bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation of Global Action Plan on the Public Health Response to Dementia (GAPD) in Sub‐Saharan Africa: Comprehensive reviews
Authors: Ddumba Isaac 
Published: December 2020

AbstractBackgroundDespite the fact that, age is a strongest know risk factor for onset of dementia, and developing countries are projected to have highest number of ageing population, few national dementia strategies have been put in place to address this impending scourge. In 2017, World Health Organization(WHO) released and called for countries to adapt and contextualize the Global Action Plan on the Public health response to dementia, few Sub‐Saharan countries have slowly adopted plan. The outcome of the unprecedented increase populations with dementia will be immense. The substantial increase in morbidity and mortality pose a threat to the over stretched health care system and undermine the potential to achieve sustainable development goal (SDGs).MethodsThis paper is a view of published and grey literature relevant to Global Action Plan On the Public Health Response to Dementia (GAPD) in sub‐Saharan Africa. The overall approach to the review had an exploratory and inductive focus. Articles were categorized around a guiding conceptual framework. Like; A description of structural arrangements and content of national dementia strategy development and normative underpinnings within policy frameworksResultsNearly all countries within the SSA hadn’t developed the national dementia strategy plans. Countries like South African, Ghana, Kenya and Ethiopia had drafts of national dementia strategy, though not yet operationalized. Few countries highlighted some of the parallel targets of GAPD within their national mental health policy and strategy, but it was not comprehensive. Countries where Civil societies that advocate/champion dementia activities were strongly presently were more likely to possess a draft of GAPD.ConclusionAlthough there some initiatives for different countries to develop national strategy for dementia plans, there are gaps in the extent of engagement of different stakeholders and how these strategies will be operationalized may limit the impact on addressing the escalating burden of dementia in Sub‐Saharan Africa. Key words: Dementia, Sub‐Sarahan Africa, national plans, GAPD.
Use of the NIH Toolbox for assessment of mild cognitive impairment and Alzheimer's disease in general population, African‐American and Spanish‐speaking samples of older adults
Authors: Gershon Richard , Nowinski Cindy , Peipert John Devin , Bedjeti Katy , Ustsinovich Vitali , Hook Julie , Fox Rina , Weintraub Sandra 
Published: December 2020

AbstractBackgroundThe world population is rapidly aging, and the prevalence of dementia due to Alzheimer’s disease (AD) and related disorders is correspondingly increasing. Thus, detecting cognitive decline in older individuals is an urgent public health concern. There is a need for brief, practical, standardized measures that are sensitive to cognitive decline and can be broadly deployed in diverse settings. Advancing Reliable Measurement in Alzheimer's Disease and Cognitive Aging (ARMADA) aims to meet this need by validating the NIH Toolbox for Assessment of Neurological and Behavioral Function® (NIHTB®) in individuals ages 65 to 85 who are cognitively healthy or diagnosed with either mild cognitive impairment (MCI) or dementia of the Alzheimer type (AD). A broad range of clinical and healthy samples have been recruited to date, including an African American sample and a Spanish‐speaking Hispanic sample to reflect the diversity of people affected by cognitive decline and to enable validation of the Spanish NIHTB. We will present baseline NIHTB results for each sample.MethodIndividuals age 65 or older who are either cognitively normal or diagnosed with cognitive impairment (MCI or early AD) have been recruited from nine clinical centers with established research cohorts. Participants complete the NIHTB and gold standard neuropsychological assessment at baseline. AD biomarkers, including PET beta amyloid level, CSF tau, and APoE genotype, are also available.ResultAs of January 2020, 656 participants have completed the baseline assessment. Early results indicate the NIHTB Cognition battery, as well as individual measures, successfully discriminates among MCI, AD and healthy controls in the general population sample (N=259). Baseline data collection for the African American and Hispanic samples will be largely complete by June 2020, and initial results will be presented.ConclusionInitial baseline results from the ARMADA study provide evidence that the NIHTB discriminates among older individuals with normal cognition, MCI, and early AD. Two annual longitudinal follow‐ups will evaluate how well NIH Toolbox measures predict future cognitive decline, their sensitivity to change and their association with AD biomarkers.
Semantic and logopenic primary progressive aphasia differ in pitch variation during a motor speech task
Authors: Pressman Peter S. , Lemieux Eric , Matthewson Gordon , O'Neill Chris , Ross Elliott D. 
Published: December 2020

