bluuebunny/crossref_metadata_2025_split huggingface dataset:
Revealing Patterns of Cognitive Function Trajectories in the Last Five Years of Life of Medicare Beneficiary
Authors: Lin Haiqun , Xia Weiyi , Zafar Anum , Montaner Olga F Jarrín 
Published: January 2025

AbstractBackgroundClinicians have observed various patterns of decline in cognitive function at the end of life. In a period of dynamic evolution in dementia care technology and delivery, tracking trends in cognitive function during last years of life provides a perspective on the need of patients and their caregivers and on demands on healthcare system. This work aims to characterize the functional decline in cognition during the last five years of life.MethodThe analytic cohort included a 10% random sample consisting of 195,240 Medicare beneficiaries who died in 2019, aged fifty or older and continuously enrolled in Medicare during their last five years of life. The group‐based trajectory modeling approach for ordered categorical outcomes was adopted to characterize beneficiaries’ changes in cognitive function over the last five years: no impairment, memory loss, mild cognitive impairment, and dementia. Cognitive function status in each quarter of the last five years of life was assembled from linked administrative, claims, and assessment data.ResultTen trajectory groups of cognitive function were identified and had a better value of Bayesian Information Criterion than either the 9‐class or the 11‐class solution. The 10 trajectory groups were categorized into four clusters: cognitively intact, mild cognitive impairment (MCI), steady decline to dementia, and early‐decline dementia. The intact cluster contains one trajectory group of 25% of beneficiaries who maintained their cognitive function throughout the last five years. The MCI cluster contains four trajectory groups with 37% in total of the beneficiaries who experienced slow decline in cognitive function and died with only MCI. The steady decline cluster contains four trajectory groups with 27% in total of the beneficiaries experienced steady decline in cognitive function and died with dementia. The early‐decline dementia cluster also contains only one trajectory group of 11% of the beneficiaries whose cognitive decline started more than five years before death. Sociodemographic and clinical factors associated with each cluster were assessed.ConclusionThis study identified distinct patterns of cognitive trajectories that varied in the timing and rate of cognitive decline during the last five years of life.
A Bias‐Corrected Three‐Step Approach to Study the Association Between Aging Trajectories and Sociodemographic and Clinical Factors
Authors: Xia Weiyi , Zafar Anum , Montaner Olga F Jarrín , Lin Haiqun 
Published: January 2025

AbstractBackgroundThis work focuses on methodological aspects in assessing the association between group‐based aging trajectories and sociodemographic and clinical factors. The group‐based trajectories are derived from the latent class analysis of longitudinal variables of clinical interest. Each individual would be assigned a class membership with the highest posterior probability (modal assignment) and each class represents a particular pattern in the trajectory of the longitudinal variables. The Bolck–Croon–Hagenaars (BCH) method for bias adjustment in assessing the association of the latent class membership and external variables has increasingly become popular during the last twenty years.MethodThe BCH method is the three‐step approach that adjusts for the misclassification error in the latent class assignment. In the first step, we fit a group‐based trajectory model. In the second step, we calculate the posterior probability of class membership of each individual which is assigned to the class with either modal assignment or proportional assignment to each of the classes. The BCH class assignment weights are estimated in this step as well. In the third step, association parameters between latent class and external variables are estimated using weights from the step two. We generate simulation data to evaluate the performance of the three‐step approach without BCH adjustment and the bias‐corrected BCH approach. Subsequently, the association analyses between aging trajectory and external variables of interest among Medicare beneficiaries were conducted.ResultThe group‐based trajectory algorithm works well with truncated normal and ordered categorical longitudinal measurements among Medicare beneficiaries. We compute the inverse of the matrix and reweighting the data to obtain the desired joint probabilities of the latent class variables and external variables. The simulation result reveals the smallest bias when utilizing BCH‐proportional estimator and largest bias with the naive three‐step estimator. The BCH‐adjusted estimator outperforms the naive three‐step method in correcting bias.ConclusionOur results show the feasibility of applying BCH in the group‐trajectory analysis for both continuous and categorical longitudinal indicators for latent classes. The bias‐corrected three‐step approach with BCH can effectively reduce the bias from the latent class misclassification error.
Fatal Iatrogenic Cerebral Amyloid‐Related Encephalitis in a woman treated with lecanemab for Alzheimer’s disease
Authors: Solopova Elena 
Published: January 2025

