bluuebunny/crossref_metadata_2025_split huggingface dataset:
Are serial position effect patterns in the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) invariant across genders?
Authors: Suhr Julie A , Do Cardinal A. , Jankowski Adrienne A. 
Published: December 2023

AbstractBackgroundAlthough more men are diagnosed with Mild Cognitive Impairment, more women are diagnosed with Alzheimer’s disease. Disparities in diagnosis may reflect a female advantage in verbal memory across the lifespan such that, when norms are collapsed across gender, women with subtle cognitive decline are not detected until further in the course of illness. Patterns of verbal memory performance, such as the serial position effect (SPE) may be invariant to gender and thus may minimize these diagnostic discrepancies. However, few studies have examined whether SPE patterns and their relationships to outcome are invariant to gender.Method338 adults 50 years of age or older participated in community dementia screening, which included the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Average age was 66.9 years, 94% were white, and 67% identified as women. None had major neuromedical or neurodegernative diagnosis. RBANS List Learning was used to identify primacy, middle, and recency recall on Trial 1 and at delayed recall. We also calculated recency ratio (percent of recency words recalled at delay/percent recency words at Trial 1).ResultWe identified expected SPE patterns for Trial 1 and at delayed recall; the patterns were invariant to gender. Primacy at Trial 1, middle of the list at Trial 1, and recency ratio all predicted RBANS Delayed Memory Index; there was no interaction with gender. Using cluster analysis, we divided the sample into those with better primacy than recency and those with better recency than primacy at Trial 1. Those with better primacy than recency on Trial 1 did better on the Delayed Memory Index; this was not moderated by gender. SPE findings were specific to delayed memory.ConclusionResults show that the SPE patterns identified on longer word list learning tasks can also be identified on a cognitive screening battery. Further, although traditional memory scores showed gender disparities, SPE patterns and relationships were invariant to gender.
Genetic predisposition to Alzheimer’s disease is differentially associated with joint volumetric variations in the disease continuum
Authors: Genius Patricia , Calle Maria Luz , Cacciaglia Raffaele , Evans Tavia E , Falcon Carles , Minguillón Carolina , Adams Hieab H.H. , Esteller Manel , Navarro Arcadi , Gispert Juan Domingo , Vilor‐Tejedor Natalia ,   for the ALFA study
Published: December 2023

AbstractBackgroundImaging genetics studies commonly assess the individual association between genetic information and brain features without considering joint brain modulations. The aim of this study was to explore the structural variation of the brain at different stages of Alzheimer’s disease (AD), depending on the genetic predisposition to AD.MethodA total of 351 cognitively unimpaired (CU) middle‐age participants from the ALFA (Alzheimer’s and FAmilies) study and 330 cognitively impaired participants from ADNI (Alzheimer’s Disease Neuroimaging Initiative) with magnetic resonance imaging scans, genetic information and CSF‐amyloid status were included. They were classified as CU Aβ‐, CU Aβ+, (mild cognitive impairment) MCI Aβ+ and AD Aβ+[Table 1]. Freesurfer was used to obtain cortical and subcortical parcellations using the Desikan‐Killiany atlas. A polygenic risk score estimating each participant’s genetic predisposition to AD (PRS‐AD) was calculated including genetic variants at the genome‐wide suggestive level (5×10‐6). Individuals were classified into high/low genetic predisposition groups. Statistical analysis was based on compositional data analysis. First, we computed the optimal multivariate brain structural variation signature (elastic net selection). Then, a logistic regression was performed to determine the association between the optimal signature and the PRS‐AD. Models were stratified by disease stage and adjusted for age and sex.ResultIndividuals at different stages on the AD continuum displayed different brain volumetric modulations associated with higher genetic predisposition to AD [Figure 1]. For instance, the optimal signature associated with an increased risk of AD was mainly characterized by increased hippocampal volumes in Aβ‐ individuals, but decreased volumes in MCI individuals along with the modulation of other temporal regions. Moreover, in AD patients at higher genetic predisposition of AD, the optimal signature was characterized by increased and decreased volumes in frontal regions (e.g. pars triangularis, lateral orbitofrontal vs. medial orbitofrontal, respectively) [Figure 2].ConclusionResults showed AD stage‐specific multivariate volumetric variation associated with an increased genetic risk of AD. Main results suggested that regions that modulated together, although differing according to AD stage, were implicated in the structural brain topology of specific memory networks. The analysis of the joint volumetric variation of brain subregions brings an innovative modeling perspective for neurogenetic studies of AD.
Association Between Internet Accessibility and Health Literacy among Community‐Dwelling Older Adults with Cognitive Frailty (CF) from Lower Socioeconomic Status (LES) group: A Cross‐sectional Study
Authors: Fadzil Nurul Hidayah MD 
Published: December 2023

