bluuebunny/crossref_metadata_2025_split huggingface dataset:
Amyloid deposition and neuroinflammation in middle‐aged to older individuals with Down syndrome: a PET evaluation
Authors: de Oliveira Laura Cavalcanti , Coutinho Artur Martins , Forlenza Orestes Vicente , Buchpiguel Carlos A , Faria Daniele P de Paula 
Published: December 2023

AbstractBackgroundDown syndrome (DS) is characterized by trisomy for chromosome 21 and presents a high incidence and early development of Alzheimer’s disease (AD) (Ram G et al. 2011). The current study aims to evaluate the presence of amyloid in people with DS in different age spans and its correlation with neuroinflammation.MethodIndividuals with DS aged 20‐34 (n = 8), 35‐49 (n = 8), ≥ 50 (n = 4), and cognitively normal individuals without DS (controls n = 11) were evaluated with [11C]PK11195 PET imaging (neuroinflammation) and [11C]PIB PET (β‐amyloid) in a hybrid PET/MRI equipment. The radiopharmaceuticals were administered intravenously (∼370 MBq), and the images were acquired dynamically during 60 min ([11C]PK11195) and 70 min ([11C]PIB). PET images were quantified in the PMOD™ v4.1 software and the results were presented in SUV (Standardized Uptake Value) for [11C]PK11195 and SUVratio with the cerebellum crus as a reference region for [11C]PIB. [11C]PIB images were also visually classified as amyloid positive or negative by an experienced nuclear physician. Statistical analysis was performed by one‐way ANOVA and Bonferroni posthoc, and the differences were considered significant when P≤0.05.ResultAll individuals with DS ≥50 years were amyloid positive and showed increased [11C]PK11195 uptake when compared to younger DS subjects and the control group. Differences were seen particularly in the ≥50 group in the following areas: a) posterior cingulate (1.32±0.05, vs. control = 0.71±0.13, p<0.0001; vs. 20‐34 group = 0.67±0.16, p<0.0001; and 35‐49 group = 0.75±0.14; p = 0.0003); b) amygdala (0.86±0.14, vs. control = 0.62±0.10, p = 0.0450; vs. 20‐34 group = 0.57±0.09, p = 0.0114); c) caudate (0.70±0.12, vs. 20‐34 group = 0.47±0.10, p = 0.0195); d) and thalamus (0.90±0.11, vs. the 20‐34 group = 0.62±0.11, p = 0.0171). [11C]PIB uptake in the posterior cingulate correlated with [11C]PK11195 uptake (r = 0.6201; p = 0.006) in individuals with DS across all age spans.ConclusionThe increased uptake of [11C]PK11195 in subjects with DS≥ 50 years indicates the presence of a neuroinflammatory process in different brain areas that may be associated with β‐amyloid plaque deposition early in the aging process.
Innovative recruitment strategies for a multi‐domain lifestyle intervention trial (FINGER‐NL) via the Dutch Brain Research Registry
Authors: Waterink Lisa , Soons Lion M. , Keun Jikke T. Boelens , van Harten Argonde C. , Sikkes Sietske A.M. , Scherder Erik J.A. , Deckers Kay , Köhler Sebastian , Flier Wiesje M. , Zwan Marissa D. 
Published: December 2023

