Current Alzheimer research最新文献

As the world's population ages, Alzheimer's disease is currently the seventh most common cause of death globally; the burden is anticipated to increase, especially among middle-class and elderly persons. Artificial intelligence-based algorithms that work well in hospital environments can be used to identify Alzheimer's disease. A number of databases were searched for English- language articles published up until March 1, 2024, that examined the relationships between artificial intelligence techniques, eye movements, and Alzheimer's disease. A novel non-invasive method called eye movement analysis may be able to reflect cognitive processes and identify anomalies in Alzheimer's disease. Artificial intelligence, particularly deep learning, and machine learning, is required to enhance Alzheimer's disease detection using eye movement data. One sort of deep learning technique that shows promise is convolutional neural networks, which need further data for precise classification. Nonetheless, machine learning models showed a high degree of accuracy in this context. Artificial intelligence-driven eye movement analysis holds promise for enhancing clinical evaluations, enabling tailored treatment, and fostering the development of early and precise Alzheimer's disease diagnosis. A combination of artificial intelligence-based systems and eye movement analysis can provide a window for early and non-invasive diagnosis of Alzheimer's disease. Despite ongoing difficulties with early Alzheimer's disease detection, this presents a novel strategy that may have consequences for clinical evaluations and customized medication to improve early and accurate diagnosis.

Discoveries in the field of medical sciences are blooming rapidly at the cost of voluminous efforts. Presently, multidisciplinary research activities have been especially contributing to catering cutting-edge solutions to critical problems in the domain of medical sciences. The modern age computing resources have proved to be a boon in this context. Effortless solutions have become a reality, and thus, the real beneficiary patients are able to enjoy improved lives. One of the most emerging problems in this context is Alzheimer's disease, an incurable neurological disorder. For this, early diagnosis is made possible with benchmark computing tools and schemes. These benchmark schemes are the results of novel research contributions being made intermittently in the timeline. In this review, an attempt is made to explore all such contributions in the past few decades. A systematic review is made by categorizing these contributions into three folds, namely, First, Second, and Third Generations. However, priority is given to the latest ones as a handful of literature reviews are already available for the classical ones. Key contributions are discussed vividly. The objectives set for this review are to bring forth the latest discoveries in computing methodologies, especially those dedicated to the diagnosis of Alzheimer's disease. A detailed timeline of the contributions is also made available. Performance plots for certain key contributions are also presented for better graphical understanding.

Introduction: Alzheimer's Disease (AD) is the leading cause of dementia and a significant public health concern, characterized by high incidence, mortality, and economic burden. This study analyzes the mortality patterns and demographic disparities in Alzheimer's disease-related deaths among the elderly population in the United States from 1999 through 2020.

Methods: Alzheimer's disease mortality data for individuals 65 and older were obtained from the CDC WONDER database, utilizing ICD-10 codes G30.0, G30.1, G30.8, and G30.9 for identification. Demographic and regional variables included age, gender, race/ethnicity, place of death, urban- rural status, and geographic region. Crude death rates (CR) and age-adjusted mortality rates (AAMR) per 100,000 individuals were calculated. Joinpoint Regression Program 5.0.2 was used to analyze trends, calculating Annual Percentage Changes (APCs) and Average Annual Percentage Changes (AAPCs).

Results: From 1999 to 2020, 1,852,432 deaths were attributed to AD among individuals aged 65 and older. The AAMR increased from 128.8 in 1999 to 254.3 in 2020, with an AAPC of 2.99% (95% CI = 2.61-3.48). The age-adjusted mortality rate (AAMR) was higher in females (218.5) than in males (163.5). Among racial and ethnic groups, non-Hispanic whites had the highest AAMR, followed by Non-Hispanic Blacks and Hispanics. Regionally, the West reported the highest AAMR, while the Northeast recorded the lowest. Most deaths occurred in nursing homes (57.3%), with a significant portion also occurring at decedents' homes (22.4%).