AbstractBackgroundThe objective of this study was to determine the association between internet accessibility, health literacy and sociodemographic factors among older adults with cognitive frailty (CF) from lower socioeconomic status (LES) group.MethodThis study was a part of the AGELESS trial’s screening phase, which was conducted from October 2021 till March 2022 for developing telehealth multi‐domain intervention. The data included were sociodemographic variables, internet access and health literacy index. About 282 community‐dwelling older people aged 60 years (mean age 68.65 ± 6.52) from lower socioeconomic status (LES) participated in this study. Purposive sampling was utilized to identify cognitive frailty using Fried’s Criteria and Clinical Dementia Rating (CDR) while health literacy was measured using Health Literacy Questionnaire HLS‐M‐18 (Health Literacy Index). Linear regression was performed to analyse the sociodemographic factors influencing health literacy.ResultIn this study, we found that more participants who accessed to Internet compared to Internet non‐users, 68.1% and 31.9%, respectively. They significantly consisted of females (54.1%), married (56.8%), obtained secondary education level (61.1%) and still working (69.7%) (p<0.05). The majority of them (75.1%) utilised digital technology devices in their daily life for example smartphones (70%), computers or laptops (4.4%), followed by tablets (3.7%) which their primary functions were for family interaction and update online news, 67.8% and 31.3% respectively. In addition, Internet users among older adults with cognitive frailty from the LES group had a 3‐fold better health literacy than internet non‐users (OR 3.248, 95% CI: 1.059 – 5.436, p<0.05). Those who were married and higher education level were also the main factors influencing their health literacy in this target population (OR 2.314, 95% CI: 0.241 – 4.386, p<0.05; OR 0.494, 95% CI: 0.219 – 0.768, p<0.05).ConclusionOur findings imply that Internet users among older people with CF from the LES group adopted the Internet mainly for family connection and update online news. Future research should emphasize the understanding of Internet adoption as a non‐pharmalogical intervention for cognitive frailty such as telehealth or mobile health (mHealth) using specific mechanisms for instance qualitative or mixed method design.
Pilot Study of Reticular Activating System (RAS) in Mild Dementia
Authors: Ho‐yin Lai Frank , Hai Eddie , Chan Catherine 
Published: December 2023

AbstractBackgroundClinically, the common early symptoms of dementia include memory problems, reduced concentration, behaviour changes, apathy and withdrawal, loss of ability to do everyday tasks. These cognitive functions are mediated by the reticular activating system (RAS) that is a collection of interconnected brain nuclei that regulates wakefulness, alertness and modulate behaviors. The RAS degenerates early during Alzheimer’s disease progression in association with abnormal tau build‐up.MethodThis study aimed to explore the relationship between the RAS functioning and older people with mild grade dementia. The Kendrick Object Learning Test (KOLT) is a test of recall of everyday objects after viewing for a brief period, an immediate recall of briefly perceived visual data. The Kendrick Digit Copying Test (KDCT) is a test of speed in processing and recording information. These tests suggested cortical excitation mediated by both the RAS and the hypothalamic limbic network which deteriorate in older people with mild grade dementia.ResultIn this pilot study, 25 demented patients with mild grade dementia and 20 participants with known depression were recruited. They are matched in age (mean age 72 with sd 4.89) and shared similar demographic background. The participants were tested with the Kendrick Object Learning Test (KOLT) and the Kendrick Digit Copying Test (KDCT). To observe the short term longitudinal change of their RAS functioning, these tests were administered again 4 weeks following baseline. With regular day activity treatment, the depressive group showed improvement in KOLT (p < 0.1), but not on KDCT (p = .82). However, in the dementia group, there were no significant difference noted in both KOLT and KDCT (p < 0.5).ConclusionThe present findings echo some findings of RAS does not function properly as in the older people with dementia. The reticular system is not compromised in group of depressive participants, there would be improvement in object learning, but no significant difference on speed in processing and recording information as measured by speed‐performance tests (KDCT). Proper and targeted rehabilitation trainings and care giving techniques could be arranged in meeting the specific patients’ needs.
The Effects of Computerized Cognitive Training on Memory Performance in Adults with Mild Cognitive Impairment or Dementia. A Systematic Review and Meta‐analysis
Authors: Chan Aaron TC , Tran Yeuk Shun Joshua , Ip Tsz Fung , Yiu Karen KL , Chan Joyce YC , Goh Wilson Wen Bin , Tsoi Kelvin KF 
Published: December 2023