AbstractBackgroundFinding eligible participants for dementia prevention trials is challenging, resulting in prolonged recruitment periods, underpowered studies, and excessive costs. The Dutch Brain Research Registry (DBRR) is an online platform to facilitate recruitment of research participants. We evaluated different recruitment strategies with the ambition to optimize recruitment for the multi‐domain lifestyle intervention trial FINGER‐NL.MethodDBRR registrants were prescreened for FINGER‐NL based on available profile information. Potentially eligible registrants received an automatic study invitation. Those interested were contacted for additional telephonic screening and, if eligible, included in the trial. Five recruitment strategies within 2022 were executed with the goal to increase the number of DBRR registrants: 1) a paid Facebook‐campaign, 2) referral via (patient)‐organizations, 3) newspaper articles, 4) live‐events, and 5) national television appearance (W.F&E.S.). Recruitment source was traced (online; UTM tags) and/or reported by the participant. For most recruitment strategies, we involved a nationally well‐known ambassador (E.S.) who advocates a healthy lifestyle to improve brain‐health (Figure 1). For each strategy, we described the number of individuals registered, eligible and included in FINGER‐NL. We calculated efficiency (%eligible/prescreened) as a reflection of the proportion of eligible participants reached, and effectiveness (%included/registered) as a reflection of the proportion of participants included in FINGER‐NLResultIn 2022, the DBRR recruited 11234 new registrants. The highest numbers of registrants and highest number of inclusions were reached with national television appearance and the Facebook‐campaign (Table 1). In particular, the Facebook advertisement with a lifestyle theme and well‐known ambassador outperformed all other advertisements in number of registrations (Figure 1). After initial prescreening, between 18‐35% of registrants were eligible. Most efficient were national television and the Facebook‐campaign. Between 4‐12% of new registrants were included in the trial. Most effective strategies were national television appearance and referrals via patient‐organizationsConclusionOur results show that mass‐media, i.e. tailor‐made Facebook‐campaigns, national television appearance and events, are efficient ways to reach large numbers of eligible participants, especially when well‐known ambassador(s) were included. Recruitment strategies with detailed information about in‐ and exclusion of the trial are most effective. The DBRR provides an efficient and effective recruitment and prescreening process for the FINGER‐NL trial.
Challenges and Opportunities in a Resource Desert: Las Vegas Boot Camp Translation
Authors: John Samantha E , Moeller Stacey , Tanner Denise Lafont 
Published: December 2023

AbstractBackgroundThe state of Nevada has the 3rd fastest growing rate of Alzheimer’s disease and related dementias (ADRD) in the country with a 30.6% projected increase between 2020 and 2025. Growth in ADRD is complemented by growth in the diversity of residents, particularly in Las Vegas, where the growth of minoritized populations outpaces national rates. Nevada is 30% Hispanic/Latino (H/L) and Las Vegas is 33% H/L. Among the challenges presented by this growth, Nevada is characterized as a ‘neurology desert’, lacking the necessary specialists to meet the state’s care demands and lacking the traditional infrastructure for care and research referral. In order to better understand local experiences seeking care and address communication barriers, we applied the Boot Camp Translation model for the Las Vegas H/L community.MethodWe identified 14 community members to participate in our ADRD BCT through community connections, targeted email blasts, and social media. BCT members ranged in age from 23 to 62 (M = 43, SD = 13.74), were majority female (10/14) and H/L (11/14), and most (10/14) were connected to local non‐profit organizations serving H/Ls, those with ADRD, and/or older adults.ResultBCT members identified messages to increase AD awareness that reflected love, “respeto” (respect), resilience, and connection; messages targeted younger and middle‐age adults and community organizations: 1) “Amar es saber” (“To love is to know”), which encourages discussions among family members; 2) “The community cares. Let’s talk.”; and 3) “Podemos afrontar el Alzheimer juntos.” (”We can face Alzheimer’s disease together.”). BCT members identified our resource desert as a key challenge to message‐based calls to action. As reflected by their messages, they also highlighted opportunities for community members to engage and support message dissemination.ConclusionThe Las Vegas BCT effectively identified messages, challenges, and opportunities to increasing AD knowledge and research engagement. Many BCT members joined our community advisory board; they emphasize the need for ongoing advocacy in the state, Spanish‐language resources, and an online presence that simplifies and supports navigation of services and information.
Differential dementia diagnosis using event‐based modelling: Alzheimer’s disease versus Dementia with Lewy Bodies
Authors: Leal Gonzalo Castro , Whitfield Tim , Walker Zuzana , Oxtoby Neil P 
Published: December 2023

