bluuebunny/crossref_metadata_2025_split huggingface dataset:
Federated BrainAge estimation from MRI: a proof of concept
Authors: Mateus Pedro , Yu Jing , Garst Swier J.F. , Harms Alexander G.J. , Cats Davy , Delgado Inigo Bermejo , Roshchupkin Gennady V. , Reinders Marcel JT , Slagboom Eline , Mei Haillang , Bron Esther E 
Published: December 2023

AbstractBackgroundThe gap between chronological and biological brain‐age, represented by MRI features, associates with dementia risk (Wang et. al., He et. al.). Age‐scores are predicted, however, using deep learning models, which require large amounts of MRI data. This poses a challenge, as patient brain MRI data is highly privacy‐sensitive and legal barriers often impede the sharing or transferring of data. Federated learning provides a potential solution by enabling training a global model on distributed data, allowing biobanks to keep data local while creating a shared model. In this study, we assess whether a federated set‐up is feasible for brain‐age estimation.MethodWe set up a federated learning framework across three biobanks (Fig. 2) to train a BrainAge model (Wang et. al). Data of healthy individuals from the ADNI dataset was randomly split across the three biobanks (N = 221, 219, 217). MRI images were pre‐processed into gray matter density maps (Good et. al.). The model was iteratively trained using federated averaging (McMahan et. al.) on data at two biobanks (70/30 training/validation split), and tested at the remaining biobank. We trained the model for ten rounds, and optimized for the number of epochs, learning rate, and learning decay hyperparameters. These results were compared to a centrally trained model, where the training samples were pooled together. Additionally, we applied the trained model to individuals with Mild Cognitive Impairment and Alzheimer’s Disease and performed a survival analysis. We assessed performance using Mean Absolute Error (MAE).ResultFederated learning (MAE = 4.02) achieves similar test performance as central learning (MAE = 3.94) (Table 1). The model yielded an MAE of 4.89 for MCI and 5.45 for AD patients; this increase may be explained by their neurodegeneration. We also see a statistically different survival curve for developing AD in individuals with a brain‐age‐gap (Fig. 1), displaying an ‘older’ profile for their chronological age. This might indicate higher risk of developing AD, in line with previous results (Wang et. al.).ConclusionResults show federated learning has the potential to address the challenge of data accessibility for machine learning in complex and data hungry research, including dementia.
Determination of genetic, serological and cognitive markers in a cohort of elderly people in Panama
Authors: Britton Gabrielle B , Villarreal Alcibiades E , Oviedo Diana C , Carreira Maria B , Rangel Giselle 
Published: December 2023

AbstractBackgroundThe Panamanian Aging‐Focused Research Initiative (PARI) aims to study age‐associated neurodegenerative diseases in older people in Panama, such as determining genetic and serological biomarkers identified as risk factors for mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Apoliprotein E (ApoE) is involved in lipoprotein metabolism and is the main carrier of cholesterol to the brain. The objective is to present the main findings on the allelic distribution of ApoE and its association with markers of inflammation and cognition in a cohort of elderly people in PanamaMethodPARI has enrolled more than 800 participants and has two recruitment waves. Informed consent was applied to all the participants, demographic data was collected, about their medical history and functional status, neuropsychological evaluations were carried out and blood samples were taken to determine the allelic frequency of the protein Apoliprotein E gene by means of PCR and various serological biomarkers. The clinical wave was made up of individuals ≥ 65 years of age who attended the CSS complex’s outpatient geriatrics, while the community wave consisted of individuals ≥ 60 years of age recruited in Panama City.ResultThe clinical wave presents greater age and cases of depression, and less education, body mass index and global cognition compared to the community wave. The presence of the ApoE2 isoform in both waves combined was 9.5%, while for ApoE 4 it was 27.4%. In the clinical wave, ApoE4 turned out to be a significant predictor with an Odds ratio of 5 (95% CI 2.11 – 12.52) for MCI. For both waves, global cognitive impairment is greater in people who have at least 1 copy of ApoE4, as well as worse ApoE 4‐associated cognitive function in female participants compared to male participants. Differences in the average levels of I‐309, IL‐18 and pancreatic polypeptide (PPY) between the groups with or without the presence of ApoE4 are significant when analyzing the cohort as a whole.ConclusionWe conclude that the determination of the ApoE allele frequency, specifically the identification of ApoE4, can be considered viable as a genetic biomarker to be applied to the evaluations of cognitive impairment.
Creating a measure of community level dementia‐friendliness in faith communities
Authors: Moore Miranda , Gunn Grayson , Chester Mia , Chan Kiera , Epps Fayron , Bender Alexis Anne 
Published: December 2023

