Current Alzheimer research最新文献

Introduction: Alzheimer's disease is a progressive neurodegenerative condition characterized by the gradual deterioration of cognitive functions. Early identification of functional brain changes is crucial for timely diagnosis and effective intervention. This study employs multiplex network analysis to examine alterations in brain connectivity topology associated with Alzheimer's Disease, to identify early biomarkers and uncover potential therapeutic targets.

Methods: This study presents a secondary cross-sectional analysis based on a publicly available EEG dataset comprising spectral coherence measurements from 25 patients with clinically diagnosed Alzheimer's Disease (AD) and 25 age- and gender-matched Healthy Controls (HC). Functional connectivity matrices were generated across seven distinct frequency bands, with each brain region modeled as a network node and inter-regional coherence values represented as weighted edges. These matrices were then used to construct multiplex brain networks, which were rigorously analyzed using graph-theoretical approaches. The analysis encompassed key metrics, including modularity, centrality measures (Betweenness and MultiRank), motif distribution, and network controllability, to characterize and compare the underlying patterns of functional brain organization in AD and healthy aging.

Results: Networks associated with AD exhibited significantly reduced modularity, disrupted centrality patterns, and a higher occurrence of 2 and 3-node motifs, indicating local reorganization of connectivity. Additionally, the spatial distribution of driver nodes was markedly altered in AD. Centrality analyses revealed a pronounced shift in network hubs toward the temporal and insular cortices, suggesting compensatory or pathological reallocation of influence. Controllability assessments demonstrated a lower energy requirement for network control in AD, accompanied by increased inter-layer fragmentation, reflecting compromised integrative function across frequency bands.

Discussion: The findings revealed specific topological alterations, including reduced modularity, altered centrality, and decreased controllability, all of which are closely linked to AD-related network degeneration. By leveraging multi-frequency EEG data, the multiplex approach shows significant clinical potential for monitoring disease progression and supporting personalized treatments, with the ability to detect subtle connectivity disruptions before cognitive symptoms manifest.

Conclusion: Multiplex network analysis reveals distinct and robust alterations in the functional brain architecture of individuals with Alzheimer's Disease. These network-level disruptions offer valuable insights into the pathophysiology of AD and highlight potential avenues for early diagnosis and targeted therapeutic strategies aimed at preserving cognitive function.

Artificial intelligence (AI) refers to a system that can simulate and execute the processes of human thinking and learning, and make informed decisions. Fueled by the development of AI, the quality and effectiveness of medical work have gained momentum. AI technology plays an increasingly important role in healthcare, exhibiting substantial potential in clinical practice and decision-making processes. In Alzheimer's disease (AD), where early diagnosis and treatment remain challenging due to clinical heterogeneity and insidious progression, AI could offer excellent solutions. AI models can integrate multi-modal data to identify pre-symptomatic biomarkers and stratify high-risk cohorts, improving diagnostic accuracy, assisting with personalizing treatment and care. Furthermore, AI can accelerate drug discovery and development through drug-target identification and predictive modeling of compound efficacy. However, data quality, supervision, transparency, privacy, and ethical concerns need to be addressed. By identifying and retrieving studies for the systematic review, this article provides a comprehensive overview of current progress and related AI applications in AD.

Introduction: Dementia is a set of acquired and progressive neuropsychiatric disorders. The most common types of dementia include Alzheimer's Disease (AD) and Frontotemporal Dementia (FTD). Early intravital diagnosis of both types of dementia is difficult. Both molecular and neuroimaging markers are important for the diagnosis of different types of dementia.

Methods: This review employed freely accessible databases, including PubMed, Google Scholar, and ScienceDirect, using keywords such as molecular parameters, neuroimaging factors, dementia, FTD, Alzheimer's disease, and fMRI.

Results: Among the molecular markers of dementia, there are parameters common to its various types and enabling their differentiation. These parameters include both genetic and biochemical factors. Markers include genetic factors that help differentiate AD (APP, PSEN1, PSEN2) from FTD (e.g., TARDBP, FUS, MAPT). Simultaneously, there are important biochemical parameters differentiating AD (amyloid-beta (Aβ), neurofibrillary tangles) from FTD (TDP-43, FUS, and different forms of tau protein aggregates). Currently, there is growing interest in neuroimaging studies in the differential diagnosis of dementia. Positron Emission Tomography (PET) imaging enables the quantification and localization of Aβ deposits in the brain through the selective binding of the Pittsburgh Compound-B (PiB) ligand. This method has become the standard in AD diagnostics. In the context of magnetic resonance imaging studies, it is worth noting the search for structural differences between AD (mainly affecting the temporal lobe, including the hippocampus and entorhinal cortex, and the parietal lobe) and FTD (primarily involving the prefrontal cortex, anterior temporal lobes, and subcortical structures, as well as exhibiting an anteroposterior gradient of atrophy). However, the method of the future appears to be functional Magnetic Resonance Imaging (fMRI), especially since functional changes precede structural changes in the development of dementia.