AbstractBackgroundDifferential diagnosis of dementias in the clinic is challenging, especially in the prodromal phase where early symptoms overlap. Here we prototype a differential diagnosis system based on event‐based modeling of MRI atrophy in two dementias.MethodPublic data from ADNI, NACC, PPMI, PDBP (N = 1978). Inclusion criteria: baseline T1w‐MRI successfully processed by FreeSurfer 7.1.1, CN/AD/DLB/MCI diagnosis. A nearest‐neighbour approach matched disease‐specific control groups to AD and DLB by Age/Sex/scanner (field strength), and Desikan‐Killiany volumes were adjusted for normal trends in Age/Sex/field‐strength/intracranial volume. The final analysis dataset consisted of 91 DLB, 298 AD, and 786 MCI (N = 1175), with matched control groups for each.One event‐based model (EBM) of regional brain atrophy was fit per disease, using Kernel Density Estimation mixture models to quantify biomarker abnormality. Input features were brain volumes having disease signal in both AD and DLB.The EBM patient‐staging tool was adapted to perform differential diagnosis. The tool converts individual data into a probability distribution over stages — stage likelihood — for each model. We define EBM diagnosis as the model having the maximum stage likelihood.ResultFigure 1 shows the event‐based model posterior (positional variance diagram) for AD (left) and DLB (right). AD atrophy starts in a subset of limbic regions before progressing to the temporal cortex and beyond. The DLB atrophy pattern diverges considerably (off‐diagonal density in Figure 1), including involvement of additional limbic regions early on. Figure 2 shows patient staging results for each model, with MCI individuals earlier than patients as expected. Differential diagnosis accuracy was 63%, which is comparable to previous studies.ConclusionWe successfully adapted event‐based modeling of MRI atrophy for differential diagnosis of AD vs DLB. More data for other dementias, especially in the prodromal phase, is needed to test and deploy such a tool in memory clinics.
Unraveling the relationship between heart rate and agitation in people with dementia
Authors: Davidoff Hannah , Van Helleputte Nick , Vandenbulcke Mathieu , De Vos Maarten , Hoof Chris Van , Bossche Maarten Van Den 
Published: December 2023

AbstractBackgroundAgitation is a critical behavioral and psychological symptom of dementia, leading alone to increased caregiver burden, more frequent hospitalization, and earlier institutionalization. The results presented here provide preliminary insights into one facet of multimodal agitation detection, specifically analyzing the relationship between heart rate and agitation.MethodTo date, 26 people with dementia have been included in our study to detect agitation using a multimodal approach1. In this analysis, heart rate is derived from the wristwatch wearable measuring photoplethysmography (PPG). Data points were included in subsequent analysis if the signal quality index of the original PPG signal was > = 0.8 (on a scale from 0‐1). For each complete survey, the mean heart rate (HR) was extracted from 1‐minute intervals in a 6‐minute window centered on the survey timestamp (± 3 minutes). For each mean HR per minute, the presence or absence of agitation was derived from the Pittsburgh Agitation Scale integrated into the survey. The data was centered within‐patient. Due to the nested structure of the data, hierarchical mixed models were used to predict presence of agitation as a binary response variable.ResultThe resulting dataset of high‐quality HR data consists of 1286 data points, from 21 patients (Age mean: 81 (8.3), nfemale: 8) The 3‐parameter model built included mean heart rate as an explanatory fixed effect, and two random intercepts: day and patient. In the model, increased HR compared to a participant’s average HR over a week, was significantly associated with an increase in odds of agitation (p< 0.001). Every 1 beat increase in mean HR over a minute, from the participants’ mean heart rate, increased the odds of that 1‐minute interval indicating agitation by 7.68% (CI: 5.43‐10.1).ConclusionThese results provide insight into the relationship between heart rate and agitation, possibly indicating activation of the autonomic nervous system, due to the association of increased HR with increased odds of agitation. Analyses like these provide the basis for future agitation detection algorithms that account for a multi‐faceted patient response.1. Davidoff, et al, 2022, Innovation in Aging, Volume 6, Issue 7, 2022, igac064, https://doi.org/10.1093/geroni/igac064
To evaluate the prevalence, subtypes and risk associations of mild cognitive impairment in elderly Indian individuals with type 2 diabetes
Authors: Gupta Anu , Goyal Alpesh , Rajan Roopa , Vishnu Venugopalan Y , Kalaivani Mani , Tandon Nikhil , Srivastava MV Padma , Gupta Yashdeep 
Published: December 2023

