bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using a Bayesian workflow approach to define the optimal level of anatomy/functionality voxels clustering for the prediction of tau propagation and cortical loss in Alzheimer’s disease
Authors: Soucy Jean‐Paul , Belasso Clyde J , Cai Zhengchen , Bezgin Gleb , Stevenson Jenna , Rahmouni Nesrine , Tissot Cécile , Lussier Firoza Z , Rosa‐Neto Pedro , Rivaz Hassan J , Benali Habib 
Published: January 2025

AbstractBackgroundTau aggregates in Alzheimer’s disease (AD) induce loss of synapses and neurons, leading to cognitive impairment. Predicting tau and neurodegeneration temporal evolution could be used for prognostication and for assessing results of therapeutic trials. Tau PET and MRI volumetry are reliable markers of disease stage, but cost and radiation protection considerations limit research measurement frequency, lowering the accuracy of disease progression modeling. Here, we evaluate, using Bayesian analysis, whether models based on limited numbers of observations can be refined to better predict the temporal trajectory of pathology.MethodImaging data comes from subjects (113; 68 females; 18 AD dementia, 23 MCI and 72 cognitively normal) of the TRIAD cohort (McGill University) who have been evaluated at least twice ( 1 year interval) with both tau PET ([18F]MK‐6240) and structural MRI. Four probability models were evaluated: 1‐ a basic one, assuming that all data points come from 1 data distribution; 2‐ one where subjects' observations are clustered within anatomical ROIs, where an independent distribution is hypothesized; 3‐ data is clustered within known physiological networks, each networks’ distribution parameters having their own specific values ; 4‐ a model assuming that subjects’ observations are described by a distribution of voxel parameters dictated by both the ROI and network(s) in which they lay. Bayesian data analysis was used to compare the predictive accuracy of those models for progression at 1 year from baseline of tau PET and MRI data.ResultModel 4 was the most accurate model for both tau and cortical thickness prediction. We therefore used it to perform posterior predictions across hemispheres, showing that the prediction curves of the left and right hemispheres for the pericalcarine cortex differ. We also noticed a decreasing trend in the CN tau curve for the left hemisphere as the rate of cortical thinning increases. In contrast, there is an increasing trend in the AD tau curve as the rate of cortical thinning increases.ConclusionThe model that incorporated both ROI‐level and network‐level information was the best predictor of progression, and such an approach can reveal underappreciated properties of the disease (i.e., laterality).
Machine Learning‐Driven Speech Biomarker Analysis: A Novel Approach for Detecting Cognitive Decline in Older Adults
Authors: Li Yatian , Chen Quan , Wu Jingnan , Chen Nan , Zhou Zhixing , Xia Huanhuan , Huang Lin , Guo Qihao 
Published: January 2025