Discussion: The review encompasses the basic diagnostic criteria for AD and FTD dementia, as well as molecular and neuroimaging parameters important for the intravital diagnosis of these dementias. It seems that the use of fMRI can contribute to both early diagnosis and early introduction of targeted treatment in developing dementia. Although it is not yet widely used clinically, its diagnostic value is increasingly recognized.

Conclusion: The benefits of fMRI studies complementing molecular markers in the diagnosis of dementia were highlighted.

Alzheimer's disease (AD) and vascular dementia (VD) are the leading causes of dementia, presenting a significant challenge in differential diagnosis. While their clinical presentations can overlap, their underlying pathologies are distinct. AD is characterized by the accumulation of amyloid plaques and neurofibrillary tangles, leading to progressive neurodegeneration. VD, on the other hand, arises from cerebrovascular insults that disrupt blood flow to the brain, causing neuronal injury and cognitive decline. Despite distinct etiologies, AD and VD share common risk factors such as hypertension, diabetes, and hyperlipidemia. Recent research suggests a potential role for oral microbiota in both diseases, warranting further investigation. The diagnostic dilemma lies in the significant overlap of symptoms including memory loss, executive dysfunction, and personality changes. The absence of definitive biomarkers and limitations of current neuroimaging techniques necessitate a multi-modal approach integrating clinical history, cognitive assessment, and neuroimaging findings. Promising avenues for improved diagnosis include the exploration of novel biomarkers like inflammatory markers, MMPs, and circulating microRNAs. Additionally, advanced neuroimaging techniques hold promise in differentiating AD and VD by revealing characteristic cerebrovascular disease patterns and brain atrophy specific to each condition. By elucidating the complexities underlying AD and VD, we can refine diagnostic accuracy and optimize treatment strategies for this ever-growing patient population. Future research efforts should focus on identifying disease-specific biomarkers and developing more effective neuroimaging methods to achieve a definitive diagnosis and guide the development of targeted therapies.

Alzheimer's disease (AD) has been ranked as the most common cause of dementia worldwide, which makes it a major cause of public health concern. The development of AD has been linked to a combination of factors, among which lifestyle-related factors can be targeted to minimize the risk of AD. A balanced diet acts as a source of all essential nutrients that can facilitate the functioning of the brain, promote cognitive longevity, safeguard against neurodegeneration, and, accordingly, reduce the risk of AD. Despite the availability of conclusive evidence highlighting the role of nutrition in the prevention of AD, a range of concerns have been identified that limit dietary adherence and public health efforts. This calls for the need to adopt a multipronged approach, including interventions targeting policy-level changes, the education sector, improvement in the food systems, and behavioural modifications to encourage long-term adherence to diets that are healthy for the brain. In conclusion, diet plays a crucial role in Alzheimer's disease, and there arises the need to incorporate food items that are healthy for the brain to maintain cognitive health and reduce the overall risk. The available data suggests that food items rich in antioxidants, omega-3 fatty acids, and B vitamins are associated with a lower risk of developing Alzheimer's disease.

Lecanemab, a therapeutic antibody designed to target amyloid-beta (Aβ) clearance, has recently been approved by the FDA and introduced in multiple countries, representing a significant milestone in advancing Alzheimer's disease (AD) treatment. However, its limited clinical efficacy underscores the need for further investigation of disease pathogenesis. Emerging evidence suggests that glucose and lipid metabolism dysfunction plays a critical role in AD, with metabolic changes emerging as one of the most significantly altered pathways in the early stage of pathology. These findings highlight the therapeutic potential of targeting metabolic regulation as a strategy to address AD.

Introduction/objective: Primary progressive aphasia (PPA) is a clinical syndrome characterized by progressive language impairment. Three subtypes have been identified: semantic (svPPA), nonfluent (nfPPA), and logopenic (lvPPA). Although clinical criteria exist to classify these subtypes, the specific ways in which semantic cognition is impaired across these variants have not yet been fully elucidated. This cross-sectional study aimed to analyze the effects of cognitive demand and imaginability on semantic cognition in patients with PPA.

Methods: Fifteen patients with PPA (five per variant) and 20 healthy controls completed a semantic association task comprising 20 items. The task included two levels of cognitive demand (low and high) and two types of concepts (concrete and abstract). Participants selected the word with the strongest semantic link to a probe word, based on synonymy, categorical relations, or shared features. Accuracy and reaction times were recorded and analyzed using nonparametric statistics.