AbstractBackgroundDiabetes is an important modifiable risk factor for dementia. The prevalence of mild cognitive impairment (MCI) in type 2 diabetes (T2D) is high (You et al, 2021). This data is largely derived using screening tools (MMSE or MoCA), with little information on MCI subtypes. Evidence from the South Asian region is particularly scarce, where prevalence of diabetes is high, and is seen a decade earlier compared to Caucasians.MethodWe have established a cohort of elders (³ 60 years of age), with and without diabetes, visiting a tertiary care hospital in North India (from 2019, ongoing). The participants underwent an interview to collect information on their demographic profile, risk associations, vascular health, and other comorbidities. Culturally validated neuropsychological battery was used for cognitive evaluation. MoCA was done in a subset of patients.ResultWe recruited 840 participants in the cohort, 683 with T2DM and 157 without T2DM (controls). The mean age of the cohort was 65.3±4.5 years, 65.2% were males. Risk profile is described in Table 1. The cognitive z scores of participants with T2DM ranged from ‐0.25 to +0.44. The worst affected domain was attention, working memory and executive functions (Table 2). Using an actuarial definition of MCI (Bondi MW et al, 2014), the prevalence in participants with T2D was 29.7%. 17.3% had amnestic impairment, 14.8% dysexecutive, 14.2% language, 2.4% visuo‐perceptual and 9.1% multidomain impairment. The cognitive raw scores (by dementia risk stratification) are provided in Table 3. On logistic regression, lower education 3.45(2.09,5.68), depression 2.04(1.26,3.29), poor sleep quality 1.77(1.15,2.71), family income 1.70(1.22,2.38), followed by age 1.05(1.00,1.10) had a significant association with global low cognition.ConclusionRoughly one‐third of elders with T2D visiting tertiary care services in North India have mild cognitive impairment. Amnestic subtype is the most frequent. Attention, working memory and executive functions are worst affected. Enhancing the cognitive reserve, mood and sleep quality may be important targets in prevention of cognitive decline in the elderly population with T2D.
Identification of genes and blood co‐expression networks associated with cerebrovascular neuroimaging phenotypes
Authors: Chen Xuan , Quicksall Zachary , Wang Xue , Reyes Denise A. , Graff‐Radford Jonathan , Nguyen Thuy , Lincoln Sarah J. , Malphrus Kimberly G. , Crook Julia E. , Reddy Joseph S. , Allen Mariet , Jack Clifford R. , Lowe Val J. , Knopman David S. , Petersen Ronald C. , Kantarci Kejal , Bu Guojun , Carrasquillo Minerva M. , Ertekin‐Taner Nilufer 
Published: December 2023

AbstractBackgroundA hallmark of Alzheimer’s disease is amyloid‐β (Aβ) deposition in the brain parenchyma as senile plaques which Aß frequently accompanies in the cerebral vasculature as cerebral amyloid angiopathy (CAA). Previous studies demonstrated that the cerebrovascular system is essential for Aβ clearance and interactions exist between cerebrovascular disease and AD. Neuroimaging data, including measures on small vessel disease, amyloid deposits, and microhemorrhages (MCH), can reflect both cerebrovascular disease and AD pathology, thereby serving as intermediate phenotypes of both conditions. We aim to identify genes and co‐expression networks in blood associated with these neuroimaging endophenotypes and the biological pathways enriched in these perturbed transcriptional networks.MethodWe conducted differential gene expression and Weighted Gene Co‐Expression Network analyses (WGCNA) on blood RNA sequencing data of 407 participants from the longitudinally followed Mayo Clinic Study of Aging cohort. The neuroimaging phenotypes include MCH, infarction, and amyloid deposits measured by Pittsburgh compound B positron emission tomography (PiB PET).ResultWGCNA analysis showed a nominally significant association (p<0.05) between several module eigengenes (MEs) and MCH and PiB PET. One module, M42, remained significantly associated with PiB PET after Bonferroni correction for all 43 modules tested. Pathway enrichment analysis of M42 identified two significant pathways (FDR‐adjusted p<0.05) including phosphodiesterase I activity and IgE binding. These pathways contain genes such as MS4A2 encoding the high‐affinity IgE receptor involved in the immune response. Similarly, ENPP2 in the phosphodiesterase I activity pathway represents an additional candidate gene previously implicated in Alzheimer’s disease.ConclusionWe generated co‐expression networks and identified one network module with a statistically significant association between brain amyloid deposits and blood transcriptome data. Further investigations of this network and its enriched pathways are necessary to understand their roles in amyloidosis, CAA, and neurodegeneration. Future studies will include seeking replication of these results in other datasets. Such studies can help elucidate the biological mechanisms of pathogenesis of cerebrovascular damage and amyloid deposits. In addition, in a clinical setting, blood levels of transcripts discovered in this study may serve as predictive or diagnostic biomarkers with mechanistic implications.
Risk‐taking behavior in older adults is related to cognitive outcomes in a domain‐specific manner
Authors: Waltrip Leah H. , Joyce Jillian L. , Chapman Silvia , Cosentino Stephanie , Sunderaraman Preeti 
Published: December 2023