AbstractBackgroundWe report the case of a 79‐year‐old woman with Alzheimer’s disease who enrolled in a clinical study of lecanemab. After the third, biweekly infusion she suffered a seizure followed by aphasia and progressive encephalopathy. Magnetic resonance imaging revealed multifocal cerebral edema and an increased burden of cerebral microhemorrhages compared to pre‐trial imaging. She was treated with an antiepileptic regimen and high‐dose intravenous corticosteroids but continued to worsen and died after five days.MethodsPost‐mortem paraformaldehyde‐fixed coronal brain slices were embedded in degassed agarose solution and scanned with human clinical MRI scanners at 3 and 7 Tesla field strength. Free‐floating sections were immunostained using validated primary and corresponding secondary antibodies and imaged using a confocal laser‐scanning microscope. For three‐dimensional lightsheet microscopy, tissue blocks were embedded in CLARITY acrylamide hydrogel, optically cleared and stained with fluorescent probes and antibodies.ResultsPost‐mortem MRI confirmed extensive microhemorrhages in the temporal, parietal and occipital lobes. The autopsy confirmed the presence of two copies of APOE4, a gene associated with a higher risk of Alzheimer’s disease, and neuropathological features of moderate severity Alzheimer’s disease and severe cerebral amyloid angiopathy with perivascular lymphocytic infiltrates, reactive macrophages and fibrinoid degeneration of vessel walls. There were deposits of β‐amyloid in meningeal vessels and penetrating arterioles with numerous microaneurysms.ConclusionWe conclude that the patient likely died as a result of severe cerebral amyloid‐related meningoencephalitis.
A Novel Approach to Identify Sundowning with Cyclomatic Complexity Movement Analysis and Noninvasive Ambient Sensors
Authors: Johnson Brian B , Jamadagni Radhakrishna S , Kresnasandi Ida Bagus , Bolstad Britni A 
Published: January 2025

AbstractBackgroundSundowning is the development or progression of neuropsychiatric symptoms (NPS) often occurring in the afternoon or early evening. Noninvasive ambient sensors (NAS) monitor individuals without the need to wear a device or use a camera. The data from NAS sensors can identify movement patterns in the context of cyclomatic complexity to indicate when an individual may be sundowning. This approach could improve the quality of life (QOL) for individuals with Alzheimer’s disease (AD) and their caregivers.MethodNAS sensors placed in an individual’s home could identify wandering due to sundowning when new patterns of movement emerge. Quantification of movement with cyclomatic complexity uses machine learning (ML) to identify and notify caregivers when new sequences of room transitions emerge. Cyclomatic complexity is represented as M = E − N + 2P where E is the amount of walking paths, N is the number of rooms, P is the total number of connected rooms (Khan & Jacobs). A new pattern of movement categorized as wandering is one signal a caregiver could consider within the constellation of symptoms.ResultThe method of approaching quantification of movement in an ML framework was pioneered by Dr. Taha Khan and Dr. Peter G. Jacobs in the study “Prediction of Mild Cognitive Impairment Using Movement Complexity”. Labeling sequences of human movement within an ML framework could lead to novel insights for understanding human behavior. Individuals that prefer to age‐in‐place could benefit from early detection of neuropsychiatric symptoms and prevention of sentinel events with proactive clinical decision‐making.ConclusionThe transition from CIN to MCI is a significant change for an individual. Current assessments are dependent on the clinical interpretation by the caregiver. Instead of waiting until a sentinel event occurs, predictive algorithms could be used for early intervention. Data could enhance the decision making‐support for further assessment or admission to a long‐term care facility. As the aging population continues to grow, affordable technological solutions will be critical for monitoring health factors in real‐time. By providing this early warning, caregivers can adjust their routines and interventions to better support the patient.
Supporting Aging through Green Exercise (SAGE): Comparing the cognitive effects of outdoor versus indoor aerobic exercise in older adults with mild cognitive impairment—A 12‐week proof‐of‐concept randomized controlled trial
Authors: Noseworthy Matt W , Wei Nathan , Grant Sofia , Zou Jammy , Puterman Eli , Handy Todd C , Liu‐Ambrose Teresa 
Published: January 2025

