully automated MMSE assessment system for cognitive screening with pretty good accuracy. [ABSTRACT FROM AUTHOR]

Recent research aimed at the discovery, integration, and communication of health outcome measures (or "biomarkers") in Alzheimer's disease has raised challenging questions related to whether, how and when results from these investigations should be disclosed to research participants. Reflecting the apparent heterogeneity of many neurodegenerative diseases, biomarker or other risk factor results are often probabilistic, interactive, multi-modal, and selective. Such characteristics make it very complex to summarize and communicate to clinicians, researchers, and research participants. Whereas the format and content of academic literature is well-managed by the peer-review process, reporting individualized results to participants involves complex, sensitive, and ethical considerations. This paper describes three key factors to consider in decisions about the return of results to research participants: complexity, precision, and responsibility. The paper also presents six practical recommendations for implementing meaningful and ethical communication with research participants. [ABSTRACT FROM AUTHOR]

BACKGROUND: Alzheimer's disease (AD) endangers the physical and mental health of the elderly, constituting one of the most crucial social challenges. Due to lack of effective AD intervention drugs, it is very important to diagnose AD in the early stage, especially in the Mild Cognitive Impairment (MCI) phase. OBJECTIVE: At present, an automatic classification technology is urgently needed to assist doctors in analyzing the status of the candidate patient. The artificial intelligence enhanced Alzheimer's disease detection can reduce costs to detect Alzheimer's disease. METHODS: In this paper, a novel pre-trained ensemble-based AD detection (PEADD) framework with three base learners (i.e., ResNet, VGG, and EfficientNet) for both the audio-based and PET (Positron Emission Tomography)-based AD detection is proposed under a unified image modality. Specifically, the effectiveness of context-enriched image modalities instead of the traditional speech modality (i.e., context-free audio matrix) for the audio-based AD detection, along with simple and efficient image denoising strategy has been inspected comprehensively. Meanwhile, the PET-based AD detection based on the denoised PET image has been described. Furthermore, different voting methods for applying an ensemble strategy (i.e., hard voting and soft voting) has been investigated in detail. RESULTS: The results showed that the classification accuracy was 92% and 99% on the audio-based and PET-based AD datasets, respectively. Our extensive experimental results demonstrate that our PEADD outperforms the state-of-the-art methods on both audio-based and PET-based AD datasets simultaneously. CONCLUSIONS: The network model can provide an objective basis for doctors to detect Alzheimer's Disease. [ABSTRACT FROM AUTHOR]

Background: Subjective cognitive decline (SCD) is a self-reported experience of declining cognitive function showing normal performance in cognitive assessments, which is a known risk factor for dementia. Recent studies highlight the importance of nonpharmacological multidomain interventions that can target multiple risk factors of dementia in older adults. Objective: This study investigated the efficacy of the Silvia program, a mobile-based multidomain intervention, to improve cognitive function and health-related outcomes of older adults with SCD. We compare its effects to a conventional paper-based multidomain program on various health indicators related to risk factors of dementia. Methods: This prospective randomized controlled trial involved 77 older adults with SCD recruited from the Dementia Prevention and Management Center in Gwangju, South Korea during May to October 2022. Participants were randomly assigned to either the mobile- or paper-based group. Interventions were administered for 12 weeks, where pre- and post-assessments were conducted. Results: The K-RBANS total score did not show significant differences between groups. The mobile group showed better improvement in K-PRMQ scores and PSS scores than the paper group. Differences within groups showed that mobile-based interventions significantly improved K-PRMQ, STAI-X-1, PSS, and EQ-5D-5 L scores, while paper-based interventions significantly improved PSS, and EQ-5D-5 L scores. Patient adherence rate was 76.6%. Conclusion: Overall, the Silvia program was effective for improving self-reported memory failures, stress, anxiety, and health-related quality of life in older adults with SCD. However, longer periods of administration for more than 12 weeks may be needed to achieve significant improvements in cognitive function by objective measures. [ABSTRACT FROM AUTHOR]

Background: Adult day services (ADS) are an important and often underutilized support resource for older adults. For persons living with dementia (PLWD), ADS is an optimal access point to not only receive therapeutic and rehabilitative activities, but as a vehicle for respite/relief for dementia caregivers. Yet, there is currently a lack of research on integrating caregiver interventions into home and community-based services such as ADS. Objective: This paper reports on qualitative findings from the Improving Outcomes for Family Caregivers of Older Adults with Complex Conditions: The Adult Day Plus (ADS Plus) Program Trial. Methods: Drawing from semi-structured interviews conducted with family caregivers and ADS site staff, we conducted a thematic analysis to examine the implementation process of ADS Plus. Results: Themes address the relational nature of the intervention, learning, influence of the administrative infrastructure, and receptivity of ADS Plus. Conclusions: Our analysis determined that implementation of ADS Plus was feasible and accepted by site staff and dementia caregivers but also calls for additional evaluation of embedded caregiver support interventions across different contexts (e.g., staff size, limited technology environments) to further identify and test implementation mechanisms across settings. [ABSTRACT FROM AUTHOR]

