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Bilingualism is thought to confer advantages in executive functioning, thereby contributing to cognitive reserve and a later age of dementia symptom onset. While the relation between bilingualism and age of onset has been explored in Alzheimer's dementia, there are few studies examining bilingualism as a contributor to cognitive reserve in frontotemporal dementia (FTD). In line with previous findings, we hypothesized that bilinguals with behavioral variant FTD would be older at symptom onset compared to monolinguals, but that no such effect would be found in patients with nonfluent/agrammatic variant primary progressive aphasia (PPA) or semantic variant PPA. Contrary to our hypothesis, we found no significant difference in age at symptom onset between monolingual and bilingual speakers within any of the FTD variants, and there were no notable differences on neuropsychological measures. Overall, our results do not support a protective effect of bilingualism in patients with FTD-spectrum disease in a U.S. based cohort.

Disinhibition is one of the most distressing and difficult to treat neuropsychiatric symptoms of dementia. It involves socially inappropriate behaviours, such as hypersexual comments, inappropriate approaching of strangers and excessive jocularity. Disinhibition occurs in multiple dementia syndromes, including behavioural variant frontotemporal dementia, and dementia of the Alzheimers type. Morphometric similarity networks are a relatively new method for examining brain structure and can be used to calculate measures of network integrity on large scale brain networks and subnetworks such as the salience network and cognitive control network. In a cross-sectional study, we calculated morphometric similarity networks to determine whether disinhibition in behavioural variant frontotemporal dementia (n = 75) and dementia of the Alzheimers type (n = 111) was associated with reduced integrity of these networks independent of diagnosis. We found that presence of disinhibition, measured by the Neuropsychiatric Inventory Questionnaire, was associated with reduced global efficiency of the cognitive control network in both dementia of the Alzheimers type and behavioural variant frontotemporal dementia. Future research should replicate this transdiagnostic finding in other dementia diagnoses and imaging modalities, and investigate the potential for intervention at the level of the cognitive control network to target disinhibition.

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Background: A few studies have suggested that light at night (LAN) exposure, i.e. lighting during night hours, may increase dementia risk. We evaluated such association in a cohort of subjects diagnosed with mild cognitive impairment (MCI). Methods: We recruited study participants between 2008 and 2014 at the Cognitive Neurology Clinic of Modena Hospital, Northern Italy and followed them for conversion to dementia up to 2021. We collected their residential history and we assessed outdoor artificial LAN exposure at subjects' residences using satellite imagery data available from the Visible Infrared Imaging Radiometer Suite (VIIRS) for the period 2014–2022. We assessed the relation between LAN exposure and cerebrospinal fluid biomarkers. We used a Cox-proportional hazards model to compute the hazard ratio (HR) of dementia with 95% confidence interval (CI) according to increasing LAN exposure through linear, categorical, and non-linear restricted-cubic spline models, adjusting by relevant confounders. Results: Out of 53 recruited subjects, 34 converted to dementia of any type and 26 converted to Alzheimer's dementia. Higher levels of LAN were positively associated with biomarkers of tau pathology, as well as with lower concentrations of amyloid β1−42 assessed at baseline. LAN exposure was positively associated with dementia conversion using linear regression model (HR 1.04, 95% CI 1.01–1.07 for 1-unit increase). Using as reference the lowest tertile, subjects at both intermediate and highest tertiles of LAN exposure showed increased risk of dementia conversion (HRs 2.53, 95% CI 0.99–6.50, and 3.61, 95% CI 1.34–9.74). In spline regression analysis, the risk linearly increased for conversion to both any dementia and Alzheimer's dementia above 30 nW/cm2/sr of LAN exposure. Adding potential confounders including traffic-related particulate matter, smoking status, chronic diseases, and apolipoprotein E status to the multivariable model, or removing cases with dementia onset within the first year of follow-up did not substantially alter the results. Conclusion: Our findings suggest that outdoor artificial LAN may increase dementia conversion, especially above 30 nW/cm2/sr, although the limited sample size suggests caution in the interpretation of the results, to be confirmed in larger investigations. [ABSTRACT FROM AUTHOR]

• What is the primary question addressed by this study? Given the brain activity's nonlinear nature, might utilizing the beta-to-theta ratio of EEG derived from nonlinear multiscale dispersion entropy (MDE) offer a more valuable physiological indicator of aging and cognitive impairment compared to this ratio based on the traditional power spectrum? • What is the main finding of this study? The beta-to-theta entropy ratio, assessed through MDE analysis, demonstrated superior sensitivity in distinguishing frontotemporal dementia (FTD) from Alzheimer's dementia (AD) compared to traditional power ratio measures. Additionally, when combined with cognitive assessment, the beta-to-theta entropy ratio offers promising accuracy in distinguishing FTD from AD, surpassing traditional power ratio measures and cognitive testing alone. • What is the meaning of the finding? The finding suggests that nonlinear EEG features, such as the beta-to-theta entropy ratio derived from MDE, could serve as valuable physiological indicators of cognitive impairment and dementia, potentially offering enhanced sensitivity and specificity compared to traditional linear measures. Additionally, the results underscore the potential benefit of integrating nonlinear EEG features into diagnostic and monitoring evaluations to enhance differentiation and comprehension of neurodegenerative disorders. Aging, frontotemporal dementia (FTD), and Alzheimer's dementia (AD) manifest electroencephalography (EEG) alterations, particularly in the beta-to-theta power ratio derived from linear power spectral density (PSD). Given the brain's nonlinear nature, the EEG nonlinear features could provide valuable physiological indicators of aging and cognitive impairment. Multiscale dispersion entropy (MDE) serves as a sensitive nonlinear metric for assessing the information content in EEGs across biologically relevant time scales. To compare the MDE-derived beta-to-theta entropy ratio with its PSD-based counterpart to detect differences between healthy young and elderly individuals and between different dementia subtypes. Scalp EEG recordings were obtained from two datasets: 1) Aging dataset: 133 healthy young and 65 healthy older adult individuals; and 2) Dementia dataset: 29 age-matched healthy controls (HC), 23 FTD, and 36 AD participants. The beta-to-theta ratios based on MDE vs. PSD were analyzed for both datasets. Finally, the relationships between cognitive performance and the beta-to-theta ratios were explored in HC, FTD, and AD. In the Aging dataset, older adults had significantly higher beta-to-theta entropy ratios than young individuals. In the Dementia dataset, this ratio outperformed the beta-to-theta PSD approach in distinguishing between HC, FTD, and AD. The AD participants had a significantly lower beta-to-theta entropy ratio than FTD, especially in the temporal region, unlike its corresponding PSD-based ratio. The beta-to-theta entropy ratio correlated significantly with cognitive performance. Our study introduces the beta-to-theta entropy ratio using nonlinear MDE for EEG analysis, highlighting its potential as a sensitive biomarker for aging and cognitive impairment. [ABSTRACT FROM AUTHOR]

Worldwide, 50 million people are living with dementia. As more individuals develop dementia while still working, dementia will increasingly become a workplace issue and a societal concern. Interventions targeted at work retainment, can reduce, and postpone the loss of cognitive functioning following dementia. However, there is a small body of research focused on recommendations for work interventions for people with dementia. The aim of this mixed-methods review was to investigate experiences of work following a dementia diagnosis from the perspective of people with dementia, their relatives, employers, co-workers and HR-professionals, with the objective of formulating recommendations for work interventions for people with dementia. A mixed-method approach guided the review. 16 original studies published between 1989 to 2023 were included, with a collective sample of 684 participants. The review shows that it is possible to live and work well with dementia, if collaborative solutions are continuously negotiated to meet the needs of the person with dementia and the workplace, and with attention to possible contextual enablers and barriers. The review highlights four key elements for successful work interventions for people with dementia: 1) Person-centered Approach, 2) Contextual Relevance, 3) Knowledge-based and 4) Dynamic Approach. [ABSTRACT FROM AUTHOR]

Abstract Background A few studies have suggested that light at night (LAN) exposure, i.e. lighting during night hours, may increase dementia risk. We evaluated such association in a cohort of subjects diagnosed with mild cognitive impairment (MCI). Methods We recruited study participants between 2008 and 2014 at the Cognitive Neurology Clinic of Modena Hospital, Northern Italy and followed them for conversion to dementia up to 2021. We collected their residential history and we assessed outdoor artificial LAN exposure at subjects’ residences using satellite imagery data available from the Visible Infrared Imaging Radiometer Suite (VIIRS) for the period 2014–2022. We assessed the relation between LAN exposure and cerebrospinal fluid biomarkers. We used a Cox-proportional hazards model to compute the hazard ratio (HR) of dementia with 95% confidence interval (CI) according to increasing LAN exposure through linear, categorical, and non-linear restricted-cubic spline models, adjusting by relevant confounders. Results Out of 53 recruited subjects, 34 converted to dementia of any type and 26 converted to Alzheimer’s dementia. Higher levels of LAN were positively associated with biomarkers of tau pathology, as well as with lower concentrations of amyloid β1−42 assessed at baseline. LAN exposure was positively associated with dementia conversion using linear regression model (HR 1.04, 95% CI 1.01–1.07 for 1-unit increase). Using as reference the lowest tertile, subjects at both intermediate and highest tertiles of LAN exposure showed increased risk of dementia conversion (HRs 2.53, 95% CI 0.99–6.50, and 3.61, 95% CI 1.34–9.74). In spline regression analysis, the risk linearly increased for conversion to both any dementia and Alzheimer’s dementia above 30 nW/cm2/sr of LAN exposure. Adding potential confounders including traffic-related particulate matter, smoking status, chronic diseases, and apolipoprotein E status to the multivariable model, or removing cases with dementia onset within the first year of follow-up did not substantially alter the results. Conclusion Our findings suggest that outdoor artificial LAN may increase dementia conversion, especially above 30 nW/cm2/sr, although the limited sample size suggests caution in the interpretation of the results, to be confirmed in larger investigations.