AbstractBackgroundEvidence from randomized controlled trials (RCTs) shows that aerobic exercise (AE) can benefit cognitive function among older adults with mild cognitive impairment (MCI). Growing research suggests that outdoor, natural (i.e., “green”) environments, compared with indoor or built environments, may augment the health benefits of exercise. However, the potential cognitive benefits of green exercise are unclear. We compared the effects of AE performed in an outdoor, green environment (O‐Ex) versus indoor AE (I‐Ex) on executive functions among older adults with MCI.MethodsA two‐arm parallel, single‐blinded, 12‐week proof‐of‐concept RCT. 72 community‐dwelling adults aged 65‐80 years with MCI were randomized (1:1) to either O‐Ex (n = 36) or I‐Ex (n = 36). Each arm involved two group‐based training sessions per week. Each session involved 10 min warm‐up, 40 min moderate‐intensity AE (progressing from 45%–75% of heart rate reserve), and 10 min cool‐down. We monitored exercise intensity using heart rate monitors and Borg’s 20‐point Rating of Perceived Exertion. AE consisted of outdoor walking in an urban forest (O‐Ex) or indoor treadmill walking or stationary cycling (I‐Ex). We measured working memory using the National Institutes of Health Toolbox (NIHTB) List Sorting Test and the Verbal Digits Forward and Backward Test. We measured set shifting and response inhibition using the NIHTB Dimensional Change Card Sort Test and Flanker Test, respectively. We performed a complete case analysis using a one‐way analysis of covariance to compare groupwise changes in executive functions (NIHTB corrected T‐score), with baseline outcome score and baseline Montreal Cognitive Assessment (MoCA) score as covariates. Overall alpha was ≤0.05.ResultsMean baseline MoCA score was 22.36 (SD = 2.55). Mean age was 74.08 years (SD = 3.92). There were 26 males and 46 females. The attrition rate was 12.5% (O‐Ex = 5; I‐Ex = 4). At 12 weeks, after adjusting for baseline outcome and baseline MoCA scores, O‐Ex had significantly better scores than I‐Ex for set shifting (estimated mean difference: 7.46; 95% CI: [2.69, 12.23]; p = 0.003) and response inhibition (estimated mean difference: 3.81; 95% CI: [0.61, 7.01]; p = 0.021), but not for working memory.ConclusionsAerobic exercise performed outdoors in nature, compared with indoor aerobic exercise, may provide greater cognitive benefits among older adults with MCI.
Baseline energy and nutrient intakes of AU‐ARROW participants using a Food Frequency Questionnaire‐ Preliminary findings
Authors: Fernando Malika G , Castro Carolina B , Gardener Samantha L , Fuller Stephanie Jane , Naismith Sharon L , Baker Laura D , Kivipelto Miia , Villemagne Victor L , Grieve Stuart , Yates Paul A , Armstrong Nicola , Anstey Kaarin J. , Sohrabi Hamid R. , Garg Manohar , Chen Juliana , Martins Ralph N 
Published: January 2025