As a non-classical post-translational modification, O-linked β-N-acetylglucosamine (O-GlcNAc) modification (O-GlcNAcylation) is widely found in human organ systems, particularly in our brains, and is indispensable for healthy cell biology. With the increasing age of the global population, the incidence of neurodegenerative diseases is increasing, too. The common characteristic of these disorders is the aggregation of abnormal proteins in the brain. Current research has found that O-GlcNAcylation dysregulation is involved in misfolding or aggregation of these abnormal proteins to mediate disease progression, but the specific mechanism has not been defined. This paper reviews recent studies on O-GlcNAcylation's roles in several neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease, Machado-Joseph's disease, and giant axonal neuropathy, and shows that O-GlcNAcylation, as glucose metabolism sensor, mediating synaptic function, participating in oxidative stress response and signaling pathway conduction, directly or indirectly regulates characteristic pathological protein toxicity and affects disease progression. The existing results suggest that targeting O-GlcNAcylation will provide new ideas for clinical diagnosis, prevention, and treatment of neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) prediction is a critical task in the field of healthcare, and researchers have been exploring various techniques to improve its accuracy. This research paper focuses on the major contributions of a hybrid deep convolutional neural network (CNN) with denoising using a multilayer perceptron (MLP) and pooling layers in AD prediction. The proposed hybrid model leverages the power of deep CNNs to extract meaningful features from molecular or imaging data related to AD. The model incorporates denoising techniques using MLP to enhance the quality of the input data and reduce noise interference. Additionally, pooling layers are employed to summarize the extracted features and capture their essential characteristics. Several experiments and evaluations were conducted to assess the performance of the proposed model. Comparative analyses were carried out with other techniques such as PCA, CNN, Resnet18, and DCNN. The results were presented in a comparison chart, highlighting the superiority of the hybrid deep CNN with denoising and pooling layers in AD prediction. The research paper further discusses the accuracy, precision, and recall values obtained through the proposed model. These metrics provide insights into the model's ability to accurately classify AD cases and predict disease progression. Overall, the hybrid deep CNN with denoising using MLP and pooling layers presents a promising approach for AD prediction. The combination of these techniques enables more accurate and reliable predictions, contributing to early detection and improved patient care. The findings of this research contribute to the advancement of AD prediction methodologies and provide valuable insights for future studies in this domain. [ABSTRACT FROM AUTHOR]

Background: There is a common agreement that Alzheimers disease (AD) is inherently complex; otherwise, a general disagreement remains on its etiological underpinning, with numerous alternative hypotheses having been proposed. Objective: To perform a scoping review of original manuscripts describing hypotheses and theories of AD published in the past decades. Results: We reviewed 131 original manuscripts that fulfilled our inclusion criteria out of more than 13,807 references extracted from open databases. Each entry was characterized as having a single or multifactorial focus and assigned to one of 15 theoretical groupings. Impact was tracked using open citation tools. Results: Three stages can be discerned in terms of hypotheses generation, with three quarter of studies proposing a hypothesis characterized as being single-focus. The most important theoretical groupings were the Amyloid group, followed by Metabolism and Mitochondrial dysfunction, then Infections and Cerebrovascular. Lately, evidence towards Genetics and especially Gut/Brain interactions came to the fore. Conclusions: When viewed together, these multi-faceted reports reinforce the notion that AD affects multiple sub-cellular, cellular, anatomical, and physiological systems at the same time but at varying degree between individuals. The challenge of providing a comprehensive view of all systems and their interactions remains, alongside ways to manage this inherent complexity. [ABSTRACT FROM AUTHOR]

This paper presents data analysis of a large dataset of outpatient records for the purpose of establishing accurate prevalence rates of dementia and Alzheimer’s disease in Bulgaria. The research is motivated by the lack of accurate prevalence data as well as statistics about the actual number of people affected by dementia at national level. Health data from pseudonymized outpatient records (1,378,355) of 642,013 unique patients (Male 39.88%, Female 61.67%) with visits to neurologists and psychiatrists in 2018 was mapped to an OMOP CDM relational database. The size of this dataset is one of largest in the EU context. Prevalence of dementia for all age groups [30,100+] years is 1.61% (Male 0.62%, Female 0.99%) and Alzheimer’ disease prevalence is 0.39% (Male 0.15%, Female 0.24%), where 24.34% of all the patients with dementia suffer Alzheimer’s disease. The mean prevalence rates of dementia and Alzheimer's disease for ages above 64 are 9.52% (CI 95%, [6.98%, 12.04%]) and 1.04 % (CI 95%, [0.84%, 1.27%,]). A comparison with EU statistics yields 0.07% difference for dementia prevalence, while data visualization confirms the known patterns of prevalence with aging and gender specifics These results stimulate further research and support the development of a national strategy for dementia and Alzheimer’s disease. [ABSTRACT FROM AUTHOR]

Accurate and reliable prediction of Alzheimer's disease (AD) progression is crucial for effective interventions and treatment to delay its onset. Recently, deep learning models for AD progression achieve excellent predictive accuracy. However, their predictions lack reliability due to the non-calibration defects, that affects their recognition and acceptance. To address this issue, this paper proposes a temporal attention-aware evidential recurrent network for trustworthy prediction of AD progression. Specifically, evidential recurrent network explicitly models uncertainty of the output and converts it into a reliability measure for trustworthy AD progression prediction. Furthermore, considering that the actual scenario of AD progression prediction frequently relies on historical longitudinal data, we introduce temporal attention into evidential recurrent network, which improves predictive performance. We demonstrate the proposed model on the TADPOLE dataset. For predictive performance, the proposed model achieves mAUC of 0.943 and BCA of 0.881, which is comparable to the SOTA model MinimalRNN. More importantly, the proposed model provides reliability measures of the predicted results through uncertainty estimation and the ECE of the method on the TADPOLE dataset is 0.101, which is much lower than the SOTA model at 0.147, indicating that the proposed model can provide important decision-making support for risk-sensitive prediction of AD progression. [ABSTRACT FROM AUTHOR]