Vanaja Thulasimani,1 Kogilavani Shanmugavadivel,1 Jaehyuk Cho,2 Sathishkumar Veerappampalayam Easwaramoorthy3 1Department of Artificial Intelligence, Kongu Engineering College, Perundurai, Tamilnadu, India; 2Department of Software Engineering and Division of Electronics and Information Engineering, Jeonbuk National University, Jeonju-Si, Republic of Korea; 3School of Engineering and Technology, Sunway University, Selangor, Darul Ehsan, MalaysiaCorrespondence: Jaehyuk Cho, Email chojh@jbnu.ac.krAbstract: Alzheimer’s Dementia (AD) is a progressive neurological disorder that affects memory and cognitive function, necessitating early detection for its effective management. This poses a significant challenge to global public health. The early and accurate detection of dementia is crucial for several reasons. First, timely detection facilitates early intervention and planning of treatment. Second, precise diagnostic methods are essential for distinguishing dementia from other cognitive disorders and medical conditions that may present with similar symptoms. Continuous analysis and improvements in detection methods have contributed to advancements in medical research. It helps to identify new biomarkers, refine existing diagnostic tools, and foster the development of innovative technologies, ultimately leading to more accurate and efficient diagnostic approaches for dementia. This paper presents a critical analysis of multimodal imaging datasets, learning algorithms, and optimisation techniques utilised in the context of Alzheimer’s dementia detection. The focus is on understanding the advancements and challenges in employing diverse imaging modalities, such as MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography), and EEG (ElectroEncephaloGram). This study evaluated various machine learning algorithms, deep learning models, transfer learning techniques, and generative adversarial networks for the effective analysis of multi-modality imaging data for dementia detection. In addition, a critical examination of optimisation techniques encompassing optimisation algorithms and hyperparameter tuning strategies for processing and analysing images is presented in this study to discern their influence on model performance and generalisation. Thorough examination and enhancement of methods for dementia detection are fundamental for addressing the healthcare challenges posed by dementia, facilitating timely interventions, improving diagnostic accuracy, and advancing research in neurodegenerative diseases.Keywords: Alzheimer’s Dementia, Machine learning, Deep Learning, Transfer Learning and Generative Adversarial Network

Abstract In Alzheimer’s disease (AD), reports on the association between false recognition and brain structure have been inconsistent. In dementia with Lewy bodies (DLB), no such association has been reported. This study aimed to identify brain regions associated with false recognition in AD and DLB by analyzing regional gray matter volume (rGMV). We included 184 patients with AD and 60 patients with DLB. The number of false recognitions was assessed using the Alzheimer’s Disease Assessment Scale’ word recognition task. Brain regions associated with the number of false recognitions were examined by voxel-based morphometry analysis. The number of false recognitions significantly negatively correlated with rGMV in the bilateral hippocampus, left parahippocampal gyrus, bilateral amygdala, and bilateral entorhinal cortex in patients with AD (p < 0.05, family-wise error [FEW] corrected) and in the bilateral hippocampus, left parahippocampal gyrus, right inferior frontal gyrus, right middle frontal gyrus, right basal forebrain, right insula, left medial and lateral orbital gyri, and left fusiform in those with DLB (p < 0.05, FWE corrected). Bilateral hippocampus and left parahippocampal gyrus were associated with false recognition in both diseases. However, we found there were regions where the association between false recognition and rGMV differed from disease to disease.

Abstract Background Reactive microglia and recruited peripheral macrophages contribute to the pathogenesis of Alzheimer’s dementia (AD). Monocytes, macrophages and microglia all express the marker colony-stimulating factor 1 receptor (CSF1R). 4-Cyano-N-(4-(4-methylpiperazin-1-yl)-2-(4-methylpiperidin-1-yl)phenyl)-1H-pyrrole-2-carboxamide (1) is a high-affinity antagonist for CSF1R. We report the radiosynthesis of both [3H]1 and [11C]1. The PET imaging properties of [11C]1 in mice and baboon were investigated. [3H]1 was studied in Bmax measurement in post-mortem autoradiography in the frontal cortex, inferior parietal cortex and hippocampus from donors diagnosed with AD and age-matched controls. In vitro binding affinity of 1 was measured commercially. Nor-methyl-1 precursor was radiolabeled with [11C]iodomethane or [3H]iodomethane to produce [11C]1 and [3H]1, respectively. Ex vivo brain biodistribution of [11C]1 was compared in normal mice versus lipopolysaccharide-administered (LPS) murine model of neuroinflammation. Dynamic PET imaging was performed in a healthy male Papio anubis baboon. Post-mortem autoradiography with [3H]1 was performed in frozen sections using a standard saturation binding technique. Results Compound 1 exhibits a high in vitro CSF1R binding affinity (0.59 nM). [11C]1 was synthesized with high yield. [3H]1 was synthesized similarly (commercially). Biodistribution of [11C]1 in healthy mice demonstrated moderate brain uptake. In LPS-treated mice the brain uptake of [11C]1 was ~ 50% specific for CSF1R. PET/CT [11C]1 study in baboon revealed low brain uptake (0.36 SUV) of [11C]1. Autoradiography with [3H]1 gave significantly elevated Bmax values in AD frontal cortex versus control (47.78 ± 26.80 fmol/mg vs. 12.80 ± 5.30 fmol/mg, respectively, P = 0.023) and elevated, but not significantly different binding in AD hippocampus grey matter and inferior parietal cortex (IPC) white matter. Conclusions Compound 1 exhibits a high in vitro CSF1R binding affinity. [11C]1 specifically labels CSF1R in the mouse neuroinflammation, but lacks the ability to efficiently cross the blood–brain barrier in baboon PET. [3H]1 specifically labels CSF1R in post-mortem human brain. The binding of [3H]1 is significantly higher in the post-mortem frontal cortex of AD versus control subjects.

Abstract Several (inter)national longitudinal dementia observational datasets encompassing demographic information, neuroimaging, biomarkers, neuropsychological evaluations, and muti-omics data, have ushered in a new era of potential for integrating machine learning (ML) into dementia research and clinical practice. ML, with its proficiency in handling multi-modal and high-dimensional data, has emerged as an innovative technique to facilitate early diagnosis, differential diagnosis, and to predict onset and progression of mild cognitive impairment and dementia. In this review, we evaluate current and potential applications of ML, including its history in dementia research, how it compares to traditional statistics, the types of datasets it uses and the general workflow. Moreover, we identify the technical barriers and challenges of ML implementations in clinical practice. Overall, this review provides a comprehensive understanding of ML with non-technical explanations for broader accessibility to biomedical scientists and clinicians.

In Alzheimer's disease (AD), reports on the association between false recognition and brain structure have been inconsistent. In dementia with Lewy bodies (DLB), no such association has been reported. This study aimed to identify brain regions associated with false recognition in AD and DLB by analyzing regional gray matter volume (rGMV). We included 184 patients with AD and 60 patients with DLB. The number of false recognitions was assessed using the Alzheimer's Disease Assessment Scale' word recognition task. Brain regions associated with the number of false recognitions were examined by voxel-based morphometry analysis. The number of false recognitions significantly negatively correlated with rGMV in the bilateral hippocampus, left parahippocampal gyrus, bilateral amygdala, and bilateral entorhinal cortex in patients with AD (p < 0.05, family-wise error [FEW] corrected) and in the bilateral hippocampus, left parahippocampal gyrus, right inferior frontal gyrus, right middle frontal gyrus, right basal forebrain, right insula, left medial and lateral orbital gyri, and left fusiform in those with DLB (p < 0.05, FWE corrected). Bilateral hippocampus and left parahippocampal gyrus were associated with false recognition in both diseases. However, we found there were regions where the association between false recognition and rGMV differed from disease to disease. [ABSTRACT FROM AUTHOR]

