bluuebunny/crossref_metadata_2025_split huggingface dataset:
Racial/ethnic disparities in new and persistent cholinesterase inhibitors treatment in Alzheimer’s disease
Authors: Zhu Carolyn W , Neugroschl Judith A , Sano Mary 
Published: December 2021

AbstractBackgroundRacial/ethnic minorities are less likely to use anti‐dementia medications and less likely to participate in dementia studies. It is unclear if treatment disparities remain in those who participate in longitudinal research at Alzheimer’s Disease Centers (ADCs).MethodsData were drawn from the National Alzheimer's Coordinating Center Uniform Data Set (9/2005‐11/2019). Baseline inclusion criteria: ≥65yo, etiology of AD, and CDR<3. Sample included Non‐Hispanic white, Non‐Hispanic Black, or Hispanic participants with ≥1 follow‐up. Main outcomes: (1) any new Acetylcholinesterase (AChEI) treatment during follow‐up, (2) persistence of treatment measured by proportion of follow‐up visits reporting AChEI use, categorized into: intermittent (<50% follow‐ups), persistent (≥50% follow‐ups), and always treated. Differences by race/ethnicity were estimated using logistic or ordered logistic regression models, controlling for participant clinical and demographic variables.ResultsSample included 5,866 white, 918 Black, and 608 Hispanic participants. Compare to the treated, those who were untreated at baseline were older, more likely to be female, lived alone, more likely to have AD (vs. MCI), with better clinical profiles (better CDR, FAQ, NPIQ, MMSE, lower rate of hypertension and diabetes). Among baseline untreated, average age=77.1±7.0, 55% female, education=14.7±3.8 years, MMSE=24.4±4.7. 51% AD. The proportion of participants with CDR=0.5, 1, 2 was 66%, 25%, and 6% respectively. 47% were referred by a clinical professional. Average follow‐up=3.9±2.2 years. 83% had a spouse/partner or child as co‐participant. Etiology remained AD for 85% of follow‐up visits. Any new AChEI treatment during follow‐up was lower among Blacks (33.7%) and Hispanics (41.4%) compared to whites (45.8%) (p<0.001). After controlling for participant characteristics, adjusted odds of any new AChEI treatment remained lower for Blacks (OR=0.707±0.068) and Hispanics (OR=0.813±0.083, both p<0.05) compared to whites. Unadjusted differences in persistence of treatment were not statistically significant (13.6% intermittent, 28,8% persistence, 57.6% always treated). However, adjusted differences in persistence of treatment was significantly lower for Blacks (OR=0.827±0.090) and Hispanics (OR=0.785±0.081, both p<0.05) compared to whites.ConclusionRacial/ethnic minorities had lower rates of AChEI treatment at study enrollment. Disparities in AChEI treatment persisted even though individuals were followed in ADCs over time and remained significant after adjusting for clinical and demographic variables.
Deep Residual Inception Encoded‐Decoder Neural Network for amyloid PET harmonization
Authors: Shah Jay , Ghisays Valentina , Luo Ji , Chen Yinghua , Lee Wendy , Li Baoxin , Benzinger Tammie L.S. , Reiman Eric M. , Chen Kewei , Su Yi , Wu Teresa 
Published: December 2021