Mild cognitive impairment (MCI) is a syndrome that occurs in the preclinical stage of Alzheimer's disease (AD) and is also an early signal of the onset of AD. Early detection and accurate differentiation between MCI and AD populations, and providing them with effective intervention and treatment, are of great significance for preventing or delaying the onset of AD. In this paper, we propose a deep learning model, SE-DenseNet, that combines channel attention and dense connectivity networks and apply it to the field of magnetic resonance imaging (MRI) data recognition for the diagnosis of AD and MCI. First, to extract MRI features with high quality, a slicing algorithm based on two-dimensional image information entropy is proposed to obtain AD brain lesion features with stronger representation ability. Second, in terms of model structure, SENet is introduced as a channel attention module and redistribute the weight of image features in the channel dimension; use DenseNet as the main architecture to maximize information flow, and each layer is directly interconnected with subsequent layers. It enables the network to learn and extract relevant features from the input data and improve the classification ability of the network. Finally, our proposed model is validated on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, the results have shown that the accuracy for the four classification tasks of AD-NC, AD-MCI, NC-MCI, and AD-NC-MCI can reach 98.12%, 97.42%, 97.42%, and 95.24%, respectively. At the same time, the sensitivity and specificity have also achieved satisfactory results, exhibited a high performance in comparison with the classic machine learning algorithm and several existing state-of-the-art deep learning methods, demonstrating the proposed method is a powerful tool for the early diagnosis and detection of AD. [ABSTRACT FROM AUTHOR]

In 2018, the Australian Dementia Network (ADNeT) was established to bring together Australia's leading dementia researchers, people with living experience and clinicians to transform research and clinical care in the field. To address dementia diagnosis, treatment, and care, ADNeT has established three core initiatives: the Clinical Quality Registry (CQR), Memory Clinics, and Screening for Trials. Collectively, the initiatives have developed an integrated clinical and research community, driving practice excellence in this field, leading to novel innovations in diagnostics, clinical care, professional development, quality and harmonization of healthcare, clinical trials, and translation of research into practice. Australia now has a national Registry for Mild Cognitive Impairment and dementia with 55 participating clinical sites, an extensive map of memory clinic services, national Memory and Cognition Clinic Guidelines and specialized screening for trials sites in five states. This paper provides an overview of ADNeT's achievements to date and future directions. With the increase in dementia cases expected over coming decades, and with recent advances in plasma biomarkers and amyloid lowering therapies, the nationally coordinated initiatives and partnerships ADNeT has established are critical for increased national prevention efforts, co-ordinated implementation of emerging treatments for Alzheimer's disease, innovation of early and accurate diagnosis, driving continuous improvements in clinical care and patient outcome and access to post-diagnostic support and clinical trials. For a heterogenous disorder such as dementia, which is now the second leading cause of death in Australia following cardiovascular disease, the case for adequate investment into research and development has grown even more compelling. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) plagues 6.5 million Americans 65+, yet treatments are lacking. The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet has been developed to address the expansive impact of dementias on the general public. This systematic review evaluated the impact of the MIND diet on cognition in those with pathologies across the dementia spectrum. Objective: To evaluate the application of the MIND diet for prevention and/or treatment of dementia. Methods: PubMed was used to conduct a search using the MIND diet and terms related to cognition. Articles were excluded if they were published prior to 2018, studied a population without dementia or significant risk factors, or did not include those 65 +. The overall quality of each source was analyzed based on the cognitive test(s) used, the selection of subjects, and the sample size. Results: The search generated 33 papers, which yielded 11 articles after screening. Of these studies, one was conducted on those with mild cognitive impairment, one with AD, two with general dementia, and seven with at-risk individuals. All the studies found a positive correlation between adherence and some form of cognitive functioning, but results were mixed for specific cognitive domains. Conclusions: These findings suggest that the MIND diet may be a useful long-term treatment option for those with various dementia pathologies. However, more research is needed on subjects with onset dementias. Additionally, there is a need for more research into the mechanisms behind the common comorbidities. [ABSTRACT FROM AUTHOR]

Microglia and astrocytes are regarded as active participants in the central nervous system under various neuropathological conditions, including Alzheimer's disease (AD). Both microglia and astrocyte activation have been reported to occur with a spatially and temporarily distinct pattern. Acting as a double-edged sword, glia-mediated neuroinflammation may be both detrimental and beneficial to the brain. In a variety of neuropathologies, microglia are activated before astrocytes, which facilitates astrocyte activation. Yet reactive astrocytes can also prevent the activation of adjacent microglia in addition to helping them become activated. Studies describe changes in the genetic profile as well as cellular and molecular responses of these two types of glial cells that contribute to dysfunctional immune crosstalk in AD. In this paper, we construct current knowledge of microglia-astrocyte communication, highlighting the multifaceted functions of microglia and astrocytes and their role in AD. A thorough comprehension of microglia-astrocyte communication could hasten the creation of novel AD treatment approaches. [ABSTRACT FROM AUTHOR]

Background: Digital cognitive tests offer several potential advantages over established paper-pencil tests but have not yet been fully evaluated for the clinical evaluation of mild cognitive impairment.Objective: The NeuroCognitive Performance Test (NCPT) is a web-based, self-directed, modular battery intended for repeated assessments of multiple cognitive domains. Our objective was to examine its relationship with the Alzheimer's Disease Assessment Scale-Cognition Subscale (ADAS-Cog) and Mini-Mental State Examination (MMSE) as well as with established paper-pencil tests of cognition and daily functioning in mild cognitive impairment (MCI).Methods: We used Spearman correlations, regressions and principal components analysis followed by a factor analysis (varimax rotated) to examine our objectives.Results: In MCI subjects, the NCPT composite is significantly correlated with both a composite measure of established tests (r = 0.78, p < 0.0001) as well as with the ADAS-Cog (r = -0.55, p < 0.0001). Both NCPT and paper-pencil test batteries had a similar factor structure that included a large "g" component with a high eigenvalue. The correlation for the analogous tests (e.g., Trails A and B, learning memory tests) were significant (p < 0.0001). Further, both the NCPT and established tests significantly (p < 0.0001) predicted the University of California San Diego Performance-Based Skills Assessment and Functional Activities Questionnaire, measures of daily functioning.Conclusion: The NCPT, a web-based, self-directed, computerized test, shows high concurrent validity with established tests and hence offers promise for use as a research or clinical tool in MCI. Despite limitations such as a relatively small sample, absence of control group and cross-sectional nature, these findings are consistent with the growing literature on the promise of self-directed, web-based cognitive assessments for MCI. [ABSTRACT FROM AUTHOR]