Introduction: Living with dementia can be challenging, even more so for people diagnosed before age 65. Loss of identity is one of the main subjective consequences dementia poses at this stage in life due to the loss of social relations and daily activities. While a growing body of research is reporting the experienced impact of early-onset dementia on identity for this group, studies synthesizing this knowledge are very limited. Therefore, we have conducted a meta-ethnographic review to explain how people with early-onset dementia form their sense of identity. Method: A systematic review of literature from five databases was conducted. Ten original studies published between 2004 and 2020 were included and analyzed using an interpretive approach. Findings: A conceptual interpretation emerged from the analysis, showing that social arenas and activities of daily life, as well as assumptions about dementia and natural aging made by the participants and society, influenced the participants' sense of identity. Conclusion: Being in nonjudgmental environments can support people with early-onset dementia in creating continuity and positive connections in their personal history. Providing such environments can be a viable venue for healthcare professionals to support people with early-onset dementia in maintaining a positive sense of identity. [ABSTRACT FROM AUTHOR]

Background: The associations between mood disorders (anxiety and depression) and mild cognitive impairment (MCI) or Alzheimer's dementia (AD) remain unclear. Methods: Data from the Australian Imaging, Biomarker & Lifestyle (AIBL) study were subjected to logistic regression to determine both cross-sectional and longitudinal associations between anxiety/depression and MCI/AD. Effect modification by selected covariates was analysed using the likelihood ratio test. Results: Cross-sectional analysis was performed to explore the association between anxiety/depression and MCI/AD among 2,209 participants with a mean [SD] age of 72.3 [7.4] years, of whom 55.4% were female. After adjusting for confounding variables, we found a significant increase in the odds of AD among participants with two mood disorders (anxiety: OR 1.65 [95% CI 1.04–2.60]; depression: OR 1.73 [1.12–2.69]). Longitudinal analysis was conducted to explore the target associations among 1,379 participants with a mean age of 71.2 [6.6] years, of whom 56.3% were female. During a mean follow-up of 5.0 [4.2] years, 163 participants who developed MCI/AD (refer to as PRO) were identified. Only anxiety was associated with higher odds of PRO after adjusting for covariates (OR 1.56 [1.03–2.39]). However, after additional adjustment for depression, the association became insignificant. Additionally, age, sex, and marital status were identified as effect modifiers for the target associations. Conclusion: Our study provides supportive evidence that anxiety and depression impact on the evolution of MCI/AD, which provides valuable epidemiological insights that can inform clinical practice, guiding clinicians in offering targeted dementia prevention and surveillance programs to the at-risk populations. [ABSTRACT FROM AUTHOR]

Background: Brain age prediction from brain MRI scans and the resulting brain age gap (BAG)—the difference between predicted brain age and chronological age—is a general biomarker for a variety of neurological, psychiatric, and other diseases or disorders. Methods: This study examined the differences in BAG values derived from T1-weighted scans using five state-of-the-art deep learning model architectures previously used in the brain age literature: 2D/3D VGG, RelationNet, ResNet, and SFCN. The models were evaluated on healthy controls and cohorts with sleep apnea, diabetes, multiple sclerosis, Parkinson's disease, mild cognitive impairment, and Alzheimer's disease, employing rigorous statistical analysis, including repeated model training and linear mixed-effects models. Results: All five models consistently identified a statistically significant positive BAG for diabetes (ranging from 0.79 years with RelationNet to 2.13 years with SFCN), multiple sclerosis (2.67 years with 3D VGG to 4.24 years with 2D VGG), mild cognitive impairment (2.13 years with 2D VGG to 2.59 years with 3D VGG), and Alzheimer's dementia (5.54 years with ResNet to 6.48 years with SFCN). For Parkinson's disease, a statistically significant BAG increase was observed in all models except ResNet (1.30 years with 2D VGG to 2.59 years with 3D VGG). For sleep apnea, a statistically significant BAG increase was only detected with the SFCN model (1.59 years). Additionally, we observed a trend of decreasing BAG with increasing chronological age, which was more pronounced in diseased cohorts, particularly those with the largest BAG, such as multiple sclerosis (−0.34 to −0.2), mild cognitive impairment (−0.37 to −0.26), and Alzheimer's dementia (−0.66 to −0.47), compared to healthy controls (−0.18 to −0.1). Conclusions: Consistent with previous research, Alzheimer's dementia and multiple sclerosis exhibited the largest BAG across all models, with SFCN predicting the highest BAG overall. The negative BAG trend suggests a complex interplay of survival bias, disease progression, adaptation, and therapy that influences brain age prediction across the age spectrum. [ABSTRACT FROM AUTHOR]

Background: Reactive microglia and recruited peripheral macrophages contribute to the pathogenesis of Alzheimer's dementia (AD). Monocytes, macrophages and microglia all express the marker colony-stimulating factor 1 receptor (CSF1R). 4-Cyano-N-(4-(4-methylpiperazin-1-yl)-2-(4-methylpiperidin-1-yl)phenyl)-1H-pyrrole-2-carboxamide (1) is a high-affinity antagonist for CSF1R. We report the radiosynthesis of both [3H]1 and [11C]1. The PET imaging properties of [11C]1 in mice and baboon were investigated. [3H]1 was studied in Bmax measurement in post-mortem autoradiography in the frontal cortex, inferior parietal cortex and hippocampus from donors diagnosed with AD and age-matched controls. In vitro binding affinity of 1 was measured commercially. Nor-methyl-1 precursor was radiolabeled with [11C]iodomethane or [3H]iodomethane to produce [11C]1 and [3H]1, respectively. Ex vivo brain biodistribution of [11C]1 was compared in normal mice versus lipopolysaccharide-administered (LPS) murine model of neuroinflammation. Dynamic PET imaging was performed in a healthy male Papio anubis baboon. Post-mortem autoradiography with [3H]1 was performed in frozen sections using a standard saturation binding technique. Results: Compound 1 exhibits a high in vitro CSF1R binding affinity (0.59 nM). [11C]1 was synthesized with high yield. [3H]1 was synthesized similarly (commercially). Biodistribution of [11C]1 in healthy mice demonstrated moderate brain uptake. In LPS-treated mice the brain uptake of [11C]1 was ~ 50% specific for CSF1R. PET/CT [11C]1 study in baboon revealed low brain uptake (0.36 SUV) of [11C]1. Autoradiography with [3H]1 gave significantly elevated Bmax values in AD frontal cortex versus control (47.78 ± 26.80 fmol/mg vs. 12.80 ± 5.30 fmol/mg, respectively, P = 0.023) and elevated, but not significantly different binding in AD hippocampus grey matter and inferior parietal cortex (IPC) white matter. Conclusions: Compound 1 exhibits a high in vitro CSF1R binding affinity. [11C]1 specifically labels CSF1R in the mouse neuroinflammation, but lacks the ability to efficiently cross the blood–brain barrier in baboon PET. [3H]1 specifically labels CSF1R in post-mortem human brain. The binding of [3H]1 is significantly higher in the post-mortem frontal cortex of AD versus control subjects. [ABSTRACT FROM AUTHOR]

Several (inter)national longitudinal dementia observational datasets encompassing demographic information, neuroimaging, biomarkers, neuropsychological evaluations, and muti-omics data, have ushered in a new era of potential for integrating machine learning (ML) into dementia research and clinical practice. ML, with its proficiency in handling multi-modal and high-dimensional data, has emerged as an innovative technique to facilitate early diagnosis, differential diagnosis, and to predict onset and progression of mild cognitive impairment and dementia. In this review, we evaluate current and potential applications of ML, including its history in dementia research, how it compares to traditional statistics, the types of datasets it uses and the general workflow. Moreover, we identify the technical barriers and challenges of ML implementations in clinical practice. Overall, this review provides a comprehensive understanding of ML with non-technical explanations for broader accessibility to biomedical scientists and clinicians. [ABSTRACT FROM AUTHOR]

Background: Recent studies propose 40 Hz neural activity induction as a promising approach for managing Alzheimer's dementia (AD). However, traditional flickering light is suboptimal in addressing cognitive and neuropsychiatric symptoms (NPS) of AD. This study aims to investigate the clinical efficacy of a novel multi-luminaire lighting technology, with reduced perceptible flickering, for treating AD NPS. Methods: This study is a prospective, convenient sampling, non-randomized case–control investigation involving seventy-eight clinically diagnosed AD patients from 7 daycare centers. Thirty-five were exposed to 40 Hz light through Delta M + BrainCare Light (M +), 4 h daily, 5 days/week, for 12 weeks. The other 43 patients served as controls. Sum of boxes of the Clinical Dementia Rating (CDR-SB) scale, Neuropsychiatric Inventory (NPI), and Zarit Burden Interview (ZBI) were assessed at baseline and the 13th week. Results: At baseline, the cases had worse cognitive function, lower cognitive score (Mini-Mental State Examination, p = 0.04; Cognitive Abilities Screening Instrument, p = 0.04), and advanced caregiver burden with higher ZBI scores (p < 0.01) than the controls. After the intervention, the cases had significant improvements in NPS as assessed using the NPI (p = 0.02), especially depression and euphoria symptoms (p = 0.04 and < 0.01, respectively) and less caregiver burden (ZBI score, p < 0.01). In global function, the control group showed a significant decline in CDR-SB score (p < 0.01), while the cases did not. Conclusions: Results suggest M + may slow global function decline, preserve cognitive function, improve NPS, and reduce caregiver burden in AD patients. Larger studies with biomarkers are needed to explore underlying mechanisms. [ABSTRACT FROM AUTHOR]