AbstractBackgroundMemory impairment is a predominant symptom in people with mild cognitive impairment (MCI) and dementia. Computerized cognitive training (CCT) has been proposed as a promising non‐pharmaceutical intervention to slow down the deterioration of cognitive functions. While previous studies have reported the benefits of CCT on global cognition, few have focused specifically on memory outcomes. Therefore, the aim of this study is to investigate the benefits of CCT on memory outcomes in adults with MCI or dementia.MethodA literature search was conducted via the PubMed, Medline, Embase and PsycINFO databases from inception to Sept 2022. Inclusion criteria included: (1) participants with MCI or dementia, (2) CCT as one of the interventions, (3) randomized trials with a non‐CCT comparison group, and (4) studies that reported changes in memory‐related neuropsychological scores before and after the intervention. The outcomes were measures of verbal memory, visual memory and working memory. With the heterogeneous definitions of CCT, the standardized mean differences (SMD) were pooled using a random‐effects model.ResultThirty‐nine clinical trials with 2,010 participants with MCI or dementia were included. The mean age ranged from 44 to 83, and the percentage of males ranged from 21% to 73%. Participants with MCI that received CCT demonstrated significantly better performance in verbal memory (SMD = 0.69, 95% CI = 0.41 to 0.90), visual memory (SMD = 0.49, 95% CI = 0.14 to 0.84) and working memory (SMD = 0.42, 95% CI = 0.12 to 0.72) than the control groups. In the sub‐group analyses of different control groups, those MCI patients who received CCT demonstrated better verbal memory performance than the usual care and the active control groups, but comparable results as the paper‐and‐pencil cognitive training group. For the studies that include dementia participants, CCT effects were not significantly better than the control groups.ConclusionComputerized cognitive training conferred significant benefits in preserving memory function in people with MCI, while the benefits were not statistically significant in patients with dementia. This study also supports that computerized cognitive training can be enhanced by using mobile devices, gamification and immersive technologies.
Can construct specification equations help us progress the biomarker‐cognition debate in dementia?
Authors: Melin Jeanette , Göschel Laura , Teunissen Charlotte E. , Hoede Patty , Lehmann Sylvain , Fillmer Ariane , Flöel Agnes , Cano Stefan , Marquis Sarah , Pendrill Leslie 
Published: December 2023

