bluuebunny/crossref_metadata_2025_split huggingface dataset:
Acceptability and validity of the smartphone‐administered version of the Cogstate Brief Battery in middle‐aged and older adults of the Healthy Brain Project
Authors: Cummins Hannah , Bransby Lisa , Fredrickson Amy , Stellman Gabriel , Maruff Paul , Edgar Chris J. , Lim Yen Ying 
Published: January 2025

AbstractBackgroundRemote and unsupervised administration of neuropsychological tests may increase opportunities to understand cognition in everyday life compared to in‐clinic assessments. The technological sophistication and widespread use of smartphones now allows this platform to be used for remote neuropsychological testing. However, it is important to ensure that the validity of neuropsychological tests extends to remote and unsupervised administration. As the Cogstate Brief Battery (CBB) has been validated for remote use on computers, the aim of this study was to now examine whether the acceptability and validity holds when administered via smartphone to cognitively unimpaired (CU) middle‐aged and older adults.MethodCU adults (n = 173) aged 41‐75 years (M(SD) = 62.72 (7.18)) enrolled in the Healthy Brain Project completed the smartphone CBB remotely. The mean speed and accuracy of performance on the Detection (DET, psychomotor function), Identification (IDN, attention), One Back (OBK, working memory) and One Card Learning (OCL, visual learning) tests were used to define performance. Acceptability was determined by the percentage of participants completing the full CBB. Relationships between CBB performance with age and test difficulty were described to inform validity. Relationships between objective CBB performance and subjective ratings of how participants felt about their overall performance, obtained via survey, were also explored.Result100% of participants completed the smartphone CBB. Increasing age was associated with slower performance on all tests (Figure 1a‐1d), and reduced accuracy on the OBK (Figure 1h). Older adults (66+ years) performed slower than middle‐aged adults (40‐65 years) on all CBB tests, and with less accuracy on OBK (Table 1). Performance speed across all tests slowed with increasing test difficulty (Figure 2). Whilst a ceiling effect was observed for accuracy of simpler tests (DET, IDN, OBK), accuracy was lowest for the most difficult test (OCL) (Figure 2). Subjective ratings of overall CBB performance was significantly, albeit weakly, correlated with OCL accuracy (r = 0.23, p = .003).ConclusionThe results support the acceptability and validity of the remote, unsupervised administration of the smartphone CBB in CU middle‐aged and older adults. These results provide a foundation for gaining further understanding of the performance of the smartphone CBB in diverse and impaired populations.
Extracellular Vesicles Treatment Induces Pro‐resolutive Microglial Changes in Experimental Models of Ischemic Stroke: A Systematic Review and Meta‐analysis
Authors: Bernardi Luis Pedro , Schlickmann Thomas Hugentobler , Carello‐Collar Giovanna , Rohden Francieli , Souza Diogo O. , Zimmer Eduardo R. 
Published: January 2025

AbstractBackgroundIschemic stroke (IS) is a risk factor for developing Alzheimer’s disease (AD). In this context, microglial activation is a shared cellular response to these two conditions that can be either beneficial or detrimental. Previous research has established that mesenchymal stem cell‐derived extracellular vesicles (MSC‐EVs) treatment leads to enhanced functional recovery and reduced brain infarct volume in animal IS models. However, current literature findings are unclear when addressing the effects of MSC‐EVs treatment on microglial activation. Thus, we aimed to investigate how MSC‐EVs treatment alters microglial activation parameters in IS models.MethodThe protocol of this systematic review was registered in PROSPERO (CRD42023463152) and followed the PRISMA 2020 statement. We searched EMBASE, PubMed, and Web of Science from database inception to October 2023 for studies with animal or cell culture IS models using MSC‐EVs as intervention and measuring microglial activation outcomes compared to