AbstractBackgroundAs the prevalence of dementia rises, modifying built and social environments of persons living with dementia (PLWD) becomes increasingly essential. Although there is a call to rigorously evaluate dementia‐friendly community initiatives, no known comprehensive evaluation tools exist to assess small communities such as churches and community centers. Therefore, we developed a person‐centered Dementia‐Friendly Community Assessment tool.MethodsThis tool consists of new and validated scales to assess the level of dementia‐friendliness among churches enrolled in a dementia‐friendly congregation program based in African American communities. An initial draft of the theory‐informed survey instrument was given to stakeholder groups (church leaders, care partners, PLWD, and the Alter advisory board) with the goal of gathering feedback on domains included in the tool, as well as general wording and appropriateness. After focus group recordings were transcribed, the team made revisions and administered the survey to 10 stakeholders (church leaders, care partners, PLWD, and lay congregants) to gather feedback on the digital version of the survey, proposed changes to the tool, and thoughts on implementation aids and barriers.ResultsOverall, the tool was well received by participants, with most participants indicating the tool’s resulting scores would be useful for their community. Additionally, the tool’s content prompted many to share personal experiences of living with dementia or caregiving for PLWD, indicating that future use of this tool may provide a starting point to address stigma.ConclusionNext steps include piloting the survey with broad church membership, and our aim is to enable programs to quantify their dementia‐friendly community initiatives.
Macro and microarchitectural features of sleep in Alzheimer’s dementia and mild cognitive impairment in a large clinical cohort
Authors: Pathmanathan Jay , Zheng Kevin , Little David , Laberinto Kim , Sadeghi Kolia , Tjipterto Dhany , Arslan Alexander , Patino Angelica , Kleinschmidt David , Alday Phillip , Puryear Corey , Westover M Brandon , Donoghue Jacob 
Published: December 2023

AbstractBackgroundRecent work has characterized polysomnographic changes in Alzheimer’s Dementia (AD) that correlate with disease severity and precede clinical diagnosis. However, relatively small sample sizes and a paucity of studies examining sleep microarchitecture have been limitations. In this study we examined sleep micro‐ and microarchitectural features in large cohorts of patients with AD and mild cognitive impairment (MCI).MethodUsing a database of over 15,000 clinical PSGs with associated clinical metadata, 125 and 173 subjects were identified with mild AD and MCI, respectively. 260 age and sex matched subjects without neurological disease were identified as healthy controls (HC). Sleep staging results were based on AASM criteria, and micro‐architectural features were assessed using an algorithm trained to predict wake (1) or sleep (0) using spectral data from 3 seconds of EEG from a unique healthy adult cohort (Wake EEG Similarity Index, WESI).ResultSleep fragmentation was apparent in both the MCI and AD cohorts (relative to healthy controls), with AD subjects demonstrating significantly more severe PSG disturbances. Healthy controls demonstrated 400 minutes of total sleep time, in contrast to 374 minutes for MCI subjects and 362 minutes for healthy controls. Healthy subjects demonstrated 33 minutes of wake after sleep onset (WASO), compared to 60 and 67 minutes for MCI and AD subjects, respectively. As has been previously reported in smaller cohorts, wakeful bouts and N1 durations were significantly prolonged for AD and (to a lesser extent) MCI subjects, while N2, N3, and REM durations were reduced (with a pronounced reduction in AD N3 percentage). Sleep microarchitectural features assessed using WESI demonstrated that AD and MCI subjects had markedly higher relative wakefulness in all sleep stages except for N3, which showed the same sleep depth as HC.ConclusionWe confirm increased sleep fragmentation and loss of deeper sleep stages, correlating to disease severity. Spectral features of all sleep stages EXCEPT N3 appear more wakeful in AD and MCI subjects ‐ suggesting microarousals or impaired sleep maintenance contribute to sleep pathology. While N3 duration was markedly reduced, depth of sleep was comparable between populations. PSG findings offer promise as early diagnostic and therapeutic targets.
Immunohistochemical detection of amyloid beta and tau proteins in the Monodelphis domestica brain
Authors: Perez Ismael , Le Truc , Barnes Brooklyn , Alaniz Esperanza I , VandeBerg John L , Gil Mario 
Published: December 2023