Conclusion: AD mortality rates in the U.S. have risen significantly, with notable disparities across age, gender, race, and geographic regions. These findings highlight the need for targeted interventions and research to address the growing burden of AD, particularly among the most affected demographic groups.

Aim: The aim of the study was to investigate the factors that underpin neuropsychiatric symptoms and how they might evolve over time in people with Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) dementia.

Background: Neuropsychiatric symptoms are psychiatric and behavioural manifestations that occur in people with AD. These are highly prevalent along the continuum of the disease, including at the stage of MCI, as well as before cognitive decline. Various small- and large-scale projects have investigated the underlying factors that underpin these symptoms; however, the identification of clear clusters is still a matter of debate; furthermore, no study has investigated how the clusters might change across the development of AD pathology by comparing different time points.

Objective: Our objective was to investigate the factors that underpin neuropsychiatric symptoms in Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) and to assess how the loadings might differ based on considerations such as the disease stage of the samples.

Methods: Data was obtained from the Alzheimer's Disease Neuroimaging Initiative database (adni. loni.usc.edu), using scores from the Neuropsychiatric Inventory, followed up yearly from baseline until month 72. Participant groups included those with MCI or AD dementia, or a mixture of both, with all participants presenting with at least one neuropsychiatric symptom. A series of exploratory Principal Component and Factor (Principal Axis) Analyses were performed using Direct Oblimin rotation.

Results: The best-fitting structure was interpreted for each time point. A consistent, unique structure could not be identified, as the factors were unstable over time, both within the MCI and AD groups. However, some symptoms showed a tendency to load on the same factors across most measurements (i.e., agitation with irritability, depression with anxiety, elation with disinhibition, delusions with hallucinations).

Conclusion: Although the analyses revealed some degree of co-occurrence of neuropsychiatric symptoms across time points/samples, there was also considerable variation. In the AD group, more discrete syndromes were evident at the early time points, whereas a more complex picture of co-occurring symptoms, with differences likely reflecting disease staging, was seen at later time points. As a clear and distinctive factor structure was not consistently identified across time points/ samples, this highlights the potential importance of sample selection (e.g., disease stage and/or heterogeneity) when studying, for example, the neurobiological underpinnings of neuropsychiatric symptoms.

Background: A poor prenatal environment adversely affects brain development. Studies investigating long-term consequences of prenatal exposure to the 1944-45 Dutch famine have shown that those exposed to famine in early gestation had poorer selective attention, smaller brain volumes, poorer brain perfusion, older appearing brains, and increased reporting of cognitive problems, all indicative of increased dementia risk.

Objective: In the current population-based study, we investigated whether dementia incidence up to age 75 was higher among individuals who had been prenatally exposed to famine.

Methods: We included men (n=6,714) and women (n=7,051) from the Nivel Primary Care Database who had been born in seven cities affected by the Dutch famine. We used Cox regression to compare dementia incidence among individuals exposed to famine during late (1,231), mid (1,083), or early gestation (601) with those unexposed (born before or conceived after the famine).

Results: We did not observe differences in dementia incidence for those exposed to famine in mid or early gestation compared to those unexposed. Men and women exposed to famine in late gestation had significantly lower dementia rates compared to unexposed individuals (HR 0.52 (95%CI 0.30-0.89)). Sex-specific analyses showed a lower dementia rate in women exposed to famine in late gestation (HR 0.39 (95%CI 0.17-0.86)) but not in men (HR 0.68 (95%CI 0.33-1.41)).

Conclusion: Although prenatal exposure to the Dutch famine has previously been associated with measures of accelerated brain aging, the present population-based study did not show increased dementia incidence up to age 75 in those exposed to famine during gestation.

Background: Multimodal sensory gamma stimulation is a treatment approach for Alzheimers disease that has been shown to improve pathology and memory in transgenic mouse models of Alzheimer's. Because rats are closer to humans in evolution, we tested the hypothesis that the transgenic rat line bearing human APP and PS1, line TgF344-AD, would be a good supplemental candidate to test the efficacy of this treatment. Current therapy approaches under investigation seek to utilize the immune response to minimize or degrade the accumulation of β-amyloid plaque load in mouse models designed to overexpress Aβ. However, many of these models lack some of the hallmarks of Alzheimer's disease, such as hyperphosphorylated tau and neuronal cell loss. The TgF344-AD transgenic rat model is a good candidate to bridge the gap between mouse models and clinical efficacy in humans.