AbstractBackgroundLifestyle modifications incorporating a healthy diet, physical activity, brain training and health monitoring have proven effective in preventing dementia and related cognitive decline (REF). The Australian‐Multidomain Lifestyle Intervention to reduce dementia risk (AU‐ARROW) is an ongoing 2‐yearintervention, which is the Australian contribution to the World‐Wide FINGERS network. Here we report on preliminary findings of baseline dietary energy and nutrient intakes of AU‐ARROW participants.MethodsData from 99 cognitively‐unimpaired adults enrolled in AU‐ARROW were included (60% female; mean age 67.8±5.3 years). Participants self‐administered the validated Cancer Council of Victoria Food Frequency Questionnaire at baseline, which was used to analyse dietary energy and nutrient intake. Nutrient intakes were compared against the Australian National Health and Medical Research Council Recommended Dietary Intakes (RDIs).ResultsParticipants’ average energy and protein intakes were 8980±1980 kJ/day and 96.8±22.6 g/day for males, and 8250±2660 kJ/day and 88.1±25.3 g/day for females. Total fat intake (males 101±25.8 g/day, females 98.9±37.0 g/day) comprised approximately 31% saturated fat, 45% monounsaturated fat and 18% polyunsaturated fat. RDIs were met by participants for most vitamins and minerals, with exceptions for sodium, zinc, calcium, vitamin A, thiamine, riboflavin, vitamin D and iodine. Males exhibited higher sodium intake (2410±588 mg/day) than the Recommended Upper Level of Intake (2300 mg/day), and lower zinc (10.9±2.7 mg/day) and vitamin A (797±310 mg/day) intake than the RDI (Zinc 14 mg/day, vitamin A 900 mg/day). Females exhibited lower thiamine (0.8±0.6 mg/day) and riboflavin (1.0±0.7 mg/day) intake than the RDI (1.1 mg/day for both). Both genders exhibited lower calcium intake (males 856±264 mg/day, females 860±345 mg/day), and iodine (males 123±40.1 µg/day, females 125±54.9 µg/day) than the RDI (calcium: males 1000 mg/day, females 1300 mg/day, iodine: 150 µg/day for both).ConclusionHabitual macro‐nutrient intakes of AU‐ARROW participants largely meet the RDI for Australians, except for higher saturated fat and lower calcium and iodine intakes. The Australian Health Survey:2011‐2012 has also reported similar concerns on Australians’ usual nutrient intakes. Attention to a healthy diet is crucial for optimal saturated fat, vitamin, and mineral levels. These baseline data identify deficiencies in the Australian diet which hopefully will be corrected following dietary‐intervention of the AU‐ARROW participants.
Association of Retinal Layer Thickness with Brain Volume and Cortical Thickness in older adults
Authors: Han Ji Won , Kim Hyeong Min , Kwon Min Jeong , Park Jieun , Kim Jun Sung , Woo Se Joon , Kim Ki Woong 
Published: January 2025

AbstractBackgroundTo elucidate the biological mechanisms underpinning the association between macular Retinal Nerve Fiber Layer (RNFL) thickness and cognitive function in older adults, this study investigates its correlation with brain volume and cortical thickness.MethodFrom a community‐dwelling prospective cohort, we included 166 non‐demented participants aged over 65 years (mean age 75.2 ± 5.3; 61.4% women) who had 3D T1 MRI images and no ocular pathologies that could affect retinal layer thickness. Using spectral‐domain optical coherence tomography, we assessed the thickness of the macular RNFL. We analyzed the relationship between RNFL thickness and regional brain volumes using voxel‐based morphometry, adjusting for age, sex, and total intracranial volume (uncorrected p < 0.001, cluster size threshold = 100 voxels). The relationship between RNFL thickness and cortical thickness by FreeSurfer was assessed using Pearson's correlation analysis, with adjustments for age and sex.ResultIncreased gray matter volumes correlating with outer RNFL thickness were present in the right inferior parietal (t=3.81), the left superior frontal (t=3.71), and left inferior temporal (t=3.95) cortices. The total RNFL thickness was associated with the volume of the right inferior parietal cortex (t=3.62). Significant associations were found between RNFL thickness and the cortical thickness of multiple brain regions. In particular, the cortical thickness in the left posterior cingulate and both supramarginal regions was significantly correlated with total, inner, and outer RNFL thickness. Upon adjusting for multiple comparisons, these associations did not retain statistical significance.ConclusionRNFL thickness was associated with various brain regions involved in sensory information processing and integration, as well as cognitive functions. We also observed correlations with brain regions implicated in the early stages of Alzheimer's disease pathology.
Cortical cholinergic pathway integrity is reduced in Parkinson’s disease dementia
Authors: Slater Nicola M , Myall Daniel J , Horne Kyla‐Louise , Anderson Tim J , Heron Campbell Le , Melzer Tracy R , Dalrymple‐Alford John C 
Published: January 2025

