bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptation and feasibility assessment of an intervention using mHealth and care navigation systems for people living with demencia and their caregivers in Peru
Authors: Flores Miriam Lucar , Cuba María Sofía , Canseco Francisco Diez , Moore Graham , Butler Christopher ,   Impact Dementia Study Group
Published: January 2025

AbstractBackgroundDementia is a complex health condition that poses challenges not only to people living with dementia (PLWD) but to their families, the health system and society as a whole. Even though there is still no cure for dementia, different interventions are showing substantial contribution. mHealth‐based assistive technology has shown the potential to provide efficient healthcare for PLWD and their caregivers in cognitive training, health and safety monitoring, educational support, and socialization. Also, Care Navigation Systems offers person‐centered, strengths‐based, and continuous support to PLWD and their caregivers across the illness trajectory and different settings through collaborative problem‐solving and coaching. The IMPACT project will propose innovative solutions for dementia using a collaborative and multidisciplinary approach. For that reason, one of its components aims to adapt an existing intervention to improve the quality of life for PLWD and wellbeing of their caregivers to develop a context‐fit intervention in Peru.MethodsTo adapt an existing intervention from a High‐Income Country to the Peruvian context: The original intervention, The Care Ecosystem, is a supportive care navigation system delivered over the phone and the internet by care team navigators who respond to PLWD and caregivers’ immediate needs, provide personalized support and education using care plan protocols.Phase 1: Will include the revision of the care protocols used by the original intervention to contrast their relevance and cultural fit with the experiences and needs of PLWD and ther caregivers from 4 regions of Peru (Lima, Tumbes, Iquitos, and Huancayo). This process will include a co‐design process with dementia experts, health providers and target population.Phase 2: Conduct a feasibility trial of the adapted intervention on 120 PLWD/caregiver dyas (60 control group, 60 intervention group) during a period of 9 months.ResultWe expect to identify core change mechanisims of the Care Ecosystem program and develop an adapted intervention that can be cosidered feasible to implement within the Peruvian context.ConclusionThe adaptation of the intervention will offer insights about the convenience of working with evidence‐ based interventions and the opportunities that can arise when they are carefully tailored to different context, norms and existing resources.
Characterization of plasma biomarkers of individuals with amyloid‐independent increased tau positron‐emission tomography uptake
Authors: Chan Tevy , Therriault Joseph , Wang Yi‐Ting , Aumont Etienne , Arias Jaime Fernandez , Macedo Arthur C. , Rahmouni Nesrine , Servaes Stijn , Trudel Lydia , Hosseini Seyyed Ali , Zheng Yansheng , Socualaya Kely Monica Quispialaya , Mathotaarachchi Sulantha , Stevenson Jenna , Jia Wan Lu , Matsudaira Takashi , Hall Brandon J , Lussier Firoza Z , Gauthier Serge , Triana‐Baltzer Gallen , Kolb Hartmuth C. , Karikari Thomas K , Ashton Nicholas J. , Benedet Andrea L. , Zetterberg Henrik , Blennow Kaj , Pascoal Tharick Ali , Rosa‐Neto Pedro 
Published: January 2025

AbstractBackgroundIncreased uptake on Tau positron‐emission tomography (PET) is sometimes observed in the absence of amyloid β accumulation. This A‐T+ PET profile might represent primary age‐related tauopathy (PART), an amyloid β‐independent 3R/4R tauopathy observed in aging brains. Although A‐T+ individuals have been shown to follow a different cognitive trajectory compared to A‐T‐ and A+T+ individuals, it remains unknown how they differ in terms of plasma biomarkers. Here, we aim to characterize the plasma biomarkers of A‐T+ individuals.MethodThis is a cross‐sectional study with data from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort. Participants were classified into four categories based on their amyloid β ([18F]AZD4694) and Tau ([18F]MK6240) PET status (A‐T‐, A+T‐, A+T+ and A‐T+). Plasma biomarkers phosphorylated tau (p‐tau)181, p‐tau217, p‐tau231, total tau (t‐tau), neurofilament light (NfL) and GFAP were compared using the Kruskal‐Wallis test with post hoc Benjamini‐Hochberg (BH) correction. Discriminative performance was assessed using the area under the receiver operating characteristic curve (AUROC).ResultAmong the total 468 participants, 64 (13.7%) had A‐T+ PET status. The A‐T+ PET participants had a mean age 66.9 years (SD: 12.8), with 62.5% women and 39.1% showing cognitive impairment. Plasma p‐tau181, p‐tau217, p‐tau231 and GFAP were significantly higher in A+T+ individuals compared to A‐T+ (all p < 0.001). On the other hand, plasma p‐tau181 and 217 were significantly different between A‐T‐ vs A‐T+ (p<0.05), but not p‐tau231 and plasma GFAP. No significant differences were found in t‐tau or NfL regarding A‐T‐. Plasma p‐tau217 and plasma GFAP had the highest discriminative accuracies for A‐T+ vs A+T+ (AUROC: 0.860 and 0.836 respectively).ConclusionOur data suggest that individuals with an A‐T+ PET status exhibit a different plasma biomarker profile than those with A+T+ and A‐T‐ status. Further characterization of fluid biomarkers could help identify this group of individuals and facilitate the differential diagnosis of adults with cognitive impairment. Furthermore, our results lend support to the use of plasma biomarkers for identifying amyloid β PET positivity.