AbstractBackgroundSpeech impairment appears at early stages of Alzheimer’s disease. A mobile voice recognition‐based cognitive assessment tool, Shanghai Cognitive Screening (SCS), was developed for detecting mild cognitive impairment (MCI) and dementia in the community. The objective of this study is to investigate speech biomarkers associated with cognitive impairments based on SCS, and to evaluate the diagnostic accuracy of speech feature‐based machine learning (ML) models for detecting MCI.MethodA total of 301 older adults were recruited to perform SCS assessments, with 135 of them were diagnosed with cognitive impairment (MCI and early dementia) and the remainder were cognitively normal. Speech features were extracted from SCS voice recordings and integrated in a dataset along with SCS scores and demographic indicators. The dataset was randomly divided into training and validation sets in a 4:1 ratio and trained in various ML models with predictive speech features examined.ResultAmong the models trained, the ML models employing SVM model, Logistic Regression, Random Forest, LightGBM, and XGBoost demonstrated higher accuracy than original SCS scores (Table 1). A ML classifier using Mel spectrograms and multimodal data fusion exhibited the highest accuracy of 0.953 (AUC = 0.967, sensitivity = 0.933, specificity = 0.933). Further analysis of the LightGBM model revealed that speech markers significantly influencing the model's output included modal particles, standard deviation of interval time, silence duration, mean interval time, total speaking time, silence time in delayed recall test, and percentage of silence time (Figure 1). These findings align with the audio waveform characteristics (i.e., smaller amplitudes, longer intervals, greater rhythm variations, and increased silence, Figure 2) in individuals with cognitive impairments. However, the top three factors were scores of delayed recall and instant memory, as well as SCS total score.ConclusionThe findings demonstrated speech biomarkers associated with cognitive impairments, facilitating more accurate detection of early cognitive impairment with ML techniques. Validation studies on larger sample sizes is necessary.
Predicting Neurodegenerative Diseases: Unveiling the Interplay of Genetics and Social Determinants
Authors: Escudero Stefanie Danielle Pina , Migeot Joaquín , Hernandez Hernan , Acosta‐Uribe Juliana , Cochran J. Nicholas , Taylor Jared W , Funes José Alberto Ávila , Matallana Diana , Lopera Francisco , Custodio Nilton , Behrens María Isabel , Chonchol Andrea Slachevsky , Bruno Martin Alejandro , Brusco Luis Ignacio , Takada Leonel Tadao , de Paula Elisa , Resende França , Reyes Pablo A , Gelvez Nancy , Franco Teresita Ramos , Bruna Bárbara , Ponce Daniela P , Durón Dafne Estefania , Montesinos Rosa , Millon Maria Beatriz Bistue , Maito Marcelo Adrian , Javandel Shireen , Godoy Maria Eugenia , Vitale Dan , Pantazis Caroline , Nalls Mike A , Singleton Andrew , Miller Bruce L. , Ibañez Agustin , Kosik Kenneth S. , Yokoyama Jennifer S. ,   Multi‐Partner Consortium to Expand Dementia Research in Latin America (ReDLat)
Published: January 2025

AbstractBackgroundPredicting Alzheimer's disease (AD) and frontotemporal dementia (FTD) using polygenic risk scores (PRS) for late‐onset forms holds promise, but its accuracy might be influenced by social determinants of health (SDOH). This study explores how considering SDOH alongside genes can improve prediction, focusing on potential differences for each disease.MethodsEmploying logistic regression in 677 individuals (287 AD, 102 FTD, and 288 controls) aged 40‐80 from the ReDLat study across six Latin American countries, we investigated the potential for SDOH to modify the association between PRS and susceptibility to AD and FTD. Analyses were adjusted for a probabilistic score derived from models comparing disease groups to controls with SDOH data (education, occupation, economic stability, healthcare access and quality, and social context) and APOE ε4 carrier status to account for confounding effects.ResultsAlthough univariate association tests revealed robust links between PRS and both diseases, adjusted models presented a nuanced picture. In AD, the SDOH score and APOE ε4 carrier status significantly attenuated the PRS effect (p=0.14), suggesting these factors modify genetic risk. In FTD, however, SDOH did not influence the PRS contribution. These findings highlight the potentially distinct roles of social factors in different neurodegenerative pathways.ConclusionThe significant modification of PRS effects in AD by SDOH and APOE ε4 underscores the need for comprehensive approaches in future research and interventions in Latin America. Conversely, the unaltered PRS contribution in FTD emphasizes distinct intricacies in gene‐environment interactions. These findings necessitate considering both realms in future efforts, paving the way for targeted strategies in AD and FTD prevention and treatment.
Does cultural and linguistic diversity impact timeliness of dementia diagnosis? Findings from the Australian Dementia Network Registry
Authors: Ahern Susannah , Lin Xiaoping , Honardoost Mohammad Amin , Wallis Kasey , Brodaty Henry , Ward Stephanie Alison ,   ADNetT Registry Steering Committee
Published: January 2025