AbstractBackgroundNormal cognitive function is supported by the neuromodulatory mechanisms of the cholinergic system. In Parkinson’s disease (PD), histological and molecular imaging evidence suggests disruption to cholinergic circuitry is associated with progression to Parkinson’s disease dementia (PDD). The primary source of cortical cholinergic input is the Ch4 region of the basal forebrain. Reduction in cholinergic projection axon integrity may precede Ch4 neuronal decline, so we examined differences in the integrity of medial and lateral Ch4‐to‐cortex pathways from three subregions of Ch4.MethodStructural and diffusion‐weighted MRI and neuropsychological assessment was acquired from a convenience sample of 108 PD patients, 60 with normal cognition, 37 with mild cognitive impairment, 12 PDD, and 41 control participants. Streamlines connecting the anterior‐lateral, anterior‐intermediate, and posterior Ch4 subregions to the cortex were grouped according to medial and lateral cortical cholinergic pathway definitions by Selden et al. [1]. Integrity was assessed using diffusion tensor, NODDI, and fixel‐based models.ResultsAccounting for age and sex, Bayesian mixed‐effects models indicated moderate to strong evidence of increased free water in PDD in all pathways, especially in connections with anterior‐intermediate and posterior Ch4 subregions (Cohen’s d (Control–PDD) = 0.47). Across connections with all subregions there was moderate to strong evidence of increased mean diffusivity (Cohen’s d (Control–PDD) = 0.76) and reduced fibre density (Cohen’s d (Control–PDD) = 1.24) in PDD. In PD‐MCI, moderate evidence of increased mean diffusivity was observed (Cohen’s d (Control–PD‐MCI)= 0.64), but no evidence for alterations in other metrics.ConclusionOur results reveal evidence of reduced integrity in the major cortical cholinergic pathways in PD‐MCI, and more extensive evidence of reduced integrity in PDD. While these findings support an association of cholinergic circuity disruption in PD‐related cognitive impairment, they contrast with a commonly held view that losses in cholinergic projection integrity may explain, and potentially precede, cognitive impairment in PD. Ch4 projection pathway integrity may be more pertinent to future cognitive decline than current cognitive status. Longitudinal investigation will examine how Ch4 projection pathway integrity relates to the progression of cognitive decline in PD.Reference:[1] Selden, et al. Brain 121, 2249–2257 (1998).
Social connection profiles of older adults as both heritable and modifiable influences on brain health: data from the Older Australian Twins Study
Authors: Samtani Suraj , Casey Anne‐Nicole , Thalamuthu Anbupalam , Lam Ben C.P. , Catts Vibeke S. , Brodaty Henry , Sachdev Perminder S. 
Published: January 2025

AbstractBackgroundSocial connections are associated with brain health, but the extent to which social connections are heritable remains unclear. Using longitudinal twin data, we explored the heritable and environmental contributions to social connections. We hypothesised that social connections patterns would be moderately heritable and would be associated with better cognitive and mental health over time.MethodWe analysed data from 333 monozygotic and 266 dizygotic twins aged 65+, collected at baseline, 2‐ and 4‐year follow‐up in the Older Australian Twins Study. Outcome variables were depressive and anxious symptoms, MMSE and neuropsychological subtest scores, and social activity items. We ran exploratory structural equation modelling, univariate heritability models, genetic correlations and linear mixed‐effects, and Inference about causation from examination of familial confounding (ICE FALCON) modelling. Fully adjusted models controlled for age, sex, education, hypertension, diabetes, smoking, alcohol use, history of depression, BMI, exercise, and additionally for APOE4 status and hearing loss (for cognition) and pain and neuroticism (for mental health).ResultWe identified three social connection factors with weak to no heritability: interacting with friends and community (h2 = 0.09,95%CI: 0.00,0.44), family interactions and childcare (h2 = 0.13,95%CI: 0.00,0.43); and involvement in religious groups and caregiving (h2 = 0.00,95%CI: 0.00,0.19). Genetic correlations indicated overlap in genetic influences for friend interactions with global cognition (r = 0.21), depressive (r = ‐0.96), and anxious symptoms (r = ‐0.47). Shared environmental correlations between friend interactions and global cognition (r = 0.24), depressive (r = ‐0.53), and anxious symptoms (r = ‐0.54) indicated some overlap in environmental influences. Friend interactions were associated with fewer depressive symptoms cross‐sectionally (B = ‐0.14, adjusted p = 0.004) and longitudinally (B = ‐0.09, adjusted p‐value = 0.010); social connections were not associated with cognition. ICE FALCON analyses did not reveal causal relationships between social factors and cognitive/mental health.ConclusionCertain social connection profiles were weakly heritable (friend and family interactions) and were associated with brain health (friend interactions). There was moderate overlap in the genetic and shared environmental influences affecting social connections and cognitive and mental health. Interacting with friends was associated with fewer depressive symptoms; social connections were not associated with cognitive change over 4 years. Health care for older adults should include paying attention to social connections to support brain and mental health.