Identifying anatomical subtypes of sporadic EOAD in LEADS via unsupervised clustering of MRI‐based regional atrophy patterns
Authors: McGinnis Scott M , Katsumi Yuta , Eckbo Ryan , Brickhouse Michael , Eloyan Ani , Nudelman Kelly N. , Foroud Tatiana M. , Dage Jeffrey L. , Carrillo Maria C. , Rabinovici Gil D. , Apostolova Liana G. , Touroutoglou Alexandra , Dickerson Bradford C. 
Published: January 2025

AbstractBackgroundNeurodegeneration in sporadic early‐onset Alzheimer disease (EOAD) is topographically heterogeneous, as suggested by variability in syndromic presentation. We performed an unsupervised clustering analysis of structural MRI data to identify anatomical subtypes of EOAD. We hypothesized that distinct clusters will be present but will: (1) share areas of overlap focused around posterior regions of our newly developed EOAD signature of cortical atrophy (Touroutoglou et al., 2023), including the posterior default mode (DMN) and frontoparietal control networks (FPN) of the cerebral cortex; and (2) show non‐overlapping topography inclusive of nodes of other networks including dorsal attention (DAN) and visual association (VIS) networks.MethodsWe analyzed structural MRI data from 183 individuals with EOAD and 88 cognitively unimpaired (CU) participants from the Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS). MRI data were processed using FreeSurfer v6.0 to estimate vertex‐wise cortical thickness, which was converted to W‐scores (i.e., Z‐scores relative to CU participants adjusted for age and sex). We then performed an agglomerative hierarchical clustering analysis on a between‐patients similarity matrix computed from rank‐ordered whole‐cortex W‐scores.ResultsAnalysis yielded 2 major clusters, with subordinate clustering failing to delineate additional unique topographies. One cluster (n=54) exhibited prominent atrophy in the anterior DMN (medial prefrontal cortex, anterior lateral temporal cortex) and rostral FPN (rostral middle and superior frontal gyri). The other cluster (n=129) showed prominent atrophy in the DAN (superior parietal lobule, caudal superior frontal gyrus, posterior temporal cortex) and VIS (posterior inferior temporal/occipital cortex, posterior parietal cortex). Both clusters showed atrophy in the posterior DMN (posterior cingulate cortex, precuneus, posterior inferior parietal lobule, mid lateral temporal cortex) and the FPN (middle and superior frontal gyri, anterior inferior parietal lobule, mid inferior temporal cortex). The clusters did not differ with respect to age, sex, education, APOE status, or clinical measures of disease severity.ConclusionsOur sample of sporadic EOAD patients comprised 2 principal anatomical subtypes, commonly overlapping with the posterior DMN and FPN that constitute the EOAD signature, one subtype uniquely overlapped with the anterior DMN/rostral FPN and the other with the DAN/VIS network. Anatomical differences between the subtypes likely correspond to aspects of phenotypic heterogeneity.
Errors on Cognitive Testing in Asymptomatic and Prodromal Familial Frontotemporal Dementia and their Prognostic Utility
Authors: Palacios Brandon R. , Sanderson‐Cimino Mark E. , Paolillo Emily W. , Casaletto Kaitlin B. , Taylor Jack C. , Wise Amy B. , Dhanam Sreya , Bui Mai Anh , Heuer Hilary W. , Forsberg Leah K. , Boeve Brad F. , Rosen Howard J. , Boxer Adam L. , Miller Bruce L. , Seeley William W. , Tempini Maria Luisa Gorno , Kramer Joel H. , Staffaroni Adam M. 