AbstractBackgroundAmyloid PET is an in vivo technology to visualize and quantify beta‐amyloid deposition in the brain. However, the use of multiple amyloid tracers with varied characteristics compounded by processing variabilities poses significant challenges to interpret or combine results from cross‐center studies, and to define common positivity threshold. In this research, we developed an encoder‐decoder based deep model as a harmonization strategy to render imputed amyloid PET images of one amyloid tracer to the images of another.Method91 PiB‐florbetapir (FBP) image pairs from the Open Access Series of Imaging Studies (OASIS) were processed using established pipelines to extract regional standard uptake value ratios (SUVRs), mean cortical SUVRs (mcSUVRs), and SUVR images. Residual Inception Encoder‐Decoder Neural Network (RIED‐Net) was implemented to learn the nonlinear mappings from the image pairs in 2D using encoding‐decoding architecture in conjunction with residual inception blocks and generating imputed images. A 10‐fold cross‐validation was implemented on axial, coronal and sagittal views separately to generate imputed PiB SUVR imaging from FBP data. The average imputed PiB image from all three views was used for performance evaluation. Correlation was evaluated between the imputed vs. real PiB SUVR image voxel‐wise, and between the virtual PiB mcSUVR derived from imputed PiB vs. the real PiB mcSUVR. The trained RIED‐Net model was also applied to an independent dataset with 46 subjects from www.gaain.org/centiloid‐project, and the same metric was used to assess performance.ResultThe imputed PiB SUVR images were visually more similar to real PiB SUVR images than FBP. Voxel‐wise correlation improved from 0.89 between PiB and FBP to 0.95 between the synthetic and real PiB SUVR image (p<0.0001) in the cross‐validation. The agreement of mcSUVR improved from r=0.91 to r=0.96 (p<0.0001) in the cross‐validation dataset and from r=0.92 to r=0.96 (p<0.001) in the independent dataset.ConclusionWe proposed a novel encoder‐decoder based deep model for synthetic imaging. The model discovered the voxel‐wise nonlinear associations between the input images and the output images which significantly improved agreements of amyloid burden measurements from different tracers. The result was further confirmed in an independent dataset demonstrating the generalizability.
Spatial covariance structure of tau‐PET changes more than Aβ‐PET across disease stages
Authors: Chen Gengsheng 
Published: December 2021

AbstractBackgroundAlzheimer disease (AD) has a long preclinical phase with pathophysiological changes such as β‐amyloid (Aβ) accumulation in early stages followed by tau deposition. Graph theory may provide additional insights into the disease processes underlying patterns of Aβ and tau deposition (Pereira et al., 2018; Hoenig,2018). This project uses graph theory to study the spatial covariance structure of Aβ‐PET and tau‐PET changes across disease stages.MethodThis study includes 254 cognitively normal participants (Clinical Dementia Rating™ (CDR™) =0) and 41 impaired participants (CDR>0) from the Washington University Knight Alzheimer Disease Research Center (ADRC, Funding: P50AG005681; P01AG003991; P01AG026276), who underwent MRI, Aβ‐PET 18F‐AV45, and tau‐PET (18F‐AV1451). Regions of interest were defined using the Freesurfer Desikin atlas. Regional Aβ and tau standardized uptake value ratios (SUVRs) were adjusted by gender and age, and used to generate Pearson correlation matrix. Aβ and tau spatial covariance structure can be built as a collection of nodes representing the mean SUVR values from different brain regions, connected by edges representing correlated deposition quantity. BRAPH toolbox (Mijalkov, 2017) were used to calculate Binary Undirected Density (BUD) graph measures. To test for significant differences between these two groups, BRAPH performs non‐parametric permutation tests. Global graph theory measures (global and local efficiency, and modularity) are used to assess the spatial covariance structure of Aβ‐PET and tau‐PET changes.ResultNo significant difference between the CDR=0 and CDR>0 groups was observed for the global measures generated from the Aβ‐PET data (Table 1 and Figure 1A‐C). However, there were significant differences between the two groups for the global measures generated from the tau‐PET data (Table 1 and Figure 1D‐F). The global and local efficiency were lower in the CDR>0 group (p=0.003 and p=0.018, respectively) indicating a higher global and local path length in the covariance structure. Moreover, the modularity was lower (p=0.005) for CDR>0 group, indicating lower fragmentation between regions in this group.ConclusionChanges in spatial correlation associated with conversion to clinical impairment are happening in the tau pattern. These spatial covariance structure changes need further evaluation to assess their utility as a biomarker of disease progression in the preclinical phase of AD.
Training of trainers in the GI‐mhGAP dementia module: National training experience in Mexico
Authors: Astudillo‐García Claudia Iveth , Xochihua‐Tlecuitl Tonatiuh , Velásquez José Javier Mendoza , López‐Montoya Alejandra , Austria‐Corrales Fernando 
Published: December 2021