AbstractBackgroundSemantic variant primary progressive aphasia (svPPA) is an uncommon neurodegenerative disease associated with selective atrophy of the dominant temporal lobe. Previous observations of left hemisphere damage suggest that prosodic expression (mediated predominantly by the right hemisphere and dorsal processing streams) is often preserved and may even be enhanced as a release phenomenon in some aphasic syndromes. We predicted left temporal injury would be associated with increased pitch variation, thereby distinguishing it from other PPA syndromes such as the logopenic variant of primary progressive aphasia (lvPPA).Method8 patients with svPPA and 10 patients with lvPPA repeated the syllable "Pa" as part of a motor speech evaluation. We compared the coefficient of variation of fundamental frequency, perceived as vocal pitch, using a separate variances two‐way t‐test. To better understand what may drive differences in pitch variation, we also correlated pitch variation with disinhibition measures on the Neuropsychiatric Symptoms Inventory Questionnaire (NPI‐Q) and the Frontal Assessment Battery (FAB).ResultCompared to 10 patients with lvPPA (M 4.5, SD 1.6), patients with svPPA (M 14.0, SD 10.3) displayed more variation of fundamental frequency (T = 2.6, p = 0.02). There was no correlation with either the NPIQ or FAB disinhibition measures.ConclusionPitch variation during simple motor speech tasks may serve as an additional diagnostic feature to distinguish between subtypes of PPA. The temporal atrophy associated with svPPA may release hyperprosodic performances on a simple motor speech task, through a mechanism beyond behavioral disinhibition as assessed in either the NPI‐Q or the FAB. Further research is needed to better understand the neural underpinnings of prosodic differences between PPA subtypes.
What predicts who becomes a study partner in an AD cohort study?
Authors: Stites Shana D , Largent Emily A , Gill Jeanine , Harkins Kristin , Karlawish Jason 
Published: December 2020

AbstractBackgroundStudies of persons with Alzheimer’s disease (AD) and related dementias typically include “study partners” (SPs) who report on participants’ wellbeing and function. But little is known about what factors predict the type of person who steps into the role. Knowing this will inform barriers to recruitment into AD research. It may also offer a model to anticipate who will be a caregiver in early diagnosis and treatment of AD.MethodsWe analyzed data from the Health and Retirement Study’s (HRS) Aging, Demographics and Memory Study (ADAMS). ADAMS enrolled a subset of individuals in HRS and, for each of these subjects, a SP. HRS data were collected one year prior to the first ADAMS interview and provided a detailed family record of all living, legal and biologic, relatives and a spouse’s rating of their own health. ADAMS data provided who served as a SP reporting on subject instrumental and basic activities of daily living (IADL/BADL). Three distinct regression models examined how psychosocial factors predicted each of the three SP types: spouse, adult child, and other.ResultsAmong subjects with spouses, multivariable analyses showed subject’s age and having a sister predicted that a spouse was less likely to serve as SP (both p<0.05). Among subjects with children, being a women, being older, having more children, more impairments in IADLS, and not having a spouse predicted that an adult child was more likely to serve as SP (all p<0.05). Having a spouse, more children, and having more years of education predicted that a non‐spousal and non‐child person was more likely to serve as SP while being a woman and having a daughter were associated with a lower probability that a non‐spouse and non‐child served as SP (all P<0.05).ConclusionsDifferent factors predict the type of person who may serve as a SP. Our findings show patterns in interpersonal relatedness, educational attainment, and gender norms that may underlie differences in decisions about who serves as SP. This information may help inform recruitment and retention in AD research.
The status of current clinical practice in diagnosis of young onset dementia in England: Findings from The Angela Project
Authors: Carter Janet , O'Malley Mary , Campbell Jackie , Stamou Vasileios , La Fontaine Jenny H. , Oyebode Jan , Parkes Jacqueline 
Published: December 2020