Background: There are currently no uniform treatments for post-stroke comorbid cognitive impairment and depression (PSCCID). Objective: To verify whether repetitive transcranial magnetic stimulation (rTMS) can improve PSCCID symptoms and explore the underlying roles of resting-state functional magnetic resonance imaging (rs-fMRI). Methods: Thirty PSCCID patients were randomized in a 1 : 1 ratio to receive 4 weeks of rTMS (intervention group) or sham rTMS (control group) over the left dorsolateral prefrontal cortex (DLPFC). rs-fMRI was acquired to analyze the functional plasticity of brain regions at baseline and immediately after the last intervention. Results: Cognition, depression status, and neural electrophysiology were improved in both intervention and control groups after treatment (p = 0.015–0.042), and the intervention group had more significant improvement than the control group. Analysis of functional connectivities (FCs) within the default mood network (DMN) showed that the connection strength of the left temporal pole/left parahippocampal cortex and right lateral temporal cortex/right retrosplenial cortex in the intervention group were enhanced compared with its pre-intervention and that in the control group after treatment (p < 0.05), and the both FC values were positively correlated with MMSE scores (p < 0.001). The intervention group had stronger FCs within the DMN compared with the control group after treatment, and some of the enhanced FCs were correlated with the P300 latency and amplitude. Conclusions: rTMS over the left DLPFC is an effective treatment for improving both cognitive impairment and depression among patients with PSCCID. The enhanced FCs within the DMN may serve as a compensatory functional recombination to promote clinical recovery. [ABSTRACT FROM AUTHOR]

Background: Intranasal insulin (INI) is being explored as a treatment for Alzheimer's disease (AD). Improved memory, functional ability, and cerebrospinal fluid (CSF) AD biomarker profiles have been observed following INI administration. However, the method of intranasal delivery may significantly affect outcomes. Objective: To show reliable delivery of insulin to the brain using the Aptar Cartridge Pump System (CPS) intranasal delivery system. Methods: To visualize INI biodistribution, we developed a novel PET radiotracer, Gallium 68-radiolabeled (NOTA-conjugated) insulin, [68Ga]Ga-NOTA-insulin. We used the Aptar CPS to administer [68Ga]Ga-NOTA-insulin to anesthetized healthy adult vervet monkeys and measured brain regional activity and whole-body dosimetry following PET/CT scans. Results: We observed brain penetration of [68Ga]Ga-NOTA-insulin following intranasal administration with the Aptar CPS. Radioactive uptake was seen in multiple regions, including the amygdala, putamen, hypothalamus, hippocampus, and choroid plexus. A safety profile and whole-body dosimetry were also established in a second cohort of vervets. Safety was confirmed: vitals remained stable, blood glucose levels were unchanged, and no organ was exposed to more than 2.5 mSv of radioactivity. Extrapolations from vervet organ distribution allowed for estimation of the [68Ga]Ga-NOTA-insulin absorbed dose in humans, and the maximum dose of [68Ga]Ga-NOTA-insulin that can be safely administered to humans was determined to be 185 MBq. Conclusions: The use of [68Ga]Ga-NOTA-insulin as a PET radiotracer is safe and effective for observing brain uptake in vervet monkeys. Further, the Aptar CPS successfully targets [68Ga]Ga-NOTA-insulin to the brain. The data will be essential in guiding future studies of intranasal [68Ga]Ga-NOTA-insulin administration in humans. [ABSTRACT FROM AUTHOR]

Background: The rise in the aging population highlights the need to address cognitive decline and neurodegenerative diseases. Intermittent hypoxia (IH) protocols show promise in enhancing cognitive abilities and brain health. Objective: This review evaluates IH protocols' benefits on cognition and brain health in older adults, regardless of cognitive status. Methods: A systematic search following PRISMA guidelines was conducted across four databases (PubMed, Scopus, Web of Science, and Cochrane Library) and two registers, covering records from inception to May 2024 (PROSPERO: CRD42023462177). Inclusion criteria were: 1) original research with quantitative details; 2) studies involving older adults, with or without cognitive impairment; 3) studies including IH protocols; 4) articles analyzing cognition and brain health in older adults. Results: Seven studies and five registered trials met the criteria. Findings indicate that Intermittent Hypoxia Training (IHT) and Intermittent Hypoxia-Hyperoxia Training (IHHT) improved cognitive functions and brain health. Intermittent Hypoxic Exposure (IHE) improved cerebral tissue oxygen saturation, middle cerebral arterial flow velocity, and cerebral vascular conductance, particularly in cognitively impaired populations. IHT and IHHT had no significant effect on BDNF levels. There is a lack of studies on IHHE in older adults with and without cognitive impairment. Conclusions: IH protocols may benefit cognition regardless of cognitive status. IHT and IHE positively affect cerebral outcomes, with all protocols having limited effects on BDNF levels. Future research should standardize IH protocols, investigate long-term cognitive effects, and explore neuroprotective biomarkers. Combining these protocols with physical exercise across diverse populations could refine interventions and guide targeted therapeutic strategies. [ABSTRACT FROM AUTHOR]