Objective: The objective of this study was to use multimodal gamma stimulation at light and auditory modalities simultaneously to test whether this enhances memory performance as measured by the object location task and the spontaneous alternation task.

Methods: In our study, we designed and built a low-cost, easy-to-construct multimodal light and sound gamma stimulator. Our gamma stimulation device was built using an Arduino microcontroller, which drives lights and a speaker at the gamma frequency. We have included in this paper our device's parts, hardware design, and software architecture for easy reproducibility. We then performed an experiment to test the effect of multimodal gamma stimulation on the cognitive performance of fourteen-month-old TgF344-AD rats. Rats were randomly assigned to either an experimental group that received gamma stimulation or a control group that did not. Performance in a Novel Object Location (NOL) task and spontaneous alternation task was evaluated in both groups before and after the treatment.

Results: Multimodal gamma stimulation did not improve memory compared to unstimulated TgF344-AD rats. However, the gamma-stimulated rats did spend significantly more time exploring objects in the novel location task than the unstimulated rats. In the spontaneous alternation task, gamma-stimulated rats exhibited significantly greater exploratory activity than unstimulated controls.

Conclusion: Multimodal gamma stimulation did not enhance memory performance in the object location task or the spontaneous alternation task. However, in both tasks, the treatment group had improved measures of exploratory activity relative to the untreated group. We conclude that several limitations could have contributed to this mixed effect, including aging complications, different animal models, or light cycle effects.

There shall probably be no "magic bullet" for Alzheimer's; rather, we should be pursuing a "magic shotgun blast" that will target multiple complementary therapeutic receptors. Although protein misfolding/oligomerization will probably be one of these targets, this alone is insufficient and will require the co-administration of other therapeutic entities engaging targets, such as immunopathy, gliopathy, mitochondriopathy, synaptotoxicity or others. Although polypharmacy is emerging as the preferred therapeutic route, many questions remain unanswered. Should this be a cocktail of biologics, a concoction of small molecules, or a judicious combination of both? Biologics and small molecule drugs display both strengths and weaknesses. When addressing a disease as complex and globally important as Alzheimer's, there should be room for the continuing development of both of these therapeutic classes. Each has much to offer, and when used with their advantages and disadvantages in clear focus, an ultimate solution will probably require contributions from both.

Introduction: The COVID-19 pandemic has had multifaceted and enduring impacts on people with dementia and their caregivers; however, our understanding of the long-term outcomes remains limited. We aimed to explore the long-term effects of the COVID-19 pandemic on cognitive symptoms and vaccination rates in people living with dementia.

Methods: This study was conducted as a part of a longitudinal study design in two specialized hospitals in South India. In this study, patients with dementia and their caregivers assessed in earlier phases ('period of lockdown with phased relaxations - phase-I' and 'cluster of cases transmission phase - phase-II') were telephonically interviewed. We adopted a quantitative approach to understand disease progression during the three-year course of the pandemic. Changes in cognition and disease severity were measured using the Clinical Dementia Rating (CDR) scale. In brief, semistructured interviews were carried out with caregivers of people with dementia to gain insights into vaccination rates. Data obtained from the current study (phase III) were compared against phase I data, which served as the baseline. Among the 72 participants contacted in the current phase, 59 (81·9%) could be reevaluated for dementia severity and vaccination status, whereas 13 (18·0%) had died. Among the 59 participants, 33 (55·9%) had severe dementia (CDR 3). This is in contrast to phases I and II, when 17·6% and 19·2% of the participants, respectively, were classified as CDR 3.

Results: A significant difference in dementia severity between the two phases (phases I and III) was observed. In addition, we observed vaccination hesitancy among caregivers of patients with dementia. This study would provide valuable insights into the long-term impact of the COVID-19 pandemic on the cognitive outcomes and vaccination status of patients with dementia.