AbstractBackgroundThe presentation of dementia in young people is complex and challenging, often resulting in delays in receiving a confirmed diagnosis and appropriate support. A recent Delphi consensus has derived minimum and gold standards for the diagnostic workup that international expert clinicians consider best practice. This presentation will review the results of a large case note audit that assessed compliance with these standards in current UK clinical practice.Method403 patient records of young people who received a diagnosis of dementia in the last 5 years were audited according to our minimum and gold standards. Records were obtained from memory services within eight different National Health Service locations from across England.ResultWe found significant differences between the sites in meeting the standards, though all sites had median scores that were below 50% compliance for both the minimum and gold standard. This suggests that current UK assessments fail to reach an acceptable standard.ConclusionFurther consultation with clinicians and young people with dementia is necessary to understand local impediments to meeting an acceptable standard and to identify interventions that can lead to improvement.
Association between integrated cognitive assessment (ICA) and measures of brain structure in mild cognitive impairment and mild Alzheimer’s disease
Authors: Khanbagi Mahdiyeh , Marefat Haniye , Karimi Hamed , Kalafatis Chris , Vahabi Zahra , Razavi Seyed‐Mahdi Khaligh 
Published: December 2020

AbstractBackgroundIntegrated Cognitive Assessment (ICA) is an artificial intelligence‐assisted test for cognitive assessment in mild cognitive impairment (MCI) and Alzheimer’s Disease (AD) (Khaligh‐Razavi et al., 2019). ICA is shown to be accurate in detection of subtle cognitive impairments in MCI/ AD, and have demonstrated a strong association with the level of neural damage, as measured by NfL. However, the link between ICA and measurements of brain atrophy has not been studied yet. Here, we investigated the link between participant’s performance in ICA test and their cortical volume and thickness; we were further interested to see whether the impairment detected by ICA precedes that of brain atrophy.MethodHigh‐resolution (1mm3) MRI scans were acquired from 45 participants (age= 64.63±7.46): 15 MCI patients, 10 mild AD, and 20 healthy controls (HC). All the participants took ICA. Structural images of the brain were then reconstructed using FreeSurfer software for volumetric and cortical thickness measurements.ResultICA shows significant correlations with cortical thickness in various brain regions, such as part of the lingual and parahippocampal cortex (r= 0.7, p<10‐11), lateral occipital (r= 0.48, p<10‐6), inferior temporal (r= 0.43, p<10‐5) and fusiform (r=0.4, p<10‐4) in the left hemisphere. Within the right hemisphere, ICA has a significant correlation with precuneus (r= 0.45, p<10‐5) and lateral occipital (r=0.5, p<10‐7). ICA has a large effect size (Cohen’s d= 0.95, p<0.001) in differentiating HC from MCI and HC from mild AD (Cohen’s d= 1.98, p<0.0001). Cortical thickness and left hippocampal volume could differentiate HC from mild AD (Cohen’s d= 0.88, p<0.05; and d= 0.8, p<0.05 respectively), but not HC from MCI.ConclusionWe found a significant association between participants’ ICA score and the thickness of the cortex in some of the key brain areas, including parahippocampal, that are anatomically identified among the early areas affected by tau‐pathology (Braak and Braak, 1991). Furthermore, participant’s ICA score could better differentiate HC from MCI or mild AD compared to their hippocampal volume, suggesting that impairment in ICA performance precedes that of hippocampal volume.
Estimating an individual's placement on a theoretical continuum using longitudinal cognitive trajectories: Relationships with longitudinal amyloid and Tau‐PET
Authors: Properzi Michael J. , Buckley Rachel F. , Papp Kathryn V. , Farrell Michelle E. , Jacobs Heidi I.L. , Hanseeuw Bernard J. , Rabin Jennifer S. , Chhatwal Jasmeer P. , Rentz Dorene M. , Johnson Keith A. , Sperling Reisa A. , Schultz Aaron P. 
Published: December 2020