AbstractBackgroundThe Australian Dementia Network (ADNeT) is a collaboration of dementia researchers and clinicians established in 2018. It includes a clinical quality registry that reports on diagnosis and early management of people with dementia or Mild Cognitive Impairment (MCI) across public, private, metropolitan and rural settings. Australia is multicultural and the registry collects information regarding cultural and linguistic diversity (CALD). The aim of this study was to determine if CALD status was associated with time to dementia diagnosis.MethodsADNeT registry data from March 2020 – Sept 2023 were analysed. Primary endpoint was time to diagnosis for three groups based on CALD status and preferred spoken language: non‐CALD; English‐speaking CALD; and non‐English‐speaking CALD. Descriptive statistics, univariate and multivariate regression analysis were undertaken for five outcome measures: (1) time from referral to diagnosis (2) time from referral to first appointment, (3) time from first appointment to diagnosis (4) age at referral, and (5) diagnostic outcome (dementia vs MCI).ResultsOf 3,634 participants, 2,817 (78%) were non‐CALD; 451 (12%) were English‐speaking CALD and 366 (10%) were non‐English speaking CALD. Overall median times were 131 days from referral to diagnosis, 75 days from referral to first appointment, and 28 days from first appointment to diagnosis. Both English and non‐English‐speaking CALD background were associated with longer time from referral to diagnosis (154/158 days vs 123 days for non‐CALD), and longer time from first appointment to diagnosis (46/70 days vs 18 days) (p<0.001), remaining significant after adjusting for demographic/health factors. There was no association between CALD and time from referral to first appointment. Non‐English‐speaking CALD background was also associated with older age at referral (80 years vs 78/77 years) and a higher likelihood of dementia diagnosis (75% vs 63/65%), although these differences disappeared after adjustment.ConclusionThis large national study shows that cultural and linguistic diversity is associated with delayed diagnosis of dementia, with further research required regarding underlying causes. This has important implications for equity of care as it may preclude people from CALD backgrounds accessing novel disease modifying treatments. People from CALD backgrounds may specifically benefit from dementia diagnostic biomarkers to facilitate earlier diagnosis.
FTD Disorders Registry (FTDDR) Participants: Understanding Social Risk Factors in Research Participation
Authors: Reddy Sweatha , Reinecker Robert , Milliard Carrie , Heuer Hilary W. , Forsberg Leah K. , Boxer Adam L. , Rosen Howard J. , Boeve Brad F. 
Published: January 2025

AbstractBackgroundFrontotemporal degeneration (FTD) is an umbrella term encompassing a range of rare neurodegenerative disorders that cause progressive changes to behavior, personality, language, and movement with onset typically before age 60. Currently, several potential FTD therapies are under investigation, underscoring the need for increased diversity in research participation. Two validated scores describe socioeconomic and geographic factors that may impact willingness to participate in research. The Area Deprivation Index (ADI) assesses socioeconomic disadvantages and captures social determinants of health. The Rural‐Urban Commuting Area Codes (RUCA) measures population density, urbanization, and daily commuting to determine individuals living in urban versus rural communities. FTDDR is a compliant, web‐based registry to facilitate FTD research. ADI and RUCA analyses of FTDDR participants can provide insight into current participants’ demographics and areas for recruitment prioritization.MethodFTDDR participants living in the United States were divided into two cohorts: (1‐FTDDR) enrolled in FTDDR only and (2‐ALLFTD) enrolled in FTDDR through ALLFTD, a longitudinal natural history study. ADI was calculated from self‐reported zip codes for 1392 participants in cohort 1 and 983 participants in cohort 2. RUCA scores were generated using self‐reported zip codes for 4565 participants from cohort 1 and 1174 participants from cohort 2.ResultADI analysis showed a low percentage (6.9% FTDDR, 5.7% ALLFTD) of participants lived in highly disadvantageous communities. 40.5% of FTDDR cohort and 49.3% of ALLFTD cohort lived in communities considered “low disadvantage,” suggesting they may have fewer socioeconomic risk factors or impediments to research participation. Most participants in both cohorts lived in urban areas (87.9% FTDDR, 85.8% ALLFD); only 3.2% of both cohorts lived in rural communities.ConclusionSocioeconomic and geographic factors may play a role in accurate diagnosis, access to medical centers, and ability to participate in research. ADI and RUCA analyses indicate that the majority of FTDDR participants, including those actively enrolled in FTD research, live in less disadvantageous neighborhoods and in urban areas, highlighting the need for outreach to more disadvantaged and rural communities. FTDDR prioritizing an engagement strategy to identify, recruit, and retain diverse individuals willing to participate in research could accelerate advancements in FTD research.
Koreans Invested in Making Caregivers Health Important (KIMCHI): A National Community‐based Project to Enhance Knowledge, Attitudes, and Behaviors about Dementia for the Korean American Community
Authors: Nam Bora , Huang Daren , Yun Stacy W , Shin Hye‐Won , Lee Eun Jeong , Phan Nicole , Park Van Ta 
Published: January 2025