AbstractBackgroundThe GI‐mhGAP (WHO) is an evidence‐based clinical guideline for the assessment and management of mental, neurological and substance use disorders (MNS) in non‐specialist health settings, which aims to improve capacity for the identification, diagnosis, management and treatment of people with MNS disorders. In Mexico, a national network of facilitators is being established to train non‐specialist mental health providers at the first level of care. Therefore, the aim of this paper is to present how participants perceive themselves in the assessment, management and follow‐up of people with dementia, as well as to provide a replication of this course to primary care personnel.MethodThe sample consisted of 651 participants (doctors, psychologists, nurses and social workers) who were in the virtual training course for facilitators in the GI‐mhGAP given between September‐November 2020, and completed the digital feedback form. Responses were aggregated in a database and analysed using the 'topicmodel' (Grün & Hornik, 2011) and 'tidytext' in R (R Core Team, 2020).ResultsThe sample consisted of 474 (72.81%) women and 177 (27.19%) men, with a mean age of 39.9 (SD=8.13). Regarding the perceived self‐efficacy for the assessment of the condition in their daily practice 70.04% (n=456) felt confident to do it, 63.75% (n=415) felt confident to manage the condition; but only half of them felt confident to train other professionals (54.84%, n=357). The results of the semantic analysis reflect the importance of providing psychoeducation to caregivers and family members, as well as training in assessment based on the identification of symptoms for proper diagnosis. It highlights the need for more training on pharmacological treatment, extending its duration and reducing technical problems with the platform, as well as having more examples and clinical cases.ConclusionThe trained facilitators feel more self‐efficient in identifying and managing the condition in their daily practice, but report the need for further training to be able to replicate the dementia module in primary care providers.
Plasma Aβ1–42 dominantly predicts cognitive decline
Authors: Yang Shieh‐Yueh , Liu H.C. 
Published: December 2021

AbstractBackgroundIn populations at‐risk for developing dementia, such as patients with Down’s syndrome, stroke, and amnestic mild cognitive impairment, it is important to be able to predict the progression to dementia or cognitive decline. is important to be able to predict the progression to dementia or cognitive decline. In clinical practice, a convenient examination that can evaluate the progression to dementia or cognitive decline is urgently needed.MethodNotably, there are limitations in this work. Only five studies are available for this review because such studies are novel.ResultAccording to this review, plasma Aβ1‐42 possibly plays a more key role in this prediction than Aβ1‐40 or Tau. This implies that abnormal levels of Aβ1‐42 might possibly be a critical trigger of the onset of developing dementia or cognitive decline.ConclusionIt would be hopeful to stop the development of dementia or delay cognitive decline by eliminating the abnormal changes in the level of plasma Aβ1‐42.
Optimization of biosensor cell lines for the detection of tau seeding competency in human CSF
Authors: Lathuiliere Aurelien , Jo Youhwa , Fan Zhanyun , Hyman Bradley T. 
Published: December 2021

AbstractBackgroundThe capacity of pathological tau aggregates to recruit and template monomeric tau into misfolded multimers is a major step in the propagation of tau pathology in Alzheimer’s Disease and other tauopathies. Recently, tau seeding activity in postmortem brain tissue was correlated to rate of clinical progression, confirming its relevance in the disease process. If tau seeds could be measured in biofluids, it may be an interesting novel biomarker potentially able to predict disease course. However, current available methods are not sensitive enough to quantify those seeds in the cerebrospinal fluid (CSF).MethodWe generated a series of Förster resonance energy transfer (FRET)‐based biosensor cell lines using rational design of tau bait sequences, linkers, and fluorescent reporter proteins in an attempt to increase assay sensitivity. Transient transfection was used to screen FRET efficiency of novel constructs by flow cytometry. Ultimately, multiple stable cell lines were produced and characterized for their ability to detect tau seeds in human brain lysate and lumbar CSF.ResultThe novel generation of tau biosensor cell lines demonstrated an enhanced sensitivity by more than one order of magnitude as compared to the standard reporter cell line. Tau seeding activity could be measured in less than 100 pg of human brain lysate and in microliters of lumbar CSF.ConclusionOptimized FRET‐based biosensor cells can be used to quantify tau seeds in the CSF of live individuals and are currently being implemented to test the hypothesis that seeding capability will vary in different individuals based on the characteristics of tau strains.
Memorability analysis for diagnostic photographs in cognitive assessment: Linking behavioral performance with biomarker status
Authors: Bai Yuetong , Schütze Hartmut , Berron David , Ziegler Gabriel , Spottke Annika , Buerger Katharina , Schneider Anja , Peters Oliver , Priller Josef , Wiltfang Jens , Laske Christoph , Teipel Stefan J. , Wagner Michael , Jessen Frank , Düzel Emrah , Bainbridge Wilma A. ,   the DELCODE Consortium
Published: December 2021