Published: January 2025

AbstractBackgroundThe earliest cognitive manifestations of asymptomatic and prodromal familial frontotemporal dementia (f‐FTD) mutation carriers are still being characterized. Patients with symptomatic FTD are known to be error prone, particularly on tasks of executive function, but little is known about the frequency or predictive utility of these errors in the earliest stages of f‐FTD. The current study compared error rates on executive functioning tasks in controls and asymptomatic and prodromal mutation carriers and investigated whether errors predict worsening clinical status as follow up.MethodThis study included 90 participants (mean age = 48.57, SD = 13.30; 51.1% female; 86.67% white) with pathogenic FTD mutations (C9orf72, n = 45; GRN, n = 30; or MAPT, n = 15) who were asymptomatic or prodromal (Clinical Dementia Rating plus FTLD; CDR®+NACC‐FTLD ≤ 0.5). Propensity score matching identified (CDR®+NACC‐FTLD = 0) who did not carry pathogenic mutation but were matched on age, education, and sex. Regressions were used to compare controls and mutation carriers on error scores (rule violations and/or repetitions) from three executive functioning tasks: design fluency, lexical fluency, and Stroop inhibition. Mutation carriers with longitudinal data within 1.5 years were binarized as stable (n = 35) or progressors (n = 13) based on whether their CDR®+NACC‐FTLD sum of boxes score was worse at follow up (mean follow up = 1.07 years). Regressions were fit to evaluate the relationship between baseline error scores and group (i.e., stable vs. progressor).ResultMutation carriers committed significantly more errors than controls on the Stroop task (β = 0.67, p = 0.03) and lexical fluency (repetitions: β = 0.27, p = 0.02). The groups did not significantly differ in errors on the remaining tasks. A greater number of Stroop errors predicted mutation carriers who progressed at follow up (β = 1.04, p<0.001). When introducing the primary outcome from each task as a covariate (e.g., correct responses), the fluency task (repetitions: β = 0.10, p = 0.03) and Stroop task (errors: β = 0.82, p<0.001) were significantly associated with progression.ConclusionErrors on executive tasks may be early cognitive features in familial FTD. Importantly, errors were uniquely predictive above and beyond total scores. Research in larger samples will enable investigations of genetic differences in error rates.
Creating Universal Tau PET Scale (Uniτ) Parametric Images – The HEAD Study
Authors: Povala Guilherme , Bauer‐Negrini Guilherme , Bellaver Bruna , Lussier Firoza Z , Amaral Livia , Ferreira Pamela C.L. , Finn Quentin , Zatt Bruno , Tudorascu Dana , Jagust William J. , Klunk William E , Lowe Val J. , soleimani‐meigooni David N. , Oh Hwamee , Pascual Belen , Gordon Brian A. , Rosa‐Neto Pedro , Baker Suzanne L. , Pascoal Tharick Ali 
Published: January 2025

AbstractBackgroundThe HEAD study focuses on collecting an extensive dataset from various tau‐PET tracers, aiming to establish robust anchor values, which are essential for harmonizing tau‐PET measurements. Here, we aim to showcase the capability of converting 3D tau‐PET images into a common scale using the Universal Tau‐PET Scale, Uniτ (tau), and to use these 3D images to subsequently obtain ROIs as needed.MethodsWe assessed 185 individuals across the aging and AD spectrum from the HEAD study, with [18F]Flortaucipir and [18F]MK‐6240 tau‐PET tracers. Tau‐PET SUVR images were standardized to a common 8mm FWHM, using the inferior cerebellar gray matter as the reference region. We generated Uniτ Tau‐PET 3D images using a single formula based on Meta‐temporal parameters in two steps: first, within‐tracer anchoring based on young (<25 years) and cognitively impaired individuals; second, between‐tracer anchoring using a piecewise transformation from [18F]Flortaucipir to [18F]MK‐6240, with smoothing at the piecewise inflection point. Subsequently, we extracted mean Uniτ values from these 3D images for key ROIs, including meta‐temporal, mesial, temporo‐parietal, frontal, and Braak stages III‐VI. Finally, we correlated Uniτ values across ROIs between the two tracers to evaluate the accuracy of estimates from the voxel‐wise transformation.ResultsThe original SUVR images present large differences between the two tau‐PET tracers (Figure 1). However, upon applying the Uniτ piecewise transformation with smoothing to all brain voxels, we were able to reasonably harmonize these images to the Uniτ scale, substantially reducing visual variability. Notably, the mean Uniτ values for the ROIs extracted from these harmonized 3D tau‐PET brain images demonstrated a high level of association between the two tracers (Figure 2). Furthermore, estimates generated from ROIs or extracted from our 3D parametric Uniτ model yielded identical estimates (Figure 3).ConclusionThe strong associations between tracers after directly harmonizing 3D images to Uniτ scale using the piecewise transformation with smoothing, underscore the effectiveness of the proposed method. This approach provides a reliable and standardized way to compare tau‐PET data across different tracers. Our results indicate the feasibility of harmonizing 3D tau‐PET images without relying on pre‐established ROIs, overcoming the limitation of restricting the analysis to only few brain regions.