The current study tested object drawing, object naming, and object-in-scene perception. We tested older people with Alzheimer's dementia (AD) because their object drawings have often lost their typical contours. We investigated whether intensive practice could improve or recover deteriorated graphic object representations in three tasks, object naming, object-in-scene, and object drawing. Ten older participants with AD and 10 healthy controls practiced for 5 consecutive days always involving the same 10 objects (item-based learning). Patients with AD closed the gap to healthy controls as reaction time decreased and accuracy increased. Performance level and task difficulty were dependent on age, education, and length of retirement duration, but interactions between practice and task difficulty were not. In accuracy, the group difference disappeared earlier in object naming < object-in-scene < object drawing. During the 5 days of practice, lost graphic object concepts could reemerge. Multiple regressions testing synergistic effects between tasks showed that rapid object-in-scene judgment and drawing time relatively consistently and reliably predicted object drawing accuracy. However, when testing day-to-day progress of the drawing score, after the first repetition, only the object drawing score of the previous session significantly predicted the graphic object representation. Thus, while perceptual judgment of an object in an appropriate visual scene predicts object drawing—just as in previous research using the Witkin Embedded Figures Test—the fine motor skills involved in visually realistic drawing are likely to be the most important factor to generate a recognizable graphic object representation. [ABSTRACT FROM AUTHOR]

Purpose of Review: We review current literature related to the clinical assessment of Mild Cognitive Impairment (MCI). We compile recommendations related to the evaluation of MCI and examine literature regarding the use of clinical biomarkers in this assessment, the role of non-pharmacologic therapy in the prevention of cognitive decline, and recent approval of anti-amyloid therapy in the treatment of MCI. Recent Findings: The role of imaging and plasma biomarkers in the clinical assessment of MCI has expanded. There is data that non-pharmacologic therapy may have a role in the prevention of neurocognitive decline. Anti-amyloid therapies have recently been approved for clinical use. Summary: Clinical assessment of MCI remains multifactorial and includes screening and treating for underlying psychiatric and medical co-morbidities. The use of biomarkers in clinical settings is expanding with the rise of anti-amyloid therapies. These new diagnostics and therapeutics require nuanced discussion of risks and benefits. Psychiatrist's skillset is uniquely suited for these complex evaluations. [ABSTRACT FROM AUTHOR]

Long-term potentiation (LTP)-like activity can be induced by stimulation protocols such as paired associative stimulation (PAS). We aimed to determine whether PAS-induced LTP-like activity (PAS-LTP) of the dorsolateral prefrontal cortex (DLPFC) is associated with cortical thickness and other structural measures impaired in Alzheimer's dementia (AD). We also explored longitudinal relationships between these brain structures and PAS-LTP response after a repetitive PAS (rPAS) intervention. Mediation and regression analyses were conducted using data from randomized controlled trials with AD and healthy control participants. PAS-electroencephalography assessed DLPFC PAS-LTP. DLPFC thickness and surface area were acquired from T1-weighted magnetic resonance imaging. Fractional anisotropy and mean diffusivity (MD) of the superior longitudinal fasciculus (SLF)—a tract important to induce PAS-LTP—were measured with diffusion-weighted imaging. AD participants exhibited reduced DLPFC thickness and increased SLF MD. There was also some evidence that reduction in DLPFC thickness mediates DLPFC PAS-LTP impairment. Longitudinal analyses showed preliminary evidence that SLF MD, and to a lesser extent DLPFC thickness, is associated with DLPFC PAS-LTP response to active rPAS. This study expands our understanding of the relationships between brain structural changes and neuroplasticity. It provides promising evidence for a structural predictor to improving neuroplasticity in AD with neurostimulation. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'. [ABSTRACT FROM AUTHOR]

This report examines extended intra-nasal insulin treatment [INI] for an Insulin Resistant early Mild Cognitive Impairment [MCI] patient. Patient [EJ] also had medial temporal lobe [MTL] damage, poor short-term memory, significant irritability, and social and linguistic withdrawal at treatment start. Compared to baseline, nine months INI treatment increased grey matter volume, lowered beta-amyloid levels, and improved MCI and FAS scores. Patient also increased pragmatic capacities in social conversation and procedural memory. These findings align with results from prior clinical trials on INI and suggest that treatment can slow neurodegenerative disease progression in early MCI patients. [ABSTRACT FROM AUTHOR]

Most of the heritability in frontotemporal dementia (FTD) is accounted for by autosomal dominant hexanucleotide expansion in the chromosome 9 open reading frame 72 (C9orf72), pathogenic/likely pathogenic variants in progranulin (GRN), and microtubule-associated protein tau (MAPT) genes. Until now, there has been no systematic analysis of these genes in the Serbian population. Herein, we assessed the frequency of the C9orf72 expansion, pathogenic/likely pathogenic variants in GRN and MAPT in a well-characterized group of 472 subjects (FTD, Alzheimer's disease - AD, mild cognitive impairment - MCI, and unspecified dementia - UnD), recruited in the Memory Center, Neurology Clinic, University Clinical Center of Serbia. The C9orf72 repeat expansion was detected in 6.98% of FTD cases (13.46% familial; 2.6% sporadic). In the UnD subgroup, C9orf72 repeat expansions were detected in 4.08% (8% familial) individuals. Pathogenic variants in the GRN were found in 2.85% of familial FTD cases. Interestingly, no MAPT pathogenic/likely pathogenic variants were detected, suggesting possible geographical specificity. Our findings highlight the importance of wider implementation of genetic testing in neurological and psychiatric practice managing patients with cognitive-behavioral and motor symptoms. [ABSTRACT FROM AUTHOR]

IntroductionFilipino Americans are one of the largest Asian American and Pacific Islander (AAPI) populations in the United States (US). Previous studies suggest that Filipino Americans have one of the highest incidence rates of Alzheimer's disease and related dementias (ADRD) among AAPI subgroups. Despite the expected increase in Filipino Americans with ADRD, no studies to-date have validated neuropsychological measures in the United States for speakers of Tagalog, a major language spoken by Filipino Americans. A significant barrier to dementia care and diagnosis is the lack of linguistically and socioculturally appropriate cognitive tasks for Tagalog speakers. To address this need, we developed and piloted the Cognitive Assessment for Tagalog Speakers (CATS), the first neuropsychological battery for the detection of ADRD in Filipino American Tagalog speakers.MethodsBased on evidence-based neuropsychological batteries, we adapted and constructed de novo tasks to measure performance across 4 main cognitive domains: visual/verbal memory, visuospatial functioning, speech and language, and frontal/executive functioning. Tasks were developed with a team of bilingual English/Tagalog, bicultural Filipino American/Canadian experts, including a neurologist, speech-language pathologist, linguist, and neuropsychologist. We recruited Tagalog-speaking participants of age 50+ through social media advertisements and recruitment registries for this cross-sectional study. We present the CATS design and protocol.ResultsTo-date, the CATS battery has been administered to 26 healthy control participants (age 64.5 ± 7.8 years, 18F/8 M) at an academic institution in Northern California, United States. The development and administration of the CATS battery demonstrated its feasibility but also highlighted the need to consider the effects of bilingualism, language typology, and cultural factors in result interpretation.DiscussionThe CATS battery provides a mechanism for cognitive assessment of Filipino Americans, a population that has been underrepresented in ADRD research. As we move toward the treatment and cure of ADRD, linguistically and socioculturally appropriate cognitive tests become even more important for equitable care.

Abstract Background The associations between mood disorders (anxiety and depression) and mild cognitive impairment (MCI) or Alzheimer’s dementia (AD) remain unclear. Methods Data from the Australian Imaging, Biomarker & Lifestyle (AIBL) study were subjected to logistic regression to determine both cross-sectional and longitudinal associations between anxiety/depression and MCI/AD. Effect modification by selected covariates was analysed using the likelihood ratio test. Results Cross-sectional analysis was performed to explore the association between anxiety/depression and MCI/AD among 2,209 participants with a mean [SD] age of 72.3 [7.4] years, of whom 55.4% were female. After adjusting for confounding variables, we found a significant increase in the odds of AD among participants with two mood disorders (anxiety: OR 1.65 [95% CI 1.04–2.60]; depression: OR 1.73 [1.12–2.69]). Longitudinal analysis was conducted to explore the target associations among 1,379 participants with a mean age of 71.2 [6.6] years, of whom 56.3% were female. During a mean follow-up of 5.0 [4.2] years, 163 participants who developed MCI/AD (refer to as PRO) were identified. Only anxiety was associated with higher odds of PRO after adjusting for covariates (OR 1.56 [1.03–2.39]). However, after additional adjustment for depression, the association became insignificant. Additionally, age, sex, and marital status were identified as effect modifiers for the target associations. Conclusion Our study provides supportive evidence that anxiety and depression impact on the evolution of MCI/AD, which provides valuable epidemiological insights that can inform clinical practice, guiding clinicians in offering targeted dementia prevention and surveillance programs to the at-risk populations.

