bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysing Remote Nocturnal Activity and Sleep Monitoring Data to Develop Predictive Models in Dementia Care
Authors: Barnaghi Payam 
Published: January 2025

AbstractBackgroundClose to 23% of unplanned hospital admissions for people living with dementia (PLWD) are due to potentially preventable causes such as severe urinary tract infections (UTIs), falls, and respiratory problems. These affect the well‐being of PLWD, cause stress to carers and increase pressure on healthcare services.MethodWe use routinely collected in‐home sensory data to monitor nocturnal activity and sleep data.ResultWe apply machine learning models to develop a new generation of dementia care solutions to analyse changes in patterns.ConclusionDeveloping machine learning models to analyze in‐home sleep data will help enable detection of sleep changes and timely interventions.
Exercising Physiological Pathways: The Impact of Exercise on Metabolic Aging, Cellular Aging, and Inflammatory Biomarkers in All‐Cause Dementia
Authors: Hanson Mitchell T , Dong Yanbin , Zhu Haidong , Soares Andre , Hergott Colleen , Waller Jennifer L , Young Lufei , Robinson‐Johnson Dawnchelle , Sams Richard , Hamrick Mark , Jehu Deborah A 
Published: January 2025

AbstractBackgroundPhysiological changes, including metabolic and cellular aging, as well as increased inflammation, occur in people living with dementia (PWD). While there is existing evidence in other populations suggesting that exercise may improve physiological outcomes, their impact in PWD remains unclear. This randomized controlled trial (RCT) aimed to assess the effects of exercise on serum levels of metabolic aging, cellular aging, and inflammatory blood biomarkers relative to usual care alone in PWD.MethodThis pilot RCT involved n=42 PWD (exercise n=21; usual care n=21) in one nursing home and one assisted living facility (NCT05488951). The adapted Otago Exercise Program involved 30 minutes of tailored lower body strength and balance exercises and 30 minutes of walking 3x/week for 6 months. We drew fasted blood at baseline and 6 months. Blood samples were stored at ‐80°F and analyzed for metabolic aging (kynurenine), cellular aging (telomere length), and inflammatory biomarkers (interleukin‐6, IL‐1b, interferon alpha2, IFNg, tumor necrosis factor a, chemokine ligand 2, IL‐8, IL‐10, IL‐12p70, IL‐17A, IL‐18, IL‐23, IL‐33). Generalized mixed models were used for intent‐to‐treat (n=42) and per protocol analyses (usual care: n=21; n=9 exercisers with ≥2/3 adherence), controlling for age, race, sex, and the Montreal Cognitive Assessment.ResultThe intent‐to‐treat analysis revealed no differences in physiological biomarkers between groups. The per protocol analysis revealed a trend for reduced inflammation in IL‐1b (exercise: 9.73 to 6.16 pg/mL; usual care:10.51 to 15.46 pg/mL; p=0.09) and IL‐8 (exercise: 39.34 to 25.92 pg/mL; usual care:78.99 to 93.04 pg/mL; p=0.09). Additionally, the control group increased telomere length compared to the exercise group (exercise:8.0 to 7.9 kb; usual care:7.9 to 8.7 kb; p=0.01).ConclusionsThe trend for exercise reducing inflammation in the per protocol analysis suggests that a greater amount of exercise (i.e., ≥2/3 exercise adherence) may be necessary to reduce inflammation in PWD. The nuanced relationship between exercise reducing cellular aging in the usual care group requires further exploration, as we had a small sample size in our per protocol analysis. Our pilot findings may inform a larger RCT to determine a potential interplay between exercise and physiological biomarkers in PWD.
Associations between Cardiovascular‐Kidney‐Metabolic Health and the Risk of Cognitive Decline and Alzheimer’s Disease Mortality in a Multiethnic Cohort Study
Authors: Liu Longjian , Gliebus Gediminas Peter , Zhao Xiaopeng ,   for the CKM‐AD/ADRD Research Group
Published: January 2025