AbstractBackgroundCurrently, there are no widely accepted causal models of how common biomarkers linked to dementia present as cognitive symptoms. In the current study, we present a methodology and preliminary findings to ascertain relations between sets of biomarkers and cognitive symptoms where memory ability was quantified by the newly developed NeuroMET Memory Metric (NMM).MethodThe sample was from the EMPIR NeuroMET cohort (n = 213 individual assessments; healthy controls [33%], subjective cognitive decline [31%], mild cognitive impairment [15%], Alzheimer’s disease [20%]). Person memory ability was measured with the NMM and the legacy test Corsi block tests (CBT), MRI and MRS biomarkers were acquired with a 7T whole‐body Magnetom MRI system and plasma biomarker levels of GFAP and pTau were measured with Simoa. To study how person memory ability can be explained, a so‐called construct specification equation (CSE) was developed using principal component regression, where person memory ability was found to depend on a linear combination of a set of explanatory co‐variables.ResultMemory ability, ϴi, was found to depend on several biomarkers expressed by the CSE and the most promising CSE yielded was: ϴi = 7(3) + 2(1) x Cortical thickness + 1.7(5) x Hippocampus left – 0.0045(8) GFAP – 0.03(10) x pTau181 – 0.127(2) x Myoinositol – 0.8(4) x Amygdala right + 0.035 x Age. A Pearson correlation coefficient of 0.77 of memory ability based on the CSE prediction against the NMM measured memory ability was achieved. In contrast, all univariate correlations between individual biomarkers and memory ability were lower (highest for Cortical Thickness, R = 0.59) and correlations to memory ability measured with CBT was also lower (R = 0.46).ConclusionThis study is the first to combine a metrologically validated metric derived from set of legacy memory tests with biomarker data in an attempt to better understand predictive links through CSEs. Reflecting the CSE methodology and superior accuracy of the NMM we can get more accurate and clearer understanding of how changes in biomarkers relate to changes in cognitive symptoms can contribute to the advancement in targeting novel drugs and interventions.
Systematic assessment of microRNA‐132 therapeutic targeting in Alzheimer’s disease using iPSC‐derived neurons and microglia
Authors: Penning Amber , Tosoni Giorgia , Walgrave Hannah , Snoeck Sarah , Balusu Sriram , Salta Evgenia 
Published: December 2023

AbstractBackgroundMapping the mechanistic heterogeneity and multifactorial nature of Alzheimer’s Disease (AD) is a key challenge for therapeutic development and the main reason why network biology and multi‐modal therapies begin to attract attention also in AD research. MiRNA‐targeted therapeutics are particularly suited for such purposes, as they regulate multiple components of several molecular cascades converging on disease‐relevant patho‐phenotypes. MicroRNA‐132 (miR‐132), a potent neuroimmune regulator, has been identified as the most robustly and significantly downregulated microRNA in the brain of AD patients and its deficiency has been functionally linked to amyloid deposition, TAU hyperphosphorylation, neuronal cell death and memory decline, in both human and rodents. Additionally, miR‐132 was recently identified as a potent regulator of adult hippocampal neurogenesis (AHN), exerting multilayered proneurogenic effects in adult neural stem cells and their progeny. Together, these observations suggest that miR‐132‐dependent network‐based gene regulation in human AD brain converges onto biological pathways that can drive disease endophenotypes. Direct miR‐132 infusion in the AD mouse brain can counteract several aspects of pathology, providing a proof‐of‐concept of its therapeutic relevance. Despite the great benefit of the multi‐targeting nature of microRNAs for treating multifactorial diseases such as AD, such approaches also entail the risk of on‐ and off‐ target toxicity, highlighting the importance of systematic genome‐wide targetome profiling. The complex multicellular miR‐132 targetome involved in AHN and the inflammatory response in AD remains elusive, and its mapping is a crucial requirement for therapeutic targeting.MethodIn order to systematically profile the mechanisms underpinning the regulatory effects of miR‐132 in AD, we employed an RNA‐sequencing approach to assess transcriptomic responses to changes in the levels of miR‐132 in AD‐relevant study systems, such as human iPSC‐derived neurons and microglia‐like cells.ResultsWe identify novel miR‐132 targets with putative neuroimmune functions possibly involved in AD pathophysiology.ConclusionOur results shed light on the involvement of miR‐132 in AD and further add to the systematic profiling of miR‐132 targetome, a prerequisite for successful translation of miR‐132 supplementation in AD.
Perturbed glycogen metabolism is an Alzheimer’s disease therapeutic target
Authors: Gentry Matthew S. 
Published: December 2023