AbstractBackgroundAnimal models have been important for the understanding of Alzheimer’s disease and related dementias (ADRD). However, most of the research involving these diseases has been with rodents. Researchers have raised awareness about the need for alternative and feasible animal models in order to understand these types of diseases. To increase the knowledge of alternative animal models for the study of ADRD, the current study proposed the use of the Monodelphis domestica animal model to detect the presence of amyloid beta and tau proteins.MethodFixed brains from young adult Monodelphis were used in the present study. A standard immunohistochemistry (ABC‐DAB) staining protocol was used to detect amyloid beta and tau proteins. To detect the presence of amyloid beta, a 1:100 anti‐amyloid primary dilution was used; for tau protein, a 1:1000 anti‐tau primary dilution was utilized. Only the hippocampal region was selected for description and quantification. An Axioscan Z.1 microscope system was utilized to capture images, and image analysis was performed using ImageJ software.ResultThe area of the hippocampus of the first coronal section was 30262602.934 um2. The results from an amyloid‐beta dilution of 1:100 detected amyloid beta in a number of neurons in the hippocampus. Amyloid beta was also detected in the hippocampus of another brain section (total area: 7048008 um2). The negative control tissue did not reveal positive signal in neurons in the hippocampal area, suggesting low levels of non‐specific binding. The results for tau antibody are pending.ConclusionOur study revealed that in Monodelphis domestica animal model brain tissue, a 1:100 dilution resulted in identification of positive amyloid beta protein. However, no abnormal amyloid beta plaque formation was found with this animal model. A possible explanation was that a natural, non‐induced animal model was used in the study.
Ultra High‐Plex Spatial Proteogenomic Investigation of Giant Cell Glioblastoma Multiforme Immune Infiltrates Reveals Distinct Protein and RNA Expression Profiles
Authors: Bonnett Shilah , Rosenbloom Alyssa , Ong Giang , Conner Mark , Newhouse Daniel , New Felicia , Sato Hiromi , Phan Chi , Ilcisin Saskia , Lyssand John , Geiss Gary , Beechem Joseph M. 
Published: December 2023

AbstractBackgroundThe advancement of spatially resolved, multiplex proteomic and transcriptomic technologies has revolutionized and redefined the approaches to complex biological questions pertaining to tissue heterogeneity, tumor microenvironments, cellular interactions, cellular diversity, and therapeutic response. Most spatial technologies yield single analyte proteomic or transcriptomic datasets from separate formalin‐fixed paraffin‐embedded (FFPE) tissues sections. Multiple studies have demonstrated a poor correlation between RNA expression and protein abundance owing to transcriptional and translational regulation, target turnover, and post‐translational protein modifications. Therefore, a workflow that accurately measures RNA and protein simultaneously within a single tissue section with distinct spatial context is critical to a more complete biological understanding of cellular interactions and activities. Such multimodal omic datasets of protein and DNA or RNA have been termed “spatial proteogenomics”.MethodHere we present a novel spatial proteogenomic (SPG) assay on the GeoMx® Digital Spatial Profiler platform with NGS readout that enables ultra high‐plex digital quantitation of proteins (147‐plex) and RNA (whole transcriptome,>18,000‐plex) from a single FFPE sample. We demonstrated high concordance, R>0.85, and minor change in sensitivity (<11%) between the SPG assay and the single analyte GeoMx Whole Transcriptome Atlas and GeoMx NGS Protein assays. We used the SPG assay to interrogate 23 different glioblastoma multiforme samples across 4 pathologies.ResultsWe observed clustering of both RNA and protein based on cancer pathology and anatomic location. The in‐depth investigation of giant cell glioblastoma multiforme (gcGBM) revealed distinct protein and RNA expression profiles compared to that of glioblastoma multiforme (GBM). Spatial proteogenomics allowed simultaneous interrogation of critical protein post‐translational modifications alongside whole transcriptomic profiles within the same distinct cellular neighborhoods.ConclusionsWithin our dataset, we observed >2‐fold higher protein expression levels of phospho‐GSK3β (Ser9) in gcGBM compared to GBM. Inactivation of GSK3β through phosphorylation has been shown to enhance proliferation of GBM cells. We also observed differential protein expression phosphorylated Tau variants. Phospho‐Thr231 Tau was >2‐fold higher in GBM compared to gcGBM. Associated with neurodegenerative Alzheimer’s disease, changes in Tau expression and phosphorylation have also been observed in glioblastoma. Our study exemplifies the utility of the SPG assay in expanding our understanding of glioblastoma multiforme molecular pathology.
Interaction of Amyloid Beta with Mitochondrial RNAs
Authors: Yurttaş Zuhal , Çamoğlu Tugay , Dursun Erdinc , Gezen‐Ak Duygu 
Published: December 2023