AbstractBackgroundCardiovascular‐kidney‐metabolic (CKM) health, a term recently defined by the American Heart Association, encompasses the interplay among metabolic, chronic kidney, and cardiovascular risk factors. We aimed to investigate the predictive significance of CKM disorders with the risk of cognitive decline and Alzheimer’s disease (AD) and AD‐related dementia (ADRD) mortality in a multiethnic population.MethodWe analyzed a cohort of 6,440 adults aged 45‐84 who participated in the Multiethnic Study of Atherosclerosis, with a baseline survey conducted in 2000‐2002, and were followed through to December 2015. Fourteen baseline measurements of established and emerging CKM factors were examined, including waist circumference, blood pressure (BP), carotid intimal‐medial thickness, serum glucose, triglyceride, high‐density lipoprotein cholesterol, C‐reactive protein (CRP), fibrinogen, interleukin‐6 (IL‐6), factor VIII, D‐Dimer, homocysteine, cystatin C concentrations, and urine albumin to creatinine ratio (ACR). Cognitive function was assessed using the Cognitive Abilities Screening Instrument (CASI) in 2010‐2012. AD/ADRD mortality was classified by clinical diagnoses. Logistic regression models estimated adjusted odds ratios (AOR) for cognitive decline (CASI score<Q1), and Cox regression models estimated adjusted hazard ratios (AHR) for AD/ADRD mortality. A sum CKM index reflecting the presence of multiple CKM risk factors was calculated to estimate the combined predictive effect of CKM disorders on AD/ADRD mortality risk.ResultOver a mean 13‐year follow‐up, AD/ARAD mortality rates (95%CI) were 3.6 (3.1‐ 4.3) in men (126 deaths) and 2.0 (1.6‐2.5) in women (84 deaths) per 1000‐person years. Cognitive decline was significantly associated with elevated homocysteine concentrations (AOR=1.2, 95%CI: 1.1‐1.4), and ACR (1.2, 1.03‐1.5). AD/ADRD mortality was significantly associated with high BP (AHR=1.7, 95%CI: 1.2‐2.4), and elevated glucose (1.4, 1.1‐1.9), CRP (1.4, 1.1‐1.9), IL‐6 (1.7, 1.3‐2.2), D‐Dimer (1.5, 1.2‐2.1), homocysteine (1.9, 1.4‐2.6), cystatin C (1.6, 1.2‐2.2), and ACR (2.1, 1.6‐2.8). An increased sum CKM index significantly predicted a higher risk of AD/ADRD mortality.ConclusionThis study underscores the significant role of CKM disorders in contributing to cognitive decline, with a notable predictive effect on the risk of AD/ADRD mortality. This research contributes to a growing body of evidence emphasizing the interconnectedness of metabolic, renal, and cardiovascular health with cognitive outcomes, paving the way for integrative approaches in managing these complex interrelations.
Multimodal intervention for risk reduction of dementia in older adults with type 2 diabetes: Post‐hoc sub‐group analyses of the J‐MINT
Authors: Sugimoto Taiki , Uchida Kazuaki , Matsumoto Nanae , Fujita Kosuke , Yokoyama Yoko , Kuroda Yujiro , Omura Takuya , Nakamura Akinori , Crane Paul K. , Arai Hidenori , Sakurai Takashi ,   J‐MINT study group
Published: January 2025