Abstract Background Irregular word reading has been used to estimate premorbid intelligence in Alzheimer’s disease (AD) dementia. However, reading models highlight the core influence of semantic abilities on irregular word reading, which shows early decline in AD. The primary objective of this study is to ascertain whether irregular word reading serves as an indicator of cognitive and semantic decline in AD, potentially discouraging its use as a marker for premorbid intellectual abilities. Method Six hundred eighty-one healthy controls (HC), 104 subjective cognitive decline, 290 early and 589 late mild cognitive impairment (EMCI, LMCI) and 348 AD participants from the Alzheimer’s Disease Neuroimaging Initiative were included. Irregular word reading was assessed with the American National Adult Reading Test (AmNART). Multiple linear regressions were conducted predicting AmNART score using diagnostic category, general cognitive impairment and semantic tests. A generalized logistic mixed-effects model predicted correct reading using extracted psycholinguistic characteristics of each AmNART words. Deformation-based morphometry was used to assess the relationship between AmNART scores and voxel-wise brain volumes, as well as with the volume of a region of interest placed in the left anterior temporal lobe (ATL), a region implicated in semantic memory. Results EMCI, LMCI and AD patients made significantly more errors in reading irregular words compared to HC, and AD patients made more errors than all other groups. Across the AD continuum, as well as within each diagnostic group, irregular word reading was significantly correlated to measures of general cognitive impairment / dementia severity. Neuropsychological tests of lexicosemantics were moderately correlated to irregular word reading whilst executive functioning and episodic memory were respectively weakly and not correlated. Age of acquisition, a primarily semantic variable, had a strong effect on irregular word reading accuracy whilst none of the phonological variables significantly contributed. Neuroimaging analyses pointed to bilateral hippocampal and left ATL volume loss as the main contributors to decreased irregular word reading performances. Conclusions While the AmNART may be appropriate to measure premorbid intellectual abilities in cognitively unimpaired individuals, our results suggest that it captures current semantic decline in MCI and AD patients and may therefore underestimate premorbid intelligence. On the other hand, irregular word reading tests might be clinically useful to detect semantic impairments in individuals on the AD continuum.

Dementia is growing exponentially worldwide. Unfortunately, the treatment available does not reverse any type of cognitive impairment. As a result, healthcare professionals are focusing on other evidence-based options, such as lifestyle medicine (LM). Current evidence demonstrates improvement in neurocognitive decline by applying the six pillars of LM, which include plant-based nutrition, physical activity, stress management, avoidance of risky substances, restorative sleep, and social connections. Plant-based nutrition has a positive impact on cognition by decreasing the risk for Alzheimer's disease (AD) with high adherence to the Mediterranean-Dietary Approach to Systolic Hypertension (DASH) Intervention for Neurodegenerative Delay (MIND). Physical activity also might prevent neurocognitive decline by increasing fibronectin type III domain-containing protein 5 (FNDC5) and Irisin in the hippocampus, which increases energy expenditure and prolongs endurance. Additionally, higher perceived stress in adulthood and the use of risky substances such as alcohol, nicotine, and opioids are significantly associated with developing mild cognitive impairment and all-cause dementia. Furthermore, there is a positive correlation between poor sleep and social isolation with a rapid progression in cognitive decline. Lifestyle changes have a substantial impact on brain health. Therefore, the focus should always be on prevention as the primary treatment tool.

Objective: To systematically evaluate the effect of physical exercise intervention on the activities of daily living (ADL) on patients with Alzheimer's dementia (AD) and explore the optimal exercise scheme. Methods: PubMed, EMBASE, the Cochrane Library, Web of Science, and Science Direct databases were searched from 1987 to December 2023 to collect randomized controlled trials (RCTs). Two investigators independently screened the literature and extracted data according to the inclusion and exclusion criteria. The quality of the included studies was evaluated using Cochrane Review Manager 5.3. And STATA 16.0 was used for performing the meta-analysis. Results: Fifteen randomized controlled trials were included. The results of the meta-analysis showed that physical exercise had a positive effect on the improvement of ADL in patients with AD [standardized mean difference (SMD) = 0.312, 95% confidence interval (CI 0.039-0.585), P = 0.02], and the difference was statistically significant. The results of subgroup analysis showed that anaerobic exercises such as strength and balance training with a medium cycle of 12-16 weeks and lasting 30-45 min each time were more ideal for the improvement of basic daily living ability of AD patients. Conclusion: Physical exercise can effectively improve activities of daily living in patients with Alzheimer's dementia and it may be a potential non-drug treatment for AD patients. [ABSTRACT FROM AUTHOR]

Based on the idea that music acts as a mnemonic aid, musical mnemonics (i.e., sung presentation of information, also referred to as 'music as a structural prompt'), are being used in educational and therapeutic settings. However, evidence in general and patient populations is still scarce. We investigated whether musical mnemonics affect working and episodic memory performance in cognitively unimpaired individuals and persons with Alzheimer's dementia (AD). Furthermore, we examined the possible contribution of musical expertise. We comprehensively searched the PubMed and PsycINFO databases for studies published between 1970 and 2022. Also, reference lists of all identified papers were manually extracted to identify additional articles. Of 1,126 records identified, 37 were eligible and included. Beneficial effects of musical mnemonics on some aspect of memory performance were reported in 28 of 37 studies, including nine on AD. Nine studies found no beneficial effect. Familiarity contributed positively to this beneficial effect in cognitively unimpaired adults, but require more extensive investigation in AD. Musical expertise generally did not lead to additional benefits for cognitively unimpaired participants, but may benefit people with AD. Musical mnemonics may help to learn and remember verbal information in cognitively unimpaired individuals and individuals with memory impairment. Here, we provide a theoretical model of the possible underlying mechanisms of musical mnemonics, building on previous frameworks. We also discuss the implications for designing music-based mnemonics. [ABSTRACT FROM AUTHOR]

Theta–gamma coupling (TGC) is a neurophysiological process that supports working memory. Working memory is associated with other clinical and biological features. The extent to which TGC is associated with these other features and whether it contributes to working memory beyond these features is unknown. Two-hundred-and-three older participants at risk for Alzheimer's dementia—98 with mild cognitive impairment (MCI), 39 with major depressive disorder (MDD) in remission, and 66 with MCI and MDD (MCI + MDD)—completed a clinical assessment, N-back-EEG, and brain MRI. Among them, 190 completed genetic testing, and 121 completed [11C] Pittsburgh Compound B ([11C] PIB) PET imaging. Hierarchical linear regressions were used to assess whether TGC is associated with demographic and clinical variables; Alzheimer's disease-related features (APOE ε4 carrier status and β-amyloid load); and structural features related to working memory. Then, linear regressions were used to assess whether TGC is associated with 2-back performance after accounting for these features. Other than age, TGC was not associated with any non-neurophysiological features. In contrast, TGC (β = 0.27; p = 0.006), age (β = − 0.29; p = 0.012), and parietal cortical thickness (β = 0.24; p = 0.020) were associated with 2-back performance. We also examined two other EEG features that are linked to working memory—theta event-related synchronization and alpha event-related desynchronization—and found them not to be associated with any feature or performance after accounting for TGC. Our findings suggest that TGC is a process that is independent of other clinical, genetic, neurochemical, and structural variables, and supports working memory in older adults at risk for dementia. [ABSTRACT FROM AUTHOR]

Background: Mild behavioural impairment (MBI) is an emergent and persistent neuropsychiatric symptom (NPS) in subjects aged 50 and older who are at risk for cognitive decline. We examined the prevalence of MBI across the spectrum from cognitively normal (CN), mild cognitive impairment (MCI), to dementia, and further investigated the association between the MBI domain and cognitive and functional impairment. Method: MBI was assessed in 2337 elderly patients in the Alzheimer's Disease Neuroimaging Initiative database (mean age, 73.04 years; 52.8% male). Among the subjects, 868 (37.1%) had normal cognition, 1066 (45.6%) had MCI, and 403 (17.2%) had mild Alzheimer's dementia (AD). MBI was evaluated in accordance with the Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment diagnostic criteria for MBI, utilising the Neuropsychiatric Inventory. We compared the prevalence of the MBI domain with CN using multinominal logistic regression analysis and further quantified the magnitude of the association between MCI/AD and the MBI domains by calculating the population attributable risk (PAR). We assessed the association between the MBI domains and cognitive and functional impairment using simultaneous linear regression analysis. Results: The most common MBI domains in each diagnostic group were affective dysregulation followed by impulse dyscontrol, decreased motivation, social inappropriateness, and abnormal perception or thought content. The PARs for MBI domains in subjects with MCI or AD were respectively: 16.60% and 24.34% for affective dysregulation; 3.72% and 18.06% for impulse dyscontrol; 4.78% and 14.13% for decreased motivation, 1.91% and 2.29% for social inappropriateness; and 0.68% and 3.85% for abnormal perception or thought content. All MBI domains except for social inappropriateness were significantly associated with a higher 11‐item Alzheimer's Disease Assessment Scale–Cognitive Subscale total score. All MBI domains were significantly associated with a higher Functional Activities Questionnaire total score. Conclusion: Our findings show that MBI is highly prevalent across subjects with CN, MCI, and AD and is associated with cognitive and functional decline. MBI could be a crucial clinical phenotype relevant to the risk of cognitive and functional impairment, and provides a useful dimension pertinent to diagnostic approaches. [ABSTRACT FROM AUTHOR]