Background: The concept of amnestic mild cognitive impairment (aMCI) was developed to identify patients at an initial stage of Alzheimer's disease (AD). However, some patients with aMCI do not present biomarkers of amyloid pathology or neuronal injury. Objective: To know the natural history of amyloid-negative and neurodegeneration-negative patients with aMCI, namely to ascertain: 1) whether these patients remain cognitively stable or they present a slow decline in neuropsychological tests; 2) whether the memory complaints subside with the apparently benign clinical course of the disorder or if they persist along the time. Methods: Patients who fulfilled criteria for aMCI with no biomarkers of amyloid pathology or neuronal injury were selected from a large cohort of non-demented patients with cognitive complaints, and were followed with clinical and neuropsychological assessments. Results: Twenty-one amyloid-negative and neurodegeneration-negative aMCI patients were followed for 7.1±3.7 years. At the baseline they had more pronounced deficits in verbal learning (California Verbal Learning Test) and were also impaired in Word Recall and Logical Memory. However, they did not decline in any cognitive test during follow-up. The patients maintained a high level of subjective memory complaints from baseline (9.7±4.1) to the follow-up visit (9.2±4.1, a non-significant difference), in spite of a statistically significant decrease in the depressive symptoms, with Geriatric Depression Scale (15 items) score 4.9±2.8 at baseline and 3.2±1.8 at the follow-up visit. Conclusions: Amyloid-negative, neurodegeneration-negative aMCI is a chronic clinical condition characterized by the long-term persistence of cognitive deficits and distressing memory complaints. Adequate strategies to treat this condition are needed. [ABSTRACT FROM AUTHOR]

Background: Mild cognitive impairment (MCI) patients are at a high risk of developing Alzheimer's disease and related dementias (ADRD) at an estimated annual rate above 10%. It is clinically and practically important to accurately predict MCI-to-dementia conversion time. Objective: It is clinically and practically important to accurately predict MCI-to-dementia conversion time by using easily available clinical data. Methods: The dementia diagnosis often falls between two clinical visits, and such survival outcome is known as interval-censored data. We utilized the semi-parametric model and the random forest model for interval-censored data in conjunction with a variable selection approach to select important measures for predicting the conversion time from MCI to dementia. Two large AD cohort data sets were used to build, validate, and test the predictive model. Results: We found that the semi-parametric model can improve the prediction of the conversion time for patients with MCI-to-dementia conversion, and it also has good predictive performance for all patients. Conclusions: Interval-censored data should be analyzed by using the models that were developed for interval- censored data to improve the model performance. [ABSTRACT FROM AUTHOR]

Background: In the era of disease-modifying therapies, empowering the clinical neuropsychologist's toolkit for timely identification of mild cognitive impairment (MCI) is crucial. Objective: Here we examine the clinimetric properties of the Montreal Cognitive Assessment (MoCA) for the early diagnosis of MCI due to Alzheimer's disease (MCI-AD). Methods: Data from 48 patients with MCI-AD and 47 healthy controls were retrospectively analyzed. Raw MoCA scores were corrected according to the conventional Nasreddine's 1-point correction and demographic adjustments derived from three normative studies. Optimal cutoffs were determined while previously established cutoffs were diagnostically reevaluated. Results: The original Nasreddine's cutoff of 26 and normative cutoffs (non-parametric outer tolerance limit on the 5th percentile of demographically-adjusted score distributions) were overly imbalanced in terms of Sensitivity (Se) and Specificity (Sp). The optimal cutoff for Nasreddine's adjustment showed adequate clinimetric properties (≤23.50, Se = 0.75, Sp = 0.70). However, the optimal cutoff for Santangelo's adjustment (≤22.85, Se = 0.65, Sp = 0.87) proved to be the most effective for both screening and diagnostic purposes according to Larner's metrics. The results of post-probability analyses revealed that an individual testing positive using Santangelo's adjustment combined with a cutoff of 22.85 would have 84% post-test probability of receiving a diagnosis of MCI-AD (LR+ = 5.06). Conclusions: We found a common (mal)practice of bypassing the applicability of normative cutoffs in diagnosis-oriented clinical practice. In this study, we identified optimal cutoffs for MoCA to be allocated in secondary care settings for supporting MCI-AD diagnosis. Methodological and psychometric issues are discussed. [ABSTRACT FROM AUTHOR]

Background: Dementia prevalence is expected to increase as populations grow and age. Therefore, additional resources will be needed to meet the global demand for care for Alzheimer's disease and related dementias (ADRD). Objective: Estimate global and country-level health care spending attributable to ADRD and the cost of informal care for people living with ADRD. Methods: We gathered data from three systematic literature reviews and the Global Burden of Disease 2019 study. We used spatiotemporal Gaussian process regression to impute estimates for the many countries without underlying data. We projected future costs to 2050 based on past trends in costs, diagnosis rates, and institutionalization rate. Results: We estimated that in 2019, the direct health care spending attributable to ADRD across 204 countries reached $260.6 billion (95% uncertainty interval [UI] 131.6–420.4) and the cost of informal ADRD care was $354.1 billion (95% UI 190.0–544.1). On average, informal care represents 57% (95% UI 38–75%) of the total cost of care. We estimated that direct health care spending attributable to ADRD will reach $1.6 trillion (95% UI 0.6–3.3) in 2050, or 9.4% (95% UI 3.9–19.6%) of projected health spending worldwide. We estimated the cost of informal care will reach $0.9 trillion (95% UI 0.3–1.7) in 2050. Conclusions: These cost estimates underscore the magnitude of resources needed to ensure sufficient resources for people living with ADRD and highlight the role that informal care plays in provision of their care. Incorporating informal care cost estimates is critical to capture the social cost of ADRD. [ABSTRACT FROM AUTHOR]

Background: The Clock Drawing Test (CDT) is used to screen for Alzheimer's disease and other dementia disorders. Normative scores on the version from the Montreal Cognitive Assessment (MoCA) do not exist in the Nordic countries. Objective: To examine the normative scores of the CDT among adults aged 70 years and older. Methods: We included 4,023 cognitively healthy persons aged 70–97 years from a population survey in Norway. They were examined with the CDT, which has a total score between zero and three. A multiple multinominal regression model was applied with a CDT score as the dependent categorical variable and estimated the probabilities of scoring a particular score, stratified by age, sex, and education. These probabilities correspond to an expected proportion of the normative population scoring at, or below a given percentile. Results: None scored zero, 2.1% scored one, 14.9% scored two, and 83% scored three. Higher age, female sex and fewer years of schooling were associated with poorer performance. Scores of zero and one deviated from the normative score regardless of age, sex and education. A score of two was within the norm for a female older than 81 and a male older than 85. Conclusions: The majority (83%) of people 70 years and older had a score of three on the CDT. Lower age, male sex, and higher education were associated with a better performance. Scores of zero and one were below the normative score. Except for the very old, a score of two was also well below the normative score. [ABSTRACT FROM AUTHOR]