control. We performed a random‐effects meta‐analysis using standardized mean differences (SMD) as the effect measure with the metafor and metaviz packages in R (v4.2.1) (FDR‐adjusted p‐value<0.05).ResultThe database search identified 294 records, from which 27 were included (Fig. 1). Meta‐analysis showed that in vivo MSC‐EVs treatment resulted in a lower number of total microglia (Iba1+ cells) (SMD = ‐1.45 [‐2.19,‐0.71 95%CI] p<0.001, Fig. 2A) and CD16+ microglia (SMD = ‐1.84 [‐2.62,‐1.05 95%CI] p<0.001, Fig. 2B), but in a higher number of CD206+ microglia (SMD = 1.95 [1.01,2.88 95%CI] p<0.001, Fig. 2C) in the brain across different IS models and age groups. In microglia cell cultures submitted to oxygen‐glucose deprivation, MSC‐EVs treatment decreased the levels of TNF‐α (SMD = ‐3.32 [‐4.95,‐1.69 95%CI] p<0.001, Fig. 3A), IL‐1β (SMD = ‐3.45 [‐5.57,‐1.32 95%CI] p<0.001, Fig. 3B), and IL‐6 (SMD = ‐2.95 [‐4.50,‐1.40 95%CI] p<0.001, Fig. 3C) in the culture medium, while increasing the gene expression levels of Arg‐1 (SMD = 5.41[3.54,7.29 95%CI] p<0.001, Fig. 3D).ConclusionWe demonstrated that MSC‐EVs treatment in IS models reduces the expression of pro‐inflammatory microglial activation markers (CD16) and cytokines (TNF‐α, IL‐1β, IL‐6) while increasing the expression of anti‐inflammatory markers (CD206, Arg‐1). Our results suggest that MSC‐EVs treatment modulates microglia towards a pro‐resolutive state, potentially contributing to the recovery of damaged brain tissue in IS and, consequently, in AD.
Navigating the Longitudinal Maze: Unravelling Challenges in the Follow‐up of a Dementia Cohort Study
Authors: HS Sunitha , Lingegodwa Abhishek Mensegere , Partha Ajith , Arvind Prathima , NM Divya , CM Amitha , HS Deva Kumar , Narayanasamy Rajitha , R Meghana , Menon Meenakshi , Vishwanath Vindhya , Velavarajan Goutham , Singh Sadhana , Malo Palash K , Stezin Albert , Sundarakumar Jonas S. , Issac Thomas Gregor 
Published: January 2025

AbstractBackgroundDementia, a global health challenge, drives the need for comprehensive understanding. Longitudinal cohort studies are vital, yet maintaining follow‐up in dementia cohorts poses challenges. This study explores challenges in follow‐up, refines protocols, and develops strategies that can elevate dementia research quality.MethodThis is an ongoing longitudinal cohort study on dementia named TLSA (Tata Longitudinal Study of Ageing) in which healthy volunteers are recruited in the community through various strategies such as awareness talks, advertisements, and referrals from other volunteers. All of them undergo a set of clinical assessments, cognitive, blood biochemistry, and MRI examinations at baseline and annual follow‐up visits and are informed about the results of the same by clinicians, thereby maintaining contact regularly. For follow‐ups, each of them is contacted via calls, messages, and Emails once a year. To enlighten them on the findings of research, regular participant meets are conducted, and monthly newsletters are issued. House visits (via mobile unit customized for various assessments) were conducted for participants who were unable to come to the research center but did not want to drop out. This study explored the distinct reasons for dropouts when the volunteers were called for follow‐ups.ResultThe total number of participants is 1484 till December 2023. The total number of dropouts is 113(7.6%). The reasons for dropouts were death 11 (9.7%), unable to contact 35 (30.9%), loss of interest in the study participation 30 (26.5%), relocation 10 (8.8%), health issues 17 (15%), family restrictions 5 (4%), and other unreported reasons 5 (4%).ConclusionEnhancing motivation strategies tailored to specific groups such as those who lack interest, have relocated, or face family restrictions can effectively boost follow‐up participation, consequently reducing dropout rates. Tailoring strategies using technology such as social media, infographics, and messaging applications to each group’s unique circumstances can reignite interest in participating in the study, ultimately leading to improved follow‐up rates, and enhancing the overall quality of the research.