AbstractBackgroundTheoretical models of the Alzheimer’s disease (AD) continuum posit a curvilinear trajectory of declining cognition, with accumulating AD pathology catalyzing an accelerated rate of decline. Assuming this continuum can be modelled, individuals can be placed along the curve based on their longitudinal cognitive performance. In this way, we can reduce multi‐dimensional data to a single parameter (simplification/parsimony) and remove non‐linearity in the cognitive data.Method317 participants from the Harvard Aging Brain Study (72 years (7.6); Female:61.5%) underwent longitudinal neuropsychological assessments (follow‐up: 5.9years (2.1) range:1.7‐9.1) and PIB‐PET imaging. A subset of participants (n=230) also underwent FTP‐PET imaging. Cognition was measured using the Preclinical Alzheimer Cognitive Composite (PACC). Using iterative non‐linear least squares optimization, we defined a curvilinear function (incorporating linear, quadratic and exponential components) that best described the group level PACC trajectory of all participants (Figure 1). Each subject’s longitudinal PACC trajectory was then located on the resulting curve using trust‐region‐reflective non‐linear least squares optimization, solving for an individual’s time offset (toffset). We examined associations between toffset, age, sex, apoe4 status, cross‐sectional PIB‐PET and FTP‐PET. We also examined toffset in relation to changing PIB‐PET and FTP‐PET.ResultIndividuals with a more advanced toffset had higher levels of entorhinal (EC) and inferior temporal (IT) FTP‐PET (r=0.42, p=<<0.001; Figure 2A&B.), and also showed higher PiB‐PET signal (r=0.36, p=<<0.001; Figure 2C.) PIB accumulation appears earlier in toffset followed by EC TAU and finally IT TAU, suggesting that a biomarker cascade is being captured by toffset (Figure 3). FTP‐PET and PIB‐PET did not interact to predict toffset. There was no effect of age or APOE4, or an interaction between the two, on toffset.ConclusionUsing toffset, estimating an individual’s position along a hypothetical clinical continuum can inform the unique contributions of AD biomarkers, and test hypotheses about temporal sequences of events. This data‐reduction approach is superior to that of pulling cognitive slopes, as the tpffest removes complex non‐linearities inherent in the data (Figure 4). We also illustrate that an interaction between FTP‐PET and PIB‐PET does not predict toffset, suggesting a common upstream mechanism that may underlie both Aβ and tau to drive decline, at least during the preclinical stages of disease.
Generation of mid‐region murine monoclonal antibodies against multiple structural isoforms of amyloid‐beta by hybridoma technology
Authors: Stockmann Julia , Beyer Léon , Galkowski Sandy , Woitzik Nathalie , Güldenhaupt Jörn , Gerwert Klaus Bernhard 
Published: December 2020

AbstractBackgroundThe immuno‐infrared‐sensor enables the diagnosis of Alzheimer’s disease by measuring the secondary structure distribution of Amyloid‐beta (Aß) in CSF and blood plasma. For this technique an antibody is essential, which binds to all conformations of the biomarker peptide. We developed different immunization strategies to generate monoclonal Aß‐antibodies (mAb) using wt and APP Knock‐Out (KO) mice.MethodKO and wt mice were immunized with different Aß peptides. With an antigen‐specific ELISA antibody‐producing hybridoma cells were screened and selected for performance tests with the immuno‐infrared sensor. Immuno‐infrared‐analyses provided a detailed characterization of the structural selectivity of the antibodies.ResultBoth KO and wt mice generated multiple Aß specific antibodies, though KO mice yielded 8 times more Aß‐positive antibodies than wt. All antibodies, probably polyclonal, revealed binding to alpha‐helical or disordered monomeric Aß as well as to ß‐sheet enriched Aß (oligomers, fibrils). Additionally, seven of these antibodies differentiated between AD patients and healthy controls in cerebrospinal fluid (CSF) samples.ConclusionWith our immunization strategy we were able to generate multiple antibodies for the diagnosis of Alzheimer’s disease with the immuno‐infrared sensor. We generated seven antibodies, which enable the differentiation of AD patients and healthy controls by analyses on CSF. References: [1] Nabers, A., Ollesch J. et al. (2016) J. Biophotonics, 9. 224‐234. [2] Nabers, A. et al. (2018) EMBO Mol. Med. 10, e8763. [3] Nabers, A et al. (2019) Alzheimer’s Dement. Diagnosis, assess. Dis. Monit., 11, 257‐263. [4] Stocker, H et al. (2019), Alzheimer's & Dementia, in press.
Data‐assisted differential diagnosis of dementia by deep neural networks using MRI: A study from the European DLB consortium
Authors: Larsen Simen Norrheim , Oppedal Ketil , Eftestøl Trygve , Ferreira Daniel , Lemstra Afina W. , Kate Mara ten , Padovani Alessandro , Rektorova Irena , Bonanni Laura , Nobili Flavio Mariano , Kramberger Milica G. , Taylor John‐Paul , Hort Jakub , Snædal Jón , Blanc Frédéric , Antonini Angelo , Borda Miguel German , Aarsland Dag , Westman Eric 
Published: December 2020