Fortea et al.'s. (2024) recent data analysis elegantly calls attention to familial late-onset Alzheimer's disease (AD) with APOE4 homozygosity. The article by Grant (2024) reviews the factors associated with AD, particularly the APOE genotype and lifestyle, and the broad implications for prevention, both for individuals with the lifestyles associated with living in resource-rich countries and for those enduring environmental adversity in poverty settings, including high exposure to enteric pathogens and precarious access to healthcare. Grant discusses the issue of APOE genotype and its implications for the benefits of lifestyle modifications. This review highlights that bearing APOE4 could constitute an evolutionary benefit in coping with heavy enteric infections and malnutrition early in life in the critical formative first two years of brain development. However, the critical issue may be that this genotype could be a health concern under shifts in lifestyle and unhealthy diets during aging, leading to severe cognitive impairments and increased risk of AD. This commentary supports the discussions of Grant and the benefits of improving lifestyle for decreasing the risks for AD while providing further understanding and modelling of the early life benefits of APOE4 amidst adversity. This attention to the pathophysiology of AD should help further elucidate these critical, newly appreciated pathogenic pathways for developing approaches to the prevention and management in the context of the APOE genetic variations associated with AD. [ABSTRACT FROM AUTHOR]

More than a century after the first description of Alzheimer's disease (AD), the road to a cure for this complex and heterogeneous neurodegenerative disorder has been paved by countless descriptive hypotheses and successive clinical trial failures. Auspiciously, the era of genome-wide association studies revolutionized the classical "neurocentric" view of AD by providing clues that brain-resident immune cells (i.e., microglia and astrocytes) are also key players in the pathological and clinical trajectory of this neurodegenerative disorder. Considering that the intercommunication among neurons, astrocytes, and microglia is fundamental for the functional organization of the brain, it is evident that the disruption of the proper functioning of this "triad" could contribute to the neuroinflammatory and neurodegenerative events that occur in the AD brain. Importantly, recent scientific progress in the burgeoning field of immunometabolism, a crossroad between metabolism and immune response, shed light on the importance of metabolic reprogramming of brain-resident immune cells in AD pathology. In this sense, the present review is aimed to summarize and discuss the current knowledge on the metabolic patterns of brain-resident immune cells during the AD continuum, putting a special focus on glucose, amino acids, and lipid metabolism. Changing the "old" picture of AD pathological basis by integrating the role of brain-resident immune cells it is imperative to establish new and feasible therapeutic interventions able to curb neuroinflammatory and neurodegenerative processes, and consequently cognitive deterioration. [ABSTRACT FROM AUTHOR]

Background: With advancing age, cognitive decline is frequently associated with endothelial dysfunction, but data on vascular performance prior to the onset of mild cognitive impairment (MCI) is scarce. Objective: To investigate the relationship between endothelial function, vital parameters and cognitive performance in older adults with subjective cognitive decline (SCD). Methods: Forty-five volunteers aged 65 years and older with SCD underwent comprehensive geriatric assessment-based prognosis evaluation by means of the Multidimensional Prognostic Index (MPI), full neuropsychological examination and peripheral arterial tonometry measurement by means of EndoPAT™2000 to evaluate endothelial flexibility and vital parameters. Six months after initial evaluation, participants were contacted by phone and a telephone-administered version of the MPI (TELE-MPI) was conducted. Results: Fifteen study participants scored below the cutoff score of 26 on the Montreal Cognitive Assessment, suggesting MCI (26.56±2.23). Nominal significant correlations were found between heart rate (HR) and trail making test (TMT) A (β= –0.49, p = 0.03), between heart rate variability (HRV) and TMT B (β= 0.78, p = 0.041), between power of low-frequency band (LF) HRV and Mini Nutritional Assessment-Short Form (β= 0.007, p = 0.037) as well as between augmentation index (AI) and CogState Detection Test (β= 0.002, p = 0.034). Conclusions: HR, HRV, and AI, but not endothelial flexibility are associated with cognitive performance in SCD and suspected MCI patients and may serve as clinical biomarkers in the early diagnosis of neurodegenerative disorders with advancing age. [ABSTRACT FROM AUTHOR]

The two major determining factors for Alzheimer's disease (AD) are genetics and lifestyle. Alleles of the apolipoprotein E (APOE) gene play important roles in the development of late-onset AD, with APOEɛ4 increasing risk, APOEɛ3 being neutral, and APOEɛ2 reducing risk. Several modifiable lifestyle factors have been studied in terms of how they can modify the risk of AD. Among these factors are dietary pattern, nutritional supplements such as omega-3 fatty acids, and B vitamins, physical exercise, and obesity, and vitamin D. The Western diet increases risk of AD, while dietary patterns such as the Mediterranean and vegetarian/vegan diets reduce risk. Foods associated with reduced risk include coffee, fruits and vegetables, whole grains and legumes, and fish, while meat and ultraprocessed foods are associated with increased risk, especially when they lead to obesity. In multi-country ecological studies, the amount of meat in the national diet has the highest correlation with risk of AD. The history of research regarding dietary patterns on risk of AD is emphasized in this review. The risk of AD can be modified starting at least by mid-life. People with greater genetic risk for AD would benefit more by choosing lifestyle factors to reduce and/or delay incidence of AD. [ABSTRACT FROM AUTHOR]