Background: Irregular word reading has been used to estimate premorbid intelligence in Alzheimer's disease (AD) dementia. However, reading models highlight the core influence of semantic abilities on irregular word reading, which shows early decline in AD. The primary objective of this study is to ascertain whether irregular word reading serves as an indicator of cognitive and semantic decline in AD, potentially discouraging its use as a marker for premorbid intellectual abilities. Method: Six hundred eighty-one healthy controls (HC), 104 subjective cognitive decline, 290 early and 589 late mild cognitive impairment (EMCI, LMCI) and 348 AD participants from the Alzheimer's Disease Neuroimaging Initiative were included. Irregular word reading was assessed with the American National Adult Reading Test (AmNART). Multiple linear regressions were conducted predicting AmNART score using diagnostic category, general cognitive impairment and semantic tests. A generalized logistic mixed-effects model predicted correct reading using extracted psycholinguistic characteristics of each AmNART words. Deformation-based morphometry was used to assess the relationship between AmNART scores and voxel-wise brain volumes, as well as with the volume of a region of interest placed in the left anterior temporal lobe (ATL), a region implicated in semantic memory. Results: EMCI, LMCI and AD patients made significantly more errors in reading irregular words compared to HC, and AD patients made more errors than all other groups. Across the AD continuum, as well as within each diagnostic group, irregular word reading was significantly correlated to measures of general cognitive impairment / dementia severity. Neuropsychological tests of lexicosemantics were moderately correlated to irregular word reading whilst executive functioning and episodic memory were respectively weakly and not correlated. Age of acquisition, a primarily semantic variable, had a strong effect on irregular word reading accuracy whilst none of the phonological variables significantly contributed. Neuroimaging analyses pointed to bilateral hippocampal and left ATL volume loss as the main contributors to decreased irregular word reading performances. Conclusions: While the AmNART may be appropriate to measure premorbid intellectual abilities in cognitively unimpaired individuals, our results suggest that it captures current semantic decline in MCI and AD patients and may therefore underestimate premorbid intelligence. On the other hand, irregular word reading tests might be clinically useful to detect semantic impairments in individuals on the AD continuum. [ABSTRACT FROM AUTHOR]

BACKGROUND: The dominant feature of Alzheimer's dementia (AD) is gradual cognitive decline, which can be reflected by reduced finger dexterity. OBJECTIVE: This review analyzed reports on hand function in AD patients to determine the possibility of using it for an early diagnosis and for monitoring the disease progression of AD. METHODS: PubMed, Web of Science, EMBASE, and Cochrane library were searched systematically (search dates: 2000–2022), and relevant articles were cross-checked for related and relevant publications. RESULTS: Seventeen studies assessed the association of the handgrip strength or dexterity with cognitive performance. The hand dexterity was strongly correlated with the cognitive function in all studies. In the hand dexterity test using the pegboard, there was little difference in the degree of decline in hand function between the healthy elderly (HE) group and the mild cognitive impairment (MCI) group. On the other hand, there was a difference in the hand function between the HE group and the AD group. In addition, the decline in hand dexterity is likely to develop from moderate to severe dementia. In complex hand movements, movement speed variations were greater in the AD than in the HE group, and the automaticity, regularity, and rhythm were reduced. CONCLUSIONS: HE and AD can be identified by a simple hand motion test using a pegboard. The data can be used to predict dementia progression from moderate dementia to severe dementia. An evaluation of complex hand movements can help predict the transition from MCI to AD and the progression from moderate to severe dementia. [ABSTRACT FROM AUTHOR]

This article describes the public health impact of Alzheimer's disease (AD), including prevalence and incidence, mortality and morbidity, use and costs of care and the ramifications of AD for family caregivers, the dementia workforce and society. The Special Report discusses the larger health care system for older adults with cognitive issues, focusing on the role of caregivers and non‐physician health care professionals. An estimated 6.9 million Americans age 65 and older are living with Alzheimer's dementia today. This number could grow to 13.8 million by 2060, barring the development of medical breakthroughs to prevent or cure AD. Official AD death certificates recorded 119,399 deaths from AD in 2021. In 2020 and 2021, when COVID‐19 entered the ranks of the top ten causes of death, Alzheimer's was the seventh‐leading cause of death in the United States. Official counts for more recent years are still being compiled. Alzheimer's remains the fifth‐leading cause of death among Americans age 65 and older. Between 2000 and 2021, deaths from stroke, heart disease and HIV decreased, whereas reported deaths from AD increased more than 140%. More than 11 million family members and other unpaid caregivers provided an estimated 18.4 billion hours of care to people with Alzheimer's or other dementias in 2023. These figures reflect a decline in the number of caregivers compared with a decade earlier, as well as an increase in the amount of care provided by each remaining caregiver. Unpaid dementia caregiving was valued at $346.6 billion in 2023. Its costs, however, extend to unpaid caregivers' increased risk for emotional distress and negative mental and physical health outcomes. Members of the paid health care and broader community‐based workforce are involved in diagnosing, treating and caring for people with dementia. However, the United States faces growing shortages across different segments of the dementia care workforce due to a combination of factors, including the absolute increase in the number of people living with dementia. Therefore, targeted programs and care delivery models will be needed to attract, better train and effectively deploy health care and community‐based workers to provide dementia care. Average per‐person Medicare payments for services to beneficiaries age 65 and older with AD or other dementias are almost three times as great as payments for beneficiaries without these conditions, and Medicaid payments are more than 22 times as great. Total payments in 2024 for health care, long‐term care and hospice services for people age 65 and older with dementia are estimated to be $360 billion. The Special Report investigates how caregivers of older adults with cognitive issues interact with the health care system and examines the role non‐physician health care professionals play in facilitating clinical care and access to community‐based services and supports. It includes surveys of caregivers and health care workers, focusing on their experiences, challenges, awareness and perceptions of dementia care navigation. [ABSTRACT FROM AUTHOR]

Large language models (LLMs) find increasing applications in many fields. Here, three LLM chatbots (ChatGPT-3.5, ChatGPT-4, and Bard) are assessed in their current form, as publicly available, for their ability to recognize Alzheimer's dementia (AD) and Cognitively Normal (CN) individuals using textual input derived from spontaneous speech recordings. A zero-shot learning approach is used at two levels of independent queries, with the second query (chain-of-thought prompting) eliciting more detailed information than the first. Each LLM chatbot's performance is evaluated on the prediction generated in terms of accuracy, sensitivity, specificity, precision, and F1 score. LLM chatbots generated a three-class outcome ("AD", "CN", or "Unsure"). When positively identifying AD, Bard produced the highest true-positives (89% recall) and highest F1 score (71%), but tended to misidentify CN as AD, with high confidence (low "Unsure" rates); for positively identifying CN, GPT-4 resulted in the highest true-negatives at 56% and highest F1 score (62%), adopting a diplomatic stance (moderate "Unsure" rates). Overall, the three LLM chatbots can identify AD vs. CN, surpassing chance-levels, but do not currently satisfy the requirements for clinical application. [ABSTRACT FROM AUTHOR]

The goal of the treatment for Alzheimer's dementia (AD) is the cure of dementia. A literature review revealed 18 major elements causing AD and 29 separate medications that address them. For any individual with AD, one is unlikely to discern which major causal elements produced dementia. Thus, for personalized, precision medicine, all causal elements must be treated so that each individual patient will have her or his causal elements addressed. Twenty-nine drugs cannot concomitantly be administered, so triple combinations of drugs taken from that list are suggested, and each triple combination can be administered sequentially, in any order. Ten combinations given over 13 weeks require 2.5 years, or if given over 26 weeks, they require 5.0 years. Such sequential treatment addresses all 18 elements and should cure dementia. In addition, any comorbid risk factors for AD whose first presence or worsening was within ±1 year of when AD first appeared should receive appropriate, standard treatment together with the sequential combinations. The article outlines a randomized clinical trial that is necessary to assess the safety and efficacy of the proposed treatments; it includes a triple-drug Rx for equipoise. Clinical trials should have durations of both 2.5 and 5.0 years unless the data safety monitoring board (DSMB) determines earlier success or futility since it is uncertain whether three or six months of treatment will be curative in humans, although studies in animals suggest that the briefer duration of treatment might be effective and restore defective neural tracts. [ABSTRACT FROM AUTHOR]