AbstractBackgroundDespite mitochondrial RNA’s (mt‐RNA) polycistronic origin, research has shown that a number of post‐transcriptional mechanisms can control transcription. The amyloidogenic proteins such as prion and aSyn are known to bind RNA. However, the main peptide responsible for the pathogenesis of Alzheimer’s disease (AD), amyloid beta 1‐42 (Aβ1‐42), is not known to interact with RNA. It is well known that Aβ1‐42 is an alpha‐helix in monomer form. However, by attaching zinc, Aβ1‐42 achieves sheet folding. Aβ’s new conformation resembles zinc finger transcription factors. Furthermore, using randomly generated RNA molecules, it has been shown that the Aβ peptide domain that interacts with metals may also interact with RNA. As a result, Aβ has the potential to interact with mtRNAs, and this possible interaction may be linked to malfunctioning mitochondria in AD. Aβ1‐42, on the other hand, may affect the LRP130 protein, which is implicated in the mtRNA post‐transcriptional processes. In the current study, we seek to determine whether Aβ1‐42 may interact with mtRNA and whether Aβ1‐42 treatment affects LRP130’s ability to bind to mtRNA.MethodIn our study, the possible interaction of Aβ1‐42‐mtRNA and whether LRP130’s binding capacity to mtRNA was changed due to 0,1µM of Aβ1‐42 peptide treatment was investigated by RNA immunoprecipitation (RNA‐IP) and qRT‐PCR in differentiated LUHMES cells.ResultAβ – RNA IP experiment revealed that certain specific mtRNA binding signals were detected in untreated cells, albeit at a low level. Compared to untreated cells, the administration of Aβ1‐42 dramatically reduced LRP130’s affinity for mtRNAs.ConclusionAβ1‐42, the major peptide of AD, may be able to influence post‐transcriptional mitochondrial expression. When we consider the significance of RNA‐protein interactions in neurodegenerative processes, we determine that our research can offer a current strategy for AD biomarker research and the generation of therapeutic RNA aptamers. This study is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) (Project ID:219Z179).
miRNAs peripheral biomarkers for early diagnosis of AD in Latinamerican population
Authors: Orellana Paulina , Caviedes Ariel , Gonzalez Carolina , Salcidua Stefanny , Henriquez Fernando , Cabello Victoria , Lillo Patricia , Villagra Roque , Cerda Mauricio , Zitko Pedro , Thumala Daniela , Gonzalez Christian , Ibanez Agustin , de la Cruz Rolando , Slachevsky Andrea , Duran‐Aniotz Claudia 
Published: December 2023

AbstractBackgroundTimely diagnosis of Alzheimer’s disease (AD) is a critical first step in clinical care treatment. However, the availability of diagnostic tools for these conditions is either unavailable or unaffordable, especially in Latin American and the Caribbean (LAC) countries. In this scenario, microRNAs (miRNA) have recently emerged as promising cost‐effective and noninvasive biomarkers since they can be readily detected in different biofluids such as plasma bound to protein or inside exosomes. Our aim is to identify new blood biomarkers to calculate the risk to develop AD in the early stages using machine learning based on exosomal miRNAs detection and different cognitive domains.MethodmiRNAs were extracted from plasma circulating exosomes samples of Subjective Cognitive Complaint subjects belonging to the GERO cohort in two different times (T1 = baseline and T2 = 18 months, n = 50). miRNAs were sequencing to identify the expression levels. Dysregulated miRNAs were analyzed and correlated with neuropsychological evaluations to create machine learning algorithms. miRNAs obtained from algorithms were validated in a new population of subjects at both stages (T1 and T2, n = 50), using qRT‐PCR and correlation analysis with neuropsychological tests.ResultFor algorithm development, we classified subjects into stationary and progressive impairment. Algorithms were trained using the sequenced miRNAs, neuropsychological tests and neuroimaging. As possible predictors of progression of cognitive impairment, the best performing algorithm was Random forest using only miRNAs data. In a new group of subjects, three miRNAs selected by the algorithm and four miRNAs obtained from the literature were validated and the ROC curves were constructed. The combination of these miRNAs (algorithm and literature miRNAs), were the best predictor of the progression of cognitive impairment.ConclusionThis study could be used in the initial phases of the diagnostic process of AD because it is minimally invasive, low cost and accessible to a large number of patients in Latin American and the Caribbean (LAC) countries.
Role of Social, Clinical, and Contextual Factors in Explaining MRI Markers of White Matter Injury and Change in Objectively‐Assessed Cognition by Race/Ethnicity: The Multi‐Ethnic Study of Atherosclerosis
Authors: Jimenez Marcia Pescador 
Published: December 2023