AbstractBackgroundThis post‐hoc sub‐group analysis of the Japan‐multimodal intervention trial for prevention of dementia (J‐MINT) aimed to examine the efficacy of the multi‐domain intervention in older adults with type 2 diabetes.MethodJ‐MINT was an 18‐month, randomized controlled trial. Participants aged 65‐85 years with mild cognitive deficits were recruited and randomized into multidomain intervention (management of vascular risk factors, physical exercise, nutritional counseling, and cognitive training) and control groups (written health‐related information every 2 months). The outcome was the change from baseline to 18‐month follow‐up in a composite score derived from several neuropsychological tests, including tests of global cognitive function, memory, attention, and executive function/processing speed. Among individuals with diabetes, stratified analyses based on age at enrollment (65‐74 years vs. 75‐85 years), presence of memory impairment (with vs. without memory impairment), HbA1c levels according to the Japan Diabetes Society/Japan Geriatric Society recommended target range (within vs. above/below the target range), and APOE phenotype (0 vs. ≥1 APOE ε4 alleles), were performed using mixed models for repeated measures.ResultOut of 531 participants enrolled in J‐MINT, 76 participants with type 2 diabetes and 356 without had at least one post‐baseline assessment and were included in the analysis. In participants with and without diabetes, there were no significant effects of the intervention on changes in the composite score. Among people with diabetes, stratified analyses revealed that the intervention effect was significant in individuals aged 65‐74 years (mean difference between the intervention and control groups, 0.310 [95% CI 0.104–0.517], p = 0.003). Moreover, the intervention appeared to be effective in those with HbA1c levels above/below the target range (0.304 [0.007–0.601], p = 0.045), although it did not reach statistical significance after Bonferroni correction (p < 0.005). There was no significant effect of intervention in stratified analyses based on memory impairment and the APOE phenotype.ConclusionThese results suggest that multidomain interventions may be particularly valuable for people with diabetes who are in the younger age group or whose glucose values are not in the target range. However, this should be confirmed in other data sets.
Older predicted age using AI EKG‐based age prediction is associated with higher Alzheimer’s disease neuropathologic change
Authors: Bermudez Camilo , Syrjanen Jeremy A. , Attia Zachi I , Friedman Paul A , Lopez‐Jimenez Francisco , Hu Mingzhao , Petersen Ronald C. , Knopman David S. , Ramanan Vijay K. , Jack Clifford R. , Nguyen Aivi T. , Reichard Ross R. , Kouri Naomi , Moloney Christina M. , Algeciras‐Schimnich Alicia , Murray Melissa E. , Mielke Michelle M. , Vemuri Prashanthi , Noseworthy Peter A , Graff‐Radford Jonathan 
Published: January 2025

AbstractBackgroundThere is increasing need for noninvasive biomarkers of Alzheimer’s Disease (AD) neuropathologic change for early detection and intervention through risk‐factor modification and disease‐modifying therapies. One such biomarker is the prediction of chronological age from routine clinical tests such as an electrocardiogram (EKG) to discriminate between observed biological age from chronological age for healthy aging. Deviation of true age from predicted age has been associated with heart failure, hypertension, and coronary heart disease. However, the association between EKG‐based age and underlying neuropathology has not been studied.MethodWe used a cohort of 336 participants from the Mayo Clinic Study of Aging, a population‐based prospective study of residents in Olmsted County, Minnesota, with antemortem EKG and post‐mortem brain autopsy (Table 1 & 2). Age was predicted from EKG using a validated convolutional neural network algorithm. We used ordinal logistic regression to identify associations between lower neuropathologic scores of AD (Thal phase, neuritic plaque score, Braak stage, and overall AD neuropathologic change) and the Age‐Gap, defined as EKG‐predicted age minus chronological age. Results were controlled for true age, sex, and APOE e4 carrier status. Neuropathologic scales were grouped into none, low, intermediate, and high categories. Observations were weighted by the inverse of years between last EKG and time of death to account for the time difference between acquisition of EKG and autopsy.ResultWe found that an increasing Age‐Gap (i.e. older predicted age) was inversely associated with lower overall AD neuropathologic change (OR 0.93 [0.89, 0.97], p = 0.002). Investigation of the components of AD neuropathologic change showed that an increasing Age‐Gap was also inversely associated with lower amyloid metrics such as Thal phase (OR 0.85 [0.80, 0.89], p < 0.001) and neuritic plaque scores (OR 0.91 [0.87, 0.96], p < 0.001), but not tau metrics like Braak staging (OR 1.05 [1.00, 1.10], p = 0.05).ConclusionIn this work, we show that older predicted age on EKG, a noninvasive biomarker associated with vascular and biological aging, is associated with higher amyloid burden and neuropathologic change of AD.
Resistance exercise and Alzheimer’s disease blood‐based biomarkers in European cognitively healthy older adults
Authors: Esteban‐Cornejo Irene 
Published: January 2025