Background: Among preventive strategies against dementia, nutrition is considered a powerful one and the recently established "nutritional cognitive neuroscience of aging" is a highly active research field. Objective: The present study was designed to deeply characterize older adults across the continuum from cognitive integrity to mild cognitive impairment (MCI) and better elucidate the prognostic role of lipophilic micronutrients within their lipidomic signature. Methods: 123 participants older than 65 years across the continuum from cognitive integrity to MCI were included [49 with subjective cognitive impairment, 29 women, 72.5±5.4 years, 26 MCI, 9 women, 74.5±5.8 years and 50 without cognitive impairment, 21 women, 70.8±4.3 years]. All participants underwent neuropsychological and nutritional examination as well as comprehensive geriatric assessment with calculation of the Multidimensional Prognostic Index (MPI) as a proxy of frailty and biological age and blood withdrawal for the analyses of lipophilic micronutrients, metabolomics and oxylipidomics. One year after the evaluation, same tests are ongoing. Results: After adjustment for age, sex, daily fruit and vegetable intake and cholesterol, we found a significant positive correlation between lutein and the number of correct words in category fluency (p = 0.016). Conclusions: This result supports the importance of carotenoids as robust biomarkers of cognitive performance independent of the nutritional status and frailty of the participants, as the entire present study collective was robust (MPI 0–0.33). The complete analyses of the metabolome and the oxylipidome will hopefully shed light on the metabolic and prognostic signature of cognitive decline in the rapidly growing population at risk of frailty. [ABSTRACT FROM AUTHOR]

Ethics Review began a decade ago with a mission to identify ethical concerns that hold back innovation and to promote solutions that would move the field forward. Over this time, blood biomarkers for brain pathology and medications that treat that pathology promise to transform research and care. A central problem is that the evidence needed to guide test interpretation and practice is accumulating and there are unanswered questions. At the same time, people living with and at risk for dementia want access to their test results and involvement in their care. We promote dialog among diverse people across many institutions through collaboration with the Advisory Group on Risk Evidence Education for Dementia (AGREEDementia.org). Over the years Ethics Review continues to publish these dialogs and solutions to overcome the paralysis of indecision and ethical concerns. [ABSTRACT FROM AUTHOR]

Background: The N-glycan structure bisecting N-acetylglucosamine (bisecting GlcNAc) is present on several N-glycans that are elevated in Alzheimer's disease (AD), and previous studies have shown that bisecting GlcNAc levels correlate with total tau and phospho-tau181 in cerebrospinal fluid at early stages of AD. A recent population-based study showed that bisecting GlcNAc correlates with total tau also in blood and that this correlation could predict conversion to dementia. Objective: In this study, we have further investigated how bisecting GlcNAc relates to total tau and phospho-tau 181 in cerebrospinal fluid samples from controls and cases with early cognitive deficits, stratified by amyloid/tau status and gender. Methods: Relative levels of bisecting GlcNAc in cerebrospinal fluid were measured by an enzyme-linked lectin assay in individuals with subjective cognitive decline, mild cognitive impairment and controls from the Norwegian Dementia Disease Initiation cohort. Results: As in our previous study, the correlation between bisecting GlcNAc and total tau or phospho-tau181 was particularly strong in the subjective cognitive decline group. The correlation was observed in amyloid negative and tau negative as well as amyloid positive and tau positive individuals, both in females and in males. Interestingly, among the amyloid negative and tau negative individuals, the correlation was observed in individuals with subjective cognitive decline but not in the controls. Conclusions: Thus, bisecting GlcNAc could be a biomarker for early cognitive decline. [ABSTRACT FROM AUTHOR]

Background: The Addenbrooke's Cognitive Examination-Revised (ACE-R) is an accessible cognitive tool that supports the early detection of mild cognitive impairment (MCI), Alzheimer's disease (AD), and behavioral variant frontotemporal dementia (bvFTD). Objective: To investigate the diagnostic efficacy of the ACE-R in MCI, AD, and bvFTD through the identification of novel coefficients for differentiation between these diseases. Methods: We assessed 387 individuals: 102 mild AD, 37 mild bvFTD, 87 with amnestic MCI patients, and 161 cognitively unimpaired controls. The Mokken scaling technique facilitated the extraction out of the 26 ACE-R items that exhibited a common latent trait, thereby generating the Mokken scales for the AD group and the MCI group. Subsequently, we performed logistic regression, integrating each Mokken scales with sociodemographic factors, to differentiate between AD and bvFTD, as well as between AD or MCI and control groups. Ultimately, the Receiver Operating Characteristic curve analysis was employed to assess the efficacy of the coefficient's discrimination. Results: The AD-specific Mokken scale (AD-MokACE-R) versus bvFTD exhibited an Area Under the Curve (AUC) of 0.922 (88% sensitivity and specificity). The AD-MokACE-R versus controls achieved an AUC of 0.968 (93% sensitivity, 94% specificity). The MCI-specific scale (MCI-MokACE-R) versus controls demonstrated an AUC of 0.859 (78% sensitivity, 79% specificity). Conclusions: The ACE-R's capacity is enhanced through statistical methods and demographic integration, allowing for accurate differentiation between AD and bvFTD, as well as between MCI and controls. This new method not only reinforces its clinical value in early diagnosis but also surpasses traditional approaches noted in prior studies. [ABSTRACT FROM AUTHOR]