AbstractBackgroundClinicopathological overlap between neurodegenerative diseases contributes to challenging differentiation between dementia types. Improving differential diagnosis is important to provide optimal patient care and better predict future needs. Deep learning techniques such as convolutional neural networks have in recent years gained much attention for their high performance in image classification. Magnetic resonance imaging (MRI) computer‐assisted diagnosis (CAD) systems based on deep learning could potentially contribute to increased reliability of clinical diagnosis.MethodAn ensemble model of 3D‐convolutional neural networks was trained and tested on a class‐balanced dataset consisting of T1‐weighted MRI brain scans for the differentiation of subjects diagnosed with Alzheimer’s disease (AD), dementia with Lewy bodies (DLB) and normal controls (NC). Total number of brain scans used for training and testing were 690 (nAD=nDLB=nNC=230) and 171 (nAD=nDLB=nNC=57) respectively. Diagnoses were clinical, not including MRI, and in a subgroup of the DLB patients the diagnosis was supported by DAT scan. All scans were skull‐stripped and spatially normalized. All classes were matched for age and sex. Data augmentation was applied using the left and right hemisphere as separate instances and a Bayesian approach was used for hyperparameter optimization. Experiments were conducted using 6‐fold cross‐validation, with the final model constructed as an ensemble of all models.ResultA final accuracy of 71.9% was reported for the three‐class differential classification of 171 stand‐out test subjects. The model classified the NC, DLB and AD subjects with 71.9%, 86.0% and 57.9% accuracy respectively. Further inspection showed that most of the miss‐classified AD patients were wrongly classified as DLB by the CAD system.ConclusionThe results of this work show promising potential for deep learning based CAD systems trained on MR brain images for differential diagnosis of dementia. Most data‐driven dementia classification models, including the one presented in this work, are limited by the amount of available data, comorbidity, and the inaccuracy of clinical diagnosis. Increasing the amount of data might significantly improve such models. The prospective E‐DLB study will provide more brain MRI data for future improvement of the suggested deep learning based CAD system.
PR001 gene therapy improved phenotypes in models of Parkinson’s disease with GBA1 mutation
Authors: Sheehan Patty , Heckman Laura D. , Fenn Tim , Wong Li Chin , Nelson Stuart , Garimalla Swetha , Haller Jorge , Daily Jenn , Politi Jason , Dai Yong , Hefti Franz , Abeliovich Asa 
Published: December 2020

AbstractBackgroundMutations in GBA1, which result in deficiency of lysosomal enzyme glucocerebrosidase (GCase), are the most common known genetic cause of Parkinson’s disease (PD). Decreased GCase activity in PD patients with GBA1 mutations (PD‐GBA) causes accumulation of glycolipid substrates, which leads to lysosomal dysfunction and neuroinflammation. With our gene therapy product candidate, PR001, we aim to increase GCase activity in PD‐GBA patients in order to ameliorate the lysosomal dysfunction and slow or stop disease progression.MethodGCase activity and α‐Synuclein levels were assessed following PR001 treatment in vitro in a cell line and in primary rodent neurons. Two mouse models of GCase deficiency that display phenotypic characteristics consistent with PD‐GBA, including decreased GCase activity, glycolipid substrate accumulation, motor behavioral phenotypes, and neuroinflammation, were used to assess the efficacy of PR001 in vivo. Safety endpoints were examined in the two mouse models as well as in nonhuman primates.ResultPR001 treatment in vitro increased GCase activity and decreased α‐Synuclein levels. In PD‐GBA models in vivo, PR001 treatment increased GCase activity, decreased glycolipid substrate accumulation, improved motor abnormalities, and decreased neuroinflammation. These therapeutic benefits were persistent, with lasting effects observed at 6 months post‐treatment. Safety studies demonstrated that PR001 was well tolerated at all doses tested.ConclusionOverall, PR001 displayed efficacy in multiple independent cell and animal models of PD‐GBA and no PR001‐related safety events or adverse findings in mice and nonhuman primates. These findings demonstrate that PR001 is a promising potential gene therapy for PD‐GBA patients. We have recently initiated a Phase 1/2 clinical trial to investigate safety, tolerability, and effects on biomarkers and measures of clinical efficacy.