AbstractBackgroundRacial and ethnic disparities in Alzheimer’s disease and related dementias (ADRD) are well documented. The mechanisms through which race and ethnicity as markers of systemic racism are associated with brain health are lacking.MethodWe used data from the Multi‐Ethnic Study of Atherosclerosis (MESA) and a causal mediation framework to determine whether the association between race/ethnicity (measured in Exam 1, 2000‐2002) and brain health is mediated through pathways represented by social (education level, health insurance (yes/no)), clinical (hypertension, diabetes, and depression symptoms), and contextual factors (neighborhood socioeconomic status) measured in Exam 1. Brain health was measured by 3T magnetic resonance imaging (MRI, N = 966) and change in cognitive scores (N = 2002). Participants completed the Cognitive Abilities Screening Instrument (CASI), Digit Symbol Coding (DSC), and Digit Span (DS) cognitive tests in Exams 5 (2010‐2012) and 6 (2016‐2018). Participants underwent MRI in 2018‐2019 to assess white matter (WM) injury assessed by WM hyperintensity volume (WMHV) and fractional anisotropy (FA). All models were adjusted for age, gender, education, marital status, income, and for WMHV models, total intracranial volume.ResultMean (SD) age at baseline was 58 (9) years, 29% participants self‐reported Black, 17% Hispanic, 11% Chinese and 43% White. Black and Hispanic participants experienced a larger decrease in CASI (‐3.3 points (95%CI: ‐4.1, ‐2.5); ‐4.7 (‐5.7, ‐3.7) respectively), DSC (‐2.2 (‐3.6,‐0.8); ‐5.3 (‐7.0,‐3.6)), and DS scores (‐0.4 (‐0.7,‐0.2); ‐1.1 (‐1.4,‐0.8)) from Exam5 to 6 than White participants, after accounting for covariates and baseline cognitive score. Black participants had greater WMHV (21% (1%, 50%)), and lower FA (‐.006 (‐0.01,‐0.002)) than White participants. We observed that the association between race/ethnicity as markers of racism and CASI change was mediated by education (proportion mediated 13% (1%, 21%)), and that the association with DSC change was mediated by health insurance (proportion mediated 9% (4%, 24%)) but not by any other social, clinical or contextual factor. The association between race/ethnicity and WM injury markers and change in DS was not mediated by social, clinical nor contextual factors.ConclusionEducation and health insurance appear as factors that may partially explain the association between race/ethnicity and cognitive decline.
Estimates of diagnosed dementia prevalence and incidence among diverse beneficiaries in Traditional Medicare and Medicare Advantage
Authors: Haye Sidra , Thunell Johanna , Joyce Geoffrey , Ferido Patricia , Tysinger Bryan , Jacobson Mireille , Zissimopoulos Julie M 
Published: December 2023

AbstractBackgroundApproximately half of Medicare beneficiaries are enrolled in Medicare Advantage (MA) ‐ a private plan alternative to Traditional Medicare (TM). Yet little is known about diagnosed dementia rates among Medicare Advantage enrollees, limiting population estimates.Methods100% claims of Medicare beneficiaries using Encounter data for MA and claims for TM were used to quantify diagnosed dementia prevalence and incidence rates in MA, compare rates to TM, and provide estimates for the entire Medicare population and for different racial/ethnic populations.ResultDementia incidence and prevalence among MA beneficiaries was 2.54% (95%CI 2.53‐2.55) and 7.04% (95%CI 7.03‐7.06). Comparison to TM adjusted for sociodemographic and health differences among beneficiaries in MA and TM; the prevalence of diagnosed dementia among beneficiaries in MA was lower (7.1%; 95%CI 7.12‐7.13) than in TM (8.7%; 95%CI 8.71‐8.72). Diagnosed dementia incidence rate was also lower in MA (2.50%; 95%CI 2.50‐2.50) compared to TM (2.99%; 95%CI 2.99‐2.99). There were lower rates in MA compared to TM for men and women and White, Black, Hispanic, Asian, American Indian/Alaska Native persons. Diagnosed dementia prevalence and incidence for the entire Medicare population was 7.9% (95%CI: 7.91‐7.93) and 2.8% (95%CI: 2.77‐2.78).ConclusionLower diagnosed dementia rates in MA compared to TM may exacerbate racial/ethnic disparities in diagnosed dementia. Rates tracked over time will provide understanding of impact on dementia diagnosis of 2020 MA risk adjustment for dementia.