Results: All PPA groups performed significantly worse than controls, showing fewer correct responses and longer reaction times. svPPA patients exhibited the greatest impairment across all conditions. nfPPA patients performed similarly to controls with concrete concepts but showed deficits with abstract words. lvPPA patients experienced greater difficulty under high cognitive demand, particularly with abstract words, indicating impaired semantic control.

Discussion: These findings suggest that svPPA is characterized by global impairment of conceptual knowledge, whereas nfPPA and lvPPA exhibit more selective deficits depending on concept type and cognitive demand.

Conclusion: The research herein highlights the importance of considering cognitive demand and imaginability when assessing semantic cognition in PPA.

Introduction: Alzheimer's Disease (AD) is the most prevalent progressive neurodegenerative disorder, leading to significant cognitive decline and dementia. Oxytocin (OXT), a peptide hormone synthesized in the hypothalamus, has emerged as a critical player in cognitive functioning. Notably, alterations in OXT levels have been reported in individuals with Alzheimer's disease.

Methods: This systematic review aims to synthesize existing literature from databases such as PubMed, Scopus, and Web of Science, focusing on the therapeutic potential of OXT in AD treatment. Two independent individuals conducted the screening procedure for all articles.

Results: Our screening revealed that studies investigating OXT therapy primarily involve animal models. These studies consistently demonstrate that, OXT administration mitigates various memory deficits in animal models of AD. These improvements are linked to mechanisms such as reduced microglial-driven inflammation and decreased amyloid-beta (Aβ) deposition, but changes in plaque load do not always correspond directly to cognitive improvement.

Discussion: While these findings are promising and oxytocin could be a potential therapeutic candidate for AD, the evidence is limited to animal studies. There is a lack of robust human data, making it difficult to draw firm conclusions about oxytocin's efficacy in people with AD. Ongoing and future clinical trials will be crucial to determine whether these preclinical benefits translate to humans.

Conclusion: Despite the limited number of studies examining the effects of OXT on AD and the inherent challenges in conducting such research, the available evidence from animal studies suggests promising results. These findings can serve as a valuable foundation for future human and complementary studies aimed at exploring oxytocin's therapeutic potential in treating AD.

Background: Prolonged or repeated psychological stress triggers dental and orthodontic diseases via inflammatory pathways and oxidative stress. This review aims to elucidate the role of inflammation, gut microbiota, stress, and cognition, exploring their impact on the development of therapeutics to enhance oral health.

Objective: The primary aim pertinent to this systematic review is to elucidate the significant implications of cognition and stress in dental and orthodontic health. Specifically, the review aims to (1) investigate the association between emotional stress and the incidence or progression of periodontal disease; (2) explore the impact of physiological and emotional stress on cellular and molecular inflammatory responses in orthodontics; (3) examine the influence of gut-mediated psychophysiological factors on emotional changes in mental health and cognition with a focus on periodontics and orthodontics; and (4) investigate the potential of gut microbiota alterations to influence oral and cognitive/mental health, including the impact of probiotic supplementation and dietary interventions.

Methods: A systematic review was conducted without comprehensive meta-analysis, focusing on literature from 1960 to 2024. Databases searched included PubMed, Embase, ReleMed, National Library of Medicine (NLM), Scopus, and Google Scholar. Keywords used were "cognition," "emotional stress," "gut microbiota," "orthodontics," "prosthetics," "pathophysiology," and "mental health." Studies were selected based on relevance, publication date, access to full texts, and adherence to PRISMA guidelines. The review integrated findings on the impact of emotional stress on periodontal disease and orthodontic health through pathophysiological implications.

Results: Age-related neurodegeneration causes Alzheimer's disease and severe dementia that subsequently promotes poor oral health. The review identified a complex interplay between emotional stress and periodontal disease. While a direct association remains to be conclusively proven, several studies highlight the influence of stress on the severity and incidence of periodontal disease through inflammatory and immunological pathways. Stress manifests in various ways, such as increased masticatory muscle tone, changes in eating behavior, and the initiation of bruxism, all of which can affect dental health. Physiological stress induces an inflammatory response to orthodontic tooth movement, impacting orthodontic treatment outcomes. Furthermore, the review elucidates the role of gut-mediated psychophysiological factors in emotional changes, influencing periodontal and orthodontic health. Emerging evidence suggests that gut microbiota alterations can significantly impact oral and cognitive health through systemic inflammation and neuroimmune mechanisms.

Conclusion: This review highlights the significant impa