AbstractBackgroundThree clinical hallmarks of AD are amyloid beta (Aβ) plaques, neurofibrillary tangles, and glucose hypometabolism. Multiple agents can decrease Aβ and tau levels, such as the recently FDA‐approved Aducanumab. However, improvements in patient cognition are disappointing and this disappointment is potentially due to a failure to normalize cerebral glucose hypometabolism.Clinical AD symptom severity strongly correlates with the degree of glucose hypometabolism. In the brain, one route of glucose metabolism is the biosynthesis of glycogen, a branched molecule that functions as an energy cache in times of energetic stress. Importantly, glycogen is critical for neuronal function and memory formation, and defective glycogen metabolism is an underlying driver of several neurological glycogen storage disorders (GSDs). An excess glycogen phenotype was reported in AD brains in the early 1980s, but to date, little is known about its involvement in AD symptoms.MethodIn this study, we first report that AD brains have an excess glycogen phenotype and that AD glycogen correlates with disease severity in human patient samples. Furthermore, the human excess AD glycogen is phenocopied in multiple AD mouse models and the accumulation of glycogen in these mice precedes cognitive deficits. Based on rigorous and striking data, we propose glycogen as a novel target for AD therapy that warrants additional preclinical development.ResultWe developed the enzyme therapy VAL‐0417 that combines a glycogen‐degrading amylase fused to an antibody fragment that facilitates intracellular delivery of recombinant enzymes. VAL‐0417 ablates excess glycogen and rescues disease phenotypes in a fatal GSD that causes childhood dementia called Lafora disease (LD). LD mice share several phenotypes with AD mouse models, including neurotoxic glycogen accumulation. Excitingly, VAL‐0417 also degrades AD glycogen both in vitro from human patient samples and in vivo in the 5xFAD AD mouse model. Furthermore, VAL‐0417 significantly reduces Ab plaque burden in 5xFAD mice and improves hippocampal long‐term potentiation.ConclusionThese studies suggest that targeting AD glycogen with VAL‐0417, either alone or in combination with other therapies targeting Aβ and/or tau, is an exciting and novel preclinical therapeutic target.
Machine Learning‐Based Brief Screening Instrument for Dementia: “Six‐Questions Based Dementia Screen Test”
Authors: Li Kuan‐Ying , Huang Tang‐Wei , Yen Chen‐Wen , Fang Chien Ching‐ , Huang Ling‐Chun , Yang Yuan‐Han 
Published: December 2023

AbstractBackgroundMachine learning (ML) applied to healthcare is increasingly and it provides innovative solutions to solve complex real‐world problems. In dementia, ML has been applied to dementia detection, discriminating different types of dementia, and prediction progression of diseases. The aim of the study was to develop a new, brief clinical tool based on machine learning for dementia screening.MethodThe training data was from 533 participants (311 dementia and 202 non‐demented participants) screened with “Six‐Question Dementia Screening Test” (6Q‐DS). The 6Q‐DS contained six simple questions to evaluate mood, memory, orientation, and concentration. We used e‐Xtreme Gradient Boosting (XGBoost) algorithm, an ensemble ML based on decision trees, to establish the prediction model for dementia.ResultA total 533 participants, 186 men and 347 women with mean age 77.6 ± 8.2 (mean± SD) years, were recruited. The dementia group was significantly older and had lower education years compared to non‐dementia group (p < 0.01 for both). The receiver‐operator characteristic (ROC) analysis showed that the area under the curve (AUC) was 0.91 for discriminating non‐dementia vs. dementia, with the sensitivity as 0.86, specificity 0.81 and accuracy 0.84. We found that the top 3 features are the second calculations for serial 3’s test, feeling of depression and the third calculations for serial 3’s test. We hypothesized that the second and third calculations required more cognitive demands because of holding information longer and depression is frequent in dementia. In our sixth question “Please count down 100 by 3 for 5 times (Serial 3’s)”, we found that the second and third calculations for serial 3’s test were important features to discriminating dementia from non‐dementia. We also found that the feeling of depression is the second important feature to distinguish dementia in our data set.ConclusionWe proposed the new, ease‐to‐use instrument with good classification of screening dementia based on ML. The 6Q‐DS showed an acceptable accuracy with a relatively high sensitivity and specificity. Further works are warranted to validate the model in different clinical settings and disease severity.