Introduction: Normal Pressure Hydrocephalus (NPH) is a prominent type of reversible dementia that may be treated with shunt surgery, and it is crucial to differentiate it from irreversible degeneration caused by its symptomatic mimics like Alzheimer's Dementia (AD) and Parkinson's Disease (PD). Similarly, it is important to distinguish between (normal pressure) hydrocephalus and irreversible atrophy/degeneration which are among the chronic effects of Traumatic Brain Injury (cTBI), as the former may be reversed through shunt placement. The purpose of this review is to elucidate the structural imaging markers which may be foundational to the development of accurate, noninvasive, and accessible solutions to this problem. Methods: By searching the PubMed database for keywords related to NPH, AD, PD, and cTBI, we reviewed studies that examined the (1) distinct neuroanatomical markers of degeneration in NPH versus AD and PD, and atrophy versus hydrocephalus in cTBI and (2) computational methods for their (semi-) automatic assessment on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans. Results: Structural markers of NPH and those that can distinguish it from AD have been well studied, but only a few studies have explored its structural distinction between PD. The structural implications of cTBI over time have been studied. But neuroanatomical markers that can predict shunt response in patients with either symptomatic idiopathic NPH or post-traumatic hydrocephalus have not been reliably established. MRI-based markers dominate this field of investigation as compared to CT, which is also reflected in the disproportionate number of MRI-based computational methods for their automatic assessment. Conclusion: Along with an up-to-date literature review on the structural neurodegeneration due to NPH versus AD/PD, and hydrocephalus versus atrophy in cTBI, this article sheds light on the potential of structural imaging markers as (differential) diagnostic aids for the timely recognition of patients with reversible (normal pressure) hydrocephalus, and opportunities to develop computational tools for their objective assessment. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Mounting evidence suggests that certain comorbidities may influence the clinical evolution of Alzheimer's dementia (AD). METHODS: We conducted logistic regression analyses on the medical history and cognitive health diagnoses of participants in the Australian Imaging, Biomarker & Lifestyle study (n = 2443) to investigate cross‐sectional associations between various comorbidities and mild cognitive impairment (MCI)/AD. RESULTS: A mixture of associations were observed. Higher comorbidity of anxiety and other neurological disorders was associated with higher odds of AD, while arthritis, cancer, gastric complaints, high cholesterol, joint replacement, visual defect, kidney and liver disease were associated with lower odds of AD. DISCUSSION: This study underscores the links between specific comorbidities and MCI/AD. Further research is needed to elucidate the longitudinal comorbidity‐MCI/AD associations and underlying mechanisms of these associations. Highlights: Comorbidities that significantly increased AD odds included anxiety and other neurological disorders.Arthritis, cancer, gastric complaints, high cholesterol, joint replacement, visual defect, kidney and liver disease were associated with lower odds of AD.Alcohol consumption had the most significant confounding effect in the study.Visual‐AD association was modified by age, sex, and APOE ε4 allele status.Anxiety‐AD and depression‐AD associations were modified by sex. [ABSTRACT FROM AUTHOR]

Background: Parkinson's disease (PD) is a condition that affects movement and is usually seen in those over the age of 50. It is caused by the death of dopaminergic neurons, particularly in the substantia nigra. PD has shifted from being perceived as an uncommon condition to a significant neurological illness, mostly due to the increasing number of elderly individuals and the impact of environmental factors. Parkinson's plus syndromes, such as progressive supranuclear palsy (PSP), multiple system atrophy (MSA), corticobasal degeneration (CBD), and vascular Parkinsonism (VaP), provide difficulties in distinguishing them clinically from PD since they have similar characteristics. Methodology: A thorough examination was performed utilizing the PubMed, Medline, Scopus, and Web of Science databases. The search utilized specific keywords like "Parkinson's disease," "Parkinson's plus syndrome," "Lewy body dementia," "Alzheimer's dementia," "progressive supranuclear palsy," and "multiple system atrophy." The selection criteria were aimed at English‐language literature, with a particular focus on examining the connection between PD and associated disorders or dementias. Results and Discussion: Parkinson's plus syndromes, such as PSP, MSA, CBD, and VaP, exhibit unique clinical characteristics, imaging results, and diverse reactions to levodopa. This makes it difficult to distinguish them from PD. LBD is characterized by Lewy bodies containing α‐synuclein, which leads to both motor and cognitive deficits. PD and Alzheimer's disease (AD) exhibit a complex interaction, including common pathogenic processes, genetic predispositions, and clinical characteristics of dementia. Conclusion: The interrelatedness of PD, Parkinson's plus syndromes, LBD, and AD highlights the significance of comprehending shared disease‐causing processes. Aberrant protein clumping, impaired functioning of mitochondria, increased oxidative stress, and inflammation in the brain are common factors which can be addressed for specific treatments. More research is essential for understanding complicated connections and developing effective therapies for these sophisticated neurological illnesses. Highlights: We discusses the association between Parkinson's disease (PD) and related syndromes like Parkinson's plus syndrome, Lewy body dementia (LBD), and Alzheimer's dementia (AD).Parkinson's plus syndrome includes disorders like PSP, MSA, and CBD, sharing similar symptoms with PD but exhibiting additional features due to progressive neurodegeneration beyond the dopaminergic system.Shared pathogenic mechanisms among these disorders include abnormal protein aggregation, mitochondrial dysfunction, oxidative stress, and inflammation.We also emphasized the potential for developing targeted therapies and diagnostic approaches by understanding these shared mechanisms, impacting treatment strategies, prognosis, and quality of life for patients. [ABSTRACT FROM AUTHOR]

Alzheimer's dementia leads to a progressive decline in the individual's cognitive capacity, interfering with activities of daily living. Applying cognitive stimuli in the early stages can add value to slowing cognitive decline. In this process, can the use of digital technologies help to avoid the use of medication and delay the institutionalization of Alzheimer's patients? Therefore, the general aim of this article was to identify their perceptions of the use of digital technologies in the cognitive stimulation of Alzheimer's patients with formal careers. To this end, an action research methodology was applied, researching the state-of-the-art digital technologies that could be used in Alzheimer's disease from the perspective of formal careers. Sixty-two formal careers participated in this study, 74.2% of whom were female and the rest (25.8%) male. All those interviewed can identify signs of Alzheimer's dementia in patients. Regarding working with digital technologies with Alzheimer's dementia patients, a large percentage of the interviewees (73.6 percent) replied that they only use them sometimes, and 26.4 percent said they never use them. The data suggest that there is still resistance or a lack of confidence in the use of digital technologies on the part of formal careers working with patients with Alzheimer's dementia. However, even if they have never received specific training in this area, especially in cognitive stimulation, we can admit this is understandable.

Abstract Background The global dementia prevalence is surging, necessitating research into contributing factors. We aimed to investigate the association between metabolic syndrome (MetS), its components, serum uric acid (SUA) levels, and dementia risk. Methods Our prospective study comprised 466,788 participants without pre-existing MetS from the UK Biobank. We confirmed dementia diagnoses based on the ICD-10 criteria (F00-03). To evaluate the dementia risk concerning MetS, its components, and SUA levels, we applied Cox proportional hazards models, while adjusting for demographic factors. Results Over a median follow-up of 12.7 years, we identified 6845 dementia cases. Individuals with MetS had a 25% higher risk of all-cause dementia (hazard ratio [HR] = 1.25, 95% confidence interval [CI] = 1.19–1.31). The risk increased with the number of MetS components including central obesity, dyslipidemia for high-density lipoprotein (HDL) cholesterol, hypertension, hyperglycemia, and dyslipidemia for triglycerides. Particularly for those with all five components (HR = 1.76, 95% CI = 1.51–2.04). Dyslipidemia for HDL cholesterol, hypertension, hyperglycemia, and dyslipidemia for triglycerides were independently associated with elevated dementia risk (p < 0.01). MetS was further linked to an increased risk of all-cause dementia (11%) and vascular dementia (VD, 50%) among individuals with SUA levels exceeding 400 μmol/L (all-cause dementia: HR = 1.11, 95% CI = 1.02–1.21; VD: HR = 1.50, 95% CI = 1.28–1.77). Conclusions Our study provides robust evidence supporting the association between MetS, its components, and dementia risk. These findings emphasize the importance of considering MetS and SUA levels in assessing dementia risk, offering valuable insights for prevention and management strategies.