Can a picture description differentiate the nonfluent/agrammatic and logopenic variants of primary progressive aphasia?: Evidence from Catalan‐Spanish bilinguals
Authors: Pugalenthi Lokesha , Montagut Núria , Marques‐Kiderle Sonia Karin , Rodriguez Camille Wagner , Iyer Ami , Chaires Jan Christian Holst , Motta Whendy Avila , Filella‐Merce Júlia , Zhu Nuole , Rubio‐Guerra Sara , Illán‐Gala Ignacio , Borrego‐Écija Sergi , Lladó Albert , Fortea Juan , Lleo Alberto , Sanchez‐Valle Raquel , Santos‐Santos Miguel A , Grasso Stephanie M 
Published: January 2025

AbstractBackgroundPrimary progressive aphasia (PPA) is a language‐based dementia linked with underlying Alzheimer’s disease (AD) or frontotemporal dementia. Clinicians often report difficulty differentiating between the logopenic (lv) and nonfluent/agrammatic (nfv) subtypes, as both variants present with disruptions to “fluency” yet for different underlying reasons. In English, acoustic and linguistic markers from connected speech samples have shown promise in machine learning (ML)‐based differentiation of nfv from lv. To our knowledge, this approach has not been evaluated in other languages nor in the context of bilingualism.MethodTwenty‐four Spanish‐Catalan bilingual patients (lv=15, nfv=9) were asked to describe a picture (WAB Picnic Scene) in both their dominant and non‐dominant language. From the participant’s recorded response, 10 acoustic features were derived with PRAAT and 15 linguistic features were derived with the Natural Language Processing (NLP) tools SpaCy and CLAN. A similarity score between the image and patient’s transcription was derived with the Vision‐Language model CLIP. The acoustic features, linguistic features, and CLIP scores, were separately fed into ML classification algorithms for differentiating nfv from lv in participants’ dominant and non‐dominant samples.ResultThe acoustic‐based classifiers achieved classification accuracy (F1 score) of 59% in the dominant and 86% in the non‐dominant language, respectively. The linguistic‐based classifiers achieved F1 scores of 73% in the dominant and 77% in the non‐dominant language, respectively. The CLIP‐based classifier achieved F1 scores of 82% in the dominant and 82% in the nondominant language, respectively. The acoustic and linguistic classifier performed 25% (p=0.077) and 4% (p=0.18) better given only non‐dominant samples compared to only dominant samples.ConclusionTaking advantage of recent advances in multilingual NLP, we achieved promising and effective differentiation of nfv from lv for Spanish‐Catalan bilingual patients using a nearly automated pipeline. Interestingly, our acoustic and linguistic‐based classifiers performed better given responses from a patient’s non‐dominant language, and the acoustic feature set was more accurate in discriminating between nfv and lv compared to the linguistic model. Future directions include examining patterns in a larger sample size and comparison of performance on different types of connected speech tasks.