Background: While drainage/removal of fluid and toxins from the brain by cerebrospinal fluid (CSF) directly into venous blood is well-known, a second drainage route has recently been (re)discovered—meningeal lymphatic vessels (mLVs)—which are responsible for up to half of total brain fluid/toxin drainage. The cytokine vascular endothelial growth factor (VEGF) increases mLV diameter and numbers to increase mLV drainage, resulting in increased mLV drainage. Alzheimer's disease (AD) is characterized by low plasma and CSF levels of VEGF. Objective: To determine if non-invasive transcranial radiofrequency wave treatment (TRFT), through modulation of VEGF levels in blood and CSF, can affect removal of toxins tau and amyloid-β (Aβ) from the brain. Methods: Eight mild/moderate AD subjects were given twice-daily 1-hour TRFT sessions at home by their caregivers. Blood and CSF samples were taken at baseline and following completion of 2 months of TRFT. Results: In plasma and/or CSF, strong baseline correlations between VEGF levels and AD markers (t-tau, p-tau, Aβ1-40, Aβ1-42) were eliminated by TRFT. This effect was primarily due to TRFT-induced increases in VEGF levels in AD subjects with low or unmeasurable "baseline" VEGF levels. These increased VEGF levels were associated with increased clearance/drainage of tau and Aβ from the brain, likely through VEGF's actions on mLVs. Conclusions: A new mechanism of TRFT is identified (facilitation of brain tau and Aβ clearance via VEGF) that is likely contributory to TRFT's reversal of cognitive impairment in AD subjects. TRFT may be particularly effective for cognitive benefit in AD subjects who have low VEGF levels. [ABSTRACT FROM AUTHOR]

Social dysfunction is a maladaptive process of coping, problem solving, and achieving one's goals. A new definition of apathy was cross-linked to social dysfunction, with a reduced goal-directed behavior and social interaction as a separate dimension. We hypothesized that these two neuropsychiatric symptoms may be included in the mild behavioral impairment diagnostic framework, operationalizing and standardizing late-life neuropsychiatric symptom assessment, to improve risk determination of dementia. Social dysfunction and apathy were transdiagnostic and prodromic for late-life cognitive disorders. A transdiagnostic approach could provide a useful mean for a better understanding of apathy and related conditions such as social behavior. [ABSTRACT FROM AUTHOR]

Background: The assessment of language deficits can be valuable in the early clinical diagnosis of neurodegenerative disorders, including Alzheimer's disease (AD). Objective: The present study aims to explore whether language markers at the macrostructural level could assist with the placement of an individual across the dementia continuum employing production data from structured narratives. Methods: We administered a Picture Sequence Narrative Discourse Task to 170 speakers of Greek: young healthy controls (yHC), cognitively intact healthy elders (eHC), elder participants with subjective cognitive impairment (SCI), with mild cognitive impairment (MCI), and with AD dementia at the mild/moderate stages. Structural MRIs, medical history, neurological examination, and neuropsychological/cognitive screening determined the status of each speaker to appropriately groupthem. Results: The data analysis revealed that the Macrostructure Index, Irrelevant Info, and Narration Density markers can track cognitive decline and AD (p < 0.001; Macrostructural Index: eHC versus AD Sensitivity 93.8%, Specificity 74.4%, MCI versus AD Sensitivity 93.8%, Specificity 66.7%; Narration Density: eHC versus AD Sensitivity 90.6%, Specificity 71.8%, MCI versus AD Sensitivity 93.8%, Specificity 66.7%). Moreover, Narrative Complexity was significantly affected for subjects with AD, Irrelevant Info increased in the narrations of speakers with MCI and AD, while Narration Length did not appear to indubitably differentiate between the cognitively intact groups and the clinical ones. Conclusions: Narrative Macrostructure Indices provide valuable information on the language profile of speakers with(out) intact cognition revealing subtle early signs of cognitive decline and AD suggesting that the inclusion of language-based assessment tools would facilitate the clinical process. [ABSTRACT FROM AUTHOR]

Senile plaques, mainly diffuse, and cerebral amyloid-β (Aβ) angiopathy are prevalent in the aging brain of non-human primates, from lemurs to non-human Hominidae. Aβ but not hyper-phosphorylated tau (HPtau) pathology is the common nominator proteinopathy of non-human primate brain aging. The abundance of Aβ in the aging primate brain is well tolerated, and the impact on cognitive functions is usually limited to particular tasks. In contrast, human brain aging is characterized by the early appearance of HPtau pathology, mainly forming neurofibrillary tangles, dystrophic neurites of neuritic plaques, and neuropil threads, preceding Aβ deposits by several decades and by its severity progressing from selected nuclei of the brain stem, entorhinal cortex, and hippocampus to the limbic system, neocortex, and other brain regions. Neurofibrillary tangles correlate with cognitive impairment and dementia in advanced cases. Aβ pathology is linked in humans to altered membrane protein and lipid composition, particularly involving lipid rafts. Although similar membrane alterations are unknown in non-human primates, membrane senescence is postulated to cause the activated β-amyloidogenic pathway, and Aβ pathology is the prevailing signature of non-human and human primate brain aging. [ABSTRACT FROM AUTHOR]

Background: There is renewed interest in whether sex differences in dementia risk exist, and what influence social and biological factors have. Objective: To review evidence from the Cognitive Function and Ageing Studies (CFAS), a multi-center population-representative cohort study in the UK; focusing on dementia and cognition, incorporating findings on participants' health and social circumstances. Methods: After identifying all CFAS publications, the results of all sex-stratified primary analyses of CFAS data were narratively reviewed. Results: Of 337 publications, 94 report results by sex (including null findings), which are summarized by theme: dementia epidemiology, cognition, mental health, health expectancy, social context and biological resource (including neuropathology). Conclusions: Where differences are found they most commonly favor men; however, greater mortality in men may confound associations with age-related outcomes. This 'survival bias' may explain findings of greater risk of dementia and faster cognitive decline in women. Age-specific dementia incidence was similar between sexes, although reduced incidence across study generations was more pronounced in men. Mood disorders were more prevalent in women, but adjusting for disability and deprivation attenuated the association. Prominent findings from other cohorts that women have more Alzheimer's disease pathology and greater risk of dementia from the Apolipoprotein E ɛ4 allele were not observed, warranting further investigation. The 'male-female health-survival paradox' is demonstrated whereby women live longer but with more comorbidity and disability. Examining why health expectancies changed differently over two decades for each sex (interacting with deprivation) may inform population interventions to improve cognitive, mental and physical health in later life. [ABSTRACT FROM AUTHOR]