Bridging the Gap between Cognition and Everyday Functioning: A linking Study in Amyloid Positive Participants
Authors: van der Putten‐Toorenburg Angela , Butterbrod Elke , Postema Merel C. , van der Veere Pieter J. , Tewolde Mukrabe E. , Schalet Benjamin D. , van Harten Argonde C. , van de Giessen Elsmarieke , Teunissen Charlotte , van der Flier Wiesje M. , Sikkes Sietske A.M 
Published: January 2025

AbstractBackgroundIt remains unclear to what extent global cognition translates to everyday functioning, although this is essential to interpreting the clinical meaningfulness of cognitive deficits. Here, we investigate potential linking between the Mini‐Mental State Examination (MMSE) and the proxy‐based Amsterdam Instrumental Activities of Daily Living Questionnaire (A‐IADL‐Q).MethodsCross‐sectional data from 1228 amyloid‐positive participants (age = 64±7yrs; 51.1%F), with Subjective Cognitive Decline(n = 156), Mild Cognitive Impairment(n = 228) or Probable Alzheimer’s Disease(n = 844) were included from the Amsterdam Dementia Cohort. Amyloid positivity was based on amyloid PET or cerebrospinal fluid, according to local cut‐off values. All participants completed MMSE, and all proxies A‐IADL‐Q. Equipercentile linking, unidimensional Item response theory (IRT) calibration and multiple regression analyses were explored as linking methods. For each MMSE quartile, we explored the proportion of reported problems on the A‐IADL‐Q total score and each A‐IADL‐Q item. We described the most commonly affected activities.ResultsAssumptions for direct linking (equipercentile/IRT) were not met (r = 0.53,95%CI[0.48,0.57]). We proceeded with multiple regression analyses, with MMSE as independent variable and A‐IADL‐Q as dependent variable (adjusted for age, sex and education). Higher MMSE scores were associated with higher everyday functioning in the total sample (B = .96;95%CI[0.87,1.04]), with a one‐point increase in MMSE corresponding to nearly one additional point in A‐IADL‐Q scores. In the highest MMSE quartile (27‐30), 35% of participants experienced ‘no problems’, while 47%,17%, and 1% experienced 'mild,’ ‘moderate,’ and ‘severe problems’ respectively (Figure 1). In the lowest quartile, 5% reported 'no problems‘, with 22%,44%, and 29% experiencing 'mild,’ ‘moderate,’ and 'severe problems’. Most commonly affected activities in the highest MMSE quartile were working (74% at least mild problems), followed by using a computer (52%) and managing the household budget (47%). The latter two activities were also most commonly affected in the lowest MMSE quartile, but to a much higher degree (93%,95%) alongside filling in forms (96%).ConclusionAlthough direct linking between cognition and daily functioning was not possible, our findings support more functional dependencies with increasing cognitive problems. Functional difficulties in the highest MMSE group suggest limited sensitivity of cognitive screening. Our findings suggest a nuanced link between global cognition and everyday functioning, supporting complementary use of both instruments.
Impaired Recovery Sleep in Individuals with Alzheimer’s Disease – The RESTED Study
Authors: Blackman Jonathan , Gabb Victoria Grace , Morrison Hamish , Turner Nicholas , Biswas Bijetri , Li Haoxuan , Whone Alan , Coulthard Elizabeth 
Published: January 2025

AbstractBackgroundHomeostatic sleep regulation is theorized to be governed by the ‘Two Process Model’ where circadian rhythm (process C) and homeostatic sleep pressure (process S) interact to determine sleep versus wakefulness. Sleep pressure accumulated during prolonged wakefulness increases the duration and intensity of subsequent ‘recovery’ sleep. Multiple sleep abnormalities are associated with Alzheimer’s Disease (AD) Dementia and Lewy Body Dementia (LBD). This study seeks to determine whether recovery sleep duration may also be compromised.MethodRESTED (Remote Evaluation of Sleep To enhance understanding in Early Dementia) was an observational cohort study with three subgroups: AD MCI/dementia, LBD MCI/dementia, and healthy controls (HC). Participants wore a wrist actigraph for 55 nights continuously and provided daily sleep diaries. Recovery sleep was assessed using a random intercept lagged panel model with a dependent variable of total sleep time (TST). Prespecified covariates included age, sex, Geriatric Depression Score, Generalised Anxiety Disorder 7‐Score and participant subgroup (AD/LBD/HC). Compensatory sleep represented a ‘within‐person’ carry‐over effect modelled with an autoregressive parameter (alpha). A negative value implies low TST nights are typically followed by higher TST nights, indicating compensatory or recovery sleep Interaction terms determined if alpha was affected by participant group or age.Result40 participants (AD = 10, LBD = 10, HC = 20) underwent full study procedures. Mean (SD) age was 70.9 (5.9) [AD = 69.2(7.9), LBD = 73.9(2.8), HC = 70.2(5.7)]. 9/40 (22.5%) participants were female (AD = 2/10, LB = 2/10, HC = 5/20). Mean (SD) Montreal Cognitive Assessment Score was 24.8 (4) [AD = 23.0(5), LBD = 21.9(4), HC = 27.1(1)].Age (β = ‐0.11, SE = 0.05, p = 0.036), diagnosis of AD (β = ‐1.75, SE = 0.57, p = 0.004) and alpha (β = ‐0.94, SE = 0.31, p = 0.002) were all negatively associated with sleep duration. There were significant positive interactions between alpha and diagnosis of AD (β = 0.13, SE = 0.06, p = 0.026) and alpha and increasing age (β = 0.01, SE = 0.004, p = 0.001). No statistically significant effects were found linking LBD to sleep duration.ConclusionLow TST nights were typically followed by higher TST nights suggesting that compensatory mechanisms were present. However, this relationship was attenuated both by the presence of AD and increasing age (approximately 10% per decade). Further research is needed to confirm these findings in larger cohorts and determine underlying pathophysiological mechanisms by which sleep recovery is compromised.