AbstractBackgroundRecent work has found that memorability, an intrinsic image property predictive of memory, shows consistency across healthy controls (HC), subjective cognitive decline (SCD) and mild cognitive impairment (MCI). Looking at memorability pattern differences between groups, certain images in which HC outperform MCI or SCD individuals can also better predict group membership with a reduced number of images. A key question is whether these diagnostic images reflect a strong link between behavioral performance and biomarker status.MethodBehavioral and biomarker data was collected from 232 participants (64 HC, 99 SCD, 48 MCI, 21 AD) from the DZNE Longitudinal Cognitive Impairment and Dementia (DELCODE) study. Participants were tested for recognition of images from a pool of 835 scene images. Aβ42, total tau, phospho‐tau, Aβ42/Aβ40, and Aβ42/phospho‐tau were collected as biomarkers. We computed linear models predicting corrected recognition with each biomarker as a separate regressor. Using hold‐out cross‐validation (80% training) across 1000 iterations, we also identified three subsets of 50 images in which performance differences between HC and MCI were the highest (“top subset”), lowest (“bottom subset”), or close to zero (“middle subset”). We tested these subsets on the remaining 20% test data, by correlating each biomarker and the average hit rate for that image subset, and comparing their performance with independent t‐tests.ResultAll five biomarkers significantly predicted corrected recognition (p<10‐5) in the linear models (Table 1). For all biomarkers, the correlation coefficients acquired from the top subsets were significantly larger than those acquired from the middle subsets or bottom subsets (Fig. 1). In contrast, the middle and bottom subsets showed small differences that were inconsistent across biomarkers.ConclusionOur results reveal that images with larger memorability differences between HC and patient groups provide stronger links between behavioral performance and biomarker status. These images are more indicative of neuropathologic changes relevant to AD and are thus more diagnostic. Future study may provide more evidence with functional imaging data.
Dementia and mild cognitive impairment in China: From the public health perspective
Authors: Jia Jianping , Jia Longfei , Du Yifeng , Chu Lan , Zhang Zhanjun , Quan Meina , Wei Cuibai , Li Fangyu , Fu Yue , Tang Yi , Lyu Diyang , Li Yan , Zhu Min , Jiao Haishan , Song Yang , Shi Yuqing , Zhang Heng , Gong Min , Fang Boyan ,   the Project of Dementia Situation in China and the COAST Group
Published: December 2021

AbstractBackgroundChina has the largest population of patients with dementia and mild cognitive impairment (MCI) in the world, imposing a heavy burden on the public and healthcare systems. The major concerns from the public health perspective include: prevalence, health economic burden, risk factors, and management strategy.MethodStatistical analyses were performed on the largest and most comprehensive dementia and MCI cohort study (fig. 1) in China. Systemic review was also done on the studies from the past 10 years.ResultFor the prevalence, our data showed that, the overall prevalence of dementia was 6.0% and of MCI was 15.5%. This represented 15.07 million individuals with dementia and 38.77 million individuals with MCI (fig. 2). For the health economic burden, our systematic review showed that the annual total costs associated with dementia would be $248.71 billion in 2020, $507·49 billion in 2030, $1·00 trillion in 2040, and $1·89 trillion in 2050 in China; on a global scale, these costs would be $1·33 trillion in 2020, $2·54 trillion in 2030, $4·83 trillion in 2040, and $9·12 trillion in 2050 (fig. 3). For the risk factors, our study found that MCI and dementia shared 9 similar, modifiable risk factors, including rural residence, fewer years of education, living alone, smoking, hypertension, hyperlipidaemia, diabetes, and heart and cerebrovascular disease.ConclusionThe above public health data indicated that dementia and MCI population has become a heavy burden not only in China but around the world, which called for us to develop systematic management strategies, including: 1) prevention strategy targeting the MCI population by controlling for the modifiable risk factors and increasing public awareness; 2) monitoring strategy for all people with MCI by anti‐dementia national surveillance network that does regular cognitive evaluation and training; 3) early diagnosis and treatment strategy for people with dementia by trained dementia professionals; 4) care strategy by an integrative dementia nursing system. These strategies would form the infrastructure that effectively control the prevalence of dementia in China.
Role of plasma ptau181, neurofilament light, and subjective cognitive decline in predicting progression to MCI in older adults from the Alzheimer’s Disease Neuroimaging Initiative
Authors: Banh Timothy , Tosun Duygu , Mackin R. Scott , Weiner Mike W. , Nosheny Rachel L. 
Published: December 2021