There are two generic approaches to curing any medical condition. The first one treats every patient for all the known possible causes that contribute to pathogenesis; the second one individualizes potentially curative therapy by only identifying in each separate patient the components of pathogenesis that are actually operative and treating those. This article adopts the second approach for formulating a cure for Alzheimer's dementia (AD). The components of AD's pathogenesis are, in alphabetical order, as follows: circadian rhythm disturbances, depression, diabetes and insulin resistance, dyslipidemia, hypertension, inflammation, metabolic syndrome, mitochondrial dysfunction, nutritional deficiencies, TGF-β deficiency, underweight, vascular abnormalities, and Wnt/β-catenin deficiency. For each component, data are described that show the degree to which its prevalence is higher in patients with mild cognitive impairment (MCI) who did not revert to having normal cognition than in those who did because the former group is the pool of patients in which future AD may develop. Only addressing the components that are present in a particular individual potentially is a curative strategy. Published data indicate that curative therapy requires the number of such components that are addressed to be ≥3. Although structural brain changes cannot be directly addressed, the impaired neural tracts result from many of the reversible causal elements, so correcting them will benefit these tracts. [ABSTRACT FROM AUTHOR]

Introduction: Personality traits and neuropsychiatric symptoms such as neuroticism and depression share genetic overlap and have both been identified as risks factors for development of aging-related neurocognitive decline and Alzheimer's disease (AD). This study aimed to examine revised personality factors derived from the Temperament and Character Inventory, previously shown to be associated with psychiatric disorders, as predictors of neuropsychiatric, cognitive, and brain trajectories of participants from a population-based aging study. Methods: Mixed-effect linear regression analyses were conducted on data for the full sample (Nmax = 1,286), and a healthy subsample not converting to ADdementia during 25-year follow-up (Nmax = 1,145), complemented with Cox proportional regression models to determine risk factors for conversion to clinical AD. Results: Two personality factors, Closeness to Experience (CE: avoidance of new stimuli, high anxiety, pessimistic anticipation, low reward seeking) and Tendence to Liabilities (TL: inability to change, low autonomy, unaware of the value of their existence) were associated with higher levels of depressive symptoms, stress (CE), sleep disturbance (TL), as well as greater decline in memory, vocabulary and verbal fluency in the full sample. Higher CE was additionally associated with greater memory decline across 25 years in the healthy subsample, and faster right hippocampal volume reduction across 8 years in a neuroimaging subsample (N = 216). Most, but not all, personality-cognition associations persisted after controlling for diabetes, hypertension and cardiovascular disease. Concerning risks for conversion to AD, higher age, and APOE-ε4, but none of the personality measures, were significant predictors. Conclusion: The results indicate that personality traits associated with psychiatric symptoms predict accelerated age-related neurocognitive declines even in the absence of neurodegenerative disease. The attenuation of some personality effects on cognition after adjustment for health indicators suggests that those effects may be partly mediated by somatic health. Taken together, the results further emphasize the importance of personality traits in neurocognitive aging and underscore the need for an integrative (biopsychosocial) perspective of normal and pathological age-related cognitive decline. [ABSTRACT FROM AUTHOR]

Introduction: The prevalence of mild and major neurocognitive disorders (NCDs), also referred to as mild cognitive impairment and dementia, is rising globally. The prevention of NCDs is a major global public health interest. We sought to synthesize the literature on potentially modifiable risk factors for NCDs. Methods: We conducted an umbrella review using a systematic search across multiple databases to identify relevant systematic reviews and meta-analyses. Eligible reviews examined potentially modifiable risk factors for mild or major NCDs. We used a random-effects multi-level meta-analytic approach to synthesize risk ratios for each risk factor while accounting for overlap in the reviews. We further examined risk factors for major NCD due to two common etiologies: Alzheimer's disease and vascular dementia. Results: A total of 45 reviews with 212 meta-analyses were synthesized. We identified fourteen broadly defined modifiable risk factors that were significantly associated with these disorders: alcohol consumption, body weight, depression, diabetes mellitus, diet, hypertension, less education, physical inactivity, sensory loss, sleep disturbance, smoking, social isolation, traumatic brain injury, and vitamin D deficiency. All 14 factors were associated with the risk of major NCD, and five were associated with mild NCD. We found considerably less research for vascular dementia and mild NCD. Conclusion: Our review quantifies the risk associated with 14 potentially modifiable risk factors for mild and major NCDs, including several factors infrequently included in dementia action plans. Prevention strategies should consider approaches that reduce the incidence and severity of these risk factors through health promotion, identification, and early management. [ABSTRACT FROM AUTHOR]

Introduction: Cognitive screening measures are an established part of a dementia assessment and often include measures of subjective difficulties, e.g., Everyday Memory Questionnaire (EMQ), informant-rated difficulty, Cambridge Behavioural Inventory – Revised (CBI-R), and objective cognitive assessments like Addenbrooke's Cognitive Examination (ACE-III). While these measures have validity for the purpose of diagnosing dementia, in clinical practice they are often used outside of their evidence base for the purpose of cognitive re-assessment. The current study sought to evaluate the psychometric properties for the repeated use of these assessments. Methods: This study used a longitudinal design, which included 49 healthy controls, 33 people with subjective memory difficulties, and 10 people with Alzheimer's disease (AD) being assessed twice, with approximately a 1-year interval between assessments. Results: The EMQ has adequate re-test reliability (r = 0.78), but people with an AD diagnosis rated their memory as better than those with SMD, making it unsuitable as a measure. The CBI-R had moderate re-test reliability (r = 0.62). However, deterioration on the CBI-R was not useful for diagnosing AD. The ACE-III has high re-test reliability (r = 0.89). A change of five was associated with reasonable classification accuracy for identifying AD and achieved statistical significance. Conclusion: Using a 1-year interval, of the three measures used in this study, only the ACE-III total score may be a useful measure of change over time, although it should be applied cautiously due to the lack of representativeness of the sample, and change scores should always be triangulated with other forms of evidence of deterioration. [ABSTRACT FROM AUTHOR]

Depression (DEP) and dementia of the Alzheimer's type (DAT) represent the most common neuropsychiatric disorders in elderly patients. Accurate differential diagnosis is indispensable to ensure appropriate treatment. However, DEP can yet mimic cognitive symptoms of DAT and patients with DAT often also present with depressive symptoms, impeding correct diagnosis. Machine learning (ML) approaches could eventually improve this discrimination using neuropsychological test data, but evidence is still missing. We therefore employed Support Vector Machine (SVM), Naïve Bayes (NB), Random Forest (RF) and conventional Logistic Regression (LR) to retrospectively predict the diagnoses of 189 elderly patients (68 DEP and 121 DAT) based on either the well-established Consortium to Establish a Registry for Alzheimer's Disease neuropsychological assessment battery (CERAD-NAB) or a flexible battery approach (FLEXBAT). The best performing combination consisted of FLEXBAT and NB, correctly classifying 87.0% of patients as either DAT or DEP. However, all accuracies were similar across algorithms and test batteries (83.0% – 87.0%). Accordingly, our study is the first to show that common ML algorithms with their default parameters can accurately differentiate between patients clinically diagnosed with DAT or DEP using neuropsychological test data, but do not necessarily outperform conventional LR. [ABSTRACT FROM AUTHOR]

Aims: The objective of this umbrella review and meta‐analysis was to evaluate the effect of diabetes on risk of dementia, as well as the mitigating effect of antidiabetic treatments. Materials and Methods: We conducted a systematic umbrella review on diabetes and its treatment, and a meta‐analysis focusing on treatment. We searched MEDLINE/PubMed, Embase, PsycINFO, CINAHL and the Cochrane Library for systematic reviews and meta‐analyses assessing the risk of cognitive decline/dementia in individuals with diabetes until 2 July 2023. We conducted random‐effects meta‐analyses to obtain risk ratios and 95% confidence intervals estimating the association of metformin, thiazolidinediones, pioglitazone, dipeptidyl peptidase‐4 inhibitors, α‐glucosidase inhibitors, meglitinides, insulin, sulphonylureas, glucagon‐like peptide‐1 receptor agonists (GLP1RAs) and sodium‐glucose cotransporter‐2 inhibitors (SGLT2is) with risk of dementia from cohort/case‐control studies. The subgroups analysed included country and world region. Risk of bias was assessed with the AMSTAR tool and Newcastle‐Ottawa Scale. Results: We included 100 reviews and 27 cohort/case‐control studies (N = 3 046 661). Metformin, thiazolidinediones, pioglitazone, GLP1RAs and SGLT2is were associated with significant reduction in risk of dementia. When studies examining metformin were divided by country, the only significant effect was for the United States. Moreover, the effect of metformin was significant in Western but not Eastern populations. No significant effect was observed for dipeptidyl peptidase‐4 inhibitors, α‐glucosidase inhibitors, or insulin, while meglitinides and sulphonylureas were associated with increased risk. Conclusions: Metformin, thiazolidinediones, pioglitazone, GLP1RAs and SGLT2is were associated with reduced risk of dementia. More longitudinal studies aimed at determining their relative benefit in different populations should be conducted. [ABSTRACT FROM AUTHOR]

Background: Studies on disease-related obstructions experienced in everyday life of younger people with dementia (YOD ≤ 65 years) and their families are encouraged. Aim: To explore how the family carers experience six predefined topics that influence the everyday life and needs of persons with YOD. Method: A quantitative and a qualitative study including family carers of persons with young-onset Alzheimer's dementia (AD) and frontotemporal dementia (FTD). Seventy-four informants responded to the Camberwell Assessment of Needs in the Elderly (CANE) and individual interviews were conducted with 13 informants. Results: Family carers of persons with YOD reported few unmet needs in the CANE assessment. Needs related to behavior and close relationships were reported significantly more frequent (p < 0.1) in persons with FTD than in persons with AD. From the qualitative data, six main themes were emphasized: daily activities turned upside down, involuntary loss of previous social network, losing close relationship, but maintaining a friendship with the spouse, unpredictable behavior adds burdens to a changing life, health and life risks, and economic insecurity for future life and caring costs. Conclusion: Whilst family carers quantitatively reported unmet needs, the individual interviews reported several major difficulties in everyday life. [ABSTRACT FROM AUTHOR]