Conclusion: This overall longitudinal study has compared dementia severity between different phases throughout the pandemic, with implications for future studies to tailor home-based support and healthcare interventions in order to meet these evolving needs.

Background: Alzheimer's Disease (AD) is characterized by a progressive neurodegenerative process leading to cognitive decline and functional impairment. Endocrine factors, particularly sex hormones and their binding proteins, play a critical role in AD pathophysiology. Understanding the relationship between these factors and AD is essential for developing targeted interventions.

Objective: To investigate the potential links between sex hormone binding globulin (SHBG) levels, sex hormone profiles, inflammatory markers, and neurocognitive decline in patients with AD.

Methods: A retrospective case-control investigation was conducted with 110 AD patients who were admitted to our hospital from January 2021 to December 2023, and the patients were classified into either a mild neurocognitive impairment group (n=59) or a moderate to severe neurocognitive impairment group (n=51) according to their cognitive function. Correlation and regression analyses were conducted to examine relationships between variable factors.

Results: The study revealed a significant neurocognitive decline in AD patients with lower Mini-- Mental State Examination (MMSE) and higher AD Assessment Scale-Cognitive Subscale (ADAS- Cog) scores in the moderate to severe neurocognitive impairment group compared to the mild neurocognitive impairment group. Additionally, the moderate to severe neurocognitive impairment group significantly increased for SHBG, estradiol, progesterone inflammatory markers [C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β)). It decreased for follicle-stimulating hormone (FSH) and luteinizing hormone (LH)]. Moreover, significant positive correlations were found between SHBG levels and ADAS-Cog scores, and significant negative correlations were found between SHBG levels and MMSE scores. FSH showed significant negative correlations with the MMSE score, while certain inflammatory markers demonstrated significant correlations with neurocognitive abilities. The correlation between sex hormones and inflammatory factors is weak. FSH, LH, SHBG, CRP, IL-6, TNF-α, and IL-1β are risk factors for neurocognitive impairment, while E2 and P are protective factors.

Conclusion: The study provides evidence of significant correlations between SHBG levels, sex hormone profiles, inflammatory markers, and neurocognitive decline in AD patients.

Background: Evidence on the association of Olfactory Impairment (OI) with age-related cognitive decline is inconclusive, and the potential influence of allergy remains unclear.

Objective: We aimed to evaluate the cross-sectional associations of allergy-related and non-allergy- related OI to cognitive function.

Methods: We included 2,499 participants from the Health and Retirement Study (HRS)-Harmonized Cognitive Assessment Protocol (HCAP) sub-study and 1,086 participants from the English Longitudinal Study of Ageing (ELSA)-HCAP. The Olfactory Function Field Exam (OFFE) using Sniffin' Stick odor pens was used to objectively assess olfactory function and an olfactory score <6/11 indicated OI. Mini-Mental Status Examination (MMSE) was used to assess global cognitive function and define cognitive impairment (<24/30). A neuropsychologic battery was used to assess five cognitive domains.

Results: Compared to non-OI participants, individuals with OI had lower MMSE z-score [β_HRS = -0.33, 95% Confidence Interval (CI): -0.41 to -0.24; β_ELSA = -0.31, -0.43 to -0.18] and higher prevalence of cognitive impairment (Prevalence Ratio (PR)HRS = 1.46, 1.06 to 2.01; PR_ELSA = 1.63, 1.26 to 2.11). The associations were stronger for non-allergy-related OI (β_HRS = -0.36; β_ELSA = -0.34) than for allergy-related OI (β_HRS = -0.26; β_ELSA = 0.13). Similar associations were observed with domain- specific cognitive function measures.

Conclusion: OI, particularly non-allergy-related OI, was related to poorer cognitive function in older adults. Although the current cross-sectional study is subject to several limitations, such as reverse causality and residual confounding, the findings will provide insights into the OI-cognition association and enlighten future attention to non-allergy-related OI for the prevention of potential cognitive impairment.