AbstractBackgroundAccurate identification of AD risk using non‐invasive biomarkers is a critical need. Recently plasma biomarkers of amyloid, phosphorylated tau, and neurodegeneration have been shown to accurately identify mild cognitive impairment (MCI), and brain amyloid levels. However, little is known about whether baseline plasma biomarker predict future progression from cognitively unimpaired (CN) to MCI. The overall goal of this study was to examine the predictive utility of markers that can easily be collected remotely.MethodWe identified a set of non‐invasive markers in ADNI: plasma p‐tau181 and neurofilament light (NfL), Neuropsychiatric Inventory Questionnaire (NPIQ), self‐ and study partner versions of a subjective cognitive decline instrument (Everyday Cognition Scale; Ecog), and APOE. In 300 ADNI participants who were CN at baseline, we determined the associations between these markers and progression to MCI using logistic regression. Models covaried for age, gender, and education level. Area under the receiver operator curve (AUC) evaluated discrimination accuracy. Likelihood ratio tests (LRT) determined the best fitting model.Result42 (14%) of participants progressed to MCI (Table 1). In the full model including all predictors (AUC = .879; Table 2 and Figure 1), study partner Ecog score was the only significant predictor associated with progression to MCI. Excluding study partner Ecog decreased model accuracy (AUC = .779; Figure 1). The LRT between this model and the full model was significant (c2(1) = 5.04, p < .05).ConclusionEven when accounting for the contributions of ptau181 and Nfl, study partner‐reported subjective cognitive decline independently predicts future progression to MCI. This approach can be used in the future to efficiently predict MCI risk without the need for in‐clinic assessment.
Perceived needs and support services of families of people with dementia
Authors: Yurrebaso‐Macho Amaia , Orgaz‐Baz Begoña , Montes‐López Estrella , Valverde Eva María Picado , del Álamo‐Gómez Nuria ,   NEUROQUALYFAM group
Published: December 2021

AbstractBackgroundDementia is one of the most important causes of dependency worldwide. These patients require constant care. This care is mainly provided by the families. Each family has specific needs and demands specific support services. To improve their quality of life, the family should be considered in the development of strategies that contribute to the provision of support services for them. Considering this, the objectives of this work are to analyse the support needs of these families, as well as the services they access.MethodThe FQOLS‐NDs instrument (Badía et al., 2020) was applied by telephone to a sample of 163 relatives of people with dementia in the Spain‐Portugal cross‐border area. The main characteristics of the research participants are: 69.9% are women, aged between 28 and 87, and do not work (63.8%). They are mainly daughters/sons (59.5%) or partners (32.5%) of the person with dementia. In addition, they are mostly their main carers (95.1%) and live with them (74.8%).ResultsThe main research findings reveal that: 1) The support services most needed by families are information about the disease (53.4%); information about support services (52.8%), and information about where to get them (44.8%). 2) Family members report not being able to access the support services they need. Among them, those to which more than 80% of families do not have access stand out. These are support groups (92.3%), psychological help (90.3%), family respite (85.5%) and spending money (81.1%). 3) There are few support services that families need and consider that they have sufficient access to. The most positive data reveal that only 18.4% of participants perceive the information they receive about the disease as sufficient; only 16.3% consider that they have enough help to run the household, and only 12.8% claim to have access to sufficient information about legal rights.ConclusionFamilies are not receiving the support services they most need. Moreover, they do not value the services they access as sufficient. References: Badía, M., Orgaz, M.B., González, E., Vicario‐Molina, I., Gómez‐Vela, M. and NEUROQUALYFAM group (2020). Family Quality of Life Scale ‐ Neurodegenerative Diseases.