AbstractIn the quest to combat Alzheimer’s disease (AD), physical exercise has emerged as one of the leading non‐pharmaceutical approaches to improve executive function and ameliorate cognitive decline. The limited understanding of the mechanisms by which exercise impacts cognition in late adulthood hinders the widespread use of exercise as a therapeutic or preventive approach for AD. This underscores the urgent need for research aimed at unraveling the mechanisms by which exercise improves cognition.This study delves into the unexplored realm of AD blood‐based biomarkers as potential mediators of the cognitive benefits induced by exercise. Despite their potential significance, no previous trials have examined the impact of exercise on these novel AD BBMs and their cognitive implications. These effects may vary based on exercise type (e.g., aerobic, high intensity interval training or mind‐body exercises), necessitating a thorough exploration of optimal exercise types and doses before advancing to comprehensive interventions.Using data from the AGUEDA trial, a single‐site, two‐arm, single‐blinded, randomized controlled trial (RCT) involving 90 cognitively normal older adults from Spain (Europe), aged 65‐80 years old, this study marks the first attempt to uncover the effects of a 24‐week resistance exercise intervention on AD BBMs and their cognitive implications. We will share promising findings on the impact of exercise on AD BBMs related to AD pathological hallmarks (i.e., amyloid‐β peptides and p‐tau isoforms), to neuronal loss (NfL); and to neuroinflammation (GFAP).This research not only will unveil the potential of resistance exercise as a powerful tool in AD prevention but also will help to set the stage for a new era of precision interventions targeting specific AD BBMs.
Beyond Credentials: Understanding Educational Gradients in Cognitive Function at Midlife
Authors: Grodsky Eric , Warren John Robert , Muller Chandra , Manly Jennifer J. , Brickman Adam M. ,   HSB
Published: January 2025

AbstractBackgroundA substantial body of research points to the persistence of educational credential gradients in cognitive function across the life course, from early adulthood through old age. Fewer studies have considered the roles of educational opportunities and achievements early in the life course in shaping (1) educational credential gradients or (2) variation in cognitive function among those with the same credentials. As a result, researchers underestimate the contribution of education writ large to variation in cognitive performance later in life.MethodWe analyze data from the nationally representative High School and Beyond (HSB) cohort, which has followed ∼25,500 people from high school in 1980 through age ∼60 in 2021‐22. The 2021‐22 round of HSB gathered high quality measures of cognition across multiple domains; the 1980‐1992 rounds gathered extensive information about educational opportunities, achievements, and attainments.ResultWe demonstrate that high school educational opportunities, and especially academic achievements, account for most of the credential gradient in cognition on selected cognition measures among adults who attended high school in the U.S. in 1980 as they approach 60 years of age. High school educational opportunities and academic achievements also help account for some of the variation in cognition among those with the same educational credential.ConclusionEducational credentials commonly employed to understand the contribution of education to cognitive aging therefore risk both mischaracterizing and understating the contributions of education to cognitive function and change over the life course.
Assessing attitudes and beliefs of dementia risk and prevention in middle‐aged adults
Authors: Simone Stephanie M. , Kaplan Marina , Giovanetti Tania 
Published: January 2025

AbstractBackgroundHealthy lifestyle behaviors (e.g., physical activity, cognitive activity) protect against cognitive decline and reduce dementia risk. Alzheimer’s disease (AD) neuropathology begins several years before the onset of clinical symptoms and disability; thus, midlife may be a critical time during which healthy lifestyle behaviors may be most effective. Motivation is essential to engage and maintain healthy lifestyle behaviors, particularly in midlife when benefits may not be observed for up to decades later. The factors that shape individuals’ motivation to engage in healthy lifestyle behaviors for dementia risk reduction remain poorly understood, but will be important for designing effective dementia prevention programs. This study identified groups of participants in midlife who possess similar beliefs and attitudes (e.g., motivation) about dementia risk and prevention using a person‐centered approach (i.e., latent profile analysis [LPA]).MethodThere were 347 middle‐aged participants (M age = 54.67±5.97; 53% women; 86.5% White; M education = 14.28±2.25) from the US general population who completed an online questionnaire using Qualtrics which assessed demographics and attitudes and beliefs about dementia and lifestyle behavior changes for dementia risk reduction. Latent profile analysis was conducted using z‐transformed scores to identify subgroups of middle‐aged adults with similar beliefs and attitudes about dementia and dementia prevention (Table 1).ResultResults suggested that a four‐profile model was the best fit for the data (Table 2), yielding four distinct subgroups that differed in beliefs and attitudes about dementia and dementia prevention (Figure 1). For example, Profile 2 showed the highest level of motivation to engage in healthy behaviors and greatest concern of everyday cognition but the lowest level of AD knowledge and health literacy, whereas Profile 4 showed a variable motivation pattern but the highest levels of apathy.ConclusionSubgroups of middle‐aged adults with different patterns of attitudes and beliefs (e.g., motivation) about dementia and dementia prevention were identified. Future work will focus on differences in healthy lifestyle behaviors (e.g., physical activity, cognitive activity) between subgroups and replication of the profiles in other cohorts. Insights gained may be used to inform who to target and how to design effective dementia prevention programs and policies for people in midlife.
Unsupervised machine learning model to predict cognitive impairment in subcortical ischemic vascular disease
Authors: Qin Qi , Yin Yunsi , Qu Junda , Tang Yi 
Published: January 2025