Unraveling the earliest phases of vascular cognitive impairment and dementia by establishing a large USA CADASIL Consortium
Authors: Paulsen Jane S , Jayadev Suman , Geschwind Michael D , Biller Jose , Elliott Jamie L , Gutierrez Jose , Seshadri Sudha , Majersik Jennifer J , Orjuela Karen D , Liebeskind David S , Lutsep Helmi L , Hajjar Ihab , Bockholt Henry J , Salloway Stephen 
Published: January 2025

AbstractBackgroundCADASIL, linked to NOTCH3 variants, is a primary monogenic cause of vascular dementia, leading to vascular cognitive impairment and dementia (VCID) observable in early stages. The NIH‐funded USA CADASIL Consortium aims to explore CADASIL's onset and progression in the USA, crucial due to varying phenotype‐genotype associations globally. The consortium will identify biological and clinical markers across the disease spectrum, contributing to clinical trial preparations. It will focus on clinical outcome assessments, biofluids and neuroimaging for biomarker identification, and disease modeling for subtypes, informing future clinical trial designs. The study will also examine genetic, health, and lifestyle factors impacting CADASIL outcomes.MethodThe methodology involves establishing a longitudinal cohort of 400 NOTCH3 carriers and 100 non‐carrier family members across 12 USA sites (www.cadasil‐consortium.org). Participants undergo annual clinical, cognitive assessments, advanced neuroimaging, and blood‐based phenotyping, targeting optimal biomarkers to determine minimal sample sizes for clinical trials.ResultsDespite COVID‐19 challenges, over 200 participants are enrolled, many already in longitudinal assessments. The Symptomatic (SYM) group, individuals with mild to moderate disability (Rankin Scale scores 1‐3), displays different cognitive and functional patterns from the Non‐Symptomatic (NSYM) group. The SYM group, mostly females (63) and Caucasians (101), has lower MOCA scores (average 25.2 vs. NSYM's 26.8) and SDMT averages (43.7 vs. NSYM's 51.4), indicating reduced cognitive function and processing speed. Functionally, SYM's average WHODAS score is 9.1, higher than NSYM's 3.1. The SYM group, averaging 53 years, is older than NSYM's 47.7 years, highlighting age's role in symptom severity.ConclusionThe upcoming AAIC presentation will provide a comprehensive overview of the US CADASIL cohort, contrasting it with international data. Efforts are ongoing to establish a worldwide CADASIL Study Group to advance knowledge and treatment for vascular cognitive impairment and dementias.
Evaluating quality of routine vs. tape‐transfer histology sections for 3D reconstruction of paraffin embedded brain tissue and correlation with 7T MRI
Authors: Ho William Hai Dang , Wang Yixin , Taghavi Hossein Moein , DiGiacomo Phillip , Nirschl Jeffrey , Chu Pauline , Georgiadis Marios , Zeineh Michael 
Published: January 2025

AbstractBackgroundSpecimen analysis is crucial for identifying imaging and neuropathological signatures. Histology is the gold‐standard, but sample preparation and sectioning induce tissue deformations which hinder quantitative analysis or registration of histology to 3D MRI providing a challenge to the development of MRI biomarkers. Overall, we aim to develop a workflow to correlate histology with high‐resolution MRI at a microscopic level (Figure 1), Here, we evaluate a critical step in this process ‐ the section quality from tissue mounting techniques, comparing: A) traditional water bath (Figure 1F), and B) tape transfer (Figure 1G), for the purpose of image segmentation and correlation with high‐resolution MRI.MethodsFixed human brain specimens were MRI scanned, dehydrated with graded ethanol, xylene‐cleared, and paraffin‐embedded. Before sectioning, the specimen surface was captured by a brightfield microscope (Figure 2, top left, “Blockface image”). Embedded tissue was sectioned at 7 μm using a Leica 100 microtome and mounted on slides using either A) traditional water bath capture onto standard charged slides (Figure 1F), or B) tape‐transfer capture onto adhesive‐coated slides (Alphametrix) (Figure 1G). Slides were hematoxylin and eosin stained followed by imaging using the same microscope settings as the blockface image, and total stained tissue area was calculated. Area of expansion was determined by change from the blockface image (Figure 2, 3rd column). Internal tissue distortions were calculated by subtracting the tissue section mask from the original blockface mask (Figure 2, 2nd column).ResultsThe tissue area measurements show that traditional capture resulted in average expansion of 16.7% relative to the blockface image, whereas tape transfer had 0.9% expansion (Figure 3). Both methods had similar amounts of average total tissue damage (approximately 3%), representing regions with tissue in the blockface image where no tissue was present on the slide. Subjectively, tissue distortion was concentrated at the periphery on traditional capture, whereas there were linear striations within internal structures on tape transfer (red arrows). Tissue yield for tape transfer was subjectively near 100% compared to traditional at approximately 60‐70%.ConclusionTape transfer had a more consistent yield and better edge preservation with blockface image but had more internal microfractures