AbstractBackgroundThe Korean American older adult population is rapidly growing, with most being foreign‐born individuals with limited English proficiency, and who experience significant health disparities. The Koreans Invested in Making Caregivers Health Important (KIMCHI) project is a national, culturally tailored, bilingual (English/Korean) initiative focused on community‐based research dissemination to empower Korean Americans with insights into healthy cognitive aging and dementia caregiving.MethodFrom the community partnership with Somang Society and AARIN, a total of 211 participants, predominantly older adults (aged 24‐ 90 years; M = 69; SD = 12.1), mostly female (70.1%), and foreign‐born (96.2%) with limited English proficiency (61.6%), engaged in the project. Paired‐sample t‐tests were employed to assess mean (M) changes in participants’ knowledge, attitudes, and behaviors regarding Alzheimer’s disease and related dementias (ADRD) pre‐ and post‐test (before and after participating in the KIMCHI presentations).ResultFrom the community partnership with Somang Society and AARIN, a total of 211 participants, Significant improvements were observed in post‐test ADRD knowledge (M = 11.51), attitudes (M = 7.13), and behaviors (M = 8.88) compared to pre‐test scores (M = 10.34, M = 6.33, M = 8.11, respectively), t(210) = 1.17, p<.05, t(210) = 0.8, p<.05, and t(210) = 0.76, p<.05, respectively. Moreover, 93.8% of participants expressed satisfaction about KIMCHI, 89.4% learned something new about ADRD, 93.8% found the presentations culturally relevant and applicable, and 89% expressed interest to learn more about ADRD training.redominantly older adults (aged 24‐ 90 years; M = 69; SD = 12.1), mostly female (70.1%), and foreign‐born (96.2%) with limited English proficiency (61.6%), engaged in the project. Paired‐sample t‐tests were employed to assess mean (M) changes in participants’ knowledge, attitudes, and behaviors regarding Alzheimer’s disease and related dementias (ADRD) pre‐ and post‐test (before and after participating in the KIMCHI presentations).ConclusionFindings indicate that a community‐based research dissemination project (i.e., KIMCHI) can positively influence ADRD knowledge, attitudes, behaviors, and satisfaction among Korean Americans. Future studies should explore additional culturally tailored interventions, including real‐life case examples, to enhance health‐related outcomes and ensure greater representation in research studies for the Korean American community.
Delivery of incretin receptor agonists to the brain
Authors: Rhea Elizabeth 
Published: January 2025

AbstractBackgroundIncretin receptor agonists (IRAs) are synthetic peptides that have beneficial effects within the brain. We investigated IRA brain uptake following two routes of delivery: across the blood‐brain barrier (BBB) and following intranasal (IN) delivery.MethodRadiolabeled IRAs were delivered intravenously or intranasally into CD‐1 mice and uptake by or distribution throughout the brain was assessed. Additionally, distribution following IN delivery was assessed in APP/PS1 and wild‐type male and female mice.ResultWe identified many, but not all, IRAs are able to cross the BBB, and some have faster transport rates than others. We also identified IRAs can be delivered intranasally and that distribution does not majorly differ in a mouse model of Alzheimer’s disease (AD).ConclusionThe ability for IRAs to access the brain directly shows promise for AD therapeutics and will advance the design of future therapeutics. The IRAs that have a greater brain uptake should be taken into consideration for testing as AD as they would have the ability to act quickly and directly within the brain.
The use of a testimonial video featuring diverse ADRC participants to change research attitudes in the elderly community
Authors: Sewell Margaret , Neugroschl Judith A. , Umpierre Mari , Chin Shehan , Nunez Jade , Martinez Scarline , Fernandez Paulette , Inoa Vielka , Sano Mary 
Published: January 2025