AbstractBackgroundIt is challenging to predict which patients who meet criteria for subcor‐ tical ischemic vascular disease (SIVD) will ultimately progress to subcortical vascular cognitive impairment (SVCI).MethodWe collected clinical information, neuropsychological assessments, T1 imag‐ ing, diffusion tensor imaging, and resting‐state functional magnetic resonance imaging from 83 patients with SVCI and 53 age‐matched patients with SIVD without cogni‐ tive impairment. We built an unsupervised machine learning model to isolate patients with SVCI. The model was validated using multimodal data from an external cohort comprising 45 patients with SVCI and 32 patients with SIVD without cognitive impairment.ResultThe accuracy, sensitivity, and specificity of the unsupervised machine learning model were 86.03%, 79.52%, and 96.23% and 80.52%, 71.11%, and 93.75% for internal and external cohort, respectively.ConclusionWe developed an accurate and accessible clinical tool which requires only data from routine imaging to predict patients at risk of progressing from SIVD to SVCI.
Exploring knowledge valorization and utilization strategies in academic health science centers in the Netherlands: multi‐case study of Alzheimer centers
Authors: Zhu Eden Meng , Buljac‐Samardžić Martina , Ahaus Kees , Huijsman Robbert 
Published: January 2025

AbstractBackground‘Intellectual assets’ generated in traditional university settings, that may not fit the interests of the standard ‘valuation criteria’ (i.e. commercially profitable), such as non‐pharmacological dementia care research, often remain siloed within their respective research disciplines and originating institutions. Implementation science can be leveraged to navigate the complexity of research innovation systems and enhance the outcomes of research valorization and utilization activities. Five specialized Alzheimer Centers were established to facilitate the creation, translation, implementation, and dissemination process for dementia research in the Netherlands. This study aims to use an implementation science‐guided approach to explore the knowledge valorization, implementation and dissemination activities present within the Centers to understand the activities and strategies used at each stage of the ‘knowledge‐to‐action’ process.MethodIndividual semi‐structured qualitative interviews from participants through purposive sampling of researchers employed across five Alzheimer Centers were conducted, and multiple case studies were produced. Interviews were conducted in‐person and virtually through Microsoft Teams, and all were audio‐recorded, transcribed verbatim, and analyzed using ATLAS.ti software. Leaders of each Alzheimer Center were involved in later stages of data analysis to help interpret and validate the results.ResultKnowledge creation, and the translation of research findings into research products, was facilitated by the proximity between researchers and dementia patients, through ‘memory clinics’ and ‘client panels’ that provided researchers the opportunity to involve end‐users in research product development. Implementation of knowledge products was often facilitated through establishing early formal public‐private partnerships, involving well‐networked external intermediary organizations and university‐based technology transfer offices to determine implementation pathways. Dissemination was facilitated through strategically leveraging social media marketing tactics to expand reach and establishing partnerships to utilize existing dissemination channels.ConclusionAlthough similar knowledge valorization and utilization strategies were identified across the five Alzheimer Centers, the degree of success for the strategies found varied across each Center, which suggests a connection between the Alzheimer Center’s organizational maturity, the implementation teams’ overall readiness, and the selected strategies’ outcomes. Future studies may explore the relationship between organizational characteristics and implementation support readiness to develop a context‐appropriate implementation mapping approach, suitable for enhancing implementation support readiness in dementia research.