AbstractBackgroundRisk tolerance, a crucial component of decision‐making, has been shown to be highly domain‐specific (Blais, 2006). Nevertheless, when risk‐taking behavior is studied in the context of aging, it is almost exclusively examined using behavioral economics tasks which focus on financial risk‐taking behavior, neglecting other important domains such as health, recreational, ethical, and social risk‐taking. Such studies have associated risk‐aversion with cognitive impairment (James, 2015; Dohmen, 2010), however no studies have evaluated domain‐specific risk‐taking behavior and cognition in older adults. Evaluating the association of risk tolerance and cognition in a domain‐specific manner can help inform whether individuals are at an increased risk of poor decision‐making, and which domains of their everyday functioning may be impacted.MethodCognitively normal participants (n = 56) completed the Domain‐Specific Risk‐Taking Scale (DOSPERT) a 30‐item self‐reported survey consisting of financial, health, ethical, recreational, and social risk‐taking domains. Participants rated their likelihood of participating in risky activities on a 7‐point Likert scale with higher scores indicating higher likelihood of risk‐taking. Sum scores for each domain were calculated. Cognitive data was collected on tasks assessing associative, verbal, and working memory, as well as semantic and category fluency. Spearman’s two‐tailed correlations adjusted for age (69.55 ± 7.35), gender (59% female), and level of education (16.69 ± 2.19) were run to evaluate the relationship between specific risk‐taking domains and cognitive function.ResultFinancial risk‐aversion was associated with better long‐term verbal memory retrieval (p = 0.009, r = ‐0.359). Ethical risk‐seeking was associated with higher semantic fluency (p = 0.036, r = 0.292). Health risk‐aversion was associated with slower processing speed (p = 0.011, r = ‐0.348).ConclusionOur findings indicate that domain‐specific risk‐taking behaviors are uniquely related to different aspects of cognition. These findings suggest that measuring risk‐taking behavior in a single domain is not sufficient. Understanding the association between cognition and risk‐taking can provide insight on whether older individuals with impaired cognitive function are more likely to engage in risk‐taking with potential negative impacts on wellbeing. Future work can be conducted longitudinally in older populations to understand whether specific domains of risk‐taking consistently map on to the same aspects of cognition.
Association between sleep difficulties, bodily symptoms, and subjective cognitive decline in urban Black men
Authors: Esiaka Darlingtina K , Nwakasi Candidus 
Published: December 2023

AbstractBackgroundSleep has been linked to subjective cognitive decline (SCD) in older adults, which may indicate an onset of cognitive decline to Alzheimer’s disease and related dementia. There is a dearth of studies on the role of sleep difficulties and bodily symptoms in influencing cognitive status of middle‐age and older Black men. This limits our understanding of the potential role of sleep and bodily symptoms on Black men’s brain health.MethodThis cross‐sectional study examined factors predicting subjective cognitive decline in Black men living in urban settings. Participants (N = 117, Mage
= 48.45) responded to a survey assessing sleep difficulties, sleep comorbidities, bodily symptoms, self‐rated health, sociodemographic characteristics, and subjective cognitive decline. SCD was operationalized as a self‐reported experience with increasing confusion or memory loss in the last 12 months.ResultHierarchical regression revealed that in Model 1 with sociodemographic characteristics, only education was a significant predictor of SCD (F (4,112) = 6.33, p<.05), accounting for 18% of the variation in SCD. In Model 2 with self‐rated health and bodily symptoms added, socioeconomic status, education, and bodily symptoms were significant predictors of SCD (F (6,110) = 11.82, p<.001) and explained an additional 39% of the variation in SCD. When sleep difficulties and sleep comorbidities were added to Model 3, sleep difficulties, sleep comorbidities, bodily symptoms, socioeconomic status, and education were significant predictors of SCD (F (8,108) = 13.79, p<.001), accounting for 50% of the variation in SCD.ConclusionOur findings may be used as a groundwork for future research examining the causal link between cognitive decline, sleep, and bodily functions. It can also inform health intervention programs for middle‐aged and older Black American men.