AbstractBackgroundBlack, Latinx, and Asian community elders remain underrepresented in dementia research. This study explored whether a video created to promote diversity in research by featuring underrepresented ADRC participants would change attitudes about research generally (e.g., that it is safe, that it will find cures), as well as change attitudes about participation in specific types of research (e.g., involving imaging or blood draws).MethodWe created a testimonial format 4‐minute video featuring three ADRC participants (Chinese, Black, Hispanic). They discussed the importance of diversity in research and the vignettes illustrated participation in blood draws, imaging, and cognitive testing. Attitudes were measured by the 7‐item Research Attitude Questionnaire, before and after watching the video. Additionally, four Likert‐style questions were asked regarding the importance of diversity participation in research and willingness to participate in studies involving imaging, blood draws, or cognitive testing.ResultThe video was presented at 6 senior centers in NYC with 91 attendees (age 52‐90). 79% female, 59% Black, 39% Hispanic/Latino, and 8% other. Regarding education, 30% < high school, 35% high school graduates, and 35% ≥ some college. Spanish was the primary language for 44%. The RAQ item “Participating in medical research is generally safe” had the greatest pre/post video delta, with a 14% increase (62% to 76%) endorsing Agree/Strongly Agree. Other RAQ items that were relevant to the video vignettes (e.g., “We all have some responsibility to help others by volunteering in research” had a more modest (5% to 7%) increase in Agree/Strongly Agree. Concerning the additional questions, the greatest increases were seen concerning the need for diversity (66% to 81% Agree/Strongly Agree), and willingness to consider imaging studies (52% to 62%). The greatest trepidation was regarding participating in studies with blood draws (46% initially endorsed Agree/Strongly Agree) which only increased to 49% after the video.ConclusionWe demonstrate here how testimonial videos with peers may impact interest in research. Future work will explore how improved attitudes toward research may increase research enrollment.
Polytreatment in a very old patient. What’s better for safe prescribing?
Authors: Gareri Pietro , Gareri Ilaria , Covello Luciana Barbara , Ammendola Manuela 
Published: January 2025

AbstractBackgroundPrescription for inappropriate drugs can be dangerous to very old people, due to the increased risk of adverse drug reactions.Case reportWe report the consequences of inappropriate prescriptions in a 99‐year‐old woman. She had a clinical history of vascular dementia, diabetes, hypothyroidism, heart failure, osteoarthritis, chronic renal failure, and hypoacusia, and was admitted to our attention for asthenia and loss of appetite. She was hospitalized two months before for third‐degree atrioventricular block, and underwent pacemaker implantation. She had a moderate cognitive impairment, and functional dependence. Pharmacological history was collected by nurses through a video‐call and revealed that she was taking bisoprolol, furosemide, acetylsalicylic acid, L‐thyroxine, valsartan, gliclazide, folate, and digoxin (0.0625 mg/day). She had been suffering from nausea and loss of appetite for one month. On geriatric consultation, she had a heart frequency of 60 bpm. Vesicular murmur was normal, the abdomen was soft on palpation, and peripheral pulses were normal. Blood pressure was 130/80 mm Hg. Electrocardiography confirmed the presence of pacemaker rhythm. Echocardiography documented a mildly depressed ejection fraction of 45%. In the suspicion of digoxin intoxication, digoxin was soon interrupted. She started citicoline 1 g intramuscularly for the first ten days and then 1 g orally. Blood exams showed renal failure (ClCR 21.4 ml/min/m2), mild anemia, digoxin 2.7 ng/ml. A couple of days after digoxin interruption she started to feed again and felt much better.ConclusionsThe present case report shows the need for wise prescriptions in very old people. Drug‐induced symptoms are the second most frequent medical problem that geriatricians encounter and collaboration with nurses can help to optimize pharmacotherapy by deprescribing inappropriate agents.