Random Forest Classifiers to predict psychotic symptoms in Alzheimer’s disease
Authors: Scarfo Sara , Moshfeghi Yashar , McGeown William J 
Published: January 2025

AbstractBackgroundPsychotic symptoms (delusions and/or hallucinations) are among the most common and impactful neuropsychiatric symptoms that occur within Alzheimer’s disease (AD): present in around half of AD patients, they are associated with increased distress for the individual and their families, poorer disease outcome, and greater risk of hospitalization and death. Using Random Forest analyses, aim of this study is to provide clarity on the value of neuroanatomical, neuropsychological, and neuropsychiatric features when predicting the presence of psychotic symptoms in AD.MethodData used in preparation for this study was obtained from the Alzheimer’s Disease Neuroimaging Initiative database (adni.loni.usc.edu). Based on the scores of the Neuropsychiatric Inventory, participants were selected with the criterion of presenting with psychotic symptoms (either delusions, or hallucinations, or both). Controls were subsequently matched, who did not present with any psychotic symptom, and did not differ from the psychosis group for disease stage, age, gender, education, genetic profile, and overall cognitive and neuropsychiatric status. The predictors were derived from: Neuropsychiatric Inventory’s scores for the other neuropsychiatric symptoms; Alzheimer’s Disease Assessment Scale‐Cognitive Subscale, to select different cognitive functions; brain metrics derived from the FreeSurfer software (available via ADNI), as measures of cortical and subcortical volumes, cortical thickness, and surface area.ResultThe Random Forest Classifiers were employed to generate feature importance ranking. While further analyses are currently underway, preliminary results suggest that it is possible to understand how the different variables interact to predict the presence of psychotic symptoms, and which of those variables hold greater importance. Among neuropsychiatric symptoms, apathy has emerged; short‐term and long‐term memory and orientation resulted as best predictors among the cognitive functions. Lastly, the anterior and posterior cingulate cortex and insula (bilaterally), and right frontal areas were identified as the most important brain areas. Overall, the brain region metrics appear to have better discriminatory ability compared to neuropsychological and neuropsychiatric data.ConclusionThe results of this study indicate (albeit preliminarily) that a machine learning technique such as the Random Forest Classifier can be used to advance our understanding of the complex interaction of different predictors in the manifestation of psychotic symptoms in AD.
Longitudinal cognitive trajectories in sporadic early‐onset Alzheimer’s Disease: Findings from LEADS
Authors: Hammers Dustin B. , Eloyan Ani , Thangarajah Maryanne , Taurone Alexander , Wong Bonnie , Dage Jeffrey L. , Nudelman Kelly N. , Carrillo Maria C. , Rabinovici Gil D. , Dickerson Bradford C. , Apostolova Liana G. ,   and ‐ LEADS Consortium
Published: January 2025

AbstractBackgroundEarly Onset Alzheimer’s Disease (EOAD) is a rare condition that manifests prior to the age of 65, and affects approximately 5% of patients with Alzheimer’s disease. The Longitudinal Early‐Onset Alzheimer’s Disease Study (LEADS) is the largest prospectively‐evaluated cohort of participants with sporadic EOAD in the United States, initiated to better understand the features of this condition. The current analyses sought to examine longitudinal cognitive trajectories of patients with EOAD over time.MethodData from 100 participants with amyloid‐positive EOAD, 30 participants with amyloid‐negative cognitive impairment (EOnonAD), and 65 cognitively normal age‐matched participants were compared. All had at least three study visits. Cognitive trajectories across a comprehensive cognitive battery across 24‐56 months were examined using mixed‐effects modeling, including the years of onset x diagnostic group interaction controlling for years since onset, education, sex, and the random effect of each participant.ResultAcross all measures, clinical groups generally displayed declines over time, with performances for the EOAD group tending to approach the lower limit of performance ranges (Figure 1). Relatedly, significantly greater slopes of decline were seen over time for the EOAD group than the CN group across all cognitive domains evaluated (ps<.001; Table 1). When comparing between clinical groups, greater declines were also evident for the EOAD group relative to the EOnonAD group for a screener of global cognition, and for specific measures of attention, verbal fluency, processing speed, language, and delayed story recall (ps .001 to .049; Table 2). No differences in trajectory were observed between clinical groups for unstructured verbal memory, visual memory, or visuospatial skills (ps>.05; Tables 1 and 2).ConclusionIn addition to worse cognition at baseline, sporadic EOAD participants displayed pronounced declines in cognition over 24‐56 months across all domains evaluated. Relative to the EOnonAD group, cognitive trajectories appear to be worse predominantly for executive and attentional processes, with variability across episodic memory tasks. This suggests that EOAD pathology is not solely directed at memory functioning. Future research will focus on comparing cognitive trajectories of EOAD and late‐onset AD, in an effort to understand similarities and differences in the types and rates of cognitive trajectories.
Computerized testing to detect cognitive decline in biomarker‐confirmed Alzheimer’s disease: Longitudinal findings from the ARMADA study.
Authors: Jutten Roos J , Ho Emily , Karpouzian‐Rogers Tatiana , Van Hulle Carol A. , Dodge Hiroko H , Nowinski Cindy J. , Gershon Richard C. , Weintraub Sandra , Rentz Dorene M 
Published: January 2025

AbstractBackgroundThe National Institutes of Health Toolbox for Assessment of Neurological and Behavioral Function (NIHTB) was developed to address the need for a brief yet comprehensive instrument to facilitate more uniform assessment in large‐scale research studies. Here, we investigated whether the cognitive measures of the NIHTB detect cognitive decline in biomarker‐confirmed Alzheimer’s disease (AD).MethodWe used data from N = 178 participants (age 76.5±8; 53% female) from the Assessing Reliable Measurement in Alzheimer’s Disease and Cognitive Aging (ARMADA) study, who were recruited across nine research centers in the United States and had amyloid PET or amyloid‐beta42/tau CSF data available within two years of their baseline NIHTB assessment. Participants’ cognitive status (normal (CN) or impaired (CI), based on standardized protocols) and amyloid status (Aβ‐/Aβ+, based on site‐specific cut‐offs) were combined to create three groups: healthy controls (CN Aβ‐, n = 113), asymptomatic AD (CN Aβ+, n = 24), and prodromal‐to‐mild AD (CI Aβ+, n = 34) (Table 1). The NIHTB was assessed at baseline, 12 and 24 months and includes five tasks measuring fluid cognition (attention, executive functions, processing speed, working memory, and episodic memory) and two tasks reflecting crystallized cognition (oral word reading and auditory word comprehension). Linear mixed‐effect models correcting for age, sex, and education were used to examine cross‐sectional and longitudinal NIHTB scores in the three study groups.ResultCompared to healthy controls, the prodromal‐to‐mild AD group had lower baseline scores on most NIHTB fluid tasks (Flanker Inhibitory Control and Attention, Dimensional Change Card Sort, Picture Sequence Memory, List Sort Working Memory) and showed accelerated decline over 12‐24 months on Pattern Comparison Processing Speed, List Sorting Working Memory and Picture Vocabulary (Figure 1). None of the NIHTB tasks detected cross‐sectional or longitudinal differences in the asymptomatic Aβ+ group compared to healthy controls over the course of this study.ConclusionThe NIHTB detects cross‐sectional impairment in episodic memory, attention, executive functions and working memory and longitudinal change in processing speed, working memory and auditory word comprehension in prodromal‐to‐mild AD. These findings further support the use of the NIHTB in AD research, but also imply that the optimal NIHTB composite to detect cognitive